Attention and memory bias for body image and health ... · Body Image and Cognitive Bias v Abstract...
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Body Image and Cognitive Bias i
Attention and memory bias for body image and health related information using an
Emotional Stroop task in a non-clinical sample.
By
Kate Mulgrew
Bachelor of Psychology (Honours)
Supervisor: Dr Nathan Moss
Associate Supervisor: Dr Doug Mahar
A thesis submitted in partial fulfilment of the requirements for the Degree of Doctor
of Philosophy
School of Psychology and Counselling
Institute of Health and Biomedical Innovation
Queensland University of Technology
2008
Body Image and Cognitive Bias ii
Keywords
Body image, Emotional Stroop, attention, memory, cluster analysis, classification,
Body Image and Cognitive Bias iii
Acknowledgements
I would first like to acknowledge and sincerely thank my supervisors Dr
Nathan Moss and Dr Doug Mahar for their continued support, invaluable feedback,
and generosity with their time. Finishing a PhD is no easy task, but neither is
supervising one. You were both there for me as mentors, but also as friends. I am so
grateful for the knowledge I have gained from working with you both. I honestly
don’t think I would be where I am today without the opportunities you both provided
me to help my career advancement. I would especially like to thank Nathan for his
attention to detail while reading through numerous drafts, and to Doug for taking the
time to write the Stroop program for me. The financial support and resources of QUT
are also gratefully acknowledged.
I would also like to give a big thank-you to my postgraduate colleagues for the
friendship, support, and many hours of laughter that you provided. I would not have
emerged (somewhat) sane without you. A special thanks to my family for all the
support and encouragement they provided. Nothing ever seemed quite so bad after
eating Mexican food and drinking margaritas with my sister. Another special thanks
to my work colleagues at ACU, especially Anne, for your enduring faith in me, the
support you provided, and listening to me complain constantly about the PhD. Thank-
you also to the students who thoughtfully ask me every semester whether I am a
doctor yet. Finally, I would like to thank the participants of this study who gave up
their time to take part in this research, and to anyone who has taken interest in my
research. Sincere thanks to the external markers who provided thorough and useful
feedback.
Body Image and Cognitive Bias iv
Statement of Original Authorship
The work contained in this thesis has not previously been submitted for a degree or
diploma at any other higher education institute. To the best of my knowledge and
belief, the thesis contains no material published or written by another person except
where due reference is made.
Name: Kate Mulgrew
Signed:
Date:
Body Image and Cognitive Bias v
Abstract
It has been proposed that body image disturbance is a form of cognitive bias wherein
schemas for self-relevant information guide the selective processing of appearance-
related information in the environment. This threatening information receives
disproportionately more attention and memory, as measured by an Emotional Stroop
and incidental recall task. The aim of this thesis was to expand the literature on
cognitive processing biases in non-clinical males and females by incorporating a
number of significant methodological refinements. To achieve this aim, three phases
of research were conducted. The initial two phases of research provided preliminary
data to inform the development of the main study.
Phase One was a qualitative exploration of body image concerns amongst males and
females recruited through the general community and from a university. Seventeen
participants (eight male; nine female) provided information on their body image and
what factors they saw as positively and negatively impacting on their self evaluations.
The importance of self esteem, mood, health and fitness, and recognition of the social
ideal were identified as key themes. These themes were incorporated as psycho-social
measures and Stroop word stimuli in subsequent phases of the research.
Phase Two involved the selection and testing of stimuli to be used in the Emotional
Stroop task. Six experimental categories of words were developed that reflected a
broad range of health and body image concerns for males and females. These
categories were high and low calorie food words, positive and negative appearance
words, negative emotion words, and physical activity words.
Phase Three addressed the central aim of the project by examining cognitive biases
for body image information in empirically defined sub-groups. A National sample of
males (N = 55) and females (N = 144), recruited from the general community and
universities, completed an Emotional Stroop task, incidental memory test, and a
collection of psycho-social questionnaires. Sub-groups of body image disturbance
Body Image and Cognitive Bias vi
were sought using a cluster analysis, which identified three sub-groups in males
(Normal, Dissatisfied, and Athletic) and four sub-groups in females (Normal, Health
Conscious, Dissatisfied, and Symptomatic). No differences were noted between the
groups in selective attention, although time taken to colour name the words was
associated with some of the psycho-social variables. Memory biases found across the
whole sample for negative emotion, low calorie food, and negative appearance words
were interpreted as reflecting the current focus on health and stigma against being
unattractive. Collectively these results have expanded our understanding of processing
biases in the general community by demonstrating that the processing biases are
found within non-clinical samples and that not all processing biases are associated
with negative functionality.
Body Image and Cognitive Bias vii
Table of Contents
Keywords……. ................................................................................................ ii
Acknowledgements .......................................................................................... iii
Statement of Original Authorship .................................................................... iv
Abstract………… ............................................................................................ v
List of Tables .................................................................................................. xiii
List of Figures .................................................................................................. xv
Chapter One: Body Image Disturbance in Non-Clinical Samples: A General
Overview of the Literature. .............................................................................. 1
1.1 Overview ........................................................................................ 1
1.2 Definition of Key Terms ................................................................ 1
1.3 Significance of the Problem ........................................................... 2
1.4 Vulnerability Factors ...................................................................... 4
1.4.1 Weight and Self-Esteem .................................................. 4
1.4.2 Attitudes Towards One’s Body ....................................... 5
1.4.3 Eating Disorder Symptomology ...................................... 6
1.4.4 Dysfunctional Behaviours as Weight Loss Strategies ..... 7
1.4.5 Other Psychopathology ................................................... 9
1.4.6 Drive for Muscularity ...................................................... 10
1.5 Classification and Sub-Typing of Body Image .............................. 11
1.5.1 Sub-Typing Eating Disorders .......................................... 12
1.5.2 Sub-Typing Non-Clinical Samples ................................. 14
1.6 Critique of the Literature ................................................................ 15
1.7 Summary of the Chapter ................................................................ 17
Chapter Two: Theoretical Review: Biased Attention and Memory for
Disorder Consistent Material .......................................................................... 19
2.1 Introduction .................................................................................... 19
2.2 Key Theories .................................................................................. 21
2.2.1 Markus’s Self-Schema Theory ........................................ 21
2.2.2 Williamson et al. Information Processing Model ............ 23
2.2.3 Thompson et al.’s Cognitive Processing Model. ............. 24
2.2.4 Vitousek and Hollon Schema Framework ...................... 25
2.2.5 Depression and Anxiety Models ..................................... 26
2.2.5.1 Williams et al. Integrative Model ......................... 27
2.2.5.2 Beck’s Schema Theory and Content Specificity
Hypothesis ........................................................................ 30
Body Image and Cognitive Bias viii
2.2.6 Bower’s Network Theory ................................................ 31
2.2.7 Encoding of Personal Information .................................. 33
2.3 Integration of Theories and Summary of Theoretical Review
Chapter.. ............................................................................................... 34
Chapter Three: Attention and Memory Bias for Body Image Information ..... 37
3.1 Overview of Chapter ..................................................................... 37
3.2 Background to the Research ......................................................... 37
3.3 The Stroop task as a Measure of Attentional Bias ........................ 38
3.4 The Emotional Stroop Task .......................................................... 39
3.4.1 The Emotional Stroop Task with Eating Disorders ........ 41
3.4.2 The Emotional Stroop Task in Non-Clinical Samples .... 46
3.4.3 Methodological Limitations ............................................ 51
3.4.3.1 Card vs Computer technique .............................. 51
3.4.3.2 Blocked vs Random Presentation of Words ...... 52
3.4.3.3 Response Strategy .............................................. 53
3.4.3.4 Order of Tasks .................................................... 54
3.4.3.5 Stimulus Sets ...................................................... 54
3.4.3.6 Sample Limitations ........................................... 56
3.4.4 Limitations Addressed in the Current Project ................ 58
3.5 Memory Bias ................................................................................. 59
3.6 Summary of Attention and Memory Bias Chapter ....................... 64
Chapter Four: Overview of Research Program ................................................ 65
4.1 Aims, Research Questions, and Hypotheses .................................. 65
Chapter Five: A Qualitative Exploration of Body Image Concerns Amongst
Men and Women From a Non-Clinical Population (Phase One) .................... 69
5.1 Overview of Chapter ...................................................................... 69
5.2 Method ........................................................................................... 69
5.2.1 Participants ..................................................................... 69
5.2.2 Procedure ....................................................................... 70
5.2.3 Data Analysis ................................................................. 72
5.3 Results ............................................................................................ 73
5.3.1 A Healthy Body Image Does Not Negatively Affect
One’s Life ............................................................................... 73
5.3.2 Having a Strong Self-Esteem / Self Image is a Protective
Factor ..................................................................................... 75
5.3.3 Importance of Health and Fitness .................................. 76
Body Image and Cognitive Bias ix
5.3.4 Recognition of Societal Ideal ......................................... 78
5.3.5 Mood Can Affect How Events are Interpreted .............. 80
5.3.6 Other Factors .................................................................. 81
5.4 Discussion ...................................................................................... 82
5.4.1 Summary of Findings ...................................................... 82
5.4.2 Limitations ...................................................................... 87
5.5 Summary of Chapter ...................................................................... 88
Chapter Six: Selection of Stroop Stimuli (Phase Two) ................................... 89
6.1 Overview of Chapter ...................................................................... 89
6.2 Stage One and Two: Generation of Stroop categories and words . 89
6.2.1 Method ............................................................................ 89
6.2.1.1 Procedure ........................................................... 89
6.2.2 Results and Discussion ................................................... 90
6.3 Stage Three: Rating and Final Selection of Experimental Stroop
Words .................................................................................... 94
6.3.1 Method ............................................................................ 94
6.3.1.1 Participants .......................................................... 94
6.3.1.2 Procedure ............................................................ 94
6.3.1.3 Materials ............................................................. 94
6.3.1.4 Method of Analysis ............................................. 95
6.4.1 Results and Discussion .................................................. 95
6.4 Stage Four: Matching of Neutral and Experimental Words ....... 96
6.4.1 Method ............................................................................ 96
6.4.1.1 Procedure ............................................................ 96
6.4.2 Results and Discussion ................................................... 96
6.5 Summary of Phase Two ................................................................. 99
Chapter Seven: Cognitive Method used to Assess Biased Processing (Phase
Three) .............................................................................................................. 100
7.1 Method ......................................................................................... 100
7.1.1 Participants ...................................................................... 100
7.1.2 Design ............................................................................. 102
7.1.3 Materials ......................................................................... 102
7.1.3.1 Emotional Stroop task ......................................... 102
7.1.3.2 Distracter Task .................................................... 104
7.1.3.3 Incidental Memory Task ..................................... 104
7.1.3.4 Demographic Form ............................................. 104
Body Image and Cognitive Bias x
7.1.3.5 Hunger Levels ..................................................... 104
7.1.3.6 Negative Mood .................................................... 104
7.1.3.7 Reasons for Exercising ....................................... 105
7.1.3.8 Dysfunctional Behaviours ................................... 105
7.1.3.9 Eating Disorder Behaviours ................................ 105
7.1.3.10 Body Mass Index .............................................. 106
7.1.3.11 Self-Esteem ....................................................... 106
7.1.3.12 Social Functioning ............................................ 106
7.1.3.13 Body Attitudes .................................................. 106
7.1.3.14 Drive for Muscularity ....................................... 108
7.1.3.15 Dietary Restraint ............................................... 108
7.1.4 Procedure ........................................................................ 108
Chapter Eight: Results and Discussion for Biased Cognitive Processing (Phase
Three)…….... .................................................................................................. 110
8.1 Preliminary Analyses ..................................................................... 110
8.1.1 Overview of Analyses ..................................................... 110
8.1.2 Data Screening ................................................................ 110
8.1.3 Scoring of the Cognitive Data ......................................... 111
8.1.3.1 Scoring of the Stroop Data .................................. 111
8.1.3.2 Scoring of the Memory Data ............................... 111
8.1.4 Identification of Sub-Groups: The Use of Cluster
Analysis ............................................................................ 112
8.1.4.1 Overview of the Cluster Analysis Technique .... 112
8.1.4.2 Results of the Cluster Analysis for Women ....... 113
8.1.4.3 Results of the Cluster Analysis for Men ............ 119
8.2 Results and Discussion for Females .............................................. 124
8.2.1 Descriptive Information .................................................. 124
8.2.2 Biased Attention .............................................................. 125
8.2.2.1 The Role of Demographic Factors in Biased
Attention ........................................................................ 128
8.2.2.2 The Role of Vulnerability Factors in Biased
Attention ........................................................................ 130
8.2.2.3 Sub-Group Differences on Biased Attention .... 136
8.2.3 Biased Memory ............................................................... 137
8.2.3.1 Percentage of Words Recalled ........................... 137
8.2.3.2 The Role of Vulnerability Factors in Biased
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Attention ......................................................................... 139
8.2.3.3 Sub-Group Differences on Biased Memory ...... 141
8.2.3.4 Relationship Between Biased Attention and
Memory .......................................................................... 143
8.2.4 Error Rates ...................................................................... 141
8.3 Results and Discussion for Males .................................................. 145
8.3.1 Descriptive Information .................................................. 145
8.3.2 Biased Attention .............................................................. 145
8.3.2.1 The Role of Demographic Factors in Biased
Attention ........................................................................ 146
8.3.2.2 The Role of Vulnerability Factors in Biased
Attention ........................................................................ 146
8.3.2.3 Sub-Group Differences in Biased Attention ..... 151
8.3.3 Biased Memory ............................................................... 153
8.3.3.1 Percentage of Words Recalled ........................... 153
8.3.3.2 The Role of Vulnerability Factors in Biased
Attention ......................................................................... 154
8.3.3.3 Sub-Group Differences on Biased Memory ...... 155
8.3.3.4 Relationship Between Biased Attention and
Memory .......................................................................... 156
8.3.4 Error Rates ...................................................................... 156
8.4 Sex Differences in Biased Cognitive Processing ........................... 158
Chapter Nine: General Discussion of Phase Three Findings and Theoretical
Integration ……... ............................................................................................ 161
9.1 Overview ..................................................................................... 161
9.2 Integration of Past Research and Theories ..................................... 161
9.2.1 High- and Low-Calorie Food Words .............................. 162
9.2.1.1 Integration of Findings with Past Research for
Females ........................................................................... 164
9.2.1.2 Integration of Findings with Past Research for
Males ............................................................................... 169
9.2.1.3 Theoretical Explanations .................................... 171
9.2.2 Positive and Negative Appearance Words ...................... 173
9.2.2.1 Integration of Findings with Past Research for
Females .......................................................................... 174
9.2.2.2 Integration of Findings with Past Research for
Body Image and Cognitive Bias xii
Males .............................................................................. 178
9.2.2.3 Theoretical Explanations ........................................ 180
9.2.3 Negative Emotion Words ................................................. 183
9.2.3.1 Integration of Findings with Past Research for
Females ........................................................................... 183
9.2.3.2 Integration of Findings with Past Research for
Males ............................................................................... 185
9.2.3.3 Theoretical Explanations .................................... 185
9.2.4 Physical Activity Words ................................................... 189
9.2.4.1 Integration of Findings with Past Research for
Females ........................................................................... 190
9.2.4.2 Integration of Findings with Past Research for
Males ............................................................................... 191
9.2.4.3 Theoretical Explanations .................................... 191
9.2.5 Sex Differences in Cognition .......................................... 193
9.3 Summary of Chapter. ..................................................................... 194
Chapter Ten: Overview, General Discussion, and Conclusions ...................... 196
10.1 Overview ...................................................................................... 196
10.2 Integration of Key Findings ......................................................... 197
10.3 Theoretical and Practical Implications ......................................... 200
10.4 Strengths, Limitations, and Suggestions for Future Research ..... 205
10.4.1 Strengths of the Research .............................................. 205
10.4.1.1 Sample Characteristics ..................................................... 205
10.4.1.2 Methodological Refinements ............................... 206
10.4.2 Limitations of the Research .......................................... 208
10.5 Summary of the Chapter .............................................................. 211
References ........................................................................................................ 212
Appendix A: Information and Consent Forms used in the Qualitative Study
Of Phase One ................................................................................................... 237
Appendix B: List of Questions and Prompts for Interview in Phase One ....... 240
Appendix C: Non-Copyrighted Questionnaires used In Phase Three ............. 241
Appendix D: Information and Consent Forms used in Phase Three ............... 244
Appendix E: Overview of Cluster Analytical Technique and Sub-Group
Formation ......................................................................................................... 247
Body Image and Cognitive Bias xiii
List of Tables
Table 6.1: Initial List of Words Generated and Expected Categorisation.
Words Proceeded with an “*” Indicate Final Selection …………93
Table 6.2: Frequency of Usage and Word Length Data Used for Matching
the Experimental and Neutral Categories ……………………..... 97
Table 8.1: BAQ Sub-Scale Scores for the Four Cluster Solution in
Women…………………………………………………………...114
Table 8.2: Differences in Demographic and Social Functioning Scores
Between the Four Sub-Groups Identified in Women
(Standard Deviations in brackets) …………………………….....117
Table 8.3: Descriptive Data for the MBSRQ Sub-Scales for the Three
Cluster Solution in Males……………………...…………………121
Table 8.4: Differences in Demographic and General Well-Being Scores
Between the Three Clusters Identified in Males ……………..….124
Table 8.5: Descriptive Statistics and Reliability Values for the Mood
and General Well-Being Measures in Women …………………..125
Table 8.6: Descriptive Statistics and Reliability Values for the Body
Image Measures in Women ……………………………………...126
Table 8.7: Mean Reaction Time and Interference Indexes (in Milliseconds)
for the Stroop Colour-Naming Task in Females (N = 144) …...…127
Table 8.8: Correlations Between Hunger Levels and Interference Indexes
in Women ……………………………………………………..….129
Table 8.9: Percentages and Stroop interference scores for women who
reported engaging in risky eating and weight management
techniques in the last six months (N = 144). Significant
differences in interference scores are noted with“*” ………….…133
Table 8.10: Mean interference scores for women classified as restrained
or unrestrained eaters on the Stroop categorie……………………135
Table 8.11: Mean Stroop Interference (in Msec) Scores Across the
Sub-Groups Identified in Women ……………………………..…136
Table 8.12: Percentage of Words Recalled Across Each Category for
Females …………………………………………………...…...…138
Table 8.13: Percentage of Words Recalled for Women who Reported
Engaging in Risky Eating and Weight Management
Techniques in the Last Six Months (N = 144). Significant
Body Image and Cognitive Bias xiv
Differences in Interference Scores are Noted with “*” …….……142
Table 8.14: Percentage of Words Recalled in Each of the Experimental
Categories from the Stroop Task Across Sub-Groups
in Women ……………………………………………….…...…..143
Table 8.15: Mean number of colour naming errors made on the Stroop
task by females…………………………………………………..144
Table 8.16: Descriptive Statistics and Reliability Values for the Mood and
General Well-Being Variables in the Male Sample …………..….145
Table 8.17: Descriptive Statistics and Reliability Values for the Body
Image Variables in the Male Sample ………………………….…147
Table 8.18: Mean Reaction Times and Interference Indexes
(in Milliseconds) for the Stroop Task in Males (N = 54) ……......148
Table 8.19: Percentage of Men who Reported Engaging in Risky Eating
and Weight Management Techniques in the Past Six Months
and Stroop Interference Scores (N = 54) …………………….…..150
Table 8.20: Mean Stroop Interference (in Milliseconds) by Sub-Group
in men. Standard Deviations in Parentheses ……………….....…152
Table 8.21: Percentage of Words Recalled Across Stroop Categories
for Males …………………………………………………..….….154
Table 8.22: Percentage of Words Recalled by Sub-Group in Men…………....156
Table 8.23: Mean number of colour naming errors made on the Stroop
task for males……………………………………………………..157
Table 8.24: Means (and Standard Deviations) for Stroop Interference
Scores Between Males (N = 55) and Females (N = 143) .............158
Table 8.25: Means (and Standard Deviations) for the Percentage of Words
Recalled Between Males (N = 55) and Females (N = 143) ..........159
Table 8.26: Means (and Standard Deviations) for the Number of Errors
Made During the Emotional Stroop Task for Males and
Females………………………………………………………….160
Body Image and Cognitive Bias xv
List of Figures
Figure 1.1: Williamsons’ et al. (2002) cognitive information processing model of
body image disturbance………………………………………….…24
Figure 5.1: Summary of Inter-Relationships Between Key Themes Identified in the
Qualitative Analysis…………………………………………….….82
Body Image and Cognitive Bias 1
Chapter One: Body Image Disturbance in Non-Clinical Samples
1.1 Overview
This thesis presents a program of research designed to increase our knowledge
about the spectrum of body image disturbance and biased cognitive processing within
non-clinical samples. This chapter provides a background to the research by defining
key terms and examining the prevalence and consequences of body image
disturbance. A range of psycho-social vulnerability factors that have been implicated
in body image disturbance will be briefly reviewed. Chapter Two will then outline the
cognitive theoretical framework used, while Chapter Three will examine the role of
biased attention and memory in more depth. Following this literature review, Chapters
Five to Eight will outline the research conducted, followed by a general discussion of
the results of the program of research.
1.2 Definitions of Key Terms
Body image can be defined as the internal view that one holds about their
outer appearance (Garner, 1997). This internal view is subjective, and may be
influenced by a variety of factors including norms prevalent in ones' culture, biology,
history of weight fluctuations, media, social pressure, and individual characteristics;
all of which interact in complex ways to form an unstable representation of ones' body
shape and size (Slade, 1994; Rievers & Cash, 1996). Generally, body image is thought
to involve three components: an attitudinal component, a cognitive component, and a
behavioural component (Slade, 1994).
In this thesis, the term body image disturbance is used to denote a broad range
of problems associated with one’s body image, such as disturbances in eating
behaviours, excessive exercising, and unhappiness with one’s appearance or body
shape. Body image disturbance occurs on a spectrum ranging from individuals who
are only mildly concerned with their appearance to those for whom body image
concerns severely impact on day to day living. According to Levine and Piran (2004),
Body Image and Cognitive Bias 2
“negative body image refers not only to body dissatisfaction but also to excessive
cognitive and behavioural investment in one’s physical appearance in defining one’s
sense of self” (p. 57). That is, negative feelings about appearance may translate into a
negative view of the self.
A specific type of body image disturbance is body dissatisfaction. Perhaps one
of the most widely used terms, and widely measured constructs in the literature, body
dissatisfaction is commonly defined as the degree of satisfaction or dissatisfaction
with one’s body. This can be a global measure (i.e., how satisfied are you with your
general appearance?) or can focus on specific bodily areas (i.e., how satisfied are you
with your stomach/thighs/hips?). In this thesis the term body dissatisfaction is defined
as a specific type of body image disturbance.
1.3 Significance of the Problem
Much of the existing literature has focused on clinical levels of body image
disturbance, despite figures indicating that a larger proportion of people fail to reach
this level of disturbance (Cash & Hicks, 1990). According to the DSM-IV-TR, the
Eating Disorder Anorexia Nervosa currently afflicts about 0.5% of women, while
Bulimia Nervosa affects slightly more women at approximately 1-3%. The respective
rates for these conditions in males are about half that seen in women (American
Psychiatric Association; APA, 2000). Community based research into body image
disturbance predominantly conceptualises this construct as dissatisfaction with
various aspects of body shape and physical appearance. When asked whether women
are satisfied with their appearance and/or shape, the majority of respondents answer
“no” (Tiggemann & Lynch, 2001). Most women report they want to be thinner
(Frederick, Peplau, & Lever, 2006), but also more toned and muscular (Butler &
Ryckman, 1993). While men also report similar levels of body dissatisfaction (Pope,
Phillips, & Olivardia, 2000), their dissatisfaction with appearance can translate into
either wanting to loose weight, or to be more muscular (Drewnowski & Yee, 1987).
Body Image and Cognitive Bias 3
Thus, current estimates of the prevalence of body dissatisfaction indicate that non-
clinical body image concerns affect a substantially larger proportion of the population
than do clinical concerns.
The importance of understanding body image disturbance is underscored by
the variety of psychological problems associated with disordered eating patterns and
dysfunctional body images. Kenardy, Brown, and Vogt (2001) found that frequent
dieting was associated with poorer mental health. Women who reported dieting five
times or more in the previous year were 45% more likely to be depressed than non-
dieters. Body dissatisfaction and any subsequent dieting have also been found to
produce psychological and physical distress (Garner & Wolley, 1991), health risks
associated with weight cycling (Lissner et al., 1991), nutritional deficits (Kenardy et
al., 2001), and a substantially increased risk of death from cardiovascular problems
(Jeffrey, 1996). In the United States, it is reported that Anorexia Nervosa has the
highest mortality rate compared to any other type of psychiatric condition, and can be
as costly to treat as Schizophrenia, whereas Bulimia Nervosa and Binge Eating
Disorder are similar in treatment cost as Obsessive Compulsive Disorder (Agras,
2001).
Some women who are dissatisfied with their appearance may subjectively see
their body shape as larger than what it is objectively. Tiggemann and Lynch (2001)
reported that over 50% of Australian women wanted to be thinner, despite being
within a normal weight range. Cash and Hicks (1990) reported that women and men
who classified themselves as overweight, when objectively they were of normal
weight, reported poor well-being, such as low life satisfaction, and feelings of
loneliness and depression. Based on a large Danish sample, 10% of women who were
objectively underweight considered their body weight to be too heavy (Kjærbye-
Thygesen, Munk, Ottesen, & Krüger Kjær, 2004). Thus, belief about one’s
appearance seems to be more important than actual body size (Cash & Hicks, 1990).
Body Image and Cognitive Bias 4
Two decades ago body dissatisfaction was so prevalent it was labelled a
normative discontent (Rodin, Silberstein, & Striegel-Moore, 1984) of epidemic
proportions (Hutchinson, 1982). Ten years ago, a worldwide survey by Psychology
Today revealed that over half of women surveyed were dissatisfied with their overall
appearance and weight. Alarmingly, 39% of female respondents said they would
forego between three and five years of their lives if they could be their ideal weight
(Garner, 1997). Australian prevalence rates reflect this ‘normative discontent’ and
show a large proportion of the population experiencing some form of body image
disturbance. For example, 77% of Australian adolescent girls (Grigg, Bowman &
Redman, 1996), and over half of Australian women (Tiggemann & Lynch, 2001)
report that they want to thinner. Whereas women receive pressure from society to be
thin, men receive pressure to be larger and bulkier (Cohane & Pope, 2001). Men are
equally as likely to report wanting weight gain as loss (Drewnowski & Yee, 1987).
1.4 Vulnerability Factors
A number of vulnerability factors have been identified in the research that
precipitate or are typically associated with body image disturbance. A brief review of
some of these vulnerability factors follows, and demonstrates the multifaceted nature
of body image disturbance. The reader is reminded that the aim of Phase Two of the
research was to identify the key vulnerability factors within non-clinical males and
females.
1.4.1 Weight and Self-Esteem
Self-esteem is the extent to which one is satisfied with themselves (Rosenberg,
1965). Low self-esteem has been recognised as a risk factor in the development of
body image disturbance in women (Paxton & Phythian, 1999) and men (Green &
Pritchard, 2003). It may also interact with other variables such as perfectionism to
make an individual more vulnerable to body dissatisfaction (Cooley & Toray, 2001).
Self-esteem contributes highly to the prediction of body satisfaction. For example,
Body Image and Cognitive Bias 5
Monteath and McCabe (1997) found that self-esteem contributed significantly to the
prediction of various measures of body satisfaction, including deviation from societal
ideal. Thus, self-esteem plays an important role in understanding body image.
Body weight is typically measured by the Body Mass Index ratio (BMI: kg /
m²) which provides an indication of adiposity relative to ones height. Monteath and
McCabe (1997) found that a higher BMI was related to higher levels of body
dissatisfaction among women. These researchers also found that BMI was a
significant predictor of various measures of body dissatisfaction. Self esteem may
interact with BMI and determine how much importance is placed on weight. For
example, women with lower self-esteem and/or a larger body weight are generally
more dissatisfied with their bodies than other women (Monteath & McCabe, 1997).
1.4.2 Attitudes Towards One’s Body
Attitudes towards one’s body have typically been measured as feelings of
body dissatisfaction (Ben-Tovim & Walker, 1991). Body dissatisfaction is recognised
as one of the key features of eating disorders (APA, 2000), even though it is much
more common in non-disordered individuals. However, extreme feelings of body
unattractiveness and disgust have been shown to be important discriminators between
those with eating disorders and non-eating disordered individuals (Ben-Tovim &
Walker, 1992).
A range of negative attitudes towards one’s body are frequently found among
women such as high levels of body dissatisfaction, perceived pressure to diet, and
feelings of fatness (Lam, Stewart, & Leung, 2002). The importance of feeling
attractive was demonstrated by Stokes and Frederick-Recascino (2003) who found
that women with higher levels of satisfaction with their appearance and feelings of
attractiveness also had high levels of life satisfaction. Level of attractiveness has also
been found to be a frequent comparison issue amongst adolescent girls, who report
comparing their attractiveness to models and celebrities (Jones, 2001). As such, it is
Body Image and Cognitive Bias 6
proposed that feelings of attractiveness are a fundamental aspect for understanding an
individual’s experience of body image.
Feeling fat is an affective component of body image (Slade, 1994). Research
has indicated that women often report feeling fat when objectively they are of normal
weight (Tiggemann, 1996). Consistent with this finding, Ben-Tovim and Walker
(1991) report only a moderate correlation between BMI and feeling fat. Thus, women
can feel fat regardless of their objective weight. Subjective feelings of fatness appear
to be an important variable in understanding body dissatisfaction. Tiggemann (1996)
found that feelings of fatness added unique variance in the prediction of body
dissatisfaction over and above objective and cognitive variables. Feelings of fatness
have also been shown to be a dominant concern in non-clinical populations (Ben-
Tovim & Walker, 1991). These feelings of fatness have been shown to be the most
frequently cited reason for dieting amongst adolescent girls (Wertheim, Paxton,
Schutz, & Muir, 1997). Thus, a range of attitude’s held by individuals need to be
included in the measurement of body image.
1.4.3 Eating Disorder Symptomology
Drive for thinness has been recognised as a key risk factor for the development
of Anorexia (APA, 2000). Drive for thinness refers to excessive thoughts about
dieting, increased importance placed on weight, and strong desire to be thin, over and
above that which is regarded as normal (Garner, Olmsted, & Polivy, 1983). Like body
image, drive for thinness has been recognised as a multidimensional construct
encompassing perceptual, affective and behavioural components (Sands, 2000). A
drive for thinness may be the outcome of a perceived discrepancy between ones’
actual and ideal figures. Therefore, drive for thinness may be the process of reducing
feelings of body dissatisfaction (Sands, 2000).
The importance of drive for thinness in non-clinical samples was demonstrated
by Wiederman and Pryor (2000) who compared disordered women and non-
Body Image and Cognitive Bias 7
disordered college women. In both groups, drive for thinness accounted for unique
variability in the prediction of body dissatisfaction beyond that of other variables such
as depression and bulimia. In fact, after the effects of drive for thinness had been
removed, the severity of bulimia was no longer related to amount of body
dissatisfaction. Thus, drive for thinness is an important element in understanding body
dissatisfaction in non-clinical samples as well (Wiederman & Pryor, 2000).
Other eating disorder symptomology have been found in high levels within
university samples. Using the Eating Attitudes Test (Garner & Garkinkel, 1979),
Clarke and Palmer (1983) found that 11% of female respondents reporting similar
levels of eating and weight pathology as women with anorexia. Australian women
show similar prevalence rates. Using the Eating Disorder Inventory (Garner, Olmsted,
& Polivy, 1983), Ball and Lee (2002) also found high levels of eating disorder
symptomology in a sample of Australian women aged between 19 and 24 years. Grigg
et al. (1996) found that 33% of Australian adolescent females reporting disordered
eating, such as binge eating, vomiting to achieve weight control, and continued weigh
loss attempts while classified as underweight. Over half of the sample (57%) reported
engaging in unhealthy dieting behaviours. An American study revealed that 69% of
women had reporting using diet pills (Ceclio et al., 2006). Therefore, individuals
within a non-clinical sample report a range of risky weight management techniques.
The presence of these symptoms has been shown to be predictive of the later
development of eating disorders (Polivy & Herman, 1985). As such, eating disorder
symptomology is important to consider within non-clinical samples.
1.4.4 Dysfunctional Behaviours as Weight Loss Strategies
In addition to eating disorder symptomology, there are a range of
dysfunctional behaviours that are also important for the understanding of body image.
One of these dysfunctional behaviours is dieting. The average age of onset for dieting
in Australian women has found to be 15.4 years (Kenardy et al., 2001). During this
Body Image and Cognitive Bias 8
adolescent period, body weight and shape are changing dramatically, and many girls
report dieting to compensate for these changes. One Australian study has found that
57% of adolescent girls reported engaging in unhealthy dieting, and an additional 36%
were classified as engaging in extreme dieting (use of laxatives, slimming tablets etc
to achieve weight loss; Grigg et al., 1996). It appears that this figures remain stable
into early adulthood, with Kenardy et al. (2001) reporting that 46% of Australian
women aged from 18 to 23 years had engaged in dieting behaviours in the last year.
Thus, a large proportion of young Australian women engage in dieting behaviours.
If dieting alone is not perceived to produce the desired weight loss, then other
compensatory strategies may be used. These include excessive exercising and purging
behaviours such as the use of laxatives, vomiting, and slimming tablets. Australian
studies indicate that 9% of non-clinical adolescent females report vomiting, 6% use
diet pills and laxatives, and 3% used diuretics to achieve weight loss (Wertheim et al.,
1992). Again, similar figures for purging behaviours are found in Australian young
adult women, with figures ranging between 2.7% for non-dieters, to 33% for frequent
dieters (Kenardy et al., 2001). These figures illustrate that dysfunctional weight loss
behaviours are not restricted to those with clinical eating disorders.
Unlike the above behaviours, exercise has a range of positive health outcomes
(DiBartolo & Shaffer, 2002). However, engaging in excessive amounts of exercise
can result in a range of negative physical and psychological results. Excessive
exercise is defined in terms of duration, frequency, and intensity (Hausenblas &
Downs, 2002). Not all individuals, however, exercise for weight loss reasons. In one
of the first empirical investigations to explore the reasons that men and women
exercise, Silberstein, Striegal-Moore, Timko, and Rodin (1988) developed the
Reasons for Exercise Inventory from which seven reasons emerged: exercising for
weight control, for fitness, health, improving body tone, physical attractiveness,
mood, and enjoyment. Men and women cited similar reasons for exercising, however
Body Image and Cognitive Bias 9
women reported exercising significantly more for weight control. Eating disorder
symptomology was found to be associated with the Weight Control and Mood
Regulation subscales. Thus, while some forms of exercise are engaged in as part of a
healthy lifestyle, other types of exercising may be related to body image disturbance.
Therefore, the type of exercise, and the reasons for engaging in exercise are important
variables to consider.
1.4.5 Other Psychopathology
In addition to the core disturbances in eating, weight, and shape found in
those with body image disturbance, a range of comorbid mental disorders have been
noted. Negative body image and depression have been found to be associated (Levine
& Smolak, 2002), and negative emotionality was found to be one of the strongest
predictors of developing an Eating Disorder (Leon, Fulkerson, Perry, & Cudeck,
1993). It has been proposed that the current ideals of attractiveness and thinness,
coupled with the importance placed on these attributes, leads to depression in women
(McCarthy, 1990). A number of body image disturbance factors (such as body
dissatisfaction and thin-ideal internalisation) have been found to be predictive of
increases in levels of depression (Stice & Bearman, 2001). For example, Stice,
Hayward, Cameron, Killen, and Taylor (2000) found that a combination of body
image disturbance factors was able to significantly predict which adolescent girls
would develop depression. Australian research has also found that early onset of
dieting is associated with depression (Kenardy et al., 2001).
The role of perfectionism in eating disorders has been well established by
research (Davis, Claridge, & Fox, 2000; Pumariega & LaBarbera, 1986; Bastiani,
Rao, Weltzin, & Kaye, 1995; Hewitt, Flett, & Ediger, 1995). Perfectionism is a
multidimensional construct involving unrealistic standards and fear of, and
overemphasis on, failure (Hewitt et al, 1995). Within Anorexia perfectionism
manifests itself as an all-encompassing drive to achieve a thin physique (Pumariega et
Body Image and Cognitive Bias 10
al., 1986; Hewitt et al., 1995). Bastiani et al. (1995) found that women with Anorexia
scored substantially higher than controls on various measures of perfectionism, a
pattern that persists even after weight gain. More recent research has found that
maladaptive aspects of perfectionism to be strongly related to weight preoccupation,
as measured by the Drive for Thinness, Body Dissatisfaction, and Bulimia subscales
of the Eating Disorder Inventory (Davis et al., 2000).
According to Fichter, Quadflieg, and Rehm, (2003), general well-being and
the presence of comorbid psychopathology are just as important, and in some cases
more important, than core eating disturbance variables in understanding and
predicting the course of the disorder long term. Therefore, general well-being is
important to consider in understanding body image disturbance.
1.4.6 Drive for Muscularity
The ideal male standard is becoming increasingly larger and more muscular; a
standard difficult for most men to achieve. The desire to achieve muscle mass has
been termed a drive for muscularity (McCreary & Sasse, 2000), and has been
identified as an important facet of men’s body image (McCreary, Sasse, Saucier, &
Dorsch, 2004). Men with a high drive for muscularity experience dissatisfaction with
their muscle mass and see themselves as less muscular than they are objectively
(McCreary & Sasse, 2000). In order to achieve this lean yet muscular physique, men
may engage in excessive weight-lifting, body building, or steroid use (Smolak,
Murnen, & Thompson, 2005).
Exercise is an important means for weight regulation, improving tone, and
generally engaging in a healthy lifestyle. Men spend a considerable amount of time
exercising and weight lifting (Phillips & Drummond, 2001), however exercise is not
always related to improvements in body satisfaction (Paxton et al., 1991). Given the
female ideal is becoming increasingly toned (Butler & Ryckman, 1993), drive for
muscularity is an important facet to consider in male and female body image.
Body Image and Cognitive Bias 11
1.5 Classification and Sub-Typing of Body Image
A number of psycho-social vulnerability factors have been identified as
important to understanding male and female body image. Research remains limited,
however, as to the inter-relationship between these variables. Further, group
comparisons are often conducted between ‘high’ and ‘low’ scorers on a particular
measure; a distinction that is sometimes arbitrary. To overcome this limitation, and to
improve our understanding of the spectrum of body image disturbance within non-
clinical samples, it is useful to consider classification of individuals along body image
measures.
Classification presents a useful means for the identification of
psychopathology. It aids clinicians with the detection and treatment of mental
disorders by specifying traits that are characteristic of each condition. The purpose of
The Diagnostic and Statistical Manual of Mental Disorders (DSM IV-TR; APA,
2000) is to provide a classificatory system for just this purpose. Currently,
classifications of Anorexia Nervosa and Bulimia Nervosa are available to explain the
extreme dissatisfaction with appearance and weight that some women experience.
There is, however, no empirical data to identify what groups exist in non-eating
disordered samples. There may exist, for example, a group of women who evidence a
high level of weight preoccupation without any resultant negative affect. The
identification of sub-groups of body image disturbance will aid group comparison by
providing empirical support for non-clinical typologies. Although clinical levels of
eating disorders are not of prime focus in the current research, the literature will be
briefly reviewed to illustrate the classification process.
The available research focuses primarily on the clinical eating disordered
groups and questions whether the range of symptomology occurs on a continuum. The
continuity/discontinuity (or dimensional versus categorical) debate revolves around
how disorders are best conceptualised. The continuity perspective states that
Body Image and Cognitive Bias 12
symptomology occurs on a continuum ranging from no symptoms, to moderate
disturbance, to high levels of symptomology indicating a clinical disorder (Franko,
Wonderlich, Little, & Herzog, 2004; Trull & Durrett, 2005). That is, differences
between clinical eating disordered groups and normal body image disturbance occurs
in degree of symptomology, or along certain dimensions. For example, a woman with
weight and eating disturbances could experience the same symptoms as a woman with
Anorexia, only to a lesser extent.
Conversely, the discontinuity perspective states that there are distinct
differences between those experiencing the particular disorder, and those with sub
clinical levels of the disorder (Franko et al., 2004; Trull & Durrett, 2005). That is,
individuals with an eating disorder experience a distinct set of symptoms compared to
those with non-clinical disturbances. This perspective states that classification is most
useful with a categorical approach, and is the approach adopted by the DSM-IV-TR
(APA, 2000). Research that examines the continuity / discontinuity perspective
typically starts with pre-defined groups and determines whether the differences
between the groups are qualitative or quantitative in nature.
1.5.1 Sub-Typing Eating Disorders
The DSM-IV-TR (2000) has identified two sub-types of Anorexia Nervosa:
restricting type and binge-eating/purging type. The restricting sub-type describes
those women who primarily engage in restrictive activities (i.e., fasting and dieting) to
achieve weight loss. The binge-eating / purging type describes those women who
primarily engaging in binging (eating a large amount of food in a small period of
time) and purging (removing ingested food through vomiting, diuretics, etc.);
behaviours similar Bulimia Nervosa. Two sub-types of Bulimia Nervosa have also
been specified. The purging sub-type is used to describe individuals who engage
primarily in purging behaviour, while the non-purging sub-type does not involve the
Body Image and Cognitive Bias 13
purging behaviours (such as vomiting) traditionally associated with Bulimia Nervosa
(APA, 2000).
Sub-typing eating disorders based on bulimic and anorexic behaviours has
provided evidence for a range of categories. Bulik, Sullivan, and Kendler (2000)
found support for six distinct clusters in a large sample of 2100 female twins. Three
classes emerged that were similar to the DSM classifications of Anorexia Nervosa,
Bulimia Nervosa, and Binge Eating Disorder. The other three presented as a range of
sub-clinical manifestations. There were two groups that had low weight without
eating disorder symptomology, and one group that had shape and weight
preoccupations without low weight. While these findings support the distinction of a
range of eating disorders, the findings also suggest that an additional cluster of
women exist that hold some eating disordered symptomology.
Two distinct sub-types have been found in women with Bulimia Nervosa
(Stice & Agras, 1999) and Binge Eating Disorder (Grilo, Masheb, & Wilson, 2001).
Sub-typing occurred along a range of dieting and negative affect dimensions. A “pure
dietary” sub-type emerged which is consistent with the traditional idea of dieting
being a core symptom of Bulimia. A “mixed dietary-depressive” sub-type also
emerged, which had similar levels of dieting behaviours to the pure dietary sub-type,
in addition to a range of other symptoms such as depression and other mood disorders,
and social maladjustment. The emergence of these two sub-types across two disorders
supports the validity of these categories and the methodologies used.
The value of sub-typing along a wider range of dimensions was demonstrated
by Westen and Harnden-Fischer (2001). Taking into account personality variables in
addition to weight and eating disturbances, three distinct subgroups of eating
disorders emerged. The first cluster was a “high-functioning / perfectionist” group
that generally had a low level of pathology with high levels of self-critique. The
second cluster was “constricted / over controlled” type that primarily consisted of
Body Image and Cognitive Bias 14
Anorexia-like symptoms and a range of personality problems. The third type that
emerged was an “emotionally dysregulated / under controlled” group. This group
primarily consisted of Bulimia-like symptoms and was associated with extreme
personality problems.
The research summarised above is intended to be a brief overview to show the
utility and importance of sub-typing. The review has show that even within clearly
defined categories, not all individuals experience the same set of pathology.
1.5.2 Sub-Typing Non-Clinical Samples
The research presented above has looked at sub-groups within eating
disorders. There is very little literature assessing what groups, if any, exist in the
normal or non-clinical population. Only one study could be located on this topic
(Garner, Olmsted, & Garfinkel, 1983; Garner, Olmsted, Polivy, & Garfinkel, 1984) 1.
The aim of their paper was to explore the differences between women diagnosed with
the eating disorder Anorexia Nervosa and women experiencing weight preoccupation
drawn from a university and ballet sample. Women were classed as weight
preoccupied if they scored highly on the Drive for Thinness subscale of the Eating
Disorder Inventory (EDI; Garner, Olmsted, & Polivy, 1983). This sub-scale assesses
“preoccupation with body weight, excessive concern with dieting, and morbid fear of
becoming fat” (Garner et al., 1983, p. 13). A non-weight preoccupied group consisted
of women who scored on the lower end of the drive for thinness subscale. This group
was included to complete the range of weight preoccupation.
Very similar EDI scores were found in the groups characterised by high
weight preoccupation and Anorexia Nervosa. Only three subscales (Ineffectiveness,
Interoceptive Awareness, and Awareness) differentiated the two groups, with the
1 This paper was published by Garner, Olmsted, and Garfinkel (1983) in the International Journal of Eating Disorders. A similar paper by Garner, Olmsted, Polivy and Garfinkel was published the following year (1984) in the journal of Psychosomatic Medicine. Even though the two papers address slightly different research questions, the data appears identical. As such, for the purposes of this literature review, these papers will be treated as the one study.
Body Image and Cognitive Bias 15
‘Anorexic’ group scoring higher on these three. There were significant differences
between the high- and low-weight preoccupied groups on all subscales except
Interpersonal Distrust. These results indicate that the differences between the clinical
and non-clinical, yet symptomatic, group are minimal. It does indicate, however, that
there exists a set of symptoms that are found only in those with clinical levels of
eating disorders; differences that were only found by examining mean levels of
symptomology.
A cluster analysis was used to determine what subgroups would emerge within
the weight preoccupation categories. Garner et al. (1983) found that two distinct
clusters of weight preoccupation emerged. The first cluster represented a group of
weight preoccupied women who had elevated scores equal to the group with Anorexia
on all EDI subscales except Ineffectiveness. Thus, this subscale seems to be important
in distinguishing clinical from sub-clinical women. The second cluster represented
those women who experienced some symptomology on the Drive for Thinness, Body
Dissatisfaction, and Perfectionism sub-scales, but otherwise low scores on all other
subscales. Garner et al. (1983) noted that this group probably represents “normal
dieters” (p. 18) that pursue weight loss, and experience some level of body
dissatisfaction, yet who’s symptoms are not associated with any significant
psychopathology.
These findings add strength to the argument that non-clinical groups must not
be presumed homogeneous in nature. The findings from Garner et al. (1983) show
that there are groups of women who experience very similar symptomology to clinical
eating disordered groups. The inclusion of these women in control groups that are
presumed to be asymptomatic represents a serious methodological flaw.
1.6 Critique of the Literature
While the above literature is useful in demonstrating the multi-faceted nature
of body image disturbance, a number of significant limitations were identified and
Body Image and Cognitive Bias 16
addressed in this thesis. Problems were identified surrounding the limited way
classification has been applied to non-clinical samples and the general limitations of
using self-report measures.
The eating disorders of Anorexia Nervosa and Bulimia Nervosa have been
extensively researched, while there is comparatively little knowledge about body
image and body image disturbance in non-clinical populations. According to Ben-
Tovim and Walker (1991), the understanding of atypical levels of eating and weight
disturbances cannot be reached without an understanding of the more typical, normal
experiences. Previous research has typically viewed non-eating disordered individuals
as a homogeneous control group, without exploring the psychological make up of the
individuals comprising this group. As control groups are typically drawn from
university samples, and university women have been shown to experience high levels
of body image disturbance (e.g., Frost & McKelvie, 2004), there is a need for a
greater understanding of body image in non-clinical populations. Thus, the current
thesis addressed this limitation by expanding the knowledge of non-eating disordered
individuals.
The use of sub-typing has been used in limited way in past research. Sub-
typing along already defined categories such as “Anorexia” or “Bulimia” restricts the
emergence of groups showing mixed symptoms. This thesis did not constrain group
membership by using pre-defined categories but rather explored what categories
naturally emerged. Limited research has examined sub-groups within a non-clinical
sample. Again, this research sub-typed within an already defined group (i.e., weight
preoccupation). Finally, previous sub-typing was been along limited dimensions (i.e.,
eating disorder symptomology or personality variables). This project expanded this
line of research by classifying along a wider range of psycho-social variables.
A review of the literature indicated an array of variables that are important for the
understanding of body image. Traditionally, these are psychosocial variables
Body Image and Cognitive Bias 17
measured using self-report questionnaires. The crucial problem with this type of
measurement is the reliance on self-report methods for a problem that may not be
amenable to self reporting. Symptom severity may be downplayed purposively, or
certain aspects of body image disturbance may not be available to conscious
awareness (Couturier & Lock, 2006; Nisbett & Wilson, 1977; Vitousek, Daly, &
Heiser, 1991). Therefore, in addition to psychosocial variables, cognitive
methodologies were also used. The current thesis proposed that increased attention,
processing, and memory for disorder-consistent material serves to develop or maintain
the disorder (Mathews & MacLeod, 1994). Information regarding this biased
processing of information is not accessible using traditional paper and pencil tests, but
is best tested by using techniques that directly assess automatic attention and selective
memory. A limitation noted by some researchers (Vitousek & Hollon, 1990; Vasey,
Dalgleish & Silverman, 2003) is that the previous research has been driven by
measurement rather than theory. Thus, a solid framework for understanding body
image that recognises psychosocial and cognitive factors is needed. The application of
cognitive approaches, in addition to psychosocial variables, will allow a multifaceted
understanding of body image and body image disturbance.
1.7 Summary of Chapter
This chapter identified a number of psycho-social variables that have been
associated with body image disturbance. From this review, the variables of self-
esteem, BMI, perfectionism, eating disorder behaviours, drive for muscularity,
reasons for exercising, and general body image attitudes were highlighted as
potentially important constructs. Despite the range of variables identified, past
research has simply compared ‘high’ versus ‘low’ scorers on a particular construct.
The use of classification was then reviewed which showed how past research has
attempted to identified sub-groups of body image disturbance along a combination of
variables. However a number of limitations were noted in this research which
Body Image and Cognitive Bias 18
precludes an understanding of sub-groups within a non-clinical sample. Additionally,
a number of researchers have questioned the usefulness of self report measures when
assessing body image disturbance. Finally, limited research has been conducted on
male body image concerns. Therefore, in order to provide a more thorough and multi-
faceted understanding of body image in both males and females, both cognitive and
psycho-social variables were used in the current thesis.
Cognitive Bias and Body Image 19
Chapter Two: Theoretical Review: Biased Attention and Memory for Disorder Consistent
Material.
2.1 Introduction
A number of researchers have argued that body image disturbance represents a
form of cognitive bias (Sarason, Sarason, & Pierce, 1994; Vitousek & Hollon, 1990;
Williamson, 1996). A range of cognitive distortions have been noted in women with
eating disorders. Women with Anorexia Nervosa and Bulimia Nervosa hold a set of
negative attitudes and beliefs around food and body shape that have been implicated in
not only the development, but also in the maintenance of these disorders (Dobson &
Dozois, 2004; Sarason et al., 1994). Research has shown that individuals who are chronic
dieters become obsessed and preoccupied with food and eating, and show hypervigilance
towards food (Lee & Shafran, 2004). Individuals with extreme body dissatisfaction will
report seeing themselves as either larger (women; Tiggemann & Lynch, 2001), or less
muscular (men; Pope et al., 2000) than they are currently. These findings implicate the
role of biased cognitive processing in body image disturbance.
In order to provide objective measures of this biased processing, paradigms such
as the Stroop task (Channon, Hemsley & de Silva, 1988), dot probe task (Boon,
Vogelzang, & Jansen, 2000), dichotic listening task (Schotte, McNally, & Turner, 1990),
and incidental memory task (Unterhalter et al., 2007) have been adapted for use from the
wider cognitive literature. Studies that focus on biased encoding examine how self-
relevant information is processed. The time taken to respond to such stimuli is measured
and considered to be related to the salience or personal relevance of the information
(Ingram & Reed, 1986). It is proposed that threatening information has a lowered
Cognitive Bias and Body Image 20
threshold for awareness receives disproportionately more attention (Williams, 1988).
Studies that focus on biased retrieval typically use incidental memory tests as an indirect
measure of the degree of elaborative processing the information has received (Ingram &
Reed, 1986). In evolutionary terms, this rapid detection and recall of threat information
meant survival for a species (Beck & Clark, 1997).
If biased cognitive processing does underlie body image disturbance, then it’s
important to determine that the processing is indeed selective for certain types of
information. According to MacLeod (1996) one way to test this is to measure
performance on a simple task in the presence of different types of distracters. Neutral
distracters or stimuli that have little importance to the individual should not impede task
performance. The presence of more threatening distracters produces a shift in attention
toward this distracter and away from the primary task. This division of attention results in
decreased task performance (MacLeod, 1996; Sarason et al., 1994). One of the most
common techniques to measure this division of attention has been the Stroop task (Ball et
al., 2004). A detailed discussion of the Stroop task and how it has been adapted as a
measure of psychopathology is provided in Chapter Three.
Individuals with a high level of body image disturbance may view stimuli related
to negative appearance and/or food as threatening. For instance, dieters are expected to
avoid foods with a high fat content and instead eat foods with a lower caloric content
(Huon & Brown, 1996). When food or appearance related distracters are presented,
performance deficits on a primary task may be experienced by those with higher levels of
body image disturbance. It may be that those with Eating Disorders, or higher levels of
body image disturbance, have difficulty in ignoring such information. Moreover, this
Cognitive Bias and Body Image 21
interference effect is selective in nature, in that performance for emotionally neutral
information should not be affected.
2.2 Key Theories
Many of the theories to be reviewed regarding biased processing implicate
schemas as responsible for selective attention and memory. Schemas can be viewed as
cognitive stores of information that serve to simplify and guide the processing of further
schema-consistent information (Winfrey & Goldfried, 1986). Schemas may be
conceptualised as similar to memories or the organisation of knowledge and experiences
that one accumulates. Schemas can both facilitate or interfere with the processing of
information depending on the nature of the task (Winfrey & Goldfried, 1986; Vitousek &
Hollon, 1990). Schemas are proposed to guide both the encoding and retrieval of self
relevant information (Winfrey & Goldfried, 1986). The enhanced retrieval of schema
consistent information is proposed to result from the highly developed and interconnected
knowledge structures found in schemas (Winfrey & Goldfried, 1986). More detail on the
role of schemas in biased processing is now provided in the theoretical review.
2.2.1 Markus’s Self-Schema Theory
According to Markus (1977), schemas represent cognitive stores of information
that serve to process self-relevant material. As a person cannot attend to every aspect of
their environment, schemas determine what information a person will attend to in any
given situation. The development of these schemas serves to selectively filter information
and “determine whether information is attended to, how it is structured, how much
importance is attached to it, and what happens to it subsequently” (Markus, 1977, p. 64).
The information that a person will attend to is dependent upon which attributes that the
person deems important to their self-concept.
Cognitive Bias and Body Image 22
In an experimental test of self-schemata, Markus (1977) concluded that people
who place more importance on a particular dimension (schematic) will process
information in a different manner to people for whom that dimension is irrelevant
(aschematic). Schematics showed significantly faster response times to material directly
related to their schema (that is, facilitated processing), and longer response times to
indirectly related material (interference). What these findings suggest is that there are
systematic differences in the processing of information about the self between schematic
and aschematic individuals.
The way most people view themselves will undoubtedly have a body image
component. However, there will be differences in the importance attributed to this aspect
of the self. Markus et al. (1987) proposed that there are at least two types of self-schemas:
universal and particularistic schemas. Universal schemas are those that everyone holds to
some degree or another. For example, everyone is aware of what they look like, but only
in certain people will physical appearance be an important aspect of self-concept. These
people hold a particularistic schema for physical appearance.
Markus et al. (1987) explored the self-schema of body weight to see its effects on
the processing of weight-relevant information. According to Markus et al. (1987), a body
weight schema is an example of both a universal and particularistic schema. It can be
expected that everyone has at least a rudimentary schema concerning their bodies. For
some people, body weight will be an integral component of their self-concept and they
will selectively attend to and process weight related information in the environment.
These people can be considered schematic for body weight, while those for whom body
weight isn’t important can be considered aschematic (Markus et al., 1987).
Cognitive Bias and Body Image 23
Evidence for self schemas have been noted in depression (Segal, Hood, Shaw, &
Higgins, 1988; Segal & Vella, 1990), and for assertiveness (Bruch, Kaflowitz, & Berger,
1988). Both of these studies, despite the use of different methodologies, have concluded
that schematic individuals processed self-relevant information differently than
aschematics.
2.2.2 Williamson et al. Information Processing Model
Williamson, Stewart, White, and York-Crowe (2002) describe a cognitive
information-processing model that describes how people with body image disturbance
process information. This model is presented in Figure 1.1. Central to this theory is the
notion of schemas which guide the processing of information. For instance, a body shape
schema will process body shape-related information. The more a schema is activated, the
denser the associated networks become within the schema. These networks link together
memories, and can also become associated with certain situations or cues. Thus a schema
can be activated by certain stimuli. The result of this activation is cognitive bias in
susceptible people. This may be evidenced as selective attention where only certain
aspects of the stimuli are attended to (such as selective interference in a Stroop task), or
selective memory (where body-related words are recalled more than neutral words). The
result of this selective attention is increased negative affect (Williamson et al., 2002). For
example, a woman who has a highly developed body schema may attend to stimuli in the
environment that are associated with fatness. As such, she experiences changes in mood
including increased depression, and increased body dissatisfaction. These changes may
feed back to the body schema, wherein negative affect is then associated with fatness
related stimuli.
Cognitive Bias and Body Image 24
Figure 1.1: Williamsons’ et al. (2002) cognitive information processing model of body
image disturbance.
2.2.3 Thompson et al.’s Cognitive Processing Model
The presence of a body image schema which helps to organise information related
to one’s view of his or her physical appearance is central to this perspective (Thompson
et al., 1999). These body image schemas serve to interpret information in the
environment, but may do so in a biased manner. If the person has a negative view of their
appearance, then they may misinterpret information in a social situation, and concepts in
their mental encyclopaedia or lexicon such as “fat” take on negative connotations such as
‘bad’. The body image schema may dominate other larger domains such as views of the
self, so that physical appearance becomes the main determinate of self-worth. This
perspective predicts that physical appearance related information will be processed in a
Cognitive Bias and Body Image 25
facilatatory or inhibitory manner. Either way, the presence of a negative body image
schema will affect “the normal input, storage, and retrieval processes of the mental
encyclopaedia” (Thompson et al., 1999, p. 272).
2.2.4 Vitousek and Hollons’ Schema Framework
Building upon the work of Markus and colleagues (Markus et al., 1977, 1987) on
schemata, Vitousek and Hollon (1990) proposed a framework to understand the cognitive
processes of women with Anorexia Nervosa and Bulimia Nervosa that emphasised a
central role of schemata. These researchers propose that the persistence of eating
disorders can be partly explained by the presence of organised cognitive structures. These
schemas influence the thought content, emotional experience, interpretation, and
behaviour of eating disordered individuals because of the close association between
issues of weight and self-concept.
Vitousek and Hollon proposed three types of schemata relevant to the eating
disorders: self-schemata, weight-related schemata, and weight-related self-schemata. The
notion of self-schemata is consistent with Markus’ ideas that these schemata serve to
process information regarding the self. Weight-related schemata process information
relevant to the stereotypes associated with varying weight status. However, these views
are not distinctive to eating disordered individuals, and may be more reflective of cultural
ideals of weight. It is proposed though, that these views are more emotionally charged
and elaborate in individuals with eating disorders. Weight-related self-schemata represent
the specific concerns of the eating disordered, as they process information about the self
in terms of weight. This is a more enduring schemata, while fleeting thoughts about body
weight can be influenced by environmental factors.
Cognitive Bias and Body Image 26
In order to determine the presence of these schemata, Vitousek and Hollon (1990)
proposed a number of indicators indicative of schemata. Only those relevant to the
current research will be reviewed here, but the interested reader is directed to the work of
Markus and colleagues (1977, 1987), and Vitousek and Hollon (1990) for further
information.
One indicator is the ease and speed of information processing related to the
schemata. This has been typically assessed using the Stroop task which will be reviewed
in depth in the next chapter. Briefly, it is assumed that interference (typically longer
response times) when presented with body weight and shape words is reflective of the
core concerns of the individual. In addition to biases in attention, evidence for schemata
can also be inferred from memory biases. Selective memory for weight related
information serves to support the central role of weight concerns in the lives of eating
disordered individuals. Thus, the cognitive biases of selective attention and memory, are
all assumed to be indicative of core schemata that selectively seek out information
consistent with current concerns.
The preceding four theories indicate that schemas hold a central role in
understanding biased information processing. All of these theories have been developed
within the body image literature. Pertinent theories within the depression and anxiety
literature have also been identified that are expected to contribute to the understanding of
biased processing. These are briefly reviewed below.
2.2.5 Depression and Anxiety Models of Biased Cognitive Processing
Research examining biased attention and memory has proliferated within the
depression and anxiety literature. This literature is guided by strong theoretical
frameworks and carefully designed methodologies. Given that biased cognitive
Cognitive Bias and Body Image 27
processing is still a relatively new area within the body image literature, theories from the
depression and anxiety literature will be adapted. Just as negative affect material is salient
for those with depression, and social threat information is important within anxiety, food
and appearance related stimuli are anxiety-provoking within body image. In all cases, self
relevant emotional information is expected to produce biased cognitive processing.
Three of the most influential cognitive theories in the depression and anxiety
literature are those of Beck (Beck 1967; Beck & Clark, 1988), Bower (1981), and the
work by MacLeod and colleagues (e.g., Williams, Watts, MacLeod, & Matthews, 1988,
1997). Each of these theories and their applicability to understanding body image will be
explored in turn
2.2.5.1 Williams et al. integrative model. One of the more developed cognitive
theories of the role of emotion in depression and anxiety was proposed by Williams et al.
(1988, 1997). First, the distinction is made between priming and elaboration. Priming is
defined as an automatic process (a process that occurs rapidly without conscious
awareness) that activates the internal representation of a stimulus. This priming serves to
make that representation more accessible when only part of the stimulus is later
presented. For example, if the word “failure” is presented, activation will enhance
recognition (i.e., make it more readily accessible) if part of the word is later presented.
Elaboration however is a strategic process that requires conscious thought. It involves
linking new concepts together, or strengthening old connections, which also makes the
stimulus more retrievable. This elaboration process may be responsible for the negative
connotations that food and body shape take in those with severe body image disturbance.
One distinctive feature of this theory is that it can explain why biases in attention
do not always lead to biases in memory, a finding that other theories had difficulty
Cognitive Bias and Body Image 28
explaining. Williams et al. (1988, 1997) explain that the processing requirements of
selective attention tasks involve priming, while memory tasks require elaboration of
previously learnt material. Depending upon the amount of elaboration that occurred at
encoding, and the nature of the disorder (i.e., whether attention is directed toward or
away from the stimuli), enhanced or inhibited retrieval of previously viewed emotional
material may occur.
The model states that information received is subject to a pre-attentive ‘decision
mechanism’. This decision mechanism makes a judgement about the affective valance of
the stimulus that determines resource allocation. State anxiety can affect the output of the
decision mechanism. Williams et al. (1988, 1997) state that non-emotionally disturbed
people hold a protective response that will serve to deflect processing of the material
away. Thus, the negative information does not receive processing. Anxious individuals
however, allocate resources toward processing of the negative material at this pre-
attentive stage. Negative material is deemed to be a priority, and thus processed as such.
The process of resource allocation is affected by trait anxiety, reflecting a more
permanent manner of responding.
The increased resource allocation acts as a prime so that the word is more likely
to be reproduced at a later stage. Williams et al. (1988, 1997) state that this priming will
occur irrespective of any elaboration that may also occur.
Elaboration occurs at the strategic stage of encoding. It involves making
associations between the stimulus and other items in memory. A further decision
mechanism evaluates the affective valence of the stimulus, as in the pre-attentive stage.
More elaborate encoding between the stimulus and associated concepts will occur if extra
resources are allocated, which serve as cues for later retrieval. The effects of elaborative
Cognitive Bias and Body Image 29
coding differ between disorders, such that conditions is which attention is directed away
from the stimulus (such as phobics’) will not involve elaboration with the feared
stimulus, which serves to make it less retrievable.
The distinction between automatic and strategic processing is also relevant to the
retrieval of the information from memory. Williams et al. (1988, 1997) suggest that
certain types of emotional states can affect both the passive (the information is recalled
without conscious awareness) and active (active search strategies are employed) recall of
information. Accordingly, anxiety is associated with passive recall through priming,
whereas depression affects strategic retrieval.
One of the strengths of this approach is the dissociation between priming and
elaboration whereby a bias may occur with one, but not the other. Other theoretical
approaches in depression and anxiety have not made this distinction which may be
important for understanding the differences between the two disorders. It also provides a
means for understanding the interaction between state and trait anxiety. There may be
differences in the resource allocation in response to threat between those with high and
low trait anxiety. For example, it may be that individuals with high trait anxiety respond
by allocating additional resources toward processing of the threat, while individuals with
low trait anxiety direct attention away from the threat (Williams et al., 1988, 1997).
State anxiety can produce selective processing of threat related material in the
environment. This is similar to the diathesis-stress models of mental disorders, wherein
persistent maladaptive attention toward threat (diathesis) coupled with state anxiety
inducing selective attention (stress) can result in pathological levels of anxiety. The
interplay of state and trait anxiety can be seen as cyclical in nature – selective attention to
Cognitive Bias and Body Image 30
threat in the environment results in a perception of the world being threatening in nature,
which serves to reinforce the disproportionate attention toward threat.
This theory is one of the most comprehensive models that seek to explain both
anxiety and depression, and is generally supported as a preliminary understanding of the
disorders. The main utility of this model in the current case, is how well it can be applied
to understanding body image. Given that research examining cognitive bias in body
image disturbance is still relatively new, it is difficult to ascertain the applicability of this
model to body image. For example, it not clear whether attention is directed toward or
away from, stimuli relating to negative appearance and food. Just as words signifying
social embarrassment present a threat for individuals with panic disorder (Ehlers,
Margraf, Davies, & Roth, 1988), it may be argued that words surrounding negative
appearance are threatening for those with high levels of body image disturbance. This
thesis examined the applicability of Williams et al’s model within body image
disturbance.
2.2.5.2 Beck’s schema theory and content-specificity hypothesis. The central role
of schemas is also emphasised in Beck’s influential theories of depression and anxiety
(Beck 1967; Beck & Clark, 1988). These theories state that processing of information is
guided by schemas. Information consistent with existing schemas is sought out in the
environment, and this information receives additional elaboration and encoding,
compared to schema-inconsistent information. For example, depressed individuals hold
schemata that contain negative information about the self, the world, and the future.
Attention is then drawn toward negative information in the environment consistent with
these schemata. Within anxious individuals the dominant concern is a focus on
threatening information. Threatening stimuli in the environment are attended to,
Cognitive Bias and Body Image 31
interpreted, and later recalled in a biased manner. According to Beck (1967, 1991), these
schemas remain dormant between periods of depression or anxiety, until they are
triggered by environment sources. These schemas then become ‘activated’ and guide the
processing of self-relevant information in a maladaptive way.
The content-specificity hypothesis was developed to explain the differences
between anxiety and depression in the types of information that is processed (Beck &
Clark, 1988). This hypothesis states that differences between anxiety and depression are
found in the types of information to which is primarily attended (Greenberg & Beck,
1989). That is, depressed individuals will selectively process negative information, while
anxious individuals will selectively process information related to threat. Support for the
content-specificity hypothesis was found for depression, where individuals with
depression recalled significantly more negative stimuli, and significantly less positive
stimuli, than non-depressed individuals (Greenberg & Beck, 1989).
2.2.6 Bower’s Network Theory
Bower’s network theory (1981) built upon Collins and Quillian’s (1969) semantic
network model. Both theories propose that concepts are stored in memory as nodes.
Similar concepts or nodes are linked together with other concepts through pathways.
When a certain node is activated by information in the environment, then the pathways
connected it to other nodes are also activated; a process known as spreading activation.
A distinctive feature of Bower’s model is the recognition that emotions are also
represented as nodes within the network. When an emotion such as depression is
experienced the corresponding emotional node becomes activated along with connected
nodes. This spreading activation makes information related to the particular mood
disproportionately more accessible. For example, the individual becomes more aware of
Cognitive Bias and Body Image 32
concepts relating to depression such as “failure” and thoughts of “I am no good”. This
priming effect is thought be an automatic process, such that the individual may not be
consciously aware of the trigger for the emotion. This theory helps to explain the mood
congruent findings in the cognitive literature such as mood-dependent recall, in that
mood activates or primes certain networks of nodes. Recall is better for mood congruent
information as it’s more salient in memory (Winfrey & Goldfried, 1986).
According to Markus et al. (1987) everyone holds schemas or knowledge stores about
their appearance, however there are differences between individuals in the strength of
these cognitive stores, how elaborate they are, and the ease of accessibility of these
schemas. It may be that schematic individuals have appearance schemas that are closely
linked in memory to negative emotions and views of the self. These schemas may be
readily accessible because they are linked to so many other concepts in a person’s
memory. For example, a woman who is dieting may have a strong and close link between
concepts of “fat” and “food”. Further, these concepts may also be strongly linked and
activation of the concepts primes the activation of the other.
According to MacLeod and Rutherford, (1992) the benefit of Bower’s theory
over Beck’s theory is the distinction between state and trait levels of anxiety. According
to Rofey, Corcoran, and Tran, (2004) “both [models] propose that emotional stimuli
attract disproportionately more processing resources due to the activation of specific
knowledge structures representing threatening information” (p. 42). The key distinction is
that Beck identifies cognitive bias as associated with enduring trait levels of anxiety,
while Bower proposes that state levels of anxiety can influence processing. Individuals
with a clinical level of a particular disorder are likely to experience both state and trait
levels of disturbance. Non clinical individuals however will not be experiencing either
Cognitive Bias and Body Image 33
state or trait levels of disturbance, unless specifically primed. MacLeod and Mathews
(1988) found that the relationship between state and trait anxiety was ambiguous. In an
attempt to disentangle the effects of state and trait anxiety, students high and low on trait
anxiety were compared at two points: once when state anxiety was low (early in a
university semester), and again when state anxiety was high (before an important test). It
was found that the effects of state anxiety on cognitive performance differed between
those students with high and low trait anxiety. When state levels of anxiety were low,
neither group showed selective attention on a probe detection task. However, when levels
of state anxiety were high, the students with high trait anxiety showed selective attention
towards threatening information, while those students with low trait anxiety showed
avoidance of the material.
Williams et al. (1988) note a number of findings that are difficult to explain under
Bower’s theory. First, Williams notes that not all types of mood have the same effects on
processing. Attention and memory for positive and negative information are different, in
that negative can sometimes result in reduced elaboration and recall. Additionally, even
when considering different types of negative mood (such as depression and anxiety),
differences are noted in attention and memory. Second, Williams et al (1988) notes that
viewing moods as nodes may be too simplistic. Moods are more diffuse than cognitions,
and often gradually increase in intensity rather than being an ‘all-or-none’ activation.
2.2.7 Encoding of Personal Information
This theory is similar to the classic Levels of Processing work (Craik & Lockhart,
1972; Craik & Tulving, 1975) which showed that information placed in context benefits
from greater elaboration and therefore better recall. A number of researchers have
implicated the importance of selecting personally relevant and meaningful stimuli
Cognitive Bias and Body Image 34
(Rogers, Kuiper, & Kirker, 1977; Ulterhalter, Farrell, & Mohr, 2007; Wingenfeld et al.,
2006). For example, Rogers et al. (1977) found that the presentation of personally
relevant information resulted in more stable memories. Rogers et al. used an incidental
memory task where participants were asked questions about a set of words that required
different types of processing ranging from shallow to deep. Their results showed that
participants recalled significantly more adjectives that they had previously rated as
describing them. However, even adjectives that participants rated as “not like them”
benefitted from enhanced recall, indicating that information receives increased processing
in a self referent encoding task. The self referent encoding task also produced higher
recall than words in the semantic condition. Therefore, understanding a word and putting
it into context results in inferior recall compared to applying the word personally. It
appears that simply thinking about how the concept relates to you, regardless of whether
it does or not, results in enhanced recall.
When applied to an Emotional Stroop task, this theory states that words which are
both personally relevant and emotionally valanced will produce greater interference than
words that are simply of an emotional nature (Cohen, Dunbar, & McClelland, 1990;
Wingenfeld et al., 2006). For example, Wingenfeld et al. found that participants were
slower to respond to personally relevant words compared to negatively valanced or
neutral words. This theory highlights the importance of carefully selecting relevant word
stimuli, an issue which is further elaborated in Section 3.4.3.5.
2.3 Integration of Theories and Summary of Theoretical Review Chapter
The purpose of this chapter was to provide a theoretical basis for the
understanding of how biased information processing within psychopathology occurs.
Theoretical development regarding biased processing has occurred more within the
Cognitive Bias and Body Image 35
depression and anxiety literature, hence it was deemed useful to consider these models.
The applicability of these models to body image is yet to be tested.
All of the theories reviewed implicate the central role of schemas in guiding
attention. Schemas determine what information is attended to or avoided, the importance
placed on this information, and the amount of elaboration the information receives.
Markus’ self schema theory (Markus et al., 1977, 1987) was the first to identify and
empirically test weight and appearance related schemata. Vitousek and Hollon (1990)
incorporated these ideas into a more comprehensive model of how schemas guide
processing in eating disorders. The central role of schemas is also recognised by
Williamson et al. (2002) and Thompson et al. (1999), with Williamson developing a
model how schemas may be activated by various internal and external cues. Models from
the depression and anxiety literature were explored, and these models highlighted the
important distinction between priming and elaboration (Williams et al., 1988, 1997), and
identified that attention and memory biases occur for information that is self referential
(Rogers et al., 1977) and related to current concerns (Beck & Clark, 1988). The model of
Bower (1981) suggests that memory bias is related to the strength of interconnections in a
network of associated concepts. Women with body image concerns may develop a highly
elaborate set of associations between sense of self, appearance, and mood, such that
negative feelings about one’s appearance become integrated with general feelings of self-
worth. Bower’s model, in addition to subsequent work by MacLeod and Mathews (1988),
implies that state and trait levels of disturbance can influence memory.
To summarise, threatening information is proposed to receive disproportionately
more attention and memory. Exposure to self relevant, content-specific information
activates congruent self-schemata that incorporate the material into already existing,
Cognitive Bias and Body Image 36
dense elaborations in memory. The associated biased attention and memory for this
material serves to confirm the processing biases of the schemata. It is therefore
hypothesised that biased attention and memory for body image stimuli will be found in
individuals with high levels of body image disturbance because of their highly developed
schemas around weight and appearance. The following chapter reviews the evidence for
these theories using an Emotional Stroop task.
Cognitive Bias and Body Image 37
Chapter Three: Attention and Memory Bias for Body Image Information
3.1 Overview of Chapter
The purpose of this chapter is to review the literature on biased attention and
memory for body image information. A review of the literature will demonstrate that the
Stroop task is the most commonly used method for assessing selective attention. Despite
the Stroop tasks’ wide usage, the existing research suffers from a number of important
limitations which precludes a thorough understanding of how cognitive biases apply to
non-clinical samples. The limitations identified from past research informed the
development of an emotional Stroop task and incidental memory task assessing a wide
variety of body image concerns for both males and females.
3.2 Background to the Research
As Chapter Two demonstrated, over the past 20 years there has been an increased
recognition of the role that cognitive processes play in the understanding of body image
disturbance. The adaptation of methodologies from cognitive psychology has provided a
unique set of tools to assess cognitive disturbances. According to Williamson (1996), “of
the new paradigms from which we might reformulate the concept of body image, I
believe that the cognitive, or information-processing, perspective has the most potential”
(p. 47-48). According to a cognitive framework, psychopathology is thought to arise from
biased processing of negative information. It’s proposed that concerns an individual hold
result in automatic and biased processing of such information in the environment
(Williamson, 1996). For example, it has been noted that individuals experiencing
depression are more likely to notice and remember negative information in their
environment, as opposed to positive information (Watkins, Mathews, Williamson, &
Fuller, 1992). This increased attention, processing, and memory for disorder-consistent
Cognitive Bias and Body Image 38
material may help to develop or maintain the psychopathology (Mathews & MacLeod,
1994). Applied to body image disturbance, a person who views themselves as too fat may
be more likely to notice an advertisement of a thin attractive model. This automatic
processing could then result in negative mood and more feelings of fatness within the
individual.
Limited information regarding this biased processing of information is accessible
using traditional paper and pencil tests, which may be open to distortion as they rely on
self report (Beck, Stanley, Averill, Baldwin, & Deagle, 1990; Cassin & von Ranson,
2005; Vitousek, Daly, & Heiser, 1991). Thus, selective processing of disorder-relevant
information is best tested by using techniques that directly assess automatic attention and
the accessibility of emotional information. Research has shown the Stroop task to be a
valid indicator of these biases in attention. In fact, MacLeod (1992) has termed it “the
‘gold standard’ of attentional measures” (p. 12). Measures of biases in attention are
expected to significantly add to the understanding of body image and body image
disturbance.
3.3 The Stroop Task as a Measure of Attentional Bias
The Stroop task (Stroop, 1935) is an example of how a methodology borrowed
and adapted from cognitive psychology has provided an enhanced understanding of a
range of disorders. In the original Stroop task, a range of words were presented and the
participants’ task was to name the colour of ink the word was written in as quickly as
possible. In the colour-consistent condition, there was a match between the colour the
word was written in, and the meaning of the word. For example, the word “blue” would
be presented in blue ink, and the correct response is “blue”. This task presented very little
cognitive demand for participants, and reaction times were typically fast. The colour-
Cognitive Bias and Body Image 39
inconsistent condition provides more of a challenge and division of resources for
participants. This time there is a mis-match between the meaning of the word and the
colour used. For example, the word “blue” is now presented in red ink, and the correct
response would be “red”. Delayed reaction times are typically found, as the semantic
meaning of the world detracts attention away from the naming the colour. That is,
participant’s attention was drawn to the meaning of the written word because this is an
automatic process in reading. Participants found it difficult to ignore the most salient
stimuli, the words, even though they were instructed otherwise. This has become known
as attentional bias.
The original Stroop task showed enormous success as a measure of bias in
information processing (Ball et al., 2004). Since the original paper, over 70 years ago,
research using the Stroop task has proliferated, and has been applied to a diverse range of
areas.
3.4 The Emotional Stroop Task
Clinical psychology has since applied the Stroop task to a range of disorders as a
measure of attentional bias. Instead of the names of colours being presented, an
Emotional Stroop task presents words related to a particular disorder. For example, an
individual experiencing a spider phobia may be highly sensitive to words such as “hairy”
and “spider”. Despite being instructed to ignore the meaning of the words and simply
name the coloured ink, attention is automatically drawn to the meaning of the stimuli,
with difficulty experienced ignoring some types of words. Words such as “hairy” are
expected take on a particular salience wherein additional resources are allocated for their
processing. The reaction time for these disorder-related words are expected to be slower
than for neutral words, as difficulty is experienced ignoring the meaning of the words. As
Cognitive Bias and Body Image 40
neutral words (such as “table”) are not expected to hold any emotional relevance, the
colour naming task should be easier, and the reaction times for these words quicker. As
the neutral words are typically matched to the target words on a number of important
dimensions (e.g., length, frequency of occurrence in the English language), any
differences in reaction times is due to the emotional salience of the words. Evidence of
attentional bias can be measured two ways: either as the time difference between colour-
naming the target words compared to the neutral matched words (i.e., a within-subjects
design), or the time difference between disordered and non-disordered participants on the
target words (i.e., a between-subjects design). Any difference in reaction times to target
versus neutral words is known as interference. Response to the experimental words can
either be faster than neutral words (facilitation) or slower (interference).
Indeed, research has shown that individuals with a spider phobia do show longer
reaction times when asked to colour name spider related word compared to general threat
words, or colour-conflicting Stroop words (Watts, McKenna, Sharrock, & Trezise, 1986).
This unique effect of spider-related words as compared to general threat words supports
the notion that biased attention is limited specifically to disorder-consistent material; that
is, there is specificity in interference.
Interference effects, as measured by the Stroop task, have been found in a range
of different disorders such as depression (Gotlib & McCann, 1984), anxiety (Matthews &
MacLeod, 1985; MacLeod & Rutherford, 1992) and morbid jealousy (Intili & Tarrier,
1998). For example, Ehlers, Margraf, Davies, and Roth (1988) found that individuals
with both clinical and non-clinical panic disorder showed longer reaction times to colour-
name threat related words than neutral words. Chapter Two proposed that this
Cognitive Bias and Body Image 41
preferential attention for information is the result of highly developed schemas developed
around the person’s concerns.
3.4.1 The Emotional Stroop Task with Eating Disorders
The Stroop task has also been applied to Eating Disorders, and to a lesser extent,
eating disturbances in non-clinical samples. This task provides a direct and objective test
of selective attention toward eating, shape, and weight related stimuli. According to Ben-
Tovim, Walker, Fok and Yap (1989), the Stroop task is “cheap, simple to apply, easy to
score, and only takes little time” (p. 686). Additionally, Dobson and Dozois (2004) in
their meta-analysis of the use of the Stroop task in eating disorders conclude that it
provides a useful task for examining attentional bias.
The Stroop applied to body image presents categories of words relevant to the
unique concerns of those with eating disorders, namely food words and body
shape/weight words. For example, participants may be asked to colour-name such words
as “fat”, “chips”, or “ugly”. Women who view their appearance negatively, or who
consistently avoid fatty foods would be expected to show an interference effect. As with
other disorders, interference is measured as increased latencies to colour-name target
words. Given the higher incidence of eating disorder in women than men (APA, 2000),
very few studies have used male participants. Therefore the research reviewed below
focuses exclusively on interference effects in females, with a discussion of possible
effects in males provided under the “Limitations” section 3.4.3.
Early studies into interference effects focused on comparing women with eating
disorders to a control group of women on colour-naming of food words and body shape
words. Channon et al. (1988) found that while both groups showed interference effects
for the food words (i.e., longer to colour name the food words than control words), the
Cognitive Bias and Body Image 42
effect was larger for the women classified as Anorexic. No interference effects were
noted for the body shape words in either group. A similar result was found by Ben-Tovim
et al. (1989) who compared Eating Disordered and non-disordered women on colour-
naming of food words and shape words. The results showed that all the women showed
some interference for food words and shape words. The women with Bulimia Nervosa
and Anorexia Nervosa however, took significantly longer to colour name the food words
than did the non-disordered control group. Additionally, the women with Bulimia
Nervosa also showed a significant interference for shape words. Thus, while evidence of
selective attention for body image related information was found in all women, it was
those women with Eating Disorders who showed larger effects.
Collectively, these early studies demonstrated the usefulness of applying a Stroop
methodology to understanding body image concerns. The presentation of stimuli related
to the core concerns of women with Eating Disorders received increased processing
compared to neutral information. Identification of these automatic processing biases may
help to elucidate the ways in which Eating Disorder are developed and maintained.
Additionally, these early findings also suggest that processing biases are not limited to
those Eating Disorders, but may also be found in other women, albeit to a lesser extent.
Since these original studies, research has continued to examine attentional bias in
individuals with Eating Disorders compared to control non-clinical samples. Studies have
either compared the eating disorder groups to each other, or to control groups. The
majority of research has focused on clinical Eating Disordered samples. As such, the
literature focusing on clinical groups will be reviewed prior to the literature concerning
non-clinical groups.
Cognitive Bias and Body Image 43
Women with Bulimia Nervosa have shown Stroop interference for eating-,
weight-, shape-, and emotion-related words compared to control groups (Cooper,
Anastasiades & Fairburn, 1992; Fairburn et al., 1991; Jones-Chester et al., 1998; Lokken,
Marx, & Ferraro, 2006). Women with Anorexia Nervosa have evidenced selective
interference for food words (Channon et al., 1988; Green, McKenna, & de Silva, 1994;
Sackville et al, 1998) and body shape words (Green, Corr & de Silva, 1999; Sackville et
al, 1998) as compared to control groups of women. Sakville et al. (1998) expanded the
types of Stroop words typically used and found that women with Anorexia Nervosa show
selective interference for a wider range of stimuli than previously identified. As well as
the usual high calorie food words and the negative weight words, additional categories of
positive weight words, low calorie food words, and positive and negative emotion words
were used. Compared to the non-disordered control group, the women with Anorexia
Nervosa showed a significant interference for negative and positive shape words, a trend
for high calorie food, and no differences for low calorie food or the emotion words.
These results indicate that Anorexia Nervosa may be associated with interference for a
wider range of stimuli, both positive and negatively valanced, than previously thought.
Studies that have included both women with Anorexia Nervosa and women with
Bulimia Nervosa allow finer discrimination between the processing biases in these
disorders. The findings seem to be consistent in suggesting that Eating Disorder groups,
when compared to an assumed homogenous control group, show selective interference.
The findings are inconsistent however, regarding the specificity of the type of
interference and the type of disorder. The most consistent finding is that both groups
show a selective interference for words related to food and eating (Ben-Tovim, et al.,
Cognitive Bias and Body Image 44
1989; Cooper & Todd, 1997; Jones-Chester et al., 1998; Perpina et al., 1998). This
confirms the central role that eating and food has in these disorders.
The effects of body size/shape words are less consistent. Some studies have found
interference in women with Anorexia Nervosa and Bulimia Nervosa, (Jones-Chester et al,
1998), other studies report effects in women with Bulimia Nervosa only (Ben-Tovim et
al., 1989) or Anorexia Nervosa only (Cooper & Todd, 1997). Yet other studies, (Perpina
et al., 1998) have found that neither women with Anorexia Nervosa nor Bulimia Nervosa
have shown interference for body/shape words. These inconsistent results may be due to
differences in the type of stimuli used. Very few studies use the same set of words in the
Emotional Stroop task. Recently, attempts have been made to develop a standardised list
of words to overcome this limitation (Cassin & von Ranson, 2005). The problems with
the stimuli used in past research are examined in detail under the “Limitations with
methodology” in section 3.4.3 of this chapter.
To date, only three studies have examined the role of emotion-related words such
as “anxious” or “depressed” within body image disturbance. The comorbidity between
mood disorders and eating disorders leads some researchers to question whether
interference effects are a result of body image concerns, or associated mood disorders
(Cooper, 1995). Sackville et al. (1998) found no differences in interference effects
between women classified as Anorexic, or high and low dietary restraint, although a
mean level interference increased with increasing symptomology. Jones-Chester et al.
(1998) found that only women with Bulimia Nervosa showed interference for these
emotion words, while no interference effects were noted within the non-clinical or
“Anorexic” groups. However, it should be noted that these interference effects were only
found when a blocked presentation of words was used, and no interference effects were
Cognitive Bias and Body Image 45
noted in any groups when the emotion words were mixed with other types of words.
Finally, Seddon and Waller (2000) found that younger women (< 21 years of age) with
high bulimic symptomology showed a tendency for avoidance of the information (i.e.,
quicker reaction times to the material), while older women (> 21 years of age) showed
greater attention toward this information. Therefore it appears that selective interference
for negative emotion information may be more specifically related to Bulimia Nervosa,
or Bulimia-like symptoms than to general body image disturbance. This finding does
need to be considered within the results of general research examining the selective
processing of mood-related information which has suggested that people automatically
attend to negative, rather than positive information (Smith et al., 2006). Clearly, more
research is needed to ascertain the nature of these differences.
Given the inconsistent findings of the literature reviewed above, and the recent
increase in papers using the Stroop task, two recent meta-analyses have emerged. Based
on all available Stroop studies investigating Eating Disorders from 1935 to May 2001,
Dobson and Dozois (2004) concluded that attentional bias can be found in, and is
confined to, Eating Disordered samples. The results showed a trend for women with
Bulimia Nervosa to show interference across a range of word categories, while the results
for women with Anorexia Nervosa were more inconsistent, but interference seemed to be
most prominent for body shape related words. This meta-analysis concluded there were
typically no differences between those with dieting concerns and non-clinical samples on
the body Stroop.
One year later, another meta-analysis was published (Johansson, Ghaderi, &
Andersson, 2005a) which used a slightly different selection criteria for study inclusion
and came to a different conclusion than did Dobson and Dozois. Twenty-seven studies
Cognitive Bias and Body Image 46
examining food/eating and/or body weight/shape words from 1978 to 2003 that met a
number of criteria were included. Comparisons were made between different word
categories, and between women with Anorexia Nervosa, Bulimia Nervosa, non-Eating
Disordered yet symptomatic groups, and controls. While Dobson and Dozois found no
interference effects in the non-clinical groups, Johansson et al found evidence of small
interference effects. It was concluded that all groups showed longer latencies to colour-
name target versus neutral words, but the effect size was small in the non-clinical groups,
and medium in clinical groups. The Eating Disordered women did show more
interference for all target categories than the non-clinical women. These differences may
be due to the studies included in the analysis, as often the psychological characteristics of
non-clinical control groups are not reported.
These meta-analyses, while supporting the existence of interference effects in
Eating Disordered samples, have not been able to provide a clear answer to whether
attentional biases are found in non-clinical groups. Additionally, given the number of
significant methodological limitations in past research (soon to be described under
section 3.4.3 “Methodological Limitations” of this chapter), any conclusions reached
must be tentative. Clearly, the question of whether biased cognitive processing is found
within non-clinical groups warrants further research.
3.4.2 The Emotional Stroop Task with Non-Clinical Samples
The majority of studies have used non-clinical samples primarily as a control
group against which to compare women with Anorexia and/or Bulimia Nervosa. As such,
these control groups are assumed to be homogenous in nature, when in fact they may
have elevated, albeit not clinical, levels of body image disturbance. Few studies have
specifically focused on non-disordered or sub clinical samples taking into account their
Cognitive Bias and Body Image 47
levels of symptomology. In Williamsons’ (1996) review of attentional bias using the
Stroop task, it was concluded that interference was not unique to those with Eating
Disorders. However, it is restricted to those with concerns about their appearance and/or
weight. Thus, the lack of research examining interference effects in non- and sub-clinical
groups is unfounded. The following section reviews the existing evidence of selection
attention for body image related information in non- or sub-clinical samples.
Studies that have looked at symptoms rather than diagnosis have generally
supported selective interference in non-clinical, but symptomatic samples. For example,
Black, Wilson, Labouvie, and Heffernan (1997) found that women classified as restrained
eaters, unrestrained eaters, and Bulimic could not be differentiated by their responses to
weight/shape words. All groups showed interference compared to neutral words. Perpina,
Hemsley, Treasure, and de Silva (1993) found that women who scored highly on restraint
or drive for thinness had comparable colour-naming interference to women with
Anorexia and Bulimia. Drive for thinness was associated with body concerns, while
restraint was associated with food concerns. Cooper and Fairburn (1992) found that
symptomatic dieters (women who had shown eating disorder symptoms previously) along
with Anorexic and Bulimic groups showed significant interference for food words
compared to the neutral words. Thus, eating disorder symptomology may be more
important than actual diagnosis.
However, not all studies have been able to show differences between clinical and
non-clinical groups, even when acknowledging the heterogeneous nature of the control
group. Ben-Tovim and Walker (1991) found no differences between women who scored
high and low on drive for thinness. Both groups were significantly faster at colour
naming target words than the eating disordered groups. However, the control group was
Cognitive Bias and Body Image 48
significantly younger, which is problematic as Seddon and Waller (2000) have found that
the type of Stroop bias depended upon age. Lokken et al. (2006) found differences
between women with Bulimia and non-symptomatic women on eating-, weight-, and
shape-related words, but when the Bulimic group were compared against a sub-clinical
group, only differences on the shape words emerged. Additionally, there was no
difference between the normal and sub-clinical group on weight words or shape words.
Other studies have found no differences between dieters and non-dieters on shape words
(Lovell, William, & Hill, 1997), or between high and low restraint groups (Sackville et
al., 1998). Collectively, these findings suggest that the differences between clinical, sub-
clinical, and control groups are not clearly defined. Alternatively, it may be that the
groups of women have not been clearly defined, as each study seems to compare women
on a different set of vulnerability factors.
Studies that have focused primarily on non-clinical samples have again found that
greater interference was associated those who had eating or weight disturbances. Green
and Rogers (1993) concluded that an attentional bias for body shape words and food
words is present in a large proportion of non-disordered females. Interference for food
words appears to be consistently found in women who reported restrained eating. Francis,
Stewart, and Hounsell (1997), and Stewart and Samoluk (1997) found that women
classified as restrained eaters showed interference effects for food words compared to
neutral words, while women classified as low in dietary restraint did not show this effect.
However, Jansen, Huygens, and Tenney (1998) found that restrained eaters did not show
an interference effect for weight and body shape words when words were presented either
subliminally or supraliminaly. The difference between these final two studies may be due
to the differences in cut-off scores used to define the restrained and unrestrained groups,
Cognitive Bias and Body Image 49
with Frances et al using a higher cut off. As such, the participants in Francis’s study may
reflect a more extreme, homogeneous group of restrained eaters. Alternatively, it may be
that restrained eaters only show interference for food words (as assessed in Francis’s
study) and not body or weight words (as assessed in Jansen’s study). However, this
discrepancy remains to be resolved in future research.
Changes in mental state prior to the Stroop task is a variant in methodology that
helps to understand how emotional state and attentional bias interact. According to Cash
(1994), certain contexts or events can serve as primes and activate appearance schemas.
Recall that Markus and colleagues (1977, 1987) proposed the existence of schemas,
which determine what information receives attention. Schematic individuals place
importance on that dimension, and process information preferentially compared to
aschematics, for whom that dimension is not relevant.
Priming methods that have been included as variants within the Stroop task
include being weighed in front of a mirror (Labarge, Cash, & Brown, 1998), consumption
of calorie-laden food (Mahamendi & Heatherton, 1993), the presentation of still pictures
representing the thin-ideal (Hargreaves & Tiggemann, 2003), short-term fasting
(Channon & Hayward,1990; Stewart & Samoluk, 1997), and staged interactions focusing
on physical appearance (Tantleff-Dunn & Thompson, 1998). These various priming
techniques have produced conflicting findings with non-clinical samples. Labarge et al.
(1998) reported that the greatest interference for physical appearance words was found in
those women who rated appearance as important, and who were weighed before hand
(i.e., primed schematics). This effect was not present when no prime was used,
suggesting the importance of contextual cues even in women who place a high
Cognitive Bias and Body Image 50
importance on appearance. No interference effect was found in aschematic women (those
for whom appearance is not important).
Mahamedi and Heatherton (1993) compared dieters (restrained eaters) and non-
dieters to see if the consumption of a high calorie meal would produce interference in
colour naming food and body shape words. The results indicated that this high calorie
preload affected the cognitive performance of both dieters and non-dieters in naming
body words, although this effect was stronger in dieters. This difference disappeared
without the preload, again supporting the importance of contextual cures. However, there
was no difference in the colour naming of food words even with a preload.
Just as the consumption of high calorie food was shown to affect Stroop
interference, inducing hunger through fasting also appears to produce selective attention.
Channon and Hayward (1990) found that long term fasting (24 hrs) produced interference
effects in both males and females for food words, as compared to neutral words, and for
those who did not fast before the Stroop task. However, it appears that short-term fasting
does not produce comparable results, as Stewart and Samoluk (1997) found that fasting
for 6 hours did not produce interference for food words. The results again point to the
central role of environmental cues in eliciting selective attention in non-clinical samples.
Collectively, these findings suggest that selective interference may not be limited
to those with a clinical Eating Disorder (Green & Rogers, 1993; Francis et al., 1997).
However, this statement warrants further investigation due to the inconsistent findings
reported above. There are a number of significant limitations that need to be addressed in
order to further elucidate the Stroop tasks’ utility in assessing cognitive interference in
clinical and non-clinical samples. A number of these limitations are now discussed.
Cognitive Bias and Body Image 51
3.4.3 Methodological Limitations
There are a number of methodological decisions to be made when implementing a
Stroop task, and there is no agreed upon ‘best practise’ identified in past research. A
diverse range of variations within the Stroop task have been used. Some of the biggest
discrepancies between studies have been the use of a card versus computerised technique
to present the words, blocked versus randomised presentation of words, response
strategy, and scoring of interference effects. These issues warrant further discussion, as
they may affect the results and therefore the comparability of studies (Dobson & Dozois,
2004; Faunce, 2002.
3.4.3.1 Card vs computerised technique. Many earlier studies used large cards to
present a matrix of words, and the time taken to respond to all words on the card was
measured via a stopwatch (e.g., Ben-Tovim et al., 1989; Channon et al., 1988). However,
this technique is also commonly used in later studies (e.g., Carter, Bulik, McIntosh, &
Joyce, 2000; Lokken et al., 2006; Stewart & Samoluk, 1997), despite the availability of
more sophisticated methods. Computerised tasks typically present words individually,
and reaction time for each Stroop category is averaged over the various presentations of
the individual words. Computerised tasks, while more time consuming to initially
program, allow the researcher more control over randomisation procedures, more precise
timing, and an enhanced ability to examine or eliminate error rates. However, research to
date has tended to use the card-based methodology more frequently. A recent meta-
analysis found no differences in interference patterns between card and computerised
presentations (Johansson et al., 2005a), however caution should be used when comparing
interference indexes between these two methods, as card-based methods typically do not
allow for randomisation to occur.
Cognitive Bias and Body Image 52
3.4.3.2 Blocked vs random presentation of words. Blocked presentation occurs
when all words from one semantic category are presented together. For example, all of
the food words would be presented, followed by all of the neutral words. Randomised
presentation occurs when the order of words across all categories are randomly ordered.
For example, the food and neutral words are mixed together in the same presentation.
Typically, a blocked presentation is used for a card methodology, while computerised
presentation allows for more randomisation to occur. The presentation of large blocks of
semantically related words has been found to influence reaction time in both clinical and
non-clinical samples (Green et al., 1999). Highly associated neutral word lists were found
to produce as much interference in the Anorexic sample as body shape words, while in a
non-clinical group this interference effect for highly associated words was greater than
other control categories with less semantic relatedness. These differences in
methodologies may account for some of the inconsistent findings in past research given
the unstandardised method of word selection.
According to Jones-Chesters et al. (1998), the use of a card-based, blocked
methodology can present both theoretical and practical problems. Theoretically, is it not
clear whether a reaction time taken for the entire card results from specific items, or the
culmination of anxiety from viewing all items. On a practical level, a computerised
presentation allows for finer temporal precision so that reaction times for individual items
can be examined, and anxiety effects are reduced as only one word is viewed at a time.
Additionally, error rates for individual items can be examined and excluded if necessary
(Davidson & Wright, 2002).
In their examination of the differences between mixed and blocked computerised
presentations, Jones-Chesters et al. (1998) found differences for emotion words only, and
Cognitive Bias and Body Image 53
only in the women with Bulimia Nervosa. When words were blocked, the Bulimic group
showed significantly more interference for the weight, food, and emotion categories,
while the difference in emotion words was not found using a mixed presentation. For the
Anorexic group, the same pattern of interference was found across presentation types. It
was also noted that the interference effects were greater overall using a blocked
methodology for both Eating Disordered groups, yet not for the non-clinical group. This
finding supports the notion that the sequential presentation of words from some semantic
categories can result in anxiety which in turn interferes with cognitive processing.
The differences between blocked and mixed presentations may only be limited to
emotion-related words, as a recent meta-analysis concluded that method of presentation
for food and body related words did not seem to influence the pattern of interference
(Johansson et al., 2005). Therefore, a computerised task with individual presentation of
words allows for more precise timing, randomisation, and other control procedures to
occur.
3.4.3.3 Response strategy. In a Stroop task, participants can be required to either
respond either verbally or through a button press. Computerised presentation of Stroop
words typically requires participants to respond via coloured keys, although some studies
have required a verbal response in addition to, or instead of, a verbal response (e.g.,
Sackville et al., 1998). A card presentation requires participants to verbally label the
colours of the set of words.
One potential problem noted by Davidson and Wright (2002) with voice-activated
controls, is the possibility of external noises being registered, or response not being loud
enough, which results in a loss of data for those trials. Conversely, the requirement to
press a button as a response allows for mistakes to be measured more accurately. In a
Cognitive Bias and Body Image 54
direct comparison of a voice-activated versus button press methodologies, Davidson and
Wright (2002) conclude that the button press is a more sensitive and reliable method, due
to the number of potential problems faced when using voice-activated responses.
Significant differences were however only noted for control participants on the colour-
conflicting condition, while no differences were noted on food categories and body shape
categories. A recent meta-analysis also noted no consistent differences were found in
interference patterns between these two response types (Johansson et al., 2005a).
However, given the practical problems with voice response, a button response is deemed
more appropriate.
3.4.3.4 Order of tasks. A further limitation identified involves the order of tasks in
the experiment. Some studies have given participants questionnaires to fill out before
completing the Stroop task (e.g., Cooper et al., 1992). This may sensitise or prime
participants to the topic, subsequently influencing their Stroop performance. It is
recommended that questionnaires are filled out after the Stroop task to avoid any
potential priming effects these questionnaires may have.
3.4.3.5 Stimulus sets
Perhaps one of the most important methodological limitations is the use of
inappropriate word stimuli. If the words are not carefully selected to reflect the unique
concerns of the particular group, or if they are not carefully matched to appropriate
control words, interpretation of the findings becomes problematic. For example, stimuli
such as “fingernails”, “lipstick”, and “stockings” have been used as appearance words
(Labarge et al., 1998). It is unlikely that these words represent serious appearance
concerns for many women. Further, it is even more unlikely that these words are relevant
Cognitive Bias and Body Image 55
for men, who were also included in Labarges’ study. Therefore it is important to ensure
that the words represent highly salient concerns of the particular sample.
Additionally, the use of a combined target category is problematic. Some studies
have presented the target words as one category combining food, weight, and shape
related words (e.g., Fairburn et al., 1991), which does not allow the subtle differences
between word categories and disorders to be partialed out. Thus, in order to gain a clearer
understanding of cognitive interference, more specific target word sets need to be used.
Similarly, a stronger distinction is needed in the research between the categories of
eating/food and body size/shape. For example, Sackville et al. (1998) found that it was
not only high calorie food that anorexics show interference for, but also low calorie
foods, along with both positive and negative shape words. Additionally, highly restrained
eaters show a general interference for food words, rather than just high calorie forbidden
foods (Francis et al., 1997). Thus, research needs to be expanded beyond the traditional
Stroop categories used, as the pattern of interference has important theoretical and
practical implications.
Careful matching of words in the target and neutral categories needs to be made to
allow for proper comparisons in response times (Larsen, Mercer, & Balota, 2006; Lee &
Shafran, 2004). In order to conclude that participants show a slower colour-naming
response to target words, there needs to be a group of words that a comparison can be
made against. As the target words are typically from one semantic category (i.e., shape
words, appearance words), the control words should also be semantically related. This
should ensure that any priming effects are similar across the categories. For example,
Green et al. (1999) have found that highly associated neutral categories produce as much
Cognitive Bias and Body Image 56
interference as the target category. That is, participants were as slow to colour name the
highly related neutral words as they were in naming the target words.
Similarly, the list of target and neutral words need to be carefully matched on
parameters that affect word recognition (Larsen et al., 2006). In their paper, Larsen et al
outline compelling reasons, reviewing evidence that demonstrates a slow-down in
recognition for infrequently used words compared to more frequently used words, and
longer words compared to shorter words. As an Emotional Stroop task does not use the
same list of words in each condition (as with a traditional Stroop task), the comparability
of response times is dependent upon the lexical equivalence of the word lists. Otherwise,
it is not clear whether differences in response times for the target and neutral words stem
from the emotional valence, or lexical differences between the words. In their review of
the lexical features of 32 studies that have compared interference for emotion versus
neutral words, Larsen et al found that the negative emotion words were significantly
longer and less frequently used than the neutral words. Therefore, target and neutral
words need to be carefully matched on length and frequency of occurrence.
3.4.3.6 Sample limitations. Most of the Emotional Stroop research to date has
focused on attentional bias in clinical groups, while there is comparatively little work
focusing exclusively on non-clinical samples. Often, the inclusion of non-clinical groups
is simply for comparison purposes, and little information is provided regarding the nature
of body image disturbances and whether they reflect a truly asymptomatic group. The
possible diverse nature of these control groups is problematic. Williamson (1996) in his
review of the evidence to date regarding attention bias using the Emotional Stroop,
concluded that interference is not unique to those with eating disorders. It is however,
restricted to those with concerns about their appearance and/or weight. Thus,
Cognitive Bias and Body Image 57
considerations need to be given to participants’ feelings/attitudes toward their appearance
and weight.
As Eating Disorders are found predominately in women, the existing body of
research represents a gendered understanding of body image disturbance. To date, there
are only three published papers that have tested male samples on an Emotional Stroop
task, and they found no differences in attentional biases between males and females (Ben-
Tovim, Walker, & Douros, 1993; Channon & Hayward, 1990; Fairburn et al., 1991).
Fairburn et al. (1991) found that there was no difference between males and females in
colour-naming eating, shape, and weight related words, nor did either group show
interference compared to the neutral words. Similarly, Ben-Tovim et al (1993) found no
differences in males and females on body shape and weight stimuli. Channon and
Hayward (1990) also found no differences between males and females in colour-naming
food and body size after being fasted for 24 hours. However, both males and females who
were in the fasting condition showed interference for the food words. Thus, the research
to date indicates that there are no gender differences in selective attention as measured by
the Stroop task. These findings may be misleading, however, for several reasons. First,
the target words used were not developed specifically for male samples and do not reflect
concerns specific to men’s body image. As males typically report wanting to be more
muscular and larger in size (Silberstein et al., 1988), while women want to be thinner, the
target words used need to reflect these differences. It is likely that further investigation of
selective attention in non-disordered and disordered males with appropriate stimuli will
yield more conclusive findings. Both these studies are, however, important first steps in
the investigation of selective interference in non-clinical males. Thus, the current thesis
used words specifically designed to reflect both male and body image concerns.
Cognitive Bias and Body Image 58
3.4.4 Limitations Addressed in the Current Project
The aforementioned limitations preclude a thorough understanding of body image
disturbance within non-clinical samples. The primary aim of the current thesis was to
expand the current literature by addressing a number of the aforementioned
methodological flaws and gaps in the research. Separate categories of target words were
used which were matched to groups of neutral words from one semantic category.
Additionally, the current line of research was expanded by including new categories of
words that have not been explored previously. Traditionally, categories that have been
used are food/eating words (e.g., Green & Rogers, 1993; Mahamedi & Heatherton, 1993),
weight/shape words (e.g., Cooper et al., 1992; Lovell et al., 1997), and appearance words
(e.g., Labarge et al., 1998). Research has also been criticised for focusing on negatively
valanced stimuli (Vitousek & Hollon, 1990), therefore both high calorie foods and low
calorie foods, in addition to positive appearance and negative appearance words were
used. A new category comprising physical activity words was also developed to reflect
the current concern within society to fit and healthy; a key theme that emerged in the
qualitative analysis. It was anticipated that words such as “jogging” and “aerobics”
would produce interference for some groups of people. As there has been no research
using this category before, its inclusion was exploratory. Similarly, words specially
designed to reflect male body image concerns were constructed. Interviews with both
males and females in Phase One of the research elucidated relevant body image concerns
within non-clinical samples. Further, the aim of Phase two was to develop appropriate
word stimuli.
Notwithstanding the limitations previously mentioned, research indicates a trend
for some forms of attentional bias in non-clinical samples. An attentional bias indicates
Cognitive Bias and Body Image 59
that increased attention has been allocated to that stimulus. Given this preferential
treatment at the encoding stage, it is plausible that preferential attention is also given at
later stages of information processing. Many information processing theories state that
increased attention to stimuli may result in enhanced memory for that information (e.g.,
Atkinson & Shriffin, 1968). Therefore, in order to provide a comprehensive model of the
way information of processed, memory bias in addition to attention bias must also be
considered.
3.5 Memory Bias
In addition to attention bias, Vitousek and Hollon (1990) propose that evidence
for weight / appearance schemata can be gained from examining memory bias. These
researchers propose that biased memory for weight related information supports current
levels of body image disturbance. Increase attention to body and shape related stimuli
may be related to greater elaboration at encoding. This enhanced elaboration means that
information is linked to numerous other concepts in memory (Williams et al., 1988,
1997). As such, there will be many cues that could activate body image concerns
(Sebastian, Williamson, & Blouin, 1996). According to Williams et al. (1988), women
with body image related problems build up a stronger network of memories through their
recurrent thoughts about body weight. The outcome of this increased cognitive
processing is the enhancement of retrieval of such information.
There is currently only limited work examining memory biases in individuals
with body image disturbance (Lee & Shafran, 2004). Only four studies to date have
examined memory bias after an Emotional Stroop task (Channon et al., 1988; Labarge et
al., 1998; Lavy & van den Hout, 1993; Mendlewicz, Nef, & Simon, 2001), whereas a
small number of studies have examined memory biases more generally in response to a
Cognitive Bias and Body Image 60
self-referent encoding task (Baker, Williamson, & Sylve, 1995; Sebastian et al., 1996), or
reading an essay (King, Polivy & Herman, 1991).
Using an incidental memory task following an Emotional Stroop task, no
evidence of implicit (Channon et al. 1988; Lavy & van den Hout, 1993; Mendlewicz et
al., 2001) or explicit (Labarge et al., 1998; Lavy & van den Hout, 1993) memory bias has
been found in women. Channon et al reported no recognition bias in Anorexic or control
women after colour naming food and body size words, despite an attentional bias
observed in both groups for the food words. Similarly, Mendlewicz found no recognition
bias in women with Anorexia Nervosa or asymptomatic control women for high calorie
food words, low calorie food words, or anxiety provoking body areas, despite attentional
bias observed two to three days earlier. Labarge et al. found no recall bias for appearance
words in participants classified as either appearance schematic or appearance aschematic,
even after half the participants had been primed (weighed) beforehand. However, a small
yet significant correlation (r = .20) was found between level of appearance schemacity
and number of appearance words recalled. Finally, Lavy and van den Hout (1993) found
no evidence of either a recall or recognition bias for food words in asymptomatic women
even in those who fasting for 24 hours beforehand, even though an attention bias was
noted. These results consistently show that strategic processing biases are not found in
women for appearance and food stimuli. Additionally, these results suggest that
differences in attention may not always reflect enhancements in memory. It may be that
observed processing biases are short-lived; however more research is needed to
substantiate this claim.
A larger volume of research has examined memory biases within body image
more broadly. Typically, participants are required to complete some type of task such as
Cognitive Bias and Body Image 61
learn a list of words, read a story, or complete a self referent encoding task (where they
are asked to imagine themselves in a situation with the word, or asked if the word is
relevant to them). Some of the material in the word lists or interspersed in the story is
related to food / appearance. Recall is then tested a short time later to assess whether the
target or neutral information is recalled better.
The most frequently used way for assessing memory bias has been through a self
referent encoding task. Participants are presented a list of words and asked to imagine a
situation involving themselves and the word. It is proposed that women concerned with
appearance and weight integrate this material into already elaborate schemas. When
asked to recall the information, they have more cues to trigger recall and hence show
greater recall of this material (Vitousek & Hollon, 1990; Williams et al., 1997).
Using this technique, Sebastian et al. (1996) found that memory bias for fat
related information was uniquely found in women with eating disorders, and not
symptomatic or asymptomatic women. As the eating disordered and weight preoccupied
groups were equal on degree of weight preoccupation, it was suggested that a factor
unique to the eating disorders produced the results. However, Baker et al. (1995)
concluded that memory bias fatness stimuli were found in symptomatic women. Women
with high body dysphoria, but not low body dysphoria, showed a biased recall for fatness
words and reduced recall or thinness words. Negative mood induction did not change
this, suggesting that biased memory is stable and not influenced by environmental cues.
Using a wider variety of word categories Hunt and Cooper (2001) found a general
memory bias in all women. Asymptomatic women and women with Bulimia Nervosa
were assessed for memory bias for positive weight / shape words, negative shape / weight
words, positive emotion words, negative emotion words, high calorie food words, low
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calorie food words, and neutral body areas. The women overall recalled more of the
weight / shape words than neutral words, while the control group of women recalled
significantly more of the food words than the women with Bulimia Nervosa.
Finally, in the only study to include male participants, and use specifically
designed word categories to reflect male and female body image concerns, Unterhalter et
al. (2007) found that men showed a memory bias for positive muscularity words, but not
negative muscularity, or positive weight / shape, or negative weight / shape. The women
showed a general memory bias for the positive and negative weight / shape categories.
Therefore, inconsistent results have been found regarding memory bias, and the
specificity of that memory bias, in women. Using a similar methodology, one study has
concluded that memory bias is restricted to women with eating disorders (Sebastian et al.,
1996), one found memory bias in symptomatic women (Baker et al., 1995), and two
found general memory biases in all women (Hunt & Cooper, 2001; Unterhalter et al.,
2007). Clearly, more research is needed to examine this issue.
Other techniques to explore memory bias have been to present word lists and ask
participants to rate the pleasantness of the words followed by an incidental memory task
(Israeli & Stewart, 2001). Using this technique, women classified as high on dietary
restraint remembered more forbidden food words than neutral words; a bias that was not
found in the women classified as low on dietary restraint. King et al. (1991) assessed
memory bias in clinical (women with Anorexia Nervosa and women classified as obese)
and non-clinical samples (restrained compared to unrestrained eaters), after they read an
essay which was interspersed with statements about weight and appearance. Memory
biases associated with individual concerns were found in both the clinical and non-
clinical groups. The women classified as restrained eaters, obese, and with Anorexia
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Nervosa recalled significantly more weight and food related aspects of the story
compared to other information neutral information in the essay. Additionally, the
restrained group recalled significantly more weight information than unrestrained
women. These findings suggest that memory biases for appearance and weight related
information is not distinctive to eating disordered individuals
Memory biases for body image related information have not been as extensively
examined as attentional biases. Only four studies to date has examined incidental
memory following an Emotional Stroop task. While more research has been conducted
using other techniques, such as a self referent encoding task, it is likely that the
mechanisms underlying biased memory in these two tasks are different. For example, in
time pressures in an Emotional Stroop task mean that threatening information must be
processed more rapidly (Sharma & McKenna, 2001). Clearly more research is needed to
examine the nature of memory biases, and the relationship between attention and memory
bias. The mechanism through which this bias occurs is not yet clear. The examination of
both biased attention and memory within the one study allows greater consideration of
whether processing biases occur at encoding, retrieval, or at both stages (Sebastian et al.,
1996).
Many of the limitations noted in the preceding section on attentional biases also
relate to the research on memory biases. Specifically, matching of neutral and target
words does not always occur (e.g., Unterhalter et al., 2007), or the neutral words may not
form a homogeneous category (e.g., Hunt & Cooper, 2001). Further, few studies have
looked beyond memory bias for food or appearance words, or beyond words with a
negative connotation. Finally, limited research has included males, resulting in a
Cognitive Bias and Body Image 64
gendered understanding of memory bias. Therefore, our understanding of memory bias
within non-clinical women and men is limited.
3.6 Summary of Attention and Memory Bias Chapter
This chapter has critically reviewed research on the Emotional Stroop task as a
measure of attentional bias. Based on the inconsistent findings and methodological
limitations, a key question remains as to whether processing biases are limited to those
with Eating Disorders, or whether they can be found within a non-clinical sample.
Limited research examining memory biases was also presented. Based on this review of
the literature, a number of significant limitations were noted that preclude a thorough
understanding of processing biases in men and women. The identification of these
limitations has informed the design of the Emotional Stroop task and incidental memory
task to be used in Phase Three of the research (discussed in Chapters Seven and Eight).
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Chapter Four: Overview of the Research Program
This thesis presents a program of work designed to examine the role cognitive
biases play in sub-types of body image disturbance within a non-clinical sample. The role
of selective attention and memory for body image related words was measured using an
Emotional Stroop task and incidental memory test. Additionally, a range of psychosocial
questionnaires were administered to assess various facets of health behaviours and body
image. To achieve this aim, three phases of research were conducted. The initial two
phases of research provided preliminary data to inform the development of the main
Stroop study.
4.1 Aims, Research Questions and Hypotheses
The purpose of Phase One was to conduct a qualitative exploration of body image
concerns amongst males and females. Participants provided information on their own
body image, and what factors they see as either positively or negatively impacting on
their self evaluations. The outcomes of this phase were used to inform later phases of the
research by identifying body image concerns that are specifically relevant within a non-
clinical sample. Specifically, the purpose of Phase One was to provide support for the
types of words to be used in the Emotional Stroop task and memory task, and also inform
the selection of psycho-social vulnerability factors.
Phase Two involved the selection and initial testing of words to be used in the
later Stroop study. Males and females provided appropriateness ratings on an initial
selection of categories of words, and the words themselves. Words receiving the highest
ratings were used, ensuring that the stimulus used was empirically supported.
Finally, Phase Three was a large-scale study assessing the central aim of the
research; the role of cognitive biases for body image information and how these biases
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differed between empirically defined sub-groups. Males and females were primarily
recruited through the general community and tested on emotional Stroop task and
incidental memory test. Following the cognitive tests, a battery of health related
questionnaires were administered. A wide range of psychosocial variables were included,
such as body image concerns, exercise behaviours and attitudes, quality of life, negative
affect, muscularity concerns, and eating disorder symptomology. The selection of
psycho-social variables was driven by the outcomes of the qualitative analysis in Phase
One.
Based on the limitations noted in past research, the cognitive measures benefited
from a number of methodological refinements. In order to increase the generalisability of
the findings, the sample included both males and females of a wide age range recruited
from the general community and universities. Bias on the cognitive measures was
examined two ways. First, the sample as a whole was examined for attention and memory
bias at a group level, followed by a comparison between the empirically derived sub-
groups. Second, cognitive measures were examined for their relation to a wide number
of vulnerability factors that go beyond the typically used body image variables.
The limitations noted in the research also informed the development of the
cognitive tasks. The research included more appropriate and carefully developed stimulus
sets that include both positively and negatively valanced words. Both the experimental
and neutral words were semantically related and matched on relevant lexical
characteristics. The types of cognitive bias were expanded by including new categories of
words and covering multiple facets of body image. Finally, the use of a computerised
Stroop task allowed for more sensitivity in timing, and randomisation of stimulus sets.
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The results from this study substantially add to our understanding of biased cognitive
processing.
Research questions and hypotheses were developed around three main areas of
enquiry. The first aim of the research was to examine whether attentional biases exist for
body image and health related information in a non-clinical sample. Specifically, it was
hypothesised that attentional biases, as evidenced by slower reaction times to body
image-related words, would be found in symptomatic participants only. No attentional
biases would be found in asymptomatic individuals.
The second aim of the research was to examine whether memory biases for this
body image and health related information would be shown. Specifically, it was
hypothesised that memory biases, as evidenced by the recall of more target words, would
only be found only in symptomatic individuals.
The final area of investigation was to examine whether gender differences would
emerge in attention to, and memory for, body image information. Specifically, it was
hypothesised that males and females would differ in their processing of sub-categories of
Stroop words given the different emphasis on body image concerns. However, given the
lack of past research in this area, the nature of these specific differences could not be
developed. These hypotheses are presented below.
Hypothesis 1: Attentional biases, as evidenced by slower reaction times to body image-
related words, will be found in symptomatic participants only. No attentional biases will
be found in asymptomatic individuals.
Hypothesis 1a: Interference effects will be different between sub-groups.
Hypothesis 1b: Greater interference effects will be associated with a range of
vulnerability factors.
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Hypothesis 2: Memory biases, as evidenced by the recall of more target words, will only
be found only in symptomatic individuals.
Hypothesis 2a: Memory bias will differ between the sub-groups.
Hypothesis 2b: Greater biases will be associated with a range of vulnerability
factors.
Hypothesis 3: Differences in processing biases between males and females may be found
in the sub-categories of Stroop words.
Now that a background to the research has been provided, the following three
chapters present the research undertaken. Chapter’s Five and Six describe the qualitative
phase and the stimuli selection phase of the research respectively. These preliminary
stages provided background information before the main Emotional Stroop phase was
undertaken.
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Chapter Five: A qualitative Exploration of Body Image Concerns Amongst Men and
Women from a Non-Clinical Population (Phase One).
5.1 Overview of Chapter
The aim of Phase One was to gain an in-depth understanding of individuals’
experiences with their body image, their body image concerns, and how these concerns
affected their lives. Particular attention was given to understanding what factors
individuals perceive as influencing their body image. The inclusion of both males and
females across a broad age spectrum increased the representativeness of the sample, and
allowed for age and gender differences to be explored. The outcomes of this phase were
then used to inform subsequent phases of the thesis, by helping to select a range of
measurement tools and stimuli that are relevant to a non-clinical sample. This chapter of
the thesis reports the methodology and outcomes of the qualitative study that was
undertaken.
5.2 Method
5.2.1 Participants
In an attempt to increase the representativeness of the sample, both males and
females were recruited. A total of 17 participants, eight of whom were male and nine of
whom were female, voluntarily participated from May to August 2005. Data collection
continued until data saturation occurred. Recruitment primarily took place through a large
Queensland university. Participants could sign up for the study via a university
recruitment notice. The notice invited people of all ages to participate in an interview
about body image and factors that shaped one’s view of themselves. In addition, the
researcher visited some classes and gave a small speech about the study. To improve the
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scope of the sample a ‘snowball’ technique was used and resulted in four participants
from outside the university.
The age of participants ranged from 18-56 years, with a mean age of 29.18 years
(SD = 11.85). Half of the sample was young adults, aged between 18 and 23 years. The
sample was well educated, with most participants currently attending university. Two of
the older participants reported completing up until grade 8 or 9 of high school. No other
demographic or descriptive information was gathered. There was no criterion for
participating in the study and some participants were offered course credit. One
participant was excluded from the analysis as she provided only minimal responses to the
questions. This case is further discussed in the Limitations section (5.4.2).
5.2.2 Procedure
Ethical clearance was received before commencement of the study through the
QUT University Human Research Ethics Committee. Participants provided written
consent after reading the information sheet and consent letter and were given the
opportunity to ask questions. A copy of the Information and Consent forms can be found
in Appendix A. Participants were asked whether they objected to the interview being tape
recorded, and all provided consent. Only demographic information of age, education, and
country of birth were provided on tape. It was explained to participants that only the PhD
candidate and the transcription company would hear the tapes. Individual interviews took
place with the PhD candidate, a young female, who had previous experience with
qualitative design.
Building rapport between the interviewer and participants was an important part
of the interview, as it was anticipated that stories and experiences regarding body image
could be difficult for some of the participants. It was the intention of the interviewer that
Cognitive Bias and Body Image 71
all participants felt comfortable and secure enough to talk about their thoughts and
experiences openly. All participants were carefully told their rights as a participant, and
told that they could stop the interview at any time without penalty. In addition,
participants were told that only needed to answer questions with which they felt
comfortable.
Once the preliminary signing of information and consent forms and rapport
building was done, sessions ranged in length from 19 - 72 minutes, with most interviews
taking about 40 minutes to complete. The length of time was guided by the participant
and how much detail or how many experiences they wished to disclose. The interviews
were guided by semi-structured questions that were determined by the research team, and
resembled an informal guided conversation. The list of questions and prompts can be
found in Appendix B. There was four parts to the interview. First, demographic
information of age, education, and country of birth was gathered. Second, participants
were invited to share their subjective definition of what the term “body image” meant to
them. This was to aid the communication between the interviewer and interviewee so that
terminology used during the interview was mutually understood. It was also to
understand whether body image was something that holistic and broad, such as
encompassing all facets of appearance and eating, or something more specific and
compartmentalised, such as satisfaction with one’s facial appearance. The third section
used the participants’ previously defined construct to ask how they would rate their own
body image, and level of body satisfaction. The final and longest section of the interview
asked what factors participants saw as influencing their body image. A number of
prompts were determined prior to the interview and included factors such as the media,
peers, family, specific situations such as going to the beach, romantic partners, and
Cognitive Bias and Body Image 72
exercise and eating habits. Participants were not specifically asked whether they had an
Eating Disorder either presently or in the past, but they were free to give this information
if they wished.
To increase the rigor of the findings, and to ensure that rapport was maintained,
reflection of content was used throughout the interview to make sure that the effective
and clear communication was occurring. In addition, a summary of key points was
provided by the interviewer at the end of each section and participants were given the
opportunity to resolve any discrepancies or clarify any ambiguities.
At the conclusion of the interview, participants were asked whether there was any
information they wished to add, or any important area that they felt wasn’t covered
adequately. If not, participants were then thanked for their time and left. The interviewer
then made any additional notes about themes arising from the interview.
Recruitment continued until data saturation occurred. That is, when no new
information was emerging from the interviews, it was deemed that an adequate coverage
of the topic had been made.
5.2.3 Data Analysis
All audio tapes, except for one, were transcribed by a professional transcription
company who were instructed to transcribe the interview verbatim. The other interview
was only half recorded due to technical errors. This was realised immediately after the
interview and detailed notes were taken. Analysis was based on the transcripts and
additional notes made at the time of the interview.
The data was analysed using an inductive, thematic analysis technique. This
technique is commonly used in research (e.g., Halliwell & Dittmar, 2003; Ziebland,
Robertson, & Neil, 2002) when the goal is to explore a previously untested idea, rather
Cognitive Bias and Body Image 73
than test an existing theory. As the existing theory is under-developed, and there is
relatively little existing research in this area, no pre-existing theories were tested. Using
thematic analysis, reoccurring ideas that are expressed by multiple participants are
grouped together into themes. Themes are originally based on the research questions, so
that individuals’ verbatim quotes are organised under the topics asked in each interview.
These themes contain verbatim quotes from participants as well as an interpretation of
their responses. Each new emerging theme is compared back to existing themes to
determine similarity. If the two themes are deemed sufficiently different, then a new
theme is developed. This process continued until all relevant information had been coded
into a theme and each theme developed represented a unique interpretation of the data.
Subthemes are then explored by examining the coded data under each theme. For
example, the role of the media was something that all participants discussed, and this
became a theme. Different opinions regarding the role of media became the subthemes –
some respondents saw the media as a motivating factor, while others saw it as a negative
influence. Coding was complete when the data was saturated, that is no new themes or
subthemes were apparent. To improve the reliability and validity of the coding, other
members of the supervisory team (both males), familiar with the study’s aims, were
consulted for feedback. This ensured that themes were clearly elucidated.
5.3 Results
A number of independent themes and subthemes emerged from the analysis. Each
theme is interpreted below and is illustrated by verbatim quotes from the interviews.
5.3.1 A Healthy Body Image Does Not Negatively Affect One’s Life
Most of the participants reported a healthy body image. When participants were
asked to rate their feelings about their appearance / body, most participants reported some
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dissatisfaction with a particular feature, but stated that they were overall quite satisfied.
For example, a 29 year old male remarked “I’d say I guess I’m not a Brad Pitt but I’ll
give myself an eight out of ten”. A similar comment was also provided by a 20 year old
female “I’m quite happy with my body image. I know that there’s some areas that I could
fix up and make nicer, but I’m quite happy with it, yes”. All of the participants were able
to separate body satisfaction from general well-being and feelings of self worth, for
example “I mean I have days where I go, oh, I look really crap and I’m really fat and I
really need to go on a diet but I never get around to it” (18 year old female). This is
further expanded under the self esteem theme.
Some of the participants, mainly the women, reported their body image was quite
labile, and influenced by things like mood. For example, an 18 year old female
commented “I don’t know, I guess you have your days, like up and down days. Like some
days you’re like, oh okay, I feel really ugly or I feel really fat today”. A 23 year old male
also commented “It’s okay at the moment, it has been better”.
Many of the participants defined their body image in terms of general health. A
22 year old male comments “Yeah I’m fairly happy. I’d like to be a little bit more fit but
that’s not so much the image, that’s more health”. The importance of health in
determining satisfaction with appearance is identified by all participants, and is further
expanded under a separate theme.
Therefore, while participants were generally satisfied with their image, most
could identify some features with which they were not satisfied. More of the women
reported dissatisfaction than males, and the females also reported more history of body
dissatisfaction, and three participants a history of eating disorder-like behaviours /
attitudes. For example, a 29 year old female reported a history of symptoms similar to
Cognitive Bias and Body Image 75
anorexia (refusal to eat, cessation of menstruation, extreme weight loss), and reported
still turning to food for comfort. In addition, two men were identified that reported
symptoms of body dysmorphic disorder, and excessive exercise and dieting.
5.3.2 Having A Strong Self-Esteem / Self Image is A Protective Factor
All of the participants identified that having a strong sense of self was an
important factor in having a healthy body image. That is, the participants did not define
their self solely in terms of appearance. Many of the participants reported a time in their
lives when they did experience body image problems, and developing a strong self
esteem was important to overcoming these problems. Some example quotes are:
“Yeah, internal features are more important for myself and those other aspects that make
up a fulfilling life and a quality of life. And I don’t believe that whether I’ve got glowing
tanned skin or whether I don’t, is really going to affect the quality of my life” (22 year old
male).
“I mean life has taught me a lot of things. I mean I probably haven’t had the most ideal
life, so I’ve realised that things are not perfect, they’re not meant to be perfect, it’s just
the way of life. And it’s alright, you know, I’m just okay with it, you know, whatever
happens, happens. That’s sort of my way of thinking. I think that’s also the way with
how I relate about myself and, oh yeah, it happens so what am I going to do about it?
Can’t sit and cry about it, just get on with life.” (18 year old female).
“… you know, well I can lose all the weight in the world but unless I’m happy in myself
then it’s not going to make a difference.” (19 year old female)
“… but it’s important to me how I see myself” (56 year old male).
Cognitive Bias and Body Image 76
Participants regularly noted that there were much more important aspects to
themselves than appearance, for example a 50 year old woman noted “I see some other
things as being far more important to my self esteem than my appearance.” Similarly, a
22 year old commented, “I guess I got more brought up with the idea that intelligence
was the main thing.”.
When asked at the end of the interview what the most important factors in
influencing their body image were, all of the participants mentioned self esteem. Even
though participants could list a significant number of factors that influenced their body
image, their reactions to those situations were dependent upon their body image – “It has
to be myself (as most important factor in my body image) because it’s how I feel that
drives my behaviour in those situations.” (49 year old women). Therefore, it appears that
having a strong sense of self is an important protective factor against body dissatisfaction,
or at least not letting it influence general wellbeing.
5.3.3 Importance of Health and Fitness
All of the participants identified the importance of being fit and healthy regardless
of whether they were currently in a fitness regime. This was considered an important
component of body image, particularly by the males who tended to define their
satisfaction with themselves in terms of their fitness. This is illustrated in the following
comment by a 23 year old male about why he exercises: “To get fit, but also for that
feeling, because I’ve noticed the days I don’t exercise I’m sluggish and I’m pretty blah.
The days I do exercise is just a better feeling.…. Because appearance isn’t that
important to me at the moment. Health is more important.”
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The women also reported engaging in exercise for health reasons, and many of the
women also defined their body image in terms of health and fitness. For example, a 50
year old female stated:
“I feel as if it (her body image) isn’t up to scratch in terms of health. I’m not that
concerned with appearance, but a little bit concerned with appearance, but it’s not all
encompassing. It’s more to do with the health, what I think could be healthier. So if I see
a muscle that’s not really firm, I think of it in terms of health and how that’s going to be
for me as I get older rather than in terms of how it might appear.”
Some of the women reporting exercising for appearance / weight loss reasons, and
typically did not enjoying it much. For example, a 20 year old female commented: “Yeah,
I try and do a little bit of exercise. I hate exercising. I hate it, but I do a little bit. I’ve
got a treadmill and I get on that sometimes. I’m trying to get back on track and to tone
up a bit at the moment, but it’s getting started is the main problem.”
The benefits of exercise were noted by all of the participants, and included things
like mood regulation, having more energy, being toned, to be social / bond with others, to
improve attractiveness, and reducing stress. The mood enhancing properties of exercise
were especially noted, for example, “I find it’s a stress relief myself, physical exertion.
Walking, to me, it’s great. It’s a good stress relief for myself” (22 year old male); “…
just want to play harder, go faster, just try and make myself feel a bit better..” (20 year
old male).
The importance of feeling healthy and fit was a consistent theme that was
emphasised by all participants. Being in good health was an important component of
body image.
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5.3.4 Recognition of the Societal Ideal
All of the participants noted an ideal physique that is perpetuated in Australian
society, one that “for women it’s slim and trim, for males… buffed and bicep-ed” (22 year
old male). Participants were not clear where they thought this image came from, but
noted the media in general as one of the major conveyors.
“…on a larger scale even I guess if you want to say media” (22 year old male)
“…I guess female artists like J-Lo, Beyonce. Also film stars. You watch the award
shows and see all their fashions and all their dresses and you see that they all look tall
and skinny.” (18 year old female).
Another participant commented that this ideal image also reflects the current
concern with health and fitness, “I think the prevailing medical discourse in a way. The
prevailing medical discourse at the moment that goes really into health. That’s probably
really influencing my body image.” (50 year old female).
Participants differed in their response to these images. Some participants, all
female, said that they images made them feel worse about themselves, “…But this year
I’ve been watching a lot more TV and I actually feel bad.” (19 year old female), while
other participants reported the media had no impact on them, “The media doesn’t play a
large part for me. I think it plays a large part for other people though, particularly
women. I really don’t think it plays a large – I’m not very influenced by who and what I
see on television as far as body image goes.” (56 year old male).
Many of the participants noted that the media made them feel angry and worried
about the unrealistic nature of the images, “No, I hate that (music television). I have a
real aversion actually to that…. I feel sick thinking that adolescent girls are watching
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that every weekend. That we’re still telling people that this is what we should all be
striving to be…. (I feel angry) That there are still teenage girls that have to grow up with
this shit, that will feel crap about themselves and will get into all sorts of problems. Then
I get angry that there are women that are prepared to portray themselves like this. That
if women refuse to do this, it wouldn’t happen.” (29 year old female).
Many of the participants reported dissatisfaction with the one type of image being
constantly presented, and a frustration with the focus on appearance and weight, for
example, “I just think because everybody’s focussed, like you see on TV and you see
everywhere that there’s the perfect image. Skinny, beautiful, but it’s all computerised
and touched up and everything. I think everybody in the world, in Australia have sort of
focused on that one image. There’s all sorts of different people and the different body
types as well.” (20 year old female).
A small number of participants reported that seeing idealised images was a
motivating factor to improve their own appearance, “I guess it helps me to gain an
understanding of what an idealised, or good looking, person would look like. And also,
that body image is achievable. You also hear a lot of history behind the actors, if they
had to loose weight, or put on body muscle… yeah, just those stories, that make it seem
more believable.” (20 year old male).
Many of the participants noted the unrealistic nature of the images, which served
as a protective factor, “Good for them” (22 year old male); “I sort of realised that they’re
basically selling a product, they’re selling themselves. So I’m like, okay, they are
supposed to look like that, they’re paid to look like that. I guess if I was paid to look like
a billion dollars then I probably would too.” (18 year old female).
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Therefore, the idealised images in the media and the strong focus on looking good
were noted by all participants. This ideal was primarily seen as a negative influence.
5.3.5 Mood Can Affect How Events Are Interpreted
Most of the participants identified mood as influencing their body image, or how
they react to situations. The females in particular identified a strong link between feeling
depressed or stressed and consequently feeling unattractive. For example:
“if you’re in a really good mood and you try on something and it doesn’t fit, it’s like,
okay I’m in a depressed mood now, but if you’re in a real crap mood and you try
something on, you just get worse and you’re like, I want a chocolate. I can’t be bothered
anymore.” (female, 20 years old).
“Well stress a lot, if I’m tired a lot. Just things like if I’m generally feeling a bit lethargic
because I have some health issues and stuff, if that’s playing up then I’ll feel not as good
about myself as normal….. I actually feel fatter, yeah, I feel like I’ve put on weight and I
probably actually haven’t.” (19 year old female).
This was also reflected in some of the male participants, for example, “So when
I’m feeling down, I guess I do become more observant of how I feel and how my image is
being portrayed….So I think when I’m happier, I feel as though I probably do have more,
or I feel more attractive because of that.” (male 22 years old).
Therefore, mood is important to consider as a temporary factor to influencing
body image. Mood was also identified as important for exercise also (explored under the
exercise theme).
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5.3.6 Other Factors
A number of other factors such as influences from family, friends, and romantic
partners were discussed, but mixed responses were gained. Although most participants
did at least mention influences from family, these were noted as more important during
childhood. As participants become older, they were able to discount any negative
influences, or use it as a motivating factor. A 50-year old women commented about her
father’s attitude towards women: “They always had to be really skinny, and there was
always talk about them eating like a bird and this type of thing.” She identified this as
something that angered her, and now she refuses to have this same attitude.
Partners were primarily seen as having a positive impact on participant’s body
image, but this was primarily through a reinforcement of their own self esteem. For
example, a 20-year old female commented, “Yeah, I suppose – I’ve had a few guys that
have treated me like crap and said you’ve got to do this and you’ve got to wear this and
you’ve got to do this. I’m like get stuffed, but the majority of the guys that I’ve been out
with, they’ve always complemented me on my body so that makes me feel good, of
course.”
Therefore, reactions from family, friends, and partners are important, but are
underscored by levels of self esteem. One women for example commented that “Even
though I don’t believe it (positive comments from family), it’s nice to hear it”, while
another women commented “It has to be myself (as most important factor) because it’s
how I feel that drives my behaviour in those situations.”
Cognitive Bias and Body Image 82
5.4 Discussion
5.4.1 Summary of Findings
The purpose of Phase One was to increase understanding of important
components of body image in men and women drawn from a non-clinical sample. The
important factors identified informed the development of the word stimuli in Phase Two,
and the selection of psycho-social variables in Phase Three. Individual interviews were
conducted with eight men and nine women, with six major themes emerging.
Interestingly, no substantial age or gender differences emerged in responses. The few
gender differences are discussed in each theme. These themes and their inter-relations are
summarised in Figure 5.1.
Figure 5.1. Interpretation of inter-relationship between key themes identified in the
qualitative analysis.
Self concept: Body image Health
Culture / Social ideal
Mood Self esteem
Healthy lifestyle
Risky weight management behaviours
Cognitive Bias and Body Image 83
This figure shows the important factor’s identified in conceptualising body image.
Cultural and societal norms are seen as having an overarching influence on what is
considered attractive which indirectly impact’s on one’s body image. The role of self-
esteem and mood are conceptualised as moderating factors in determining how these
societal ideals are interpreted. Body image and health are seen as part of one’s self
concept. The strength of one’s body image determines whether an individual engages in a
healthy lifestyle or engages in risky weight management behaviours. Each of these
factors is now explored in more detail.
The first theme to emerge was the distinction between evaluative and investment
components of body image. While most of the participants were generally satisfied with
their appearance, they could all identify parts of their body that produced dissatisfaction.
However, this dissatisfaction did not have a large impact on their life. This finding
suggests that typical measures of body dissatisfaction may be misleading if they are
simply asking about satisfaction with particular areas, and not considering the impact or
importance of this dissatisfaction. Therefore, in Phase Three of the research
questionnaires were selected that incorporate a measure of both level of dissatisfaction
and importance / impact of these feelings on general functioning.
While most of the participants reported satisfaction with their appearance, a small
group reported currently engaging in behaviours that would be considered ‘risky’ weight
management behaviours. Two of the men reported excessive levels of exercise, high
levels of dietary restraint, and an extreme preoccupation with weight loss, muscle gain
and general appearance. Many of the women reported dieting for both weight loss and
general health reasons either currently or recently, and one woman reported bulimia-like
symptoms (overeating, weight cycling). Three of the women reported experiencing an
Cognitive Bias and Body Image 84
eating disorder in the past, even though it was never formally diagnosed. These findings
suggest that even within a non-clinical sample, levels of body image disturbance are
moderate, and it may be useful to consider the prevalence of risky weight management
techniques as opposed to formal diagnosis.
The importance of being fit and healthy was noted by all participants, and was
therefore identified as a key theme. In fact, many participants defined their body image in
terms of satisfaction with their health and fitness levels. This was not restricted to males,
or even those who currently reported exercising. Many participants noted that the
increased cultural focus on eating healthy, being a healthy weight, and engaging in
regular exercise was important in shaping their beliefs. The majority of participants
reported that their exercising was primarily for health reasons, but that changes in
appearance were also important. Only three participants reported exercising for purely
appearance reasons. Many of the participants emphasised the importance of being fit in
their self concept and generally feeling good about themselves. Given this strong
emphasis on health and fitness, it was considered important to include exercise-related
stimuli in the Emotional Stroop task, and also to include attitudes towards fitness within
the psycho-social variables.
Another key theme to emerge was the importance of having a strong sense of self
that was not reliant on evaluations around appearance and weight. Many participants
commented on the number of other factors that were more important within their self
concept, such as achieving at university, securing a career, and having a supportive
family. However, the importance of feeling confident (which was related to looking
good) when achieving these goals was regularly highlighted. Having a strong self esteem
was rated by all participants as one of the most important factors in influencing their
Cognitive Bias and Body Image 85
body image. Believing in one’s self worth was identified as a protective factor when
exposed to things like comments from family or friends or being exposed to idealised
images in the media. Developing a strong self esteem was identified as the means through
which individuals could overcome times when they were experiencing body image
disturbance. Therefore it was considered important to include it as a psycho-social
variable in Phase three of the research.
All participants in the study identified the cultural obsession with being thin and
attractive, and the stigma against being overweight, so this was made into another key
theme. Participants could not clearly identify where this message come from, although
the media was regularly acknowledged. Most of the participants reported that they were
not negatively affected by these images in the media, but did acknowledge the images
were harmful in creating an unrealistic social idea. Most of the participants identified the
unrealistic nature of these images, but a few of the women reported that it was difficult
for them to completely ignore. Many of the female participants reported frustration at
only being exposed to the one type of image (i.e., thin, tall, attractive women). The men
seemed better able to ignore these images than the women, perhaps because some of the
men reported the images as motivating to improve their own appearance.
The media wasn’t identified as the main conveyor of this ideal, but it seemed that
participants did not know where else to attribute this message. Some participants talked
about ‘society’ and ‘culture’ as a whole, and that is was likely that this ideal was
conveyed in multiple ways, such as advertising, books, television, and social groups.
Where ever this ideal was ascribed to, all participants did report an awareness of it and
acknowledged that it was important in creating a society obsessed with appearance.
While this emerged as a strong theme, it was not clearly enough articulated by
Cognitive Bias and Body Image 86
participants to inform measurement selection in subsequent phases. Also, the reaction to
this cultural ideal appeared to be moderated by an individual’s body image, which was
further influenced by their self esteem. That is, everyone is exposed to the cultural ideal,
but only some people respond negatively to it.
Another key theme to emerge was the effect of mood on body image. Participants
regularly noted that their feelings of attractiveness fluctuated depending upon things like
mood. A general bias was noted such that feelings of stress or depression were associated
with viewing the self more negatively, while feelings of happiness or excitement resulted
in a more positive evaluation. As well as influencing body image, negative mood was
also the outcome of body dissatisfaction. Participants reported feeling depressed if they
could not find clothes to fit, or felt that they did not look nice. Some of the women
reported that they actually felt fatter when depressed. Therefore, the experience of
negative mood is important to consider as word stimuli in Phase Two, and also as a
psycho-social variable in Phase Three.
The final theme to emerge reflected the influence of family and friends on body
image. While all participants noted family and friends, not many reported this as a
negative influence. At least half of the participants reported some negative comments in
childhood about appearance, but none of the participants reported any long-term effects
of those comments. Friends and romantic partners were primarily seen as positive
influences, but this simply reinforced their own feelings of self worth. That is, by having
a strong self esteem participants were already confident in themselves. Therefore, the
influence of family and friends was not included in subsequent phases of the research as
it was not seen as a major influencing factor.
Cognitive Bias and Body Image 87
Therefore, the results of the qualitative analysis in Phase One identified important
components of male and female body image to be included in subsequent phases of the
research. A few limitations should be noted however with the research.
5.4.2 Limitations
One limitation of the study may be that only those interested in the topic of body
image volunteered, thereby reducing the generalisability of the findings. It’s also
conceded that for some people the topic of body image may be sensitive one, and
therefore chose not to participate. While interviews were chosen for this reason over
focus groups, it’s acknowledged that other, more anonymous methodologies, such as
mailed questionnaires, may have encouraged more respondents. However, given the
exploratory nature of the research questions, interviews were considered preferable.
A second limitation of the study reflects the incentives that some participants
received. Eligible first year students received course credit for taking part in the study,
while other participants received no incentives. Whilst it’s difficult to ascertain the exact
influence that this difference in incentives had on the results of the study, there was only
one participant who seemed ‘closed-off’ in the interview. This was one of the first year
students who received credit for participation, and her interview was excluded from
analysis. During the interview she answered questions very briefly, providing little detail
or elaboration. Additionally, she did not acknowledge many factors as influencing body
image, and seemed reluctant to provide any in-depth comments. It is acknowledged that
this may not have reflected her participating for gain only, but may have reflected a
communication or rapport breakdown with the interviewer. Either way, it was deemed
appropriate that this interview be excluded from analysis.
Cognitive Bias and Body Image 88
A third possible limitation of the study may be that the interviews were conducted
by a young female (aged 23 years). It is difficult to determine what effect this may have
had on respondents, and whether a male interviewer, or an older interviewer would have
elicited different information. Whilst the age and gender of the interviewer is a factor
acknowledged in other qualitative studies (e.g., Halliwell & Dittmar, 2003; Ziebland,
Robertson, & Neil, 2002), the precise nature of this influence is yet to be clearly
established.
The typical methodology used in body image research is standardised
questionnaires. While the use of questionnaires undoubtedly has advantages, they can at
times fail to capture the rich experiences, beliefs, and stories of participants. As issues
regarding body image may be sensitive for some people, one-on-one interviews were
chosen over group discussions. Interviews provide more privacy and intimacy, which
should facilitate open sharing of experiences. This study was useful in identifying the key
factors that are important in understanding the body image of males and females.
5.5 Summary of Chapter
This chapter presented Phase One of the research program. Interviews conducted
with eight males and nine females highlighted a number of important influential factors
in body image, such as the importance of health and fitness, the distinction between
evaluation and investment in body image, the importance on being attractive in society,
the moderating effect of mood, and importance of having strong self esteem. These
factors are to be included as word stimuli in Phase Two of the research, and as psycho-
social vulnerability factors in Phase Three of the research.
Cognitive Bias and Body Image 89
Chapter Six: Selection of the Stroop Stimuli (Phase Two)
6.1 Overview of Chapter
This chapter presents Phase Two of the research where studies were undertaken to
select the stimuli to be used for the cognitive measures. The importance of using
carefully selected word stimuli was highlighted in the literature review in Chapter Two.
To ensure the robustness of word stimuli to be used in the Emotional Stroop task, the aim
of this phase was to develop an empirically supported stimulus set that incorporated
words used in past research and the themes previously identified in the qualitative
analysis of Phase One. This chapter provides the Method, Results, and Discussion for
these studies.
Development of the Stroop stimuli occurred in four stages. Stage One involved
the generation of a list of word categories that would encompass multiple facets of body
image. These categories were developed based on frequently used categories in past
research as well as gaps identified from this research. Further, categories were added
based on the outcomes of the qualitative study in Phase One. After the selection of six
word categories relating to body image, Stage Two generated an initial list of words to fit
these categories. Independent ratings were then sought for these words in stage three to
determine appropriateness. Finally, in Stage Four, neutral words were matched to the
selected target words.
6.2 Stages One and Two: Initial Generation of Stroop Categories and Words
6.2.1 Method
6.2.1.1 Procedure. A literature review using EbscoHost was conducted to
determine the type of words and word categories used in past body image research
examining attentional bias. The types of Stroop categories used and the individual words
Cognitive Bias and Body Image 90
representing the categories were noted. Additionally, guidelines were sought for the
procedure used in the selection of individual words.
6.2.2 Results and Discussion
Based on procedures identified from the literature review in Chapter Three, four
criteria were developed for the selection of the Stroop stimuli to be used in the next phase
of the research. First, the Stroop categories should encompass a broad range of health and
body image concerns relevant to both males and females from a non-clinical sample.
Second, the individual words selected for each Stroop category should have high
semantic inter-relatedness, and be a good representation of their category. Third,
frequency data should be available for the words. Lastly, each category of experimental
words should be matched to a category of neutral words. The selected target words are
matched to the neutral words on length and frequency of occurrence in the English
language. The neutral words from each category should also be carefully selected to
ensure a high semantic relatedness. These guidelines ensure that the experimental and
neutral words are matched on relevant dimensions, with only the emotional salience of
the words being different.
Information on each word’s frequency of usage has typically been gained from
Kucera and Francis (1967). However, a newer source has also become available (Leech,
Rayson, & Wilson, 2001), based on British frequency data. Thus, both sources were used
in the current study to provide frequency data.
Based on word categories used in past body image research and themes identified
in the qualitative analysis, six experimental categories were developed. These categories
were: high- and low-calorie food words, positive- and negative-appearance words,
negative emotion words, and physical activity words.
Cognitive Bias and Body Image 91
Food- and appearance-related words were identified as the most commonly used
Stroop categories in past body image research. The inclusion of these categories is
important, as both food- and appearance-related concerns represent core pathologies in
body image disturbance.
Examination of the words used to represent appearance-related concerns showed
that both positive and negative concerns were commonly being represented in the one
category (e.g., “overweight” and “beautiful” in the same category of “body size / shape”).
It is likely that words signifying being overweight or unattractive represent a distinct set
of concerns to words signifying being thin or attractive. Positive appearance words such
as “thin” may signify a goal to achieve, or elicit negative affect if this goal is not
achieved; a finding that was supported in the qualitative analysis. Thus, to allow finer
discrimination between appearance words with a positive and negative connotation, two
categories representing appearance-related concerns were developed: negative
appearance words and positive appearance words. This distinction had not commonly
been made in past research.
While food-related words have been used frequently in past research, only a
small number of studies to date have directly examined the effects of both high calorie /
forbidden foods, and low calorie / non-forbidden foods (Sackville et al., 1998; Huon &
Brown, 1996). As these studies have reported that selective attention was different for
these two categories, combining a range of food words into the one category does not
allow for subtle distinctions to be made. Within the qualitative analysis both men and
women discussed the importance of eating health and avoiding fattening foods. Thus, two
categories were selected to represent high calorie / forbidden food words and, low calorie
/ healthy food words.
Cognitive Bias and Body Image 92
Food words and appearance words have been used frequently in past research,
however there is limited research examining other facets of body image disturbance.
Given the focus on engaging in a healthy lifestyle and increasing exercise levels
identified in the qualitative study, the category of physical activity / sport words was
developed. Exercise may also represent a means for body change or weight regulation.
No research to date has examined whether stimuli related to physical activity will elicit
attention and memory biases. Thus, this category of physical activity words was included
for exploratory purposes.
Only limited previous research has examined whether words related to negative
emotion would elicit selective attention and memory (Jones-Chesters et al., 1998;
Sackville et al., 1998; Seddon & Waller, 2000). Yet the results of the qualitative analysis
in Phase One highlighted the importance of mood in moderating body image. Past
research provides evidence of cognitive avoidance and attention for this information,
which appears to be linked with Bulimia Nervosa, or Bulimia Nervosa-like symptoms.
The inclusion of words related to negative affect allow for general psychopathology to be
assessed in addition to more specific body image concerns; an important distinction to
make considering the high comorbidity between mood disorders and eating disorders
(Cooper, 1995; Sebastian et al., 1996; Leon et al., 1993).
The aim of Stage One was to develop a list of Stroop categories representative of
a broad range of health and body image concerns reported in males and females from a
non-clinical sample. The six experimental categories developed in stage one
corresponded to concerns surrounding positive- and negative-appearance, high- and low-
calorie foods, negative affect, and physical activity. The aim of Stage Two was to
develop an initial list of words that represented the concerns of each of the six
Cognitive Bias and Body Image 93
experimental Stroop categories. These initial lists of words were generated based on
those used in past Stroop studies, in addition to the identification of core concerns that
emerged in the qualitative analysis in Phase One. Table 6.1 shows the preliminary list of
words generated along with the final selection, which is discussed next.
Table 6.1
Initial list of words generated and expected categorisation. Word proceeded with “*”
indicate final selection.
Positive
appearance
High calorie
foods
Physical
activity
Low calorie
foods
Negative
emotion
Negative
appearance
*Muscular *Chips *Jogging *Apple *Hate *Ugly
*Toned *Pizza *Aerobics *Carrot *Angry *Fat
*Slim *Lolly *Swimming *Vegetable *Stress *Obese
*Attractive *Hamburger *Sport *Celery *Depressed *Overweight
*Slender *Chocolate *Gym *Banana *Anxiety *Unattractive
Thin Cake Hiking Low fat Teasing Plump
Pretty Donut Work out Rice crackers Punishment Cellulite
Skinny Sugar Weights Diet Sad Chubby
Beautiful Ice cream Running Lettuce Alone Fat rolls
Petite Calories Panic Heavy
Biscuits Weight
Fudge
Cognitive Bias and Body Image 94
At the completion of Stages One and Two, the purpose of Stage Three was to
examine the appropriateness of the initial experimental words by seeking independent
raters. Stage Four then matched neutral words to the final selection of experimental
words. Stages Three and Four are now discussed in turn.
6.3 Stage Three: Rating and Final Selection of Experimental Stroop Words
6.3.1 Method
6.3.1.1 Participants. A total of thirty participants (12 males; 17 females) were
recruited from a university and offered course credit for participation. Ages ranged from
17 to 56 years, with an average age of 25.41 years (SD = 10.12). No exclusion criteria
were used.
6.3.1.2 Procedure. Ethical clearance was sought and granted from the University
Ethics Committee. Participants were recruited through the first year notice board and
offered course credit for their participation. Participants were given a brief explanation
of the study and given a booklet containing an information sheet, consent form, and a list
of the words. These documents can be found in Appendix C. Completion of the
questionnaire took approximately 15 minutes.
6.3.1.3 Materials. Sixty-one words were presented from the six experimental
categories previously developed in Stage One and Two (shown in Table 6.1). Participants
were given a rating booklet which asked two questions about each of these words. First,
participants were asked to indicate which category the word best represented from the six
alternatives provided. For example, if the word “thin” was presented, participants had to
circle what type of word “thin” was: positive / negative appearance, high / low calorie
food, negative emotion, or physical activity. Second, participants were asked to rate how
well the word fit the chosen category on a 1-5 scale, where 1 = “Not very representative”
Cognitive Bias and Body Image 95
and 5 = “Very representative. That is, if the participant thought that “thin” was a negative
appearance word, they might rate it as “4”.
6.3.1.4 Method of analysis. Data was examined to find which words were most
representative for each of the six experimental categories. For each word, frequencies
were examined for classification of the word and the representativeness rating. First, the
words were examined for the most common way they were classified. For example, the
word “thin” could be categorised as a positive or negative appearance word. Words that
were clearly placed into one category were then examined for how well they
characterised that category. Words were selected when there was clear agreement
regarding category membership, and the words were rated as being a good representation
(i.e., a rating of “4” or “5”) of that category. That is, a word like “attractive” could only
be included in the final selection if clear agreement was noted that “attractive” was a
good representation of a positive appearance word.
6.4.1 Results and Discussion
The aim of Stage Three was to gather empirical support for the final selection of
experimental words to be used in the Stroop task. Words that were not clearly categorised
as belonging to only one of the options available were excluded. This included the words
“thin”, “low fat”, “teasing”, “calories”, “punishment”, “diet”, “weight”, and “skinny”.
The remaining words were identified as belonging to the categories shown previously in
Table 6.1. The remaining words were examined for their representativeness ratings.
Words that received the highest ratings, and had data available on frequency of
occurrence in the English language, were selected as the final list of experimental words.
This process ensured that the final experimental words used in the Stroop task had
empirical support for their use, and that they were rated as being the most representative
Cognitive Bias and Body Image 96
of the category. The final selection of words to be used in the experimental condition of
the Stroop task is shown in Table 6.1.
6.4 Stage Four: Matching of Neutral and Experimental Words
6.4.1 Method
6.4.1.1 Procedure. Following the final selection of the experimental words
previously described, six categories of neutral words were to be selected. Various word
categories were brainstormed and frequency data for individual words were examined. If
a sufficient match could be found, this word was retained. As with the selection of the
target words, the neutral words had to form a clear semantic category, and be matched to
the target words on length and frequency of occurrence in the English language, as
provided by norms in Kucera and Francis (1967) and Leech et al. (2001).
6.4.2 Results and Discussion
Table 6.2 shows the final selection of words including information on frequency
of usage and word length. For each of the matched categories, a paired samples t-test was
run to ensure there were no significant differences in frequency of occurrence and word
length. Adequate matching was achieved, as no significant differences were noted for any
of the neutral and experimental word categories.
Cognitive Bias and Body Image 97
Table 6.2
Frequencies of Usage and Word Length Data used for Matching of Experimental and Neutral Categories.
Experimental category
Frequency Word length
Neutral category
Frequency Word length
Frequency Word Length
Negative emotion
Subject areas t p t p
Depressed 15 9 Mathematics 20 11 Anxiety 27 7 Medicine 34 8 Stress 38 6 Drama 38 5 Angry 42 5 Historian 30 11 Hate 27 4 Psychology 26 10 Mean (SD) 29.80 (10.61) 6.20 (1.92) Mean (SD) 29.60 (6.98)
8.6 (2.30) 0.58 0.59 -1.98 0.11
Negative appearance
Nationalities
Overweight 3 10 European 7 8 Obese 5 5 Asian 10 5 Fat 33 3 French 32 6 Ugly 21 4 Greek 20 5 Unattractive 3 12 Australian 4 10 Mean (SD) 13.00 (13.49) 6.80 (3.96) Mean (SD) 14.60 (11.43) 6.80 (2.10) -0.20 0.84 0.00 1.00 Low calorie foods
Astronomy
Celery 4 6 Saturn 3 6 Apple 15 5 Mars 19 4 Vegetable 26 9 Astronomy 24 9 Carrot 5 6 Telescope 4 9 Banana 5 6 Jupiter 9 7 Mean (SD) 11.00 (9.51) 6.4 (1.51) Mean (SD) 11.80 (9.31) 7.00 (2.12) 0.10 0.92 0.46 0.66
Cognitive Bias and Body Image 98
Physical activity
Gardening
Sport 45 5 Grass 55 5 Gym 4 3 Tulip 6 5 Aerobics 1 9 Gardening 2 9 Jogging 1 7 Palm 2 4 Swimming 18 8 Rose 18 4 Mean (SD) 13.80 (18.80) 6.40 (2.40) Mean (SD) 16.6 (22.44) 5.40 (2.07) 0.18 0.86 -1.18 0.32 High calorie foods
Animals
Hamburger 10 9 Seal 17 4 Chocolate 9 9 Dolphin 5 7 Lolly 3 5 Mosquito 2 8 Chips 2 5 Cockatoo 1 8 Pizza 3 5 Parrot 2 6 Mean (SD) 5.40 (3.78) 6.60 (2.19) Mean (SD) 5.40 (6.65) 6.60 (1.67) 0.00 1.00 0.00 1.00 Positive appearance
Transport
Attractive 52 10 Holiday 76 7 Slender 19 7 Flying 19 6 Slim 13 4 Transport 14 9 Muscular 16 8 Helicopter 16 10 Toned 1 5 Sedan 1 5 Mean (SD) 20.20 (19.04) 6.80 (2.38) Mean (SD) 25.20 (29.21) 7.40 (2.07) -0.38 0.72 0.33 0.75
Table 6.2 continued
Cognitive Bias and Body Image 99
6.5 Summary of Phase Two
The aim of Phase Two was to develop an empirically supported set of stimuli to
be used in the later Emotional Stroop task. A limitation noted in past research employing
the Stroop task has been the problematic manner in which the words are developed. A
broader set of word categories were developed to overcome the limited manner in which
past research has conceptualised body image. Words relating to both positive and
negative appearance were selected, in addition to a wide range of food words. The
inclusion of words representing negative affect allows for general psychopathology to be
assessed. Additionally, words relating to physical activity and sport were developed; a
category that has not previously been explored with a Stroop task. Words within each of
these six experimental categories were rated for appropriateness by independent raters to
ensure that only the most representative words were included.
Additional methodological refinements were made by ensuring the careful
selection and matching of neutral words. The lack of homogeneity between the neutral
words within a category as compared to the experimental word categories is problematic
given that selective attention is influenced by how highly related words are (Green and
Rogers, 1999). Therefore, in the current study, care was taken to ensure the semantic
homogeneity within each category of experimental and neutral words. Furthermore, the
neutral words were carefully matched to the experimental words on length and frequency
of usage in the English language. This process ensures that only the valance of the words
differed between the experimental and neutral categories, and that any differences in
reaction times are due to the emotional content of the words. The next chapter of the
thesis outlines the methodology the Stroop and memory task these words were in to
assess biased cognitive processing.
Cognitive Bias and Body Image 100
Chapter Seven: Cognitive Methodology Used to Assess Biased Processing (Phase Three).
7.1 Overview of Chapter
The purpose of this chapter is to describe the methodology used for the main
study of the current project. The chapter describes the sample, design, and measures used.
7.1 Method
7.1.1 Participants
A National sample of 201 participants was recruited from the general community
and from two universities. Of the 144 women providing complete data sets, 30% were
recruited from the general community, while 70% were full time university students
studying psychology. Thirty-seven percent of these university students were recruited
from a university in Melbourne, while the remaining 33% were recruited from Brisbane
Universities. Most of the sample (63%) had at least completed 12 years of schooling, and
30% had completed some form of university degree, from a diploma to PhD. The
majority of the sample was Australian-born (86%), and 90% identified themselves as
Caucasian. When marital status was assessed, 30% were single, 32% were married or in a
de facto relationship, 31% were currently dating, and 6% were widowed / separated /
divorced. A wide age range was reported, with ages ranged from 17 to 70 years, with an
average age of 27.71 years (SD = 12.16), however 50% of the sample were aged 21 years
and under. Body Mass Index was calculated from self reported height and weight. Based
on guidelines from the World Health Organisation (2000), 8.3% of the women were
classified as underweight (BMI under 18.5), 62.5 were of a normal weight (BMI 18.5-
24.9), 16.7% were overweight (BMI 25-29.9), while 8.3% were classed as obese (BMI
greater than 30).
Cognitive Bias and Body Image 101
Of the 55 males in the study, just over half (58%) had been recruited from the
general community, and the remaining 42% recruited from Queensland (17%) and
Melbourne (24%) universities. Age ranged from 17 to79 years, with a mean age of 34.54
years (SD = 14.76), with just under half the sample (47%) were aged 29 years and under.
The average BMI of the men was 25.70, with none of the men being classified as
underweight, 50% falling within the normal weight range, 31% being classed as
overweight, and 14.5% as obese. The majority of the sample was well educated, with
only 14% not completing at least a high school education. The majority of the sample
(83%) was Australian born, and 92% identified themselves as Caucasian. A small
percentage described themselves as Asian, Aboriginal or Torres Straight Islander, or
European. When marital status was assessed, 41% of the men were married or in a de
facto relationship, 31% were single, 20% were dating, and 7% were divorced, separated,
or widowed.
Recruitment of participants from the general community was completed through a
series of media campaigns, including local radio and newspaper stories, and a small
segment on a National morning television program. These segments provided a brief
outline of the research and invited interested individuals to contact the researcher via
phone or email. These contacts were followed up and a mutually convenient testing time
was organised. These participants weren’t offered any incentives for participation, but
were given a nominal monetary amount to cover transport costs to and from the
university for testing.
The student participants were sourced from two local universities in Brisbane and
a university in Melbourne. The majority of these students were majoring in psychology,
Cognitive Bias and Body Image 102
and were offered course credit for participation. Testing either took place at the
respective university or at the participant’s home.
Normal colour vision was required to take part in the Stroop colour naming task.
No additional exclusion criteria were applied.
7.1.2 Design
The first Independent Variable was Stroop word category with six levels of the
experimental words. This was a repeated measures variable. The Dependent Variable was
the reaction time in milliseconds to respond to each of the Stroop categories. An
interference index was used wherein the reaction time of each of the experimental
categories was taken from the average of the matched neutral category, to gain an index
of how different the reaction times were for the experimental versus the neutral words.
The second Independent Variable was the body-image category participants were
assigned to during the cluster analysis. This was a between groups variable. Correlations
were also used to explore the relationship between the cognitive variables and a range of
additional psycho-social and demographic factors.
7.1.3 Materials
Two cognitive tasks were used to assess biased attention and memory, and a
battery of questionnaires assessed health and body image. Non-copyrighted
questionnaires are included in Appendix C.
7.1.3.1 Emotional Stroop task. A modified Stroop task was used to assess
selection attention for a range of body image related information. A computerised task
was developed by the associate supervisor, Dr. Doug Mahar, who had extensive
experience in programming psychological experiments. Testing took place on Windows
compatible computer with the screen resolution set to 800 X 600 pixels. A plain blue
Cognitive Bias and Body Image 103
background was used with a grey display box measuring 18 X 25 cm appearing in the
middle of the screen. Participants ran the experiment within this display box. The text in
the display box was presented in the appropriate colour (i.e., red, blue, green, or yellow).
Words in the display box were presented one at a time, were 1.5cm high, in lowercase,
and centred. If no response was given within two seconds, the word disappeared and a
reminder was given to participants to respond as quickly as possible. Participants
responded via four colour keys on the keyboard placed over the arrow buttons. Incorrect
or missed trials were not repeated.
Four colours were used for the words, red, green, yellow, and blue. The
presentation of the words was randomised for each participant, including the order of the
words, and the colour of the word.
Fourteen categories of words were used which consisted of six experimental
categories, six neutral categories, a colour consistent, and colour conflicting condition.
Each of the experimental and neutral categories consisted of five words per category,
while the colour conditions contained the four colour words. This resulted in a total of 68
words. For a full list of these words see Table 6.2 in Chapter Six.
As past research has shown rapid habituation effects (e.g., McNally, Riemann, &
Kim, 1990), each word was only presented twice in the Stroop task, giving a total of 136
trials. Pressing the space bar started each individual trial. Additionally, 10 practice trials
were given prior to the Stroop task, using a set of words revolving around office furniture
that did not appear in the actual task. Participants could repeat these practice trials if
needed. Testing took place individually, or in small groups, and took approximately four
minutes to complete.
Cognitive Bias and Body Image 104
7.1.3.2 Distracter task. Participants were asked to complete as many simple
multiple choice mathematics questions as they could within two minutes. This was to
reduce any effects of short term memory before the incidental memory task.
7.1.3.3 Incidental memory task. Participants were asked to list as many words as
they could remember from the Stroop task within three minutes on paper.
Following the cognitive tasks, a battery of psycho-social questionnaires was then
administered.
7.1.3.4 Demographic form. Participants were asked standard demographic
information such as their gender, age, height and weight (to calculate Body Mass Index),
ethnicity, and marital status. Information was also sought regarding any history of an
Eating Disorder, highest and lowest adult weight, and the type and frequency of exercise
in which they typically engage.
7.1.3.5 Hunger levels. Current level of hunger was assessed on a 1-10 scale, along
with an open ended question asking how long it had been since food had been consumed.
This was intended to rule out any effect hunger may have on performance in the Stroop
task.
7.1.3.6 Negative mood. The Depression, Anxiety, Stress Scale (Lovibond &
Lovibond, 1995) was used to measure self reported negative affect. Each of the three
subscales (Depression, Anxiety, and Stress) contains seven statements that respondents
indicate how much the statement has applied to them over the past week. Response
options range from 0 (did not apply to me at all) to 3 (applied to me very much, or most
of the time). Scores on the three subscales range from 0-42, with higher scores indicating
higher levels of negative affect. High alpha coefficients for all subscales have been
reported (Lovibond & Lovibond, 1995). All participants completed the Depression
Cognitive Bias and Body Image 105
subscale but due to a photocopy error only 30% of participants completed the Anxiety
and Stress subscales.
7.1.3.7 Reasons for Exercise. Reasons for exercise was measured using the Reasons
for Exercise Inventory (Silberstein et al., 1988). Twenty-four items cover seven general
domains of reasons for engaging in exercise, namely: exercising for weight control,
physical attractiveness, improving mood, body tone, health, and enjoyment. Each
subscale contains between three and four items that are answered on a 1 (not at all
important) to 7 (extremely important) semantic differential scale. Six out of seven scales
show acceptable internal consistency, with a range from .67 for enjoyment to .81 for
weight control.
7.1.3.8 Dysfunctional behaviours. Participants were asked to indicate “Yes” or “No”
as to whether they have engaged in the following behaviours to achieve weight loss in the
last six months: vomiting, laxative use, diuretic use, use of slimming tablets, fasting,
excessive exercising, dieting for health reasons, and dieting for weight loss. Additionally,
these were asked about whether they had binged on large amounts of food, and if they
felt a loss of control over that binging episode.
7.1.3.9 Eating Disorder Behaviours. The Eating Disorder Inventory (EDI; Garner,
Marion, Olmsted, & Polivy, 1983) is a 64-item questionnaire that assesses the
psychological and behavioural characteristics commonly found in eating disorders. Each
item is responded to on a 6 point Likert scale ranging from “always” to “never”. It
consists of eight subscales, namely Drive for Thinness, Bulimia, Body Dissatisfaction,
Ineffectiveness, Maturity Fears, Interpersonal Distrust, Interoceptive Awareness, and
Perfectionism. Research has shown this test to be reliable and valid, and scores are able
to differentiate eating disordered groups from other groups (Garner, et al., 1983).
Cognitive Bias and Body Image 106
7.1.3. 10 Body Mass Index (BMI). Self reported height and weight was obtained as
part of the demographic form. BMI was calculated by using the formula: kg/height in
meters². BMI is a general measure of body size.
7.1.3. 11 Self-esteem. The Rosenberg Self-Esteem Scale (Rosenberg, 1965) is the
most widely used questionnaire for measuring self-esteem. It is a short, 10-item measure
of general feelings of ones' self worth. Respondents rate the items on a 4 point Likert
scale from "Strongly Agree" to "Strongly Disagree". Half the items are reversed scored
so that higher scores indicate higher levels of self esteem. This scale shows adequate
psychometric properties with a test-retest reliability of .85, and it correlates satisfactorily
with other measures of self-esteem (Heinberg et al., 1995).
7.1.3.12 Social functioning. To measure general well-being, the Social
Functioning Questionnaire (Tyrer et al., 2005) was used. This brief 8-item measure is
based on the earlier Social Functioning Questionnaire which in turn was based on the
semi-structured interview protocol the Social Functioning Schedule. These two earlier
assessment tools were used extensively to measure well-being in a number of domains,
yet were quite lengthy. As such, the more recent version provides a brief, yet
psychometrically sound, assessment of social functioning (Tyrer et al., 2005).
Questions assess functioning in a range of life domains such as money problems,
relationships with others, and work satisfaction. Responses are made on a 4-point scale
and indicate how often problems in this arena occur. Normative data from a large non-
psychiatric sample are available. Scores range from 0-24, with higher scores indicative of
poorer social functioning.
7.1.3.13 Body attitudes. To assess a range of body image attitudes, two scales
were used, the full 69-item version of the Multidimensional Body-Self Relations
Cognitive Bias and Body Image 107
Questionnaire (MBSRQ; Cash, 2000), and The Body Attitudes Questionnaire (BAQ;
Ben-Tovim & Walker, 1991).
The MBSRQ consists of 10 subscales. The first six subscales measure satisfaction
with, and investment in appearance, fitness, and health (Appearance Evaluation; seven
items; Appearance Orientation; 12 items; Fitness Evaluation; three items; Fitness
Orientation; 13 items; Health Evaluation; six items; Health Orientation; eight items). The
Illness Orientation subscale measures reactivity to feelings of illness, while the final three
subscales measure satisfaction with particular body areas (Body Areas Satisfaction Scale;
nine items), self- and other-perceived weight status (Self-Classified Weight; nine items),
and fear of fatness / diet attempts (Overweight Preoccupation; four items). Some items
are reversed-scored, so that higher scores are more pathological.
Large-scale studies reveal the MBSRQ to be psychometrically sound, with high
Cronbach’s alphas (none less than .70). Sound test-re-test reliability for all subscales
(none less than .71) have also been noted across male and female samples (Cash, 2000).
To assess a range of attitudes women hold about their bodies, the BAQ was
deemed most appropriate. The BAQ contains six self-report subscales that will be used
namely Feeling Fat, Body Disparagement, Strength and Fitness, Salience of Weight and
Shape, Attractiveness, and Lower Body Fatness. Each of these subscales has been shown
to reflect body concerns that Australian women have, based on a community sample.
There are 44 items in total, with sub-scales ranging from four items (lower body fatness)
to 13 items (feeling fat).
This scale has sound psychometric properties: The full scale has a Cronbach’s
alpha of .87 indicative of high internal consistency. This scale is also reliable with a split-
half Kuder Richardson correlation coefficient of .92 and a test-retest reliability of .90 for
Cognitive Bias and Body Image 108
the feeling fat subscale (Ben-Tovim & Walker, 1993). Additionally, normative values are
available for Australian women.
7.1.3.14 Desire for muscularity. To assess pursuit of a muscular physique the
Drive for Muscularity scale (McCreary & Sasse, 2000) was used. This 15-item measure
assesses desire to improve tone and muscularity, and the means through which this is
achieved (such as weight lifting, drinking protein shakes). Each item is scored on a six
point scale ranging from always to never, with higher scores indicating greater drive for
muscularity. Adequate psychometric properties of this scale have been reported in both
males and females (McCreary & Sasse, 2000).
7.1.3.15 Dietary restraint. The Restraint Scale (Herman, Polivy, Pliner,
Threlheld, & Munic, 1978) is a widely used measure of dieting behaviours,
preoccupation with eating, and history of weight fluctuations. This scale consists of 10
items with higher scores indicating a higher level of dietary restraint, which appears to be
associated with chronic dieting (Ricciardelli & Williams, 1997). Adequate psychometric
properties have been reported (Ricciardelli & Williams, 1997).
7.1.4 Procedure
During recruitment, participants were not informed of the full nature of the study
to try and reduce demand characteristics. Instead, a cover story was given that the study
was examining speed of information processing and health behaviours, with a focus on
body image. Participants were told the study consisted of two components: some tasks
that measured reaction time, and then a set of questionnaires that measured a range of
health behaviours including questions about body image. A copy of the information and
consent forms can be found in Appendix D.
Cognitive Bias and Body Image 109
The Stroop was completed first. Participants were told they were completing a
measure of speed of information processing and to respond as quickly but as accurately
as possible, to words that would appear on the screen. They were instructed to ignore the
meaning of the words and just focus on the colours.
Upon completion of the Stroop task, the distracter task was given. Participants
were told this was also a measure of speed of information processing, and they needed to
answer as many questions as possible within two minutes.
The incidental memory task was then given. Participants were asked to recall as
many words as possible that they had seen on the screen during the colour naming task,
even though they had been previously instructed to ignore these words. Participants were
encouraged to use the full three minutes, even if they felt they could not recall any words.
Full debriefing was then provided, including the reasons for the use of mild
deception (e.g., that participants could not know about the memory task as it would
influence their responses). Participants were then asked to complete a questionnaire
package that assessed a range of health behaviours and attitudes, with a focus on body
image.
Cognitive Bias and Body Image 110
Chapter Eight: Results and Discussion for Biased Cognitive Processing
8.1 Preliminary Analyses
8.1.1 Overview of Analyses
The results are examined first for females, followed by the results for males, and
finally an examination of sex differences. Within each of these three main sections, the
results are further divided into the analyses examining group membership, selective
attention, selective memory, and the relationship between attention and memory.
Differences between groups were analysed using ANOVA’s, while correlations were run
to examine how the psycho-social variables were related to the cognitive data.
8.1.2 Data Screening
All analyses were conducted using The Statistical Package for the Social Sciences
(SPSS), and were evaluated against a 0.05 significance level for 2-tailed tests, unless
otherwise specified. Given the exploratory nature of this research, trends are also reported
(i.e., p values of 0.06 or 0.07). Prior to analyses, all variables were examined for accuracy
of entry and missing values. Missing data was coded when participants missed a
question, a page, or gave multiple responses. There was only a small amount of missing
data and was thus coded as such. As a cluster analysis cannot be conducted on variables
with missing values, a mean replacement was used on the BAQ subscales. Histograms of
all cognitive and psychosocial variables were examined for normality and outliers. All
data was reasonably normally distributed, no significant skewness or kurtosis was noted,
and no outliers were identified. Scores on the Depression, Anxiety, and Stress subscales
of the DASS showed some positive skewing, indicating low levels of these constructs
within the sample. Analyses involving these variables were run with both the original
scores and transformed scores, and both sets of results are given when relevant.
Cognitive Bias and Body Image 111
8.1.3 Scoring of the Cognitive Data
8.1.3.1 Scoring of the Stroop data. The average reaction time to respond to each
of the Stroop categories was analysed. Examination of error rates, which included the
selection of an incorrect colour, or a missed trial through responding too slowly / quickly
were manually examined. Overall, the number of errors participants made was small,
with the average being less than one error in each experimental and neutral category.
Two participants were excluded due to large error rates: one female participant who made
errors on 28% of trials and one male who made errors on 16% of trials. Responses greater
than two seconds were automatically excluded from the data by the Stroop program.
Given the large age range in the sample, and the recommendations made by
Dobson and Dozois (2004), interference indexes were calculated for the Stroop data to
allow for age differences in responding. Preliminary analyses revealed that age had very
strong significant correlations with raw reaction times, with older people taking longer to
respond to the all of the Stroop categories. To allow for age differences in response times,
interference indexes were calculated. These indexes are a measure of how much longer
each participant took to respond to the experimental words as compared to the neutral
words. Six interference indexes were calculated, corresponding to each of the six
experimental categories. For example, the interference index for the Negative Emotion
words was calculated by subtracting the reaction times for the Subjects category. A
negative score on the interference index indicates that response times were faster for the
experimental words than for the matched neutral words, while positive scores indicate
that response times are slower for the experimental words.
8.1.3.2 Scoring of the memory data. In addition to biased attention scores,
memory biases were also assessed. First, words in each category were scored as correct if
Cognitive Bias and Body Image 112
they had been previously presented on the Stroop task, or were a close variant of the
word (e.g., stress / stressed). Second, raw scores were converted into percentages to
account for individual differences in the total number of words recalled. Responses were
scored as the total number of correctly recalled words from each of the six experimental
categories divided by the total number of words recalled across all categories. It is
important to consider percentage scores as they give more information than raw scores.
For example, if a person correctly recalled ten words, but only three of those were
experimental words, they are responding quite differently from a second person who
correctly recalls only three words, but all three of these words are from experimental
categories.
8.1.4 Identification of Sub-Groups: The use of Cluster Analysis
8.1.4.1 Overview of the cluster analysis technique. As noted in the literature
review, past research using the Stroop task has typically compared a clinical group to a
presumed homogeneous control group, or has compared control groups on one
vulnerability factor. This rather simplistic analysis fails to acknowledge a wide range of
vulnerability factors, and the complex interaction of these factors. In order to examine
sub-groups of body image disturbance within a non-clinical sample, a cluster analysis
was conducted. The purpose of a cluster analysis was to examine whether participants
can be divided into homogenous sub-groups based on a similar profile of scores.
An overview of cluster analysis as a statistical technique is provided in Appendix
E. Briefly, cluster analysis is a statistical technique applied to multivariate data designed
to identify homogenous sub-groups (Aldenderfer & Blashfield, 1984). Conceptually, it is
similar to factor analysis in that it searches for underlying latent variables. However, in a
Cognitive Bias and Body Image 113
cluster analysis, this procedure is applied to variables rather than individual cases. The
outcome of a cluster analysis is set of homogenous groups.
Based on these recommendations from the literature (Aldenderder & Blashfield,
1984; Hair, Black, Babin, Anderson, & Tatham, 2006; Lange, Iverson, Senior, &
Chelune, 2002) a hierarchical cluster analysis using an average linkage method and
squared Euclidian distance measure was used. It should be noted that the cluster analysis
was used simply to provide some basic empirical support for the types of sub-groups
within the non-clinical sample. While it is recognised that cluster analysis has a number
of limitations, this procedure was deemed more useful than simply comparing individuals
on a median split, as past research has typically done. Instead of defining groups by one
variable, a cluster analysis allows for a more comprehensive understanding, as multiple
variables are taken into account.
The cluster analysis was completed separately for males and females for two
reasons. First, different factors were identified as influencing males and females body
image in the literature review and the outcomes of the qualitative analysis in Phase One.
Second, it was hypothesised that males and females would differ on their cognitive
processing therefore it was not meaningful to combine these two samples.
8.1.4.2 Results of cluster analysis for women. Core body image concerns, as
assessed by the BAQ were entered as six variables into the cluster for the 143 women.
Missing variables on the BAQ were replaced with the mean of the respective sub-scale.
In order to determine how many clusters were meaningful, a number of indicators were
examined. Based on the outcomes of the dendrogram, Icicle plot, and fusion coefficients,
a four cluster solution was deemed most appropriate. The decision processes is provided
Cognitive Bias and Body Image 114
in more detail in Appendix E along with the description of the cluster analytical
procedure.
Descriptive information for the four cluster solution is shown in Table 8.1. In the
four cluster solution, the emergence of a discrete highly symptomatic group is noted. This
was not evident within the two or three cluster solution.
Table 8.1
BAQ Sub-Scale Scores for the Four Cluster Solution in Women.
Cluster 1
(n = 62)
Cluster 2
(n = 28)
Cluster 3
(n = 36)
Cluster 4
(n = 17)
BAQ sub-
scale
M SD M SD M SD M SD
Attractiveness 14.08 2.18 15.57 1.39 11.52 2.13 13.76 2.25
Disparagement 13.84 2.70 11.07 1.58 20.67 3.14 20.82 3.76
Feeling fat 35.65 7.18 32.79 7.59 49.72 6.28 53.58 6.71
Salience 19.14 3.56 17.14 4.17 25.02 3.93 30.64 2.62
Lower body
fatness
11.05 3.16 8.92 2.52 14.30 2.77 16.29 3.07
Strength /
fitness
16.41 3.09 22.60 2.31 14.80 3.11 19.17 2.83
Examination of the profiles within the four cluster solution revealed four distinct
groups. Cluster one and two show similar means on most of the BAQ subscales. These
groups are characterised by higher feelings of attractiveness, little loathing of one’s body,
Cognitive Bias and Body Image 115
low feelings of fatness and low importance of appearance in one’s life. Cluster one and
two differ however on Lower Body Fatness and Strength / Fitness, with Cluster two
showing higher feelings of strength and fitness and less feelings of lower body fatness.
Cluster three and four appear to reflect groups of women with highly dysfunctional body
image attitudes. In particular, the means in Cluster four are similar to, or more
dysfunctional, than the scores found in Anorexic samples (Ben-Tovim & Walker, 1992).
Based on these scores, cluster one and two appear to reflect a group with very
little body image concerns. The distinguishing features between cluster one and two are
the high reports of strength and focus on fitness (and perhaps corresponding lower body
fatness) within cluster two. Hence these clusters were named “Normal” and “Athletic”
respectively. Cluster three appears to reflect a group that experiences moderate level of
dissatisfaction, and were therefore labelled “Dissatisfied”. Cluster four, having the most
dysfunctional profile closely representing scores of Eating Disordered samples, were
therefore labelled “Symptomatic”.
One criticism of cluster analysis has been that the use of different cluster
techniques can result in alternate group formations (Aldenderder & Blashfield, 1984;
Hair et al., 2006; Lange et al., 2002). In an attempt to overcome this limitation, the cluster
analysis was re-run using a different algorithm. A Wards’ method was used, as some
researchers recommend the use of this algorithm (e.g., Francis, 2004). Using this Ward’s
method, a similar result emerged to the previously described cluster solution.
According to Aldenderder and Blashfield (1984), additional support for the
validity of the clusters may be sought by comparing them on other key variables. The
four clusters were compared on relevant demographic variables of BMI and age, in
Cognitive Bias and Body Image 116
addition to other functionality measures of negative mood, self esteem, quality of life,
and number of risky weight management behaviours.
Cluster membership was entered as an Independent Variable in a one-way
Independent Groups ANOVA, with the functionality measures and demographic
variables as Dependent Variables. A breach of the homogeneity of variance assumption
was noted for BMI. Examination of the distributions within each cluster revealed no
outliers, nor any significant skewness or kurtosis. Log 10 and Square root transformations
of the data did not change the overall significance of the ANOVA. Additionally, the ratio
of smallest to largest variance did not exceed three, therefore the original scores were
maintained (Keppel, 1991). A significant breach of the homogeneity assumption was also
noted for depression scores. This appeared to be the result of small Standard Deviation in
the Athletic group compared to a large Standard Deviation in the Symptomatic group. A
square root transformation was applied to all depression scores which resulted in the
assumption being met. The transformed depression scores were retained for this analysis,
but did not change the outcome of the ANOVA, nor the pattern of significant post hoc
tests, therefore untransformed scores were retained for ease of interpretation.
A breach of the homogeneity of variance assumption was noted for age.
Examination of the distributions within each cluster revealed no outliers, nor any
significant skewness or kurtosis. Log 10 and Square root transformations of the data did
not change the overall significance of the ANOVA, or the pattern of significance with the
post hoc tests. Additionally, the ratio of smallest to largest variance did not exceed three,
therefore the original scores were maintained for ease of interpretation.
Scores on anxiety also showed a significant breach of the homogeneity of
variance assumption. Applying a square root transformation resulted in the assumption
Cognitive Bias and Body Image 117
being met, but the ANOVA was no longer significant. In this case, transformed scores
were retained.
Results of the ANOVA’s revealed that the four clusters differed significantly on
most of the functionality indicators. Significant differences were followed up with post
hoc tests with a Bonferonni adjustment (.05 / 4 = .012). Means are shown in Table 8.2.
Table 8.2
Differences in Demographic and Social Functioning Scores Between the Four Sub-
Groups Identified in Women (Standard deviations in brackets).
Normal
(n = 62)
Athletic
(n = 28)
Dissatisfied
(n = 36)
Symptomatic
(n = 17)
M (SD) M(SD) M(SD) M(SD)
Age 26.16 (10.73) 35.53 (15.27) 25.50 (9.73) 25.64 (12.15
BMI 22.06 (3.68) 22.44 (2.33) 25.07 (5.17) 25.62 (4.64)
Depression 6.16 (6.07) 2.89 (2.72) 9.94 (8.77) 10.05 (10.24)
Anxietyⁿ 1.78 (1.42) 1.59 (0.62) 2.83 (1.43) 2.62 (1.98)
Stress 10.52 (6.52) 9.57 (5.99) 16.36 (9.25) 14.50 (12.04)
Self esteem 30.63 (4.10) 33.55 (3.97) 27.11 (3.95) 27.52 (4.78)
Social
functioning
7.60 (3.19) 4.92 (2.20) 8.86 (2.97) 9.76 (4.54)
Dietary
restraint
10.96 (5.02) 10.84 (4.99) 16.62 (4.79) 20.06 (4.13)
Quality of life 0.98 (0.87) 1.59 (0.79) -0.04 (0.96) 0.28 (1.25)
ⁿ Square root transformed scores.
Cognitive Bias and Body Image 118
There was a significant difference between the clusters on depression scores, F (3,
138) = 6.68, p = .0001. The Athletic group reported much lower depression scores than
the other groups, although there was no significant difference between the Athletic and
Normal groups. Both of these groups had significantly lower depression scores than the
Dissatisfied, but only the Athletic group was significantly lower than the Symptomatic
group. There was no difference between the Dissatisfied and Symptomatic groups.
The groups did not significantly differ on stress, F (3, 37) = 1.56, p = .21 or
anxiety scores, F (3, 38) = 1.87, p = .15. Significant differences were noted in age, F (3,
139) = 5.14, p = .002, with the Athletic group being significantly older than all the other
groups. The groups could be significantly distinguished on BMI, F (3, 136) = 6.45, p =
.0001. The Athletic and Normal groups had the lowest BMI’s, and were not significantly
different from each other. Similarly, the Dissatisfied and Symptomatic groups were not
significantly different from each other on BMI. Both of these latter two groups were
significantly heavier than the former groups.
The four groups also differed significantly on self esteem, F (3, 135) = 14.89, p =
.0001, the impact that one’s body image has on quality of life, F (3, 132) = 18.39, p =
.0001, and social functioning, F (3, 139) = 6.42, p = .0001. Self esteem and quality of
life did not differ between the Dissatisfied and Symptomatic groups, but both groups
were significantly lower on self esteem and higher on quality of life, than the Athletic and
Normal groups. In addition, the Athletic group had significantly better self esteem and
better quality of life than the Normal group. The Athletic group had significantly better
social functioning than the other three groups. The Normal, Dissatisfied, and
Symptomatic groups did not differ. Finally, the groups differed significantly on dietary
restraint, F (3, 133) = 22.42, p < .001. The Normal and Athletic group reported a low
Cognitive Bias and Body Image 119
level of dietary restraint, and were not significantly different from one another. The
Dissatisfied and Symptomatic group reported levels indicative of high dietary restraint,
and were significantly higher than the Normal and Athletic groups.
Together, these results provide support for the existence of independent sub-
groups within a non-clinical sample. The women classified as Symptomatic in this
sample had similar scores on the body image variables that have been reported in
Anorexic samples. Compared to the other sub groups identified, the Symptomatic group
reported the poorest social functioning and self esteem, report more depression, and have
the highest BMI’s. The Dissatisfied group also report symptomatic scores on all body
image variables, and report moderate levels of the functionality measures. The women
classified as Normal and Athletic appear to not experience negative body image
concerns, and they also report better overall functioning.
8.1.4.3 Results of the cluster analysis for men. The measure used for the cluster
analysis in females, the BAQ, was developed specifically to encompass women’s body
image concerns, thus it was not deemed useful to categorise males. Instead, the MBSRQ
was used. A full description of the MBSRQ was given in the Stroop Materials section.
Briefly, the MBSRQ is one of the few measurement tools available that adequately assess
a wide variety of male body image concerns. Additionally, this scale reports excellent
psychometric properties, and normative data is available. Six subscales of the MBSRQ
were used in the cluster analysis for males: the Appearance Evaluation and Orientation
subscales, the Fitness Evaluation and Orientation subscales, the Health Orientation
subscale, and the Overweight Preoccupation Subscale. These subscales were selected to
cover feelings of attractiveness, general health and fitness, importance placed on
appearance and fitness, and dietary restraint; key variables that emerged in the qualitative
Cognitive Bias and Body Image 120
study of Phase One. The other four subscales of the MBSRQ were not used in the cluster
analysis for two reasons. First, those subscales did not emerge as core facets of men’s
body image concerns (e.g., illness preoccupation and perceived weight category).
Second, given the relatively small data set, only a limited number of clustering variables
could be used (Aldenderder & Blashfield, 1984). As cluster analysis requires a complete
data set, missing data was replaced with the mean of the subscale.
Core body image concerns, as measured by the six subscales of the MBSRQ,
were entered for the 54 men. A hierarchical cluster analysis using a Ward’s Method and
squared Euclidian distance measure was run on standardised scores. In order to determine
how many clusters were meaningful, a number of indicators were examined. Inspection
of the agglomeration schedule, fusion coefficients, and the dendrogram revealed that a
three cluster solution was most appropriate. A full description of this decision processing
is provided in Appendix E. The means for the MBSRQ subscales are shown in Table 8.3
for the three cluster solution.
This three cluster solution resulted in quite distinct groups that differed both
qualitatively and quantitatively. Group one was the largest group (n = 26), and reported
normative levels on most of the body image variables (sub-scales of the MBSRQ). This
group reported moderate feelings of attractiveness, high feelings of fitness, and low
overweight preoccupation. Little importance was placed on appearance, health, or fitness
in their lives. This group could perhaps be summarised as being happy with their body
image and placing low importance on body image. This group was therefore labelled
“Normal”.
Cognitive Bias and Body Image 121
Table 8.3
Descriptive Data for the MBSRQ Sub-Scales for the Three Cluster Solution in Males.
Cluster 1
(n = 26)
Cluster 2
(n = 19)
Cluster 3
(n = 9)
MBSRQ subscale M (SD) M (SD) M (SD)
Appearance Evaluation 3.69 (0.55) 2.52 (0.57) 3.97 (0.37)
Appearance Orientation 2.85 (0.51) 3.40 (0.64) 3.54 (0.78)
Fitness Evaluation 4.06 (0.55) 3.47 (0.78) 4.48 (0.50)
Fitness Orientation 3.22 (0.76) 3.16 (0.42) 4.35 (0.32)
Overweight Preoccupation 1.34 (0.33) 2.46 (0.80) 2.58 (0.53)
Health Orientation 3.33 (0.74) 3.12 (0.77) 4.18 (0.58)
Group two was a slightly smaller group of men (n = 19) with low feelings of
attractiveness and fitness, average overweight preoccupation, and a low importance
placed on appearance, fitness, and health. Compared to the Normal group, group two
reported lower levels of attractiveness, but placed more importance on appearance. Group
two also reported lower feelings of fitness, but were not motivated to do anything about
it. Therefore this group was labelled “Dissatisfied”.
A clear picture emerged with the characteristics of Group three (n = 9) who
represented a group of men who were driven by health and fitness. This group reported
the highest levels of feeling attractive, but placed only a moderate importance on
appearance. Additionally, high levels of fitness and a high importance on regular fitness
and maintaining a healthy lifestyle were noted. This group also reported very high levels
Cognitive Bias and Body Image 122
of fat anxiety / weight vigilance; higher levels than either Group one or Group two. Based
on these characteristics, this group was termed “Health Conscious”.
To gain additional support for the validity of the three cluster solution, the three
clusters were compared on additional variables not included in the cluster analysis.
Support for the distinctiveness of the three clusters should come from differences in
demographic (age and BMI) and functionality measures (mood, self esteem, quality of
life, number of risky behaviour in last six months, and social functioning).
Cluster membership was entered as an Independent Variable in a one way
Independent Groups ANOVA, with the functionality measures as Dependent Variables.
The results for anxiety and stress could not be used, given the small sample size of men
who actually completed these measures. The homogeneity of variance assumption was
breached for three of the variables: number of risky behaviours in the last six months,
quality of life, and BMI. Examination of the frequency distributions for the number of
risky behaviours in the last six months revealed that the Normal group was positively
skewed, in that most of the group reported none of risky behaviours. The Dissatisfied and
Health Conscious groups were more normally distributed. A log 10 transformation
resulted in the assumption being met, but the ANOVA was no longer significant. While
the transformed scores were retained, it is worthwhile noting the substantially lower
levels of risky weight management behaviours in the Normal group.
Examination of the histograms for BMI revealed no skewness, kurtosis, or
outliers. However, the standard deviation of the Dissatisfied group was twice as large as
the Normal and Health Conscious groups. Applying a square root transformation resulted
in the homogeneity of variance assumption being met, and did not change the significant
result of the ANOVA. Therefore, for aid of interpretation, the untransformed BMI scores
Cognitive Bias and Body Image 123
are retained. Table 8.4 provides a comparison of the demographic and functionality
scores across the three clusters.
Examination of the means revealed that the Dissatisfied had consistently poorer
functioning than the Normal and Health Conscious groups. On every one of these general
well-being variables, the Dissatisfied group had the most dysfunctional scores.
Additionally, they were older and heavier, and the only group to be classed as
overweight. Despite these mean differences, results of the ANOVA’s revealed significant
differences on only two of the functionality indicators. Significant group differences only
emerged for self esteem, F (2, 49) = 4.87, p = .01, and BMI, F (2, 48) = 3.39, p = .04.
These significant differences were followed up with post hoc tests applying a Bonferroni
adjustment (.05 / 4 = .012). The Normal group had significantly higher self esteem scores
than the Dissatisfied group, and a trend (p = .05) was noted for the Health Conscious
group to also have higher self esteem scores than the Dissatisfied group. There was no
difference between the self esteem of the Normal and Health Conscious groups.
Following up the significant BMI difference revealed that there was a trend for
the Dissatisfied group to have a higher BMI than the other groups No differences were
noted in the BMI of the Normal and Health Conscious groups.
Together, these results provide some support for the classification of body image
typologies in males. As a further check of the validity of the three cluster solution, the
ANOVA’s examining demographic and functionality measures were re-run using the two
cluster solution. Using the two cluster solution, significant differences were found on
most of the functionality indicators. It may therefore be argued that the two cluster
solution in fact has more external validity, given the consistent differences in other
variables not used in the original clustering process. Recall that the difference between
Cognitive Bias and Body Image 124
the two and three cluster solution was the emergence of the small health conscious group
in the three cluster solution. However, given the quite divergent nature of this smaller
group, it was still deemed appropriate to view it as a separate cluster. Group two and
three represent quite distinctive profiles, and therefore it was considered appropriate to
use the three cluster solution.
Table 8.4
Differences in Demographic and General Well-Being Scores Between the Three Clusters
Identified in Males.
Normal
(n = 26)
Dissatisfied
(n = 19)
Health Conscious
(n = 9)
M (SD) M (SD) M (SD)
Age 32.76 (14.16) 37.42 (16.43) 30.33 (8.84)
BMI 24.21 (3.13) 27.59 (6.26) 23.96 (3.24)
Depression 5.03 (6.50) 6.72 (8.40) 3.33 (6.63)
Risky behaviours ⁿ 0.19 (0.23) 0.34 (0.17) 0.35 (0.09)
Self esteem 33.36 (5.24) 28.84 (4.66) 32.87 (4.29)
Social functioning 5.58 (2.45) 7.44 (3.08) 5.33 (1.36)
ⁿ Log 10 transformed scores
8.2 Results and Discussion for Females
8.2.1 Descriptive Information
Table 8.5 and 8.6 shows the means, standard deviations, and Cronbach’s alphas
for all of the psycho-social questionnaires used in the female sample (N = 144). All sub-
Cognitive Bias and Body Image 125
scales of the Body Attitudes Questionnaire demonstrated adequate validity as shown by
the Cronbach alpha’s.
Table 8.5
Descriptive Statistics and Reliability Values for the Mood and General Well-Being
Measures in Women.
Scale M SD Min / Max value No. items Cronbach alpha’s
Depression
6.94 7.42 0-42 14 .96
Anxiety
6.66 7.18 0-42 14 .91
Stress
12.51 8.35 0-42 14 .94
Self esteem
29.93 4.70 10-40 10 .83
Social Functioning
7.85 3.45 0-24 8 .74
8.2.2 Biased Attention
Table 8.7 shows the mean reaction for each of the Stroop categories, in addition to
the interference indexes and t-tests. Minimal interference effects were found, indicating
that reaction times for neutral and experimental words were similar. Paired samples t-
tests were conducted to compare the average reaction time of each experimental category
to the matched neutral category. No significant differences were noted for any
comparison. However, high standard deviations were noted indicating substantial
variability in response times, hence the need to examine the role of vulnerability factors.
Cognitive Bias and Body Image 126
Table 8.6
Descriptive Statistics and Reliability Values for the Body Image Measures in Women.
Scale M SD Min / Max value
No. items Cronbach’s alpha
REI
Weight Control 4.75 1.37 1-7 3 .57
Fitness 4.89 1.24 1-7 4 .83
Mood 4.39 1.29 1-7 4 .77
Health 5.23 1.16 1-7 4 .85
Attractiveness 4.46 1.62 1-7 3 .80
Enjoyment 3.84 1.53 1-7 3 .84
Tone 4.73 1.51 1-7 3 .78
BAQ
Attractiveness 13.69 2.48 4-20 4 .78
Body Disparagement 15.86 4.82 8-40 8 .80
Feeling Fat 40.86 10.76 13-65 13 .89
Salience 21.67 5.75 8-40 8 .78
Lower Body Fatness 12.10 3.81 4-20 4 .70
Strength / Fitness 17.52 4.10 6-30 6 .82
MBSRQ
Appearance Evaluation 3.18 0.72 1-5 7 .89
Appearance Orientation 3.50 0.59 1-5 12 .80
Fitness Evaluation 3.37 0.86 1-5 3 .77
Fitness Orientation 3.03 0.78 1-5 13 .89
Health Evaluation 3.43 0.73 1-5 6 .84
Health Orientation 3.25 0.74 1-5 8 .80
Illness Orientation 3.04 0.69 1-5 5 .70
Overweight Preoccupation 2.78 0.96 1-5 4 .77
EDI
Drive for Thinness 27.25 8.96 7-42 7 .91
Interoceptive Awareness 44.25 8.31 10-60 10 .89
Bulimia 34.26 5.62 7-42 7 .88
Ineffectiveness 45.31 7.72 10-60 10 .94
Cognitive Bias and Body Image 127
Maturity Fears 35.33 6.14 8-48 8 .82
Interpersonal Distrust 29.40 5.82 7-42 7 .86
Perfectionism 22.36 5.65 6-36 6 .82
Drive for Muscularity 1.70 0.55 1-6 15 .80
Restraint Scale 13.45 5.90 0-35 10 .80
Table 8.7
Mean Reaction Time and Interference Indexes (in Milliseconds) for the Stroop Colour-
Naming Task in Females (N = 144).
M SD t p
Negative Emotion 899.60 123.89 -1.03 .30
Control 907.63 117.96
Interference index -8.02 93.11
Negative Appearance 911.84 119.11 1.29 .19
Control 902.13 119.35
Interference index 9.70 86.27
Positive Appearance 907.21 109.08 -0.27 .78
Control 902.18 115.38
Interference index 5.02 87.78
Low Calorie foods 901.68 112.82 -0.91 .36
Control 908.97 117.74
Interference index -7.28 89.56
High Calorie 903.52 109.69 0.21 .82
Control 906.69 111.33
Interference index -3.16 81.92
Physical Activity 901.66 110.10 -0.56 .57
Control 905.51 113.47
Interference index -3.84 84.25
Table 8.6 cont.
Cognitive Bias and Body Image 128
8.2.2.1 The role of demographic factors in biased attention. To examine the role
of demographic factors in Stroop interference, a series of one-way Independent Groups
ANOVA’s were run with relevant demographic variables as Independent Variables, and
interference scores as Dependant Variables. There was no significant difference between
the BMI weight categories (underweight, normal, overweight, and obese) on any of the
interference indexes: Negative Emotion, F (3, 134) = 0.73, p = .53; Negative Appearance,
F (3, 134) = 0.01, p = 0.99; Low Calorie Foods, F (3, 134) = 1.01, p = .35; Physical
Activity, F (3, 134) = 1.35, p = .26; High Calorie Foods, F (3, 134) = 0.12, p = .94, and
Positive Appearance, F (3, 134) = 0.23, p = .89. No significant differences were noted for
perceived weight status either: Negative Emotion, F (4, 100) = 0.32, p = .50; Negative
Appearance, F (4, 100) = 0.57, p = .59; Low Calorie Foods, F (4, 100) = 0.44, p = .77;
Physical Activity, F (4, 100) = 0.79, p = .53; High Calorie Foods, F (4, 100) = 1.17, p =
.32; Positive Appearance, F (4, 100) = 0.86, p = .48. These results indicate that neither
actual nor perceived weight status is related to biased attention.
As previous research has noted age differences in interference effects (e.g.,
Seddon & Waller, 2000), age was correlated with each index. There were no significant
correlations between age and any interference index (i.e., r’s < .10).
To examine whether hunger affected attention, correlations were run between the six
interference indexes and participants current level of hunger and time since last meal. As
can be seen in Table 8.8, current hunger levels did not seem to be consistently related to
interference effects. Only interference for positive appearance words showed a weak,
negative relationship with current hunger levels. Examination of the correlations between
amount of time since last meal consumption and interference indexes revealed that
Cognitive Bias and Body Image 129
positive appearance again was the only variable to show a significant correlation. Thus,
the demographic factors of age, BMI, and perceived weight were not related to any of the
six Stroop interference indexes.
Table 8.8
Correlations Between Hunger Levels and Interference Indexes in Women.
1. 2. 3. 4. 5. 6. 7. 8.
1. Hunger - -
2. Last meal .35** -
3. Negative
emotion
.04 .008 -
4. Negative
appearance
.008 -.05 .05 -
5. Low calorie
foods
.05 .14 .16 -.15ⁿ -
6. Physical
activity
-.13 -.02 .15 -.07 -.17* -
7. High calorie
foods
-.02 .06 .03 .15ⁿ -.08 .09 -
8. Positive
appearance
-.17* -.19* .07 .09 -.09 .09 .06 -
* p < .05. ** p < .01. ⁿ p = .06.
Also shown in Table 8.8 are the inter-correlations between the interference
indexes. Only a small number of these inter-correlations are significant, or show a trend
towards significance, indicating that these indexes are assessing distinct types of body
image concerns.
Cognitive Bias and Body Image 130
8.2.2.2 The role of vulnerability factors in biased attention. A series of bivariate
correlations were run in order to examine the influence of a range of psycho-social
variables on Stroop interference scores. Core body image attitudes, mood, and social
functioning variables were examined for their relationship with the six interference
indexes.
Interference for negative emotion words was significantly associated with lack of
anxiety, r = -.30, p = .05, and a trend for low levels of stress, r = -.29, p = .059. Higher
self esteem was associated with attention toward negative emotion information, r = .20, p
= .01. The relation between negative emotion interference and the body image variables
only approached significance, where avoidance was associated with higher feelings of
loathing one’s body (as assessed by BAQ Disparagement subscale; r = -.15, p = .06),
higher feelings of fatness (as assessed by BAQ Feeling Fat; r = -.14, p = .08 and BAQ
Lower Body Fatness; r = -.15, p = .06), more overweight preoccupation (as assessed by
MBSRQ; r = -.15, p = .07), and higher dietary restraint, r = -.15, p = .06. Thus, a quicker
reaction time for negative emotion words was consistently associated with poorer mood,
well-being, and poorer body image.
Attention toward negative appearance related words was moderately correlated
with higher anxiety scores, r = .38, p = .01, and stress, r = .36, p = .02. No significant
correlations were reported with social functioning, self esteem, or body image variables.
Thus, a quicker reaction time for negative appearance words signified better functioning.
Interference for low calorie food words was not significantly associated with any of the
mood variables, self esteem, or social functioning. Attention toward low calorie food
words was the only significant correlation with higher feelings of fitness (MBSRQ
Cognitive Bias and Body Image 131
Fitness Evaluation; r = .19, p = .02). Thus, a quicker reaction time for low calorie foods
was associated with poorer health and fitness. Interference for high calorie food words
however, was not significantly associated with any of the psychosocial variables.
Interference for physical activity words was only significantly correlated with two
of the body image measures. Attention toward these words was associated with higher
receptivity to feelings of illness (MBSRQ Illness Orientation; r = .17, p = .03), and a low
level of dietary restraint, r = -.18, p = .03.
Interference for positive appearance words showed a number of
significant, or near significant, correlations with body image variables. Attention toward
positive appearance words appears to be related to better functioning. Longer reaction
times for positive appearance words were associated with less feelings of body loathing
(BAQ Disparagement; r = -.16, p = .04), lower importance of appearance in daily life
(BIQLI; r = .16, p = .06), and a positive evaluation of one’s appearance (MBSRQ
Appearance Evaluation; r = .16, p = .05). Additionally, attention toward positive
appearance words was also associated with more importance placed on health (MBSRQ
Health Orientation; r = .16, p = .04), and lower levels of depression (DASS; r = -.16, p =
.05).
To summarise, it appears that more interference effects (i.e., a longer reaction
time) are associated with better functioning for Positive Appearance words, Low Calorie
food words and Negative Emotion words, while interference effects for Negative
Appearance words indicates poorer functioning. Reaction times for High Calorie food
words and Physical Activity words were not consistently related to any of the mood,
general well being, or body image variables.
Cognitive Bias and Body Image 132
Initially, it was planned to run regression analyses to determine the best predictors
of Stroop interference scores. However, given the small number of significant
correlations, and the weak correlation values of those that did approach significance,
regressions were not deemed appropriate.
As past research has not been able to ascertain whether attentional biases are
reliably found within non-clinical samples, and some research has suggested that these
biases are restricted to clinical groups, it may be that interference effects are only found
in those people who engage in highly dysfunctional, risky eating behaviours. Given that
the current research was targeting a non-clinical population, it was expected that the
prevalence of these risky behaviours would be low. Table 8.9 shows the number of
women who have engaged in a range of risk eating and weight loss behaviours in the last
six months. The results for laxative use and diuretic use are not reported, as only four
woman reported using laxatives in the last 6 months, and only two women reported
diuretic use.
These prevalence rates show that a range of dysfunctional eating and weight
management techniques are being used within non-clinical samples. The average number
of dysfunctional techniques was 1.81 (SD = 1.86), with a range from zero to nine. Just
over half of the women (56%) reported none or one risky behaviour, while 25% reported
between two and six risky behaviours, and only 2% engaged in more than six risky
behaviours. To examine whether women who engage in these behaviours show selective
attention for body image related information, independent groups t-tests were run. Given
the small number of women who engage in some of these behaviours, some of the results
should be viewed with caution.
Cognitive Bias and Body Image 133
Table 8.9
Percentages and Stroop interference scores for women who reported engaging in risky eating and weight management techniques in
the last six months (N = 144). Significant differences in interference scores are noted with“*”.
Vomited Slimming
tablets
Fasted Diet for health Diet for weight
loss
Excessive
exercise
Binge Binge no
control
Y N Y N Y N Y N Y N Y N Y N Y N
% 10 89 7 92 23 77 19 78 57 42 15 84 27 73 18 80
NE -36.69 -4.67 -38.45 -5.49 -38.08 0.98* 1.04 -10.02 -9.41 -6.16 -31.32 -4.01 -8.73 -7.77 -23.05 -6.19
NAP 61.43 3.63* 44.01 6.84 38.94 0.93* 7.66 9.62 20.69 -5.07# 1.34 11.14 -12.07 17.58# -13.99 14.11
LC 1.93 -8.36 -0.06 -7.88 -17.54 -4.21 1.06 -8.78 -14.07 1.83 11.15 -10.46 -17.66 -3.53 -1.35 -9.56
PAC 34.37 -8.32# 3.54 -4.46 -4.09 -3.77 -22.75 0.61 -7.12 0.55 1.75 -4.81 -1.53 -4.68 -17.96 -1.63
HC -1.21 -3.39 -12.66 -2.37 2.67 -4.92 -14.74 0.01 0.98 -8.75 13.75 -6.08 -21.75 3.55* -17.75 -0.95
PAP -24.89 8.53 -26.85 7.68 -10.23 9.60 -21.41 13.09 1.23 10.12 -23.02 9.85 -11.49 11.00 -22.98 12.19#
Note. NE = negative emotion words; NAP = negative appearance words; LC = low calorie food words; PAC = physical activity words; HC = high calorie food words; PAP = positive appearance words. * p < .05. # p = .06
Cognitive Bias and Body Image 134
At a descriptive level, those women who had engaged in risky weight
management behaviours in the last six months consistently showed enhanced interference
effects compared to those women who had not engaged in these behaviours. However
only a few differences reached significance. Women who reported purposely vomiting
after food consumption in the last six months exhibited significantly higher interference
for negative appearance words, t (142) = 2.52, p = .01, and a trend more interference for
physical activity words, t (142) = 1.88, p = .06, compared to women who did not report
vomiting recently. Those women who reported fasting recently to improve appearance
showed significantly quicker reaction times for negative emotion words, t (142) = -2.14,
p = .03, and significantly slower reaction times for negative appearance words, t (142) =
2.28, p = .02, compared to non-fasting women. Those women who reported dieting to
improve appearance showed a trend toward slower reaction times to negative appearance
words, t (142) = 1.72, p = .08. Binging was associated with a trend for faster reaction
times to negative appearance words, while non-bingers showed slower reaction times, t
(142) = -1.91, p = .05. Bingers also showed a quicker reaction to high calorie food words,
t (142) = -1.96, p = .05. Loss of control over these binging episodes was associated with a
trend for negative interference scores for positive appearance words, t (140) = -1.83, p =
.06. The women who reported use of slimming tablets and excessively exercising did not
differ in interference scores from women not engaging in these behaviours. Thus, it
appears that high interference scores may be associated with some risky weight
management techniques.
These results support the pattern of correlations reported previously between
Stroop interference indexes and the psycho-social variables. That is, slower reaction
Cognitive Bias and Body Image 135
times for Negative Appearance words was associated with poorer functioning (vomiting,
fasting, and dieting for appearance), while slower reaction times for Positive Appearance
words was associated with better functioning (dieting for health, non-binging, and not
loosing control over a binge).
One vulnerability factor used extensively in past research is restraint status. As
previously outlined, level of dietary restraint is typically measured using Herman and
Polivy’s Restraint Scale (1980). This scale measures restriction of food intake due to
weight concerns, history of weight fluctuations, and preoccupation with dieting. In
accordance with past research (e.g., Francis et al., 1997), the women were categorised
into restrained eaters if they scored 16 or above on the Restraint scale, or unrestrained
eaters if they scored below 16. Even though the sample was non-clinical in nature, a large
number of women were classified as restrained eaters (N = 56, or 41%). No significant
differences were noted between the women classified as restrained and unrestrained
eaters on any of the six interference indexes (all p’s > .05). Means are shown in Table
8.10.
Table 8.10
Mean interference scores for women classified as restrained or unrestrained eaters on
the Stroop categories.
Unrestrained Restrained t p
High calorie foods -1.00 .27 -0.89 .37
Low calorie foods -0.32 -1.02 0.44 .66
Physical activity -0.17 -0.67 0.33 .74
Negative appearance 0.97 1.26 -0.19 .84
Positive appearance 1.50 -0.33 1.19 .21
Negative emotion 0.05 -2.13 1.45 .14
Cognitive Bias and Body Image 136
8.2.2.3 Sub-group differences in biased attention. The primary function of the
cluster analysis was to identify sub-groups of women that differ in body image attitudes
so that their Stroop interference scores could be compared. To examine whether
interference for body image related information was a function of level of body image
disturbance, a series of ANOVA’s were conducted. To determine whether the groups
differed on interference scores for any of the categories, a MANOVA was run with group
membership as the Independent Variable and the six interference scores as multiple
Dependent Variables. Examination of histograms, skewness and kurtosis statistics, and
Kolmogorov-Smirnov tests revealed that univariate normality was not breached. As the
sample sizes were different between the groups, Box’s M was examined, but revealed no
significant breach of the assumption of equality of covariances matrices. The mean
interference scores for each sub-group across each of the six interference indexes are
shown in Table 8.11.
Table 8.11
Mean Stroop Interference (in Msec) Scores Across the Sub-Groups Identified in Women.
Cluster
Normal Athletic Dissatisfied Symptomatic
High calorie foods -2.118 -1.201 -1.695 -13.357
Low calorie foods -1.318 -18.430 -22.645 21.817
Physical activity 9.319 -18.140 -10.627 -13.984
Negative appearance 19.917 -.556 5.866 -2.525
Positive appearance 21.553 20.431 -30.176 -6.066
Negative emotion -4.786 15.162 -17.443 -38.115
Cognitive Bias and Body Image 137
Examination of the mean interference indexes for each of the Stroop categories
across the four clusters revealed some differences between the groups in interference
indexes. Using the Roy’s Largest Root statistic, there was a significant group difference,
F (6, 136) = 2.15, p = .05, in interference scores. Examination of the univariate tests
revealed a difference between the groups on interference for Positive Appearance words,
F (3, 139) = 3.18, p = .026. The post hoc tests revealed that the Dissatisfied group
showed significantly more negative interference (i.e., faster reaction times to the
experimental than neutral words) than the other three groups2.
To determine if there were any significant differences between the Stroop
categories within each of the groups, a Repeated Measures ANOVA’s was conducted for
each group. There was no difference between the six interference scores for the Normal
group, F (5, 57) = 1.12, p = .35; for the Athletic group, F (5, 23) = 1.99, p = .11; for the
Dissatisfied group, F (5, 31) = 0.68, p = .63; or the Symptomatic group, F (5, 12) = 1.02,
p = .44. These results indicate that women within each of these groups responded
similarly to each of the Stroop categories.
8.2.3 Biased Memory
8.2.3.1 Percentage of words recalled. The data was examined to see whether the
women recalled a higher percentage of experimental words compared to neutral words.
There was a higher amount of variability for recall of percentage of experimental words,
ranging from 0 (no experimental words recalled) to 100 (100% of words recalled were
2 It is noted that mixed design ANOVA could have been conducted instead of the MANOVA. This analysis was run and the same pattern of results emerged. There was no significant main effect of word type, F (5, 135) = 0.61, p = .69, and no significant interaction between word type and group, F (15, 411) = 0.91, p = .53. There was a significant main effect of group, F (1, 139) = 2.82, p = .04, with the Dissatisfied group showing the largest negative interference scores.
Cognitive Bias and Body Image 138
experimental). Comparatively, the variability for recall of neutral words ranged from 0%
to 62.5 %.
To determine whether the women showed an enhanced memory for experimental
words overall, a paired samples t-test was run on percentage values. Mean recall rates and
outcomes of the t-tests are shown in Table 8.12.
Table 8.12
Percentage of Words Recalled Across Each Category for Females.
M SD t p
Experimental 32.66 22.06 3.89 .001
Neutral 22.35 15.06
Negative Emotion 5.99 11.22 0.09 .92
Control 5.88 9.40
Negative Appearance 10.10 11.41 6.08 .001
Control 3.36 6.90
Positive Appearance 3.89 7.09 0.01 .98
Control 3.87 7.58
Low Calorie Foods 5.89 10.57 4.62 .001
Control 1.27 5.25
High Calorie Foods 3.51 7.39 0.68 .49
Control 3.04 6.58
Physical Activity 3.05 6.39 -2.44 .01
Control 5.19 7.66
A significantly higher percentage of experimental words was recalled compared
to neutral words. Examination of percentage rates in each of the six experimental
categories showed enhanced recall for three of the six categories. The women recalled
Cognitive Bias and Body Image 139
significantly more negative appearance words, low calorie food words, and physical
activity words, compared to the matched neutral categories. No significant differences
were noted for the recall of negative emotion words, positive appearance words, and high
calorie food words.
8.2.3.2 The role of vulnerability factors in biased memory. To examine whether
the percentage of experimental words recalled was related to any body image and
wellbeing variables, a series of bivariate correlations were run. Percentage of negative
appearance words recalled was associated with mood; higher recall was significantly
associated with higher anxiety, r = .32, p = .03, and a trend was noted for higher levels of
depression, r = .15, p = .06. Higher recall was also associated with higher levels of
dietary restraint, r = .18, p = .03. The recall of positive appearance words was not
associated with any of the psychosocial measure, although trends were noted for higher
recall to be associated with higher anxiety, r = .27, p = .08, N = 41, and higher stress r =
.27, p = .08, N = 40.
The percentage of negative emotion words recalled was negatively associated
with three of the EDI subscales, Interoceptive Awareness, r = -.19, p = .05,
Ineffectiveness, r = -.24, p = .01, and Perfectionism, r = -.19, p = .05. That is, inhibited
recall of negative emotion words appears to be related to eating disorder-like attitudes. A
trend was noted between higher recall of negative emotion words and poorer social
functioning, r = .17, p = .07.
The percentage of high calorie words recalled was only related to two body image
variables, the Maturity Fears subscale of the EDI, r = .19, p = .05, and a trend for
exercising for weight control, as assessed by the REI, r = .16, p = .07. Percentage of low
Cognitive Bias and Body Image 140
calorie food words recalled however, was significantly correlated with a large number of
body image variables. Higher recall of low calorie food words was associated with higher
pursuit of thinness (MBSRQ Overweight Preoccupation, r = -.20, p = .01; EDI Drive for
Thinness, r = .18, p = .06), and higher self esteem, r = .16, p = .05. Women who reported
exercising to improve attractiveness, r = -.17, p = .05, and to improve tone, r = -.22, p =
.01 (all assessed by REI), reported lower recall of low calorie food words. Poor recall of
low calorie food words was also associated with higher feelings of body loathing (BAQ
Disparagement, r = -.17, p = .03). Overall, these findings regarding recall of low calorie
food words showed mixed findings. Thus, high recall of low calorie food words is
generally associated with better body image.
Higher recall of physical activity words was significantly correlated with higher
feelings of fitness (BAQ Strength / Fitness, r = .18, p = .02 and MBSRQ Fitness
Evaluation, r = .16, p = .05), and higher importance placed on health and fitness
(MBSRQ Fitness Orientation, r = .25, p = .001, MBSRQ Health Orientation, r = .28, p =
.001, and MBSRQ Illness Orientation, r = .16, p = .04). Higher recall was also associated
with exercising for health and fitness reasons (REI Health, r = .29, p = .001, and REI
Fitness, r = .16, p = .06). Thus, a focus on health and fitness appeared to be consistently
related to a higher percentage of physical activity words recalled. Higher recall was also
associated with higher levels of Interoceptive Awareness (EDI, r = .20, p = .05), and
more negative mood. Higher recall was also significantly associated with higher levels of
anxiety (DASS, r = .30, p = .05).
To examine whether memory bias was associated with eating disorder symptoms,
comparisons were conducted between women who had, and had not, recently reporting
Cognitive Bias and Body Image 141
engaging in risky weight management techniques. Differences in the percentage of
experimental words recalled are shown in Table 8.13. Few significant differences
emerged. Women who reported excessively exercising showed enhanced recall of the
negative appearance words, t (140) = 2.41, p = .01, but lower recall of the low calorie
food words, t (139) = -1.44, p = .008, compared to women who did not report excessive
exercise. A trend was noted for the women who reported dieting for health reasons to
recall more negative appearance words than women who did not diet, t (139) = 1.83, p =
.06. Therefore, memory biases did not appear to be related to eating disorder symptoms.
8.2.3.3 Sub-group differences on biased memory. To examine whether the sub-
groups identified via the cluster analysis differed on their memory performance, a four
(cluster membership) by six (Stroop interference) Mixed Design ANOVA was conducted
with percentage of words correctly recalled as Dependent Variables. Table 8.14 shows
the average percentage of experimental words recalled across sub-groups.
Results of the Mixed Design ANOVA showed that there was a significant main
effect of word category, F (5, 134) = 9.06, p < .001, no significant effect for group, F (3,
138) = 0.19, p = .90, and no significant interaction between group and word category, F
(15, 408) = 0.76, p = .72. Examination of the follow up tests for the significant main
effect of word category revealed that regardless of group membership, the women
showed enhanced recall for negative appearance words.
Cognitive Bias and Body Image 142
Table 8.13
Percentage of Words Recalled for Women who Reported Engaging in Risky Eating and Weight Management Techniques in the Last
Six Months (N = 144). Significant Differences in Interference Scores are Noted with“*”.
Vomited Slimming
tablets
Fasted Diet for health Diet for weight
loss
Excessive
exercise
Binge Binge no
control
Y N Y N Y N Y N Y N Y N Y N Y N
% 10 89 7 92 23 77 19 78 57 42 15 84 27 73 18 80
NE 3.07 6.39 3.60 6.24 6.82 5.80 6.39 6.00 6.79 5.03 7.81 5.75 5.18 6.34 8.47 5.54
NAP 9.07 10.30 14.29 9.83 10.46 10.08 13.67 9.27# 9.56 10.98 15.80 9.25* 10.37 10.10 12.49 9.55
LC 4.17 6.73 11.61 6.02 4.04 7.19 5.19 6.83 4.84 8.60 2.35 7.13* 5.39 6.83 4.10 6.57
PAC 2.16 3.10 7.02 2.66 2.49 3.16 2.29 3.20 3.05 2.94 5.37 2.61 2.63 3.18 3.39 2.97
HC 4.59 3.46 4.50 3.50 3.02 3.75 3.45 3.65 2.97 4.39 2.80 3.71 2.67 3.90 2.52 3.87
PAP 4.46 3.85 4.58 3.86 4.57 3.72 2.40 4.20 3.66 4.25 3.09 4.05 3.82 3.95 2.78 4.01
Note. NE = negative emotion words; NAP = negative appearance words; LC = low calorie food words; PAC = physical activity words; HC = high calorie food words; PAP = positive appearance words. * p < .05; # trend noted (p = .06)
Cognitive Bias and Body Image 143
Table 8.14
Percentage of Words Recalled in Each of the Experimental Categories from the Stroop
Task Across Sub-Groups in Women.
Normal Athletic Dissatisfied Symptomatic
Negative Emotion 5.15 (9.45) 6.05 (10.30) 6.89 (13.62) 7.53 (13.95)
High Calorie foods 3.30 (7.64) 3.87 (7.92) 2.76 (5.94) 6.04 (8.67)
Low Calorie foods 7.85 (17.95) 7.69 (11.50) 5.50 (8.43) 1.04 (4.16)
Positive Appearance 4.69 (7.42) 4.08 (7.42) 3.13 (6.11) 2.39 (7.64)
Negative Appearance 9.18 (9.20) 10.35 (12.46) 11.58 (14.10) 10.55 (11.37)
Physical Activity 2.46 (5.39) 4.19 (8.16) 2.26 (5.81) 4.69 (7.64)
8.2.3.4 Relationship between biased attention and memory. To examine the
relationship between attention and memory biases, interference and memory recall
percentages were correlated. Only the recall of negative appearance words was related to
interference for physical activity words, r = -.18, p = .02. That is, a quicker reaction time
for physical activity words was associated with enhanced recall of negative appearance
words. No other significant correlations were found between memory percentage scores
and interference indexes.
8.2.4 Error Rates
The number of errors made in each of the six experimental conditions of the
Stroop task was recorded. Overall, the number of errors made in each condition was very
low, with the average number of errors under one. In order to examine the trade-off
participants may have made between speed of responding and accuracy, correlations were
conducted between total number of errors, and raw reaction time scores for of the Stroop
Cognitive Bias and Body Image 144
categories. All of the correlations revealed that a trade-off occurred, such that faster
reaction times were associated with more errors.
To examine whether there was any differences in the number and types of errors
made between the sub groups, a MANOVA was conducted with group membership as
the Independent Variable, and the error rates for each of the six experimental categories
as multiple Dependent Variables. Means are shown in Table 8.15.
Table 8.15
Mean number of colour naming errors made on the Stroop task by females.
Normal Athletic Dissatisfied Symptomatic
Negative Emotion 0.16 0.14 0.13 0.35
High Calorie foods 0.12 0.32 0.27 0.29
Low Calorie foods 0.30 0.14 0.11 0.29
Positive Appearance 0.24 0.14 0.25 0.17
Negative Appearance 0.12 0.03 0.05 0.29
Physical Activity 0.30 0.14 0.08 0.23
The MANOVA was significant, Roy’s Largest Root F (6, 136) = 2.57, p = .02.
Examination of the univariate tests revealed that only errors for Negative Appearance
related words showed significant group differences, F (3, 139) = 2.59, p = .05. The post
hoc tests, applying a Bonferroni adjustment (.05 / 4 = .012), showed that the
Symptomatic group made significantly more errors (M = .29) than the Healthy (M = .03)
and Dissatisfied (M = .05) group.
Cognitive Bias and Body Image 145
8.3 Results and Discussion for Males
8.3.1 Descriptive Information
A total of 55 male participants were recruited from the general community and
universities across Queensland and Melbourne. Tables 8.16 and 8.17 shows the
descriptive statistics for all of the psychosocial questionnaires used. All values are
consistent with normative values, and all questionnaires show acceptable validity.
Table 8.16
Descriptive Statistics and Reliability Values for the Mood and General Well-Being
Variables in the Male Sample
Scale M SD Min / Max value No. items Cronbach’s alpha
Depression
5.22 7.14 0-42 14 .95
Anxiety
2.87 2.41 0-42 14 .62
Stress
7.81 7.16 0-42 14 .93
Self esteem
31.62 5.21 10-40 10 .83
Social Functioning
6.06 2.57 0-24 8 .82
8.3.2 Biased Attention
Table 8.18 shows the mean raw reaction times for each of the Stroop categories,
in addition to the interference indexes. Paired samples t-tests were conducted to compare
the average reaction time of each experimental category to the matched neutral category.
A significant difference was noted between reaction times to Negative Emotion words
Cognitive Bias and Body Image 146
and the matched neutral category, such that the men were 20 milliseconds slower on
average to respond to the Negative Emotion words. Minimal interference effects were
noted for the five other Stroop categories, and none of these comparisons were
significant.
8.3.2.1 The role of demographic factors in biased attention. A series of one-way
Independent Groups ANOVA’s were conducted to examine the relationship between
demographic factors and Stroop interference scores. No differences in interference scores
was found between the normal weight, overweight and obese men for any of the six
interference indexes (all p’s > .05), although a trend was noted for the high calorie food
words, F (2, 47) = 2.78, p = .07, such that the men of normal weight showed attention
toward these words, while the overweight and obese men directed their attention away.
Age was not significantly correlated with any of the interference indexes (i.e., all r’s
<.20). Neither self rated hunger level, nor amount of time since last meal, were
significantly correlated to any of the Stroop interference indexes.
8.3.2.2 The role of vulnerability factors in biased attention. In order to examine
the relationship between psycho-social variables and biased attention, a series of bivariate
correlations were run. Each interference index was examined for it’s relationship with
body image, mood, and general well-being variables.
Quicker reaction times to colour name Negative Emotion words was significantly
correlated with lower appearance evaluation (MBSRQ; r = .31, p = .02). That is, a
facilitation effect for Negative Emotion words was associated with poorer body image,
but was not related to any of the mood or general well-being variables.
Cognitive Bias and Body Image 147
Table 8.17
Descriptive Statistics and Reliability Values for the Body Image Variables in the Male
Sample
Scale M SD Min / Max value
No. items
Cronbach’s alpha
REI
Weight Control 3.58 1.74 1-7 3 .85
Fitness 4.71 1.32 1-7 4 .77
Mood 3.86 1.57 1-7 4 .75
Health 5.40 1.16 1-7 4 .79
Attractiveness 4.24 1.70 1-7 3 .87
Enjoyment 3.47 1.46 1-7 3 .71
Tone 4.04 1.78 1-7 3 .88
MBSRQ
Appearance Evaluation 3.33 0.80 1-5 7 .84
Appearance Orientation 3.16 0.66 1-5 12 .83
Fitness Evaluation 3.92 0.72 1-5 3 .79
Fitness Orientation 3.36 0.75 1-5 13 .83
Health Evaluation 3.78 0.73 1-5 6 .83
Health Orientation 3.39 0.80 1-5 8 .83
Illness Orientation 3.05 0.89 1-5 5 .84
Overweight Preoccupation 1.96 0.81 1-5 4 .74
Drive for Muscularity 2.23 0.85 1-6 15 .89
Restraint Scale 9.83 5.15 0-35 10 .77
Cognitive Bias and Body Image 148
Table 8.18
Mean Reaction Times and Interference Indexes (in Milliseconds) for the Stroop Task in
Males (N = 54)
M SD t p
Negative Emotion 941.86 143.69 -2.16 .03*
Control 964.83 145.09
Interference index -22.97 81.60
Negative Appearance 964.51 156.91 0.02 .97
Control 964.92 148.35
Interference index -0.40 76.09
Positive Appearance 962.92 146.51 0.01 .98
Control 961.74 144.99
Interference index 1.17 84.06
Low Calorie 963.73 156.56 1.36 .17
Control 953.29 159.97
Interference index 10.43 89.53
High Calorie 957.2 150.79 1.24 .30
Control 963.49 156.29
Interference index -6.24 114.89
Physical Activity 972.61 161.42 0.51 .61
Control 967.36 162.57
Interference index 5.25 93.02
* p < .05
Quicker reaction times to colour name Negative Appearance words was only
significantly correlated with higher levels of stress (DASS; r = -.50, p = .04). Thus,
Cognitive Bias and Body Image 149
facilitation effects are only reliably related to poorer mood, although given the small
sample size for this correlation (N = 16), caution is warranted3.
Interference for Positive Appearance words was not associated with any of the
body image, mood, or general well-being variables. Interference for Physical Activity
words also did not show any correlations with the psycho-social variables.
Faster reaction times for Low Calorie food words were associated with lower
levels of stress (DASS; r = .51, p = .04, N = 16). That is, a facilitation effect for Low
Calorie food words was only associated with better mood, but not body image or general
well-being. Again, caution is warranted, as this finding is only based on 16 participants.
Faster reaction times for High Calorie food words was associated with exercising
for weight control reasons (REI; r = -.32, p = .02), and a trend for a lower drive for
muscularity (r = .25, p = .06). That is, a facilitation effect for High Calorie food words
was associated with a more positive body image.
To summarise, quicker reaction times to Negative Emotion and Positive
Appearance words appeared to be associated with poorer body image, while quicker
reaction times to High Calorie food words was associated with a better body image.
Response to Negative Appearance and Low Calorie food words was associated with
mood only, with quicker reaction times for Negative Appearance words related to poorer
mood, and Low Calorie food words associated with better mood. In this sample of men,
biased attention was not related to any of the general wellbeing or social functioning
variables.
3 The reader is reminded that due to a photocopying error, the full version of the DASS was only administered to a small proportion of the sample.
Cognitive Bias and Body Image 150
As with females, the number of risky weight management techniques was
examined. The prevalence rates of these behaviours in the last six months for men were
very low. None of the men reported vomiting on purpose after eating, use of laxatives or
diuretics. Only a small number of men reported using slimming tablets (n = 2),
excessively exercising (n = 4), binging (n = 6) or being unable to control their eating (n =
4). Thus, Table 8.19 only shows the number of men who reported dieting for appearance-
related reasons, and dieting for health reasons in the last six months. The average Stroop
interference scores are also shown for these groups.
Table 8.19
Percentage of Men who Reported Engaging in Risky Eating and Weight Management
Techniques in the Past Six Months and Stroop Interference Scores (N = 54).
Diet for health Diet for weight loss
Y N Y N
% 16 81 29 68
Negative Emotion -3.21 -2.62 -1.58 -3.21
Negative Appearance -0.19 -0.16 0.95 -0.65
Positive Appearance 0.47 0.67 1.82 0.13
Low Calorie Foods -0.64 2.09 1.08 1.86
High Calorie Foods -2.07 0.22 -1.41 0.37
Physical Activity 2.09 -0.28 0.01 -0.16
Cognitive Bias and Body Image 151
The average number of dysfunctional techniques was 0.87 (SD = 1.21), with a
range from zero to four. Most of the men (61%) had not engaged in any risky weight
management techniques in the last six months, only 5% of the men reported one risky
behaviour, 22% reported two, and 11% reported three or four behaviours.
No significant differences were noted in any of the Stroop interference scores
between the men who had, and had not, reported dieting for weight loss in the past six
months (i.e., all p’s > .05). Similarly, no significant differences were noted between the
men who reported dieting for health reasons, and those who did report dieting, in any of
the Stroop interference scores (all p’s > .05).
These prevalence rates indicate that this sample of men was not engaging in
unhealthy weight management techniques. A small proportion of the sample reported
dieting, but this was not related to biased attention for body image related information.
8.3.2.3 Sub-group differences in biased attention. The primary function of using a
cluster analysis was to provide an empirically-supported method for comparing the men
on Stroop interference. To examine whether the three groups identified differed on the six
Stroop interference indexes, a MANOVA was conducted with group membership as the
Independent Variable, and the six interference indexes are multiple Dependent Variables.
As recommended by Field (2005), the data was examined for univariate normality
of homogeneity of variance. Additionally, Box’s M was examined to test for
homogeneity of covariance matrices. No significant breaches were noted. The mean
interference indexes for each of the sub-groups are shown in Table 8.20.
Cognitive Bias and Body Image 152
Table 8.20
Mean Stroop Interference (in Milliseconds) by Sub-Group in men. Standard Deviations in
Parentheses
Cluster
Normal (n = 26) Dissatisfied (n = 19) Health Conscious (n = 9)
High Calorie 5.42 (99.69) -2.22 (110.61) -54.76 (189.64)
Low Calorie 24.57 (79.11) -13.40 (94.46) 52.56 (94.79)
Physical Activity 16.48 (88.26) -11.94 (100.45) 24.81 (97.41)
Negative Appearance -7.96 (66.73) -6.97 (82.29) 39.57 (88.31)
Positive Appearance -6.63 (85.20) -8.42 (83.53) 71.31 (63.52)
Negative Emotion -6.36 (69.93) -37.02 (96.57) -32.59 (70.14)
Examination of the mean interference indexes revealed that for all groups minimal
interference were evident. The overall MANOVA was non-significant, Pillai’s Trace F
(12, 94) = 0.97, p = .97, indicating no differences between the three groups on any of the
six Stroop interference indexes. Power levels however, were very low (.18), suggesting
that an increase in sample size was needed4.
Within each of the three groups, a Repeated Measures ANOVA was used to
assess for differences in responding between the six interference indexes. The Normal
group responded similarly to each of the interference indexes, F (5, 21) = 1.06, p = .41.
No differences emerged for the Dissatisfied group in response to the different word
4 It is noted that a mixed design ANOVA could have been conducted here instead of the MANOVA. This analysis was run, and the same pattern of results emerged. There was no significant main effect of word type, (F (5, 47) = 1.49, p = .20), group, (F (2, 51) = 0.33, p = .71), or interaction, (F (10, 96) = 1.03, p = .42).
Cognitive Bias and Body Image 153
categories, F (5, 14) = 0.46, p = .79, or for the Health Conscious group, F (5, 4) = .45, p =
.79.
To summarise, no evidence of interference effects were found within the current
male sample, even when a number of vulnerability factors were examined. That is, there
was no evidence of selective attention for body image related information.
8.3.3 Biased Memory
8.3.3.1 Percentage of words recalled. For each of the six experimental Stroop
categories, a percentage score was calculated that indicated the percentage of words
recalled that were related to the experimental categories. For example, a score of 10 for
Negative Emotion words would indicate that 10% of the total number of words recalled
was related to negative emotion. Table 8.21 provides descriptive information on the
percentage of words the men recalled across the Stroop categories.
To determine whether the men showed an enhanced memory for the experimental
words, paired samples t-tests were run and are shown in Table 8.21. The men recalled a
significantly higher percentage of experimental words compared to neutral words. The
men also showed enhanced memory for the Negative Emotion, Negative Appearance, and
Low Calorie food words, compared to the matched neutral categories. No significant
differences were noted in the recall rates for Positive Appearance, High Calorie, of
Physical Activity words and the matched neutral categories.
Cognitive Bias and Body Image 154
Table 8.21
Percentage of Words Recalled Across Stroop Categories for Males
M SD t p
Experimental 31.91 23.15 3.15 .003
Neutral 16.90 19.08
Negative Emotion 8.25 14.20 1.93 .05
Control 3.73 7.67
Negative Appearance 9.66 17.14 2.27 .02
Control 3.30 9.32
Positive Appearance 2.90 6.60 0.39 .69
Control 2.37 6.58
Low Calorie Foods 5.74 9.04 3.20 .002
Control 1.37 4.21
High Calorie Foods 1.83 4.68 0.43 .66
Control 2.28 5.30
Physical Activity 3.81 7.11 -0.01 .99
Control 3.83 7.79
8.3.3.2 The role of vulnerability factors in biased attention. The percentage of
words recalled across the six experimental categories were correlated with the body
image, mood, and general well-being psycho-social variables. The percentage of Positive
Appearance and High Calorie foods words recalled were not related to any of the psycho-
social variables. Percentage of Negative Appearance words was not significantly
correlated with any of the variables, but a trend was noted such that higher recall of these
words was associated with lower importance placed on appearance (MBSRQ; r = -.25, p
= .06). Similarly, a trend was noted for higher recall of Physical Activity words and a
higher BMI, r = .25, p = .06.
Cognitive Bias and Body Image 155
Recall of Low Calorie food words was related to three of the body image
variables, but none of the mood or functionality variables. Higher recall was associated
with having a higher BMI, r = .36, p = .009, and reporting less satisfaction with body
areas (MBSRQ; r = -.28, p = .04). That is, recall of Low Calorie food words is associated
with being heavier and dissatisfaction with appearance.
Recall of the negative emotion words was associated with not significantly
associated with any of the variables, although two trends were noted for higher recall to
be associated with lower importance of appearance (BAQ; r = -.25, p = .06), and lower
anxiety (DASS; r = -.47, p = .07, N = 15).
To summarise, the percentage of experimental words recalled were not correlated
with any of the mood or general well-being measures. Only recall of Low Calorie food
words was significantly correlated to body image variables, with higher recall associated
with poorer body image.
8.3.3.3 Sub-group differences on biased memory. To examine whether memory
performance was related to different typologies of body image, a three (cluster) by six
(word category) mixed design ANOVA was conducted. Table 8.22 shows the average
percentage of words recalled across the six word categories for each of the sub-groups.
Results of the ANOVA revealed a significant main effect of word, Pillai’s F (5,
46) = 6.25, p = .0001, no significant main effect of group, Pillai’s F (2, 50) = 0.72, p =
.49, and no significant interaction between group and word category, Pillai’s F (10, 94) =
1.25, p = .26. Examination of the follow up tests for recall across word categories showed
that regardless of group membership, the men had high recall of Negative Appearance
and Negative Emotion words, coupled with very low recall of Low Calorie food words.
Cognitive Bias and Body Image 156
Table 8.22
Percentage of Words Recalled by Sub-Group in Men
Normal Dissatisfied Health Conscious
Negative Appearance 7.47 9.07 21.26
Positive Appearance 3.62 2.15 0.00
Low Calorie foods 4.46 9.09 2.38
High Calorie foods 2.29 1.47 1.11
Physical Activity 3.51 4.94 1.11
Negative Emotion 7.23 6.94 12.53
8.3.3.4 Relationship between biased attention and memory. To see whether biased
attention was related to biased memory, a series of bivariate correlations were conducted
between the six interference indexes and the six recall percentages. No significant
correlations emerged, although a trend was noted for higher interference effects for
Positive Appearance words related to more memory bias for these words, r = .23, p = .08.
8.3.4 Error Rates
The number of errors made across each of the six experimental categories in the
Stroop task was manually recorded. Overall, the number of errors made in each category
was very low, with an average of less than one error per category. In order to examine
whether the men focused on speed or accuracy when completing the Stroop task,
correlations were run between the number of errors made and the raw reaction times for
each of the experimental Stroop categories. The total number of errors made was
significantly and negatively correlated with each of the six experimental categories of
Cognitive Bias and Body Image 157
Stroop raw scores. This indicated that a trade-off occurred such that faster reaction times
were associated more errors.
To determine whether there was any difference in the number and types of errors
made between the sub-groups, a MANOVA was conducted with the Independent
Variable as group membership and the error rates for the six experimental categories as
the multiple Dependent Variables. Mean scores are shown in Table 8.23.
Table 8.23
Mean number of colour naming errors made on the Stroop task for males.
Normal Dissatisfied Health Conscious
Negative Appearance 0.11 0.23 0.66
Positive Appearance 0.40 0.14 0.33
Low Calorie foods 0.29 0.28 0.16
High Calorie foods 0.25 0.33 0.16
Physical Activity 0.22 0.23 0.16
Negative Emotion 0.29 0.19 0.50
The MANOVA effect was non-significant, F (12, 94) = 0.38, p = .96. This
demonstrated that there was no difference between the cluster groups on type of errors.
To summarise, the men only made a small number of errors and the type of errors was
not related to other body image measures.
Cognitive Bias and Body Image 158
8.4 Sex Differences in Biased Cognitive Processing
In order to determine if there were differences between males and females in their
response to the Emotional Stroop task, a number of Independent Samples t-tests were
conducted comparing their Stroop interference, incidental memory, and errors rates. As
can be seen in Table 8.24, all interference scores were close to zero, and no consistent
differences emerged between the sexes. However, at a descriptive level the men showed
much more attention toward the negative emotion words compared to the women. None
of differences approached significance though any of the six Stroop interference indexes.
Table 8.24
Means (and Standard Deviations) for Stroop Interference Scores Between Males (N =
55) and Females (N = 143)
Female Male t p
Negative Emotion -8.02 (93.11) -22.97 (81.60) 1.04 .29
Negative Appearance 9.70 (86.27) -0.40 (76.09) 0.76 .44
Positive Appearance 5.02 (87.78) 1.17 (84.06) -0.66 .50
Low Calorie Foods -7.28 (89.56) 10.43 (89.53) -1.24 .21
High Calorie Foods -3.16 (81.92) -6.24 (114.89) 0.21 .83
Physical Activity -3.84 (84.25) 5.25 (93.02) .28 .78
No significant differences in any of the six experimental categories were noted
between males and females in the percentage of the words recalled. As can be seen in
Table 8.25, males and females showed a similar pattern of memory performance.
Cognitive Bias and Body Image 159
Table 8.25
Means (and Standard Deviations) for the Percentage of Words Recalled Between Males
(N = 55) and Females (N = 143)
Female Male t p
Negative Emotion 6.04 (11.25) 8.10 (14.11) 0.29 .76
Negative Appearance 10.17 (11.42) 9.49 (17.02) 0.32 .74
Positive Appearance 3.92 (7.11) 2.84 (6.55) 0.96 .33
Low Calorie Foods 6.46 (13.75) 5.95 (9.07) 0.25 .80
High Calorie Foods 3.58 (7.41) 1.80 (4.64) 1.64 .10
Physical Activity 3.00 (6.39) 3.74 (7.06) -0.69 .48
Experimental 32.68 (22.13) 31.63 (23.02) -1.06 .28
Finally, an Independent Samples t-test was conducted to test whether males and
females differed in the number and type of errors made during the Stroop task. Again, no
significant differences emerged, suggested that males and females responded similarly to
the task. Means, standard deviations, and the results of the t-tests are shown in Table
8.26.
To summarise, no significant differences were noted between males and females
on the Emotional Stroop task. That is, sex does not appear to affect selective attention,
memory, or error rates. Results for males and females are still reported separately given
the different pattern of correlations between the cognitive and psycho-social variables
that were reported previously.
Cognitive Bias and Body Image 160
Table 8.26
Means (and Standard Deviations) for the Number of Errors Made During the Emotional
Stroop task for males and females.
Female
(N = 143)
Male
(N = 55)
t p
NE 0.17 (0.41) 0.27 (0.54) -1.37 .17
NA 0.11 (0.33) 0.21 (0.56) -1.61 .10
PA 0.21 (0.47) 0.29 (0.59) -0.91 .36
LC 0.22 (0.46) 0.27 (0.59) -0.61 .54
HC 0.22 (0.50) 0.27 (0.65) -0.55 .57
PAct 0.20 (0.50) 0.23 (0.54) -0.32 .74
Cognitive Bias and Body Image 161
Chapter Nine: General Discussion of Phase Three and Theoretical Integration
9.1 Overview
This final phase examined whether attention and memory biases exist for body-
image and health related information within a non-clinical sample. To achieve this aim,
empirically defined sub-groups were compared on an Emotional Stroop task and
incidental memory test. Correlations were also examined between the cognitive measure
and a range of psycho-social questionnaires. Research questions and hypotheses were
developed around three main areas of enquiry. The first aim was to examine the presence
of attentional biases for body image and health related information in a non-clinical
sample. Specifically, it was hypothesised that attentional biases, as evidenced by slower
reaction times to body image-related words, would be found in symptomatic participants
only, while no attentional biases will be found in asymptomatic individuals. The second
aim of the research was to examine whether memory biases for this body image and
health related information exist. Specifically, it was hypothesised that memory biases, as
evidenced by the recall of more target words, would only be found only in symptomatic
individuals. These first two areas of investigation were explored separately for males and
females. The final area of investigation was to examine whether gender differences would
emerge in attention to, and memory for, body image information. Specifically, it was
hypothesised that males and females would differ in their processing of sub-categories of
Stroop words, given the different emphasis on body image concerns. However, given the
lack of past research in this area, the nature of these specific differences could not be
developed.
Cognitive Bias and Body Image 162
There was some evidence of attention and memory biases within the sample
thereby providing partial support for all of the hypotheses. However some of the
processing biases were associated with having a more positive body image, rather than
being indicative of a more dysfunctional body image as identified in past research. These
findings suggest that some types of processing biases may be able to distinguish between
asymptomatic and symptomatic groups of women. These findings also suggest that there
may be qualitative differences between those diagnosed with an Eating Disorder, and
non-clinical, yet symptomatic women. Given the small number of men in the current
study who showed evidence of dysfunctional weight management behaviours,
conclusions regarding the association between processing bias and clinical status could
not be drawn. However, this is the first study that has explicitly looked at processing
biases in men thereby providing an important development in the literature.
The following section provides an in-depth discussion of the results for each word
category and integrates the findings from attention, memory and error rates. The results
are viewed within the context of past research and theoretical explanations are suggested.
The findings and implications from the male participants are presented in exploratory
terms only, given the limited number of past studies that have included male participants
in an Emotional Stoop task.
9.2 Integration of Past Research and Theories
The comparison of the current findings to past research is organised into six
sections, with each section focusing on a specific word category. Within each section, the
results from attention, memory, and errors rates are integrated to form a coherent picture
Cognitive Bias and Body Image 163
of the way in which each type of word is processed. Additionally, comments are made
about the differences in processing between males and females.
9.2.1 High- and Low-Calorie Food Words
Food words have been one of the most frequently used Stroop categories in past
research with women, yet little research exists on men’s reaction to these stimuli. Issues
surrounding food and eating represent a core factor in body image concerns. It is likely
that these concerns are found in a wide proportion of the population; from those who diet
for appearance-related concerns, to those who are health conscious, and those individuals
who continually obsess over caloric content. For example, hyper-attention to food words
may be found in women who are currently dieting (Boon et al., 2000). In the current
study, methodological refinements were made for the inclusion of food words so that the
effects of high calorie or forbidden foods could be disentangled from low calorie or non-
forbidden foods, a distinction that only a few past studies have made (i.e., Mahamedi &
Heatherton, 1993; Huon & Brown, 1996; Francis et al., 1997). This distinction between
high and low calorie food words is important as they represent different concerns. High
calorie foods for example are generally something to be avoided, as these words elicit
anxiety in chronic dieters (Huon & Brown, 1996). This study offered an additional
methodological refinement by ensuring the high semantic relatedness of the words within
these categories, rather than including general eating related words such as “meal” as in
Channon and Hayward’s (1990) study. That is words were selected on their caloric
content or how ‘forbidden’ they were, rather than just selecting general words related to
eating.
Cognitive Bias and Body Image 164
9.2.1.1 Integration of Findings with Past Research for Women. Past research
examining women’s reaction to food words has produced mixed results. Attentional
biases, as indicated by longer reaction times to food words compared to neutral words,
appears to be restricted to women with highly dysfunctional dieting behaviours and
attitudes, typically defined as highly restrained eaters (Cooper & Fairburn, 1992; Stewart
& Samoluk, 1997; Black et al., 1997; Green & Rogers, 1993). Other researchers however,
have failed to find this bias amongst restrained eaters (Lokken et al., 2006; Mahamedi &
Heatherton, 1993), or have observed biases in non-restrained eaters (Black et al., 1997).
Limited research does suggest that attentional bias for food words is not found in those
women with high drive for thinness scores (Perpina et al., 1993), or report normative
dieting (Cooper & Fairburn, 1992). Research does seem to consistently show that
interference for food words is not found in asymptomatic women (Cooper & Fairburn,
1992; Stewart & Samoluk, 1997; Mahamedi & Heatherton, 1993; Lokken et al., 2006;
Green & Rogers, 1993; Perpina et al., 1993).
Given the divergent nature of the current study to past research, a direct
comparison of the findings is problematic. The current study focused on and examined a
wider range of vulnerability factors than has been reported in past research, and also
made the distinction between high and low calorie foods. The current study did find some
evidence of interference effects within a non-clinical group for low calorie food words.
However, the pattern of interference supports the claim made by Huon and Brown (1996)
that interference effects for these words may represent engaging in a healthy lifestyle.
Although these researchers did not find selective attention to low calorie food words, the
results of the current study found that attention toward low calorie food words was
Cognitive Bias and Body Image 165
associated with higher feelings of fitness and more importance placed on health. Thus, for
non-clinical women, attention to low calorie healthy foods may be part of a healthy
lifestyle. However, it should be noted that these correlations were quite weak, and the
Athletic group that emerged from the cluster analysis did not show any interference
effects for low calorie food words. This result was surprising considering the
distinguishing feature of this group was the high focus on health and fitness. It may be
that these women focus more on exercise than food intake as a means to a healthy
lifestyle, or that food does not produce enough of an emotional response for schema
activation (Bower, 1981).
The results from the current study regarding interference effects for high and low
calorie foods can only be directly compared to the work of Francis et al. (1997) and
Sackville et al. (1998). The current results are somewhat consistent with Sackville et al.’s
finding of no differences between restrained and non-restrained eaters. Sackville et al.
compared women classified as Anorexic, high restraint, and low restraint on a number of
body image-related Stroop categories, two of which were high calorie food words and
low calorie food words. Using a blocked computerised task requiring a verbal response,
no significant differences were noted between the women classified as Anorexic, high
restraint or low restraint on colour naming low calorie food words, (although all groups
showed longer reaction times to the low calorie foods compared to the matched neutral
words). Similarly, the high and low restraint group did not differ in their response to high
calorie food words, although a trend was noted for the Anorexic group to show more
interference. Thus, these findings are consistent with the current results that interference
Cognitive Bias and Body Image 166
effects to low calorie food words and high calorie food words are not found within non-
clinical, yet symptomatic, women.
The current results however are inconsistent with Francis et al.’s findings of
interference effects in restrained eaters. The work of Francis et al. was the first to
distinguish between forbidden and non-forbidden food words in an Emotional Stroop
task. Francis et al. compared restrained and unrestrained eaters on a computerised Stroop
task and found that the women classified as restrained eaters responded significantly
slower to both types of food words (as compared to the matched neutral words), while the
unrestrained group showed longer response times to the neutral words. Francis et al.
(1997) interpreted these findings as an overall bias that restrained eaters show to all types
of food, and suggest that the distinction between forbidden and non-forbidden foods
occurs later in processing (i.e., that is not assessed by the Stroop task). The results of the
current study are not consistent with Francis et al. Despite a similar methodology,
restraint status did not significantly interact with response to the food words. At a mean
level, the women classified as non-restrained eaters showed a bigger negative
interference effect (i.e., quicker reaction times) to the high calorie food words, while the
women classified as restrained eaters showed a negative interference effect to the low
calorie food words. Hence, even the pattern of means between the current study and the
work of Francis et al are not similar.
The reason for these inconsistent findings remains unclear. Both studies used a
randomised Stroop task with comparable words. In both studies, the target and neutral
words were from one semantic category, had empirical support for their use, and were
carefully matched on length and frequency of occurrence. Small differences were noted
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in the methodology between Francis et al and the current study. In the Francis et al study,
a total of 15 words were used in each category, making a total of 120 trials (where each
word is presented twice). In the current study only 5 words per category were used,
making only 40 trials of the food words. Thus, participants in Franics et al’s study were
exposed to far more presentations of the food words. This could potentially have lead to
habituation effects, as noted by Green and Rogers (1993). Habituation effects do not
appear to explain these discrepant findings however, as it would be expected that Francis
would have reported the non-significant findings, rather than the current study. Therefore,
habituation effects do not appear to explain these results. A second difference is the type
of response required. Francis et al used voice activated responses, while in the current
study button presses were used. However, previous research has demonstrated that
although button press is preferable, no differences emerge in interference indexes
between the two methods (Davidson & Wright, 2002; Johansson et al., 2005a).
Another potential factor to explain the differences in results may be that the
Francis study was more homogeneous in that only food and matched neutral words were
presented, while in the present study the food words were presented in amongst eight
other categories of target and neutral words. This explanation would also be consistent
with the findings of Sackville et al. (1998) who also used eight other categories of words
and found no differences between the high and low restraint women. That is, perhaps the
higher rates of exposure in Francis’ study lead to more interference effects. Given the
small number of studies to include multiple categories of Emotional Stroop words, this
argument warrants future research.
Cognitive Bias and Body Image 168
While the research specifically examining low calorie food words remains scarce,
high calorie food words have been more typically used. In the current study, some
evidence of interference effects was found for high calorie food words, but these effects
were limited to women who reported binging in the last six months. That is, the
hypothesis that interference effects would only be found in symptomatic women, was
supported for high calorie food words. No other evidence of interference for high calorie
food words was found, nor did any of the psychosocial variables show significant
correlations with the interference index for high calorie food words. The women did not
show enhanced recall for high calorie food words, a finding that is supported in previous
research with non-clinical samples (Boon et al., 2000; Lavy & van den Hout, 1993;
Mendlewicz et al., 2001).
This is the first study to look specifically at weight management behaviours and
Stroop interference in a non-clinical sample. Only one previous study was identified that
specifically examined frequency of eating disorder behaviours in relation to interference,
however this was conducted on women diagnosed with Bulimia (Cooper & Fairburn,
1993). Cooper and Fairburn (1993) found that interference effects on a target card
containing words related to negative appearance and food was only related to eating
disorder symptoms and frequency of purging. Frequency of purging in the last 28 days
was the best predictor of Stroop interference. Given that binging is one symptom of
Bulimia, comparisons could also be made to studies using Bulimic women. For example,
Lokken et al. (2006) found that interference effects for a combined category of high
calorie / eating words was associated with bulimic symptoms, but that no differences
emerged between the women classified as Bulimia, and the women classified as having
Cognitive Bias and Body Image 169
sub-clinical bulimic symptoms. However, given that other behaviours associated with
Bulimia did not show any relation to interference scores on high calorie food words in the
current study (e.g., purging, excessive exercising, and loss of control over binge), these
comparisons are problematic. Thus, the conclusion made by Cooper and Fairburn (1993)
that interference effects are related to symptom severity, rather than diagnosis per se, is
supported in the current study. More research is needed however to substantiate this
argument.
To summarise, the hypothesis that interference effects would only be found in
symptomatic women was only partially supported. No differences were noted between
the subgroups identified in the cluster analysis in colour naming either the high calorie or
low calorie food words. Attention toward low calorie foods words was associated with
more feelings of fitness and importance placed on health, while avoidance of high calorie
food words was only found in women who reported binging recently. The results from
the current study do converge with past research that forbidden and non-forbidden food
words represent different concerns, and therefore should not be included together into a
combined “eating” or “food” category (Placanica et al., 2002; Sackville et al., 1998;
Francis et al., 1997).
9.2.1.2 Integration of past findings with past research for males. In the current
study, little evidence of processing biases for food related stimuli were found within the
male sample. The men did not show any significant attentional bias for either high calorie
food words or low calorie food words. The men did however recall a significantly higher
percentage of low calorie food words. Also, a different pattern of correlations emerged
between the psycho-social variables and the low and high calorie food words, supporting
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the distinct nature of these categories. Faster reaction times for high calorie food words
were associated with a more positive body image (exercising for weight control, lower
drive for muscularity), while quicker reaction times for low calorie food words were
associated with better mood (lower stress). No significant group differences emerged
between the sub-groups identified in the cluster analysis in response to either the high or
low calorie food words.
No evidence of biased memory for high calorie food words was found, and recall
was not associated with any of the psycho-social variables, sub-groups, or risky
behaviours. A memory bias was observed for low calorie food words, and higher recall
was associated with being heavier and reporting more dissatisfaction with appearance. No
significant differences were noted between the men who had, and had not, reported
dieting for appearance or dieting for weight loss purposes, in response to low calorie food
words. More colour naming errors for both high and low calorie food words was
associated with higher stress. However, only 16 men provided this data, so this result
should be viewed with caution. Together, these findings suggest that processing biases
were not consistently noted within this sample.
Previous research examining processing biases in males is limited. Channon and
Hayward (1990) included males in their sample, but as part of a larger group with
females. Although they note that no evidence was found of differences between males
and females in response to body shape and food words, the neutral words used were not
homogenous. The comparison of reaction times from a homogenous group of words to a
non-homogenous group of words is problematic, as the level of semantic association
between words is associated to interference effects (Green et al., 1999). That is, the
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slower reaction times noted for the target words may have been due to the highly
associated nature of these words, compared to neutral words that did not form one
semantic category. Similarly, Fairburn et al. (1991) reported no differences between
males and females in response to a combined category of eating, weight, and shape
related words. However, given the card based methodology, non-homogeneous nature of
both the experimental and neutral words, and failure to use words specific to males
concerns with body image, these findings are problematic. Therefore, given the divergent
nature of the current study to these past studies, a comparison of results is not useful.
9.2.1.3 Theoretical Explanations. In theoretical terms, the results of the current
study suggest that food related words do not receive any preferential attention, but that
low calorie food words may receive increased elaboration in both men and women
(Williams et al., 1988a, 1997). The lack of either biased attention or memory for high
calorie food words suggests that, within this sample, food information is not important
enough to receive preferential attention, or threatening enough to interference with task
performance. Biased attention was found for high calorie food words for women who
recently reported binging. This finding supports the notion that women who engage in
unhealthy weight management behaviours have maladaptive schemas surrounding high
calorie food words (Vitousek & Hollon, 1990). Descriptive accounts show that binging
occurs with high calorie / forbidden foods (Woell, Fichter, Pirke, & Wolfram, 1989), but
it appears that this obsession is also represented by cognitive bias. It may be argued those
women who are prone to binging will find high calorie foods threatening; and this is
supported by the cognitive avoidance of such information. The distinction between
priming and elaboration identified in Williams et al. (1988a, 1997) theory means that
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although this threatening material ‘grabs’ attention, further elaboration is avoided,
explaining the lack of memory bias for women who binge.
It is somewhat surprising that biased memory for low calorie food words was so
widespread in the sample. There was nothing unique about the sample that could explain
this bias (such as high level of dieting, restraint, or body dissatisfaction; or being
recruited from a gym or diet group). Therefore the widespread bias must stem from a
common factor within the sample. Perhaps the particular attention that Australian society
has paid to health-related issues such as weight loss, the high rates of obesity, and a focus
on healthy eating may explain these findings (Davis, Shapiro, Elliott, & Dionne, 1993).
Given the older age of the male participants (mean age = 34 years), concerns over health
in general and weight in particular, may result in a selective processing of low calorie /
healthy foods. It is interesting however that this biased processing was not found for
physical activity words in either the men or women (discussed later). Both engaging in
regular exercise and eating low calorie foods are means for engaging in a healthy lifestyle
and achieving weight loss, so it is not clear why only the one method received enhanced
elaboration. Future research could address this question.
The differential processing of high and low calorie food words suggest that
differentiation between these categories occurs early in processing, a conclusion that is
inconsistent with Francis et al. (1997). This finding suggests that the ‘pre-attentive
detection mechanism’ reported in anxiety and depression (Williams et al., 1988a, 1997)
may also be relevant within the body image research. Within anxiety, it is proposed that
state levels of anxiety can affect the allocation of resources, however it appears that
material associated with low calorie foods receive elaboration in most individuals.
Cognitive Bias and Body Image 173
It should be noted that the higher recall of low calorie food words may simply be
an artefact of the low recall for the matched neutral words. Recall for these neutral words
was very low compared to the other neutral categories. However, the matching process
ensured that there were no significant differences on key features of the experimental and
neutral words; hence this explanation is not favoured.
To summarise, both men and women showed a similar response to the food
words. However, given the different pattern of associations between the psycho-social
variables and processing of the food words, it is still useful to consider males and females
separately. In females, processing of the food words had stronger relations to the body
image variables than was observed in men.
9.2.2 Positive and Negative Appearance Words
The other most commonly used Stroop category is appearance related words.
Again, words related to body shape, weight, and general appearance have been used
frequently with women, while little research exists on men’s reaction to these words.
Given that dissatisfaction with weight and appearance are key factors in clinical and non-
clinical body image disturbance, and the high rates of body dissatisfaction reported in
males (Grogan & Richards, 2002) and females (Tiggemann & Lynch, 2001), it is
important to understand whether this disturbance is represented cognitively.
As outlined in the literature review, a number of significant limitations have been
noted in past research using appearance related words which warrant further
investigation. The current study aimed to address these limitations by separating positive
appearance / body shape words (e.g., “attractive”) from words with a more negative
connotation (e.g., “ugly”). Vitousek and Hollon (1990) note that our understanding of
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processing biases for body image stimuli is limited by focusing on negative shape words
only. They argue that avoidance of counter-schematic information (such as words related
to thinness) is just as important to consider as attention for schematic information (such
as words related to fatness). To date, only limited research has used both categories of
words to examine selective attention (Sackville et al., 1998; Reiger et al., 1998), and
selective memory (Unterhalter et al., 2007). Additional methodological refinements were
made in the current study by ensuring the high semantic relatedness of the words in each
of these categories. Each word was carefully selected and independently rated to ensure a
good representation of the category. Past research has included more general words in
appearance categories (e.g., Lokken et al., 2006; Long et al., 1994). For example, the
“shape” words used by Lokken et al. (2006) contained only two words indicative of
negative shape (“fat” and “flabby”), while the remaining words were general body areas
(e.g., “thighs”). Additionally, the “weight” words primarily reflected being overweight
(e.g., “heavy”), so it’s not clear how this category is distinct from the “shape” category
used. The aim of the current study therefore was to address these limitations. Careful
selection of words ensured that both male and female body image concerns were
reflected. For example, words like “muscular”, “attractive” and “ugly” are expected to
equally relevant to males and females.
9.2.2.1 Integration of findings with past research for females. The results of the
current study clearly indicate that concerns surrounding positive appearance are distinct
from negative appearance. The positive appearance words were the only category to be
related to current hunger levels and time since last meal. Higher hunger levels and more
Cognitive Bias and Body Image 175
time since last food consumption were weakly, yet significantly, related to quicker
reaction times to colour name positive appearance words.
The pattern of correlations between the positive appearance interference index
and psychosocial variables revealed that longer reaction times (that is, attention toward
these words), was associated with better body image. Comparatively, longer reaction
times to colour name the negative appearance words was associated with poorer mood.
Both indexes were associated with risky weight management behaviours. Women who
reported vomiting after food consumption and fasting reported significantly longer
reaction times for negative appearance words, compared to women who did not engage in
these behaviours. Additionally, a trend was noted for women for dieted for weight loss
and binged to have longer reaction to negative appearance words than who didn’t report
these behaviours.
Although no significant differences emerged between the groups identified in the
cluster analysis, mean differences were noted. The Normal and Athletic group showed
high interference indexes indicating they spent longer colour naming the positive
appearance words, while the Dissatisfied group demonstrated quicker reaction times. The
Symptomatic group reported only a small interference index. In response to the negative
appearance words, only the Normal group showed a large interference index, indicating
attention toward the words. To summarise, longer reaction times to positive appearance
words was indicative of better body image and associated with less risky behaviours,
while longer reaction times for negative appearance words was associated with poorer
mood, and engaging in more risky weight management behaviours.
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Only two studies to date have included positive body shape words when
examining biased attention (Reiger et al., 1998; Sackville et al., 1998). Both studies
compared women with eating disorders to a group of control women high and low on
dietary restraint, and found that interference effects increased with symptom severity.
Significant interference effects were only noted in the clinical groups, and both studies
found no evidence of interference effects in the non-clinical women. These results are
somewhat consistent with the current findings, as interference effects were limited to
women reporting more risky weight management behaviours, particularly for the negative
appearance words. It therefore appears that interference effects for appearance related
words are associated with increased symptom severity (Ben-Tovim & Walker, 1991;
Cooper et al., 1992; Green & Rogers, 1993; Lokken et al., 2006), and that interference is
associated with negative mood (Cooper et al., 1992; Leon et al., 1993).
No evidence was found of a memory bias for the positive appearance words in
this sample of women. As a group, the women did not recall many of the positive
appearance words, nor were the psycho-social variables related to recall. Additionally, no
group differences emerged when comparisons were made along the risky behaviours or
the cluster analysis groups. The women did however show a memory bias for the
negative appearance words. As a group, they recalled significantly more of the negative
appearance words compared to the matched neutral words. Higher percentage of negative
appearance words recalled was significantly related to poorer mood and higher restraint.
Additionally, women who reported excessive exercise and dieting for health showed
significantly higher recall than those women who did not report these behaviours.
Regardless of which group the women were classified into, they showed higher recall of
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the negative appearance words. Finally, a small number of errors when colour naming
both the positive and negative appearance words was associated with poorer body image.
These findings suggest a widespread memory bias for words associated with being
overweight and unattractive.
These findings are consistent with previous research which has noted a general
memory bias for weight and appearance stimuli in women (Boon et al., 2000; Unterhalter
et al., 2007). Boon et al. (2000) found that all women (classified as restrained or
unrestrained eaters) showed a recognition bias for the body shape / size words, but no
details were provided regarding the valence of these words (whether negative or positive
appearance). Using a self referent encoding task where women were asked to rate how
relevant a set of words to them followed by an incidental memory task, Unterhalter et al.
(2007) found that women reported significantly higher recall of both positive and
negative weight / shape words compared to the neutral words. Results of the current study
suggest that memory bias is limited to negative appearance words. The high recall of
positive appearance words in Unterhalter et al’s study may be due to the use of a self
referent encoding task that required more cognitive processing of stimuli compared to an
Emotional Stroop task where participants to instructed to ignore the stimuli (Sharma &
McKenna, 2001). Also, the difference in time of the distracter task (20 seconds in
Unterhalter et al; three minutes in the current study) may mean that positive appearance
words are quickly forgotten, particularly if they are deemed not relevant.
Together, these results indicate that there is no link between encoding and
retrieval of positive or negative appearance words. Longer reaction times to colour name
positive appearance words was associated with better image, but no associations were
Cognitive Bias and Body Image 178
found for recall for these words. A higher number of errors made on this task were
associated with more body image dysfunction, indicating perhaps that more attention was
paid to the task of colour naming. Women with better image spend longer looking at
positive appearance words, but no further elaboration occurs. It appears that opposite
pattern of results emerges in response to negative appearance words. No evidence of
attentional bias was found, yet this was the only category of words that all women
showed increased recall for. Regardless of what sub-group women were classified as, the
percentage of negative appearance words recalled was high.
9.2.2.2 Integration of findings with past research for males. No evidence of
attention bias was found in this sample of men for either positive or negative appearance
words. Quicker reaction times for positive appearance words were associated with a
poorer body image (higher drive for thinness, trend for higher drive for muscularity),
while quicker reaction times for negative appearance words were related to higher stress.
Engaging in weight management behaviours was not significantly associated with biased
attention. No significant differences emerged the groups identified in the cluster analysis
on attention for either positive or negative appearance words.
The sample as a whole showed a memory bias for the negative appearance words,
but not positive appearance words. The percentage of words recalled was not related to
any of the psycho-social variables, engaging in risky weight management behaviours, or
sub-group. Errors when colour naming the negative appearance words were not
significantly associated with any of the measures, while a higher number of errors when
colour naming the positive appearance words was associated with exercising more for
fitness reasons, and having a lower BMI.
Cognitive Bias and Body Image 179
Based on these results, the hypothesis that processing biases would only be found
in symptomatic men was not supported for either positive or negative appearance words.
The men overall showed higher recall of negative appearance words; a relationship that
was not modified by any of the psycho-social variables.
Previous research examining processing biases in males is limited. As discussed
in the previous section on food words, only two studies to date have included male
participants when studying biased attention (Channon & Hayward, 1990; Fairburn et al.,
1991), and the designs of these projects were problematic (i.e., combined word
categories, non-homogeneous neutral words). Although both these studies did find some
evidence of interference effects, the homogeneous nature of the target words compared to
the neutral words could explain this difference (Green et al., 1991).
Processing biases in males may be limited to stimuli that focus more on
muscularity. Unterhalter et al. (2007) found that men recalled words related to
muscularity more frequently than general appearance related words. While the women
showed a memory bias for all appearance words, the men only showed enhanced recall
for the words related to high muscularity (e.g., “muscular”), as opposed to words
indicative of low muscularity (e.g., “scrawny”). That is, the men in Unterhalter et al’s
study reported memory bias for only positive muscular words, while in the current study
the men showed enhanced recall of a general category of negative appearance words. The
use of a self referent encoding task in Unterhalter et al’s study may have resulted in the
high recall of positive muscularity words, if the men were able to form rich and elaborate
memories of themselves as large and muscular (i.e., an ideal they would like to achieve).
After a short distracter task of 20 seconds, these memories could still have been
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accessible. Self referent encoding tasks require cognitive processing of the stimuli as the
men were asked how strongly the word related to them. In an Emotional Stroop task,
participants are not required to actively engage with the stimuli; in fact they are instructed
to ignore it. As such the Emotional Stroop task is a better measure of shallow,
unintentional processing (Russo et al., 2006). The different task demands between the
two studies in addition to the longer distracter task used in the current study (two
minutes) may explain these discrepant findings. Future research should examine how
instructions to either engage with, or ignore the stimuli affects memory. This is the first
study to date that has examined processing biases in males using stimuli specifically
developed to represent male body image concerns. Clearly more research is needed to
further explore the generalisability of these findings.
9.2.2.3 Theoretical Explanations. In theoretical terms, the results of the current
study suggest that appearance related words do not receive any preferential attention, but
that negative appearance words may receive increased elaboration in both men and
women (Williams et al., 1988a, 1997). These findings may be interpreted in two ways.
The high levels of body image disturbance would implicate a highly developed schema
network surrounding negative appearance, which guides biased recall of negative
appearance information. This interpretation is not favoured in males however, given that
levels of body image disturbance were either low, or consistent with normative values.
This explanation is more plausible for women, and the findings may be interpreted within
the cognitive theories of Vitousek and Hollon (1990). Cognitive processing is directed
toward schema consistent information which in this case is negative appearance
information. The large number of women in the current sample who reported body image
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disturbance reflects a ‘normative discontent’ (Rodin et al., 1984), which results in more
processing of negative appearance information. These findings suggest that more
elaboration (Williams et al., 1988a, 1997) occurs for self relevant information (Rogers et
al., 1977) consistent with one’s self schemata (Markus 1977, 1987).
The alternate explanation is that enhanced memory for negative appearance
information may reflect the increasing importance of being attractive, toned / muscular
for men, and thin for women (Davis et al., 1993). It can be argued that seeing one’s self
as not fitting this ideal (i.e., as fat and unattractive) has comparatively more negative
outcomes than viewing one’s self positively (i.e., as attractive and muscular) has positive
outcomes (Baumeister, Bratslavsky, Finkenauer, & Vohs, 2001). This may explain why a
memory bias was observed for negative, but not positive appearance words. The pressure
within society for women to look thin and attractive, and the negative connotations with
“fat” and “ugly” may result in this widespread processing bias. The recall of more
negative appearance information may serve to maintain body image concerns, as this
information is more readily accessible.
The widespread memory bias suggests that increased processing of negative
appearance stimuli is not restricted to clinical groups, or even symptomatic groups.
However a different pattern of processing the appearance words was found for males and
females. In males, the widespread bias suggests that although men may not be aware of,
or consciously effected by this pressure, it does influence cognitive processing. That is, it
may reflect a more general bias, rather than a bias that is specifically associated with
negative body image. None of the psycho-social variables were associated with increased
memory for negative appearance information in men, therefore the typically used
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explanation in past research that bias is indicative of negative functioning must be viewed
with caution. Material that is selectively recalled is assumed to have some relevance to
the individual, however in this case it may simply reflect living within a society that is
obsessed with appearance. Men may have formed schemas surrounding appearance, but
these schemas are not linked to a wider concept of the self. That is, more generalised
schemas were developed, rather than self related schemas (Vitousek & Hollon, 1990).
This explanation would explain the higher recall of negative appearance material and the
lack of associations with the psycho-social variable, however clearly research is needed
to replicate this effect.
The different pattern of results for negative and positive appearance words
demonstrates the importance of considering these categories separately. These findings
challenge the notion that interference effects are always associated with poorer
functioning, as interference for positive appearance words was associated with better
body image in women. Therefore the hypothesis that interference effects would only be
found in symptomatic women was partially supported. Engaging in risky weight
management behaviours was associated with more interference effects in both positive
and negative appearance words in women. Additionally, positive appearance words were
the only category to show significant group differentiation, with the Dissatisfied female
group showing more interference. However, this study also indicated that longer reaction
times for positive appearance words were associated with better body image. This was
the first study to specifically examine both positive and negative appearance words in the
general community. Results indicated that these categories represent distinct concerns,
and highlight the need for more research examining these words separately.
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9.2.3 Negative Emotion Words
Despite the growing recognition of the association between negative mood and
body image disturbance (Cooper, 1995; Leon et al., 1993), very little research has
included these words as stimuli in an Emotional Stroop in women, and no study to date
has used male participants. The present study included this category of words to explore
whether dysfunctional body image attitudes was associated with selective attention for
negative affect words (e.g., “anxiety”, “depressed”).
9.2.3.1 Integration of findings with past research for females. Findings of the
current study suggested that quicker reaction times for negative emotion words were
associated with poorer body image, mood, and general wellbeing. At a mean level,
women who recently engaged in vomiting, use of slimming tablets, fasting, excessive
exercise and reported loss of control over binging, showed quicker reaction times to
colour name negative emotion words compared to women who did not engage in these
behaviours. Significant differences were only noted for use of fasting though.
Examination of the groups identified in the cluster analysis revealed no significant
differences in interference effects for negative emotion words, although effects did
become progressively larger as symptomology increased. Therefore, the hypothesis that
interference effects for negative emotion words would only be found in symptomatic
individuals was partially supported.
To date, only three previous studies have examined attention bias for negative
emotion words in adults. Sackville et al. (1998) found no differences in interference
effects between women classified as Anorexic, or high and low dietary restraint, although
at a mean level interference increased with increasing symptomology. Jones-Chesters et
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al. (1998) found interference effects in women with Bulimia, but not Anorexia, or control
groups, but only when the words were presented in a blocked format. Finally, Seddon
and Waller (2000) found that younger women (< 21 years) with high bulimic
symptomology showed a tendency for cognitive avoidance of the negative emotion
words, while the older women (>21 years) showed attention toward this information.
Based on this literature, it appears that interference for negative emotion words may be
related to bulimic symptoms. This is the first study to consider a wider range of psycho-
social vulnerability factors, and shows that cognitive avoidance of negative emotion
words has wider relations to poorer mood, well-being, and body image.
Higher recall of the negative emotion words was only associated with three body
image variables: lower interoceptive awareness, ineffectiveness, and perfectionism. No
significant differences in recall rates for negative emotion words were found between
women who had, and had not, engaged in risky weight management behaviours recently.
No significant differences emerged between the cluster analysis sub-groups, suggesting
that memory bias, or rather lack of memory bias, is only found in women with more
severe eating disorder-like symptoms. Therefore the hypothesis that a memory bias
would found in symptomatic women was not supported.
Fewer errors when colour naming the negative emotion words was associated
with poorer body image (high drive for thinness, bulimia symptoms, and body
dissatisfaction). That is, it appears that women with higher body image disturbance were
better able to ignore the valanced stimuli, and accurately complete the task. Jones-
Chesters et al. (1998) also found that the women classified as Bulimic made more errors
when colour naming negative emotion words.
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9.2.3.2 Integration of findings with past research for males. In this sample of
men, increased processing of the negative emotion words was noted. The men overall
showed a facilitation effect when colour naming the negative emotion words. This was
the only category of words to show a significant interference effect. On average, the men
were 20 msec quicker to colour name the negative emotion words compared to the
matched neutral words. The men also showed a memory bias for these words, recalling a
significantly higher percentage of negative emotion words compared to the matched
neutral words. However, increased interference was not significantly related to increased
memory, which is consistent with Williams et al.’s (1988a, 1997) model that priming and
elaboration are separate processes. Examination of a wide range of psycho-social
variables revealed limited associations to biased attention and memory. Quicker reaction
times for negative emotion words was related to poorer body image (lower feelings of
attractiveness and higher bulimic symptoms), but no significant associations were noted
with memory scores. No significant differences were noted between the sub-groups on
attention, memory, or errors. Therefore, these results do not support the hypothesis that
interference effects would be found in symptomatic men only; biased attention and
memory for negative emotion words was found across the whole of sample of men.
9.2.3.3. Theoretical Explanations. Both males and females showed selective
recall of negative emotion words, and selective attention was noted in the men. However,
the pattern of correlations between the cognitive and psycho-social variables suggests that
the relationship is different for males and females. In males, limited associations between
the psycho-social variables and avoidance of the negative emotion words were noted,
while no associations were noted with biased memory. In women, avoidance of this
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information was consistently associated with poorer functioning, but not associated with
biased memory.
In theoretical terms, words connoting negative emotions received preferential
processing in this sample. Affective material may have a lowered threshold for awareness
and be noticed much more rapidly than neutral material, particularly in women with
poorer body image. Examination of literature outside of the body image area reveals that
biased attention for negatively valanced information is not a new finding (Smith et al.,
2006). Baumeister et al. (2001) in their review of the literature examining attention for
negative information conclude that “We have found bad to be stronger than good in a
disappointingly relentless pattern” (p. 362). They suggest that people try and avoid
negative emotion in favour of more positive stimuli as a means of affect regulation. They
review evidence to shows that people tend to recall more negative information than
neutral or positive information. Smith et al. (2006) have found however that this effect
can be moderated by exposure to positive information. When participants were
subliminally primed using positive words (e.g., “friends”), or were treated very kindly by
the experimenter, the attentional bias toward negative information disappeared. It appears
that the positive prime does not create attention toward positively-valanced information,
but simply reduces the focus on negatively-valanced information.
This claim is also consistent the findings of MacLeod and Rutherford (1992) who
found that individuals low on trait anxiety showed an avoidance of threat information
when levels of state stress were high. It is possible that the high task demands and the
rapid presentation of the words in the Emotional Stroop task resulted in a high stress
condition for the participants (Sharma & McKenna, 2001). Research has noted that
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shorter inter-stimulus intervals produce more interference effects (Sharma & McKenna,
2001). Under this pressure, the rapid detection of negative threat information is even
more important. By screening out threatening information, the emotional impact is
reduced. This is thought to be a strategic rather than automatic process, as MacLeod and
Rutherford (1992) found this avoidance only using a Stroop methodology wherein
participants were aware of the stimuli. The rapid detection of threat information is
consistent with the pre-attention decision mechanism proposed by Williams et al. (1988a,
1997). This mechanism makes a decision about the affective valence of material and
guides processing according. In non-emotionally disturbed individuals, as in the current
sample where levels of negative affect were low, attention is diverted away from
threatening information. Therefore, the results of the current study regarding biased
attention are consistent with the wider research on processing biases for negatively
valanced information. The men and asymptomatic women are showing the expected
attention bias toward negative emotion information, but symptomatic women showed
avoidance of this information.
The reason for this cognitive avoidance in only the symptomatic women is not
clear. One possible explanation is that the avoidance of negative material may serve to
maintain the women’s non-clinical status. For example, the negative emotion material
may be deemed too threatening, and thus is avoided. This suggestion is also consistent
with the decreased recall rates, and lower number of errors for negative emotion words
found in women with higher symptomology. These women may pre-attentively define
negatively valanced information as too threatening, and thus allocate more attention to
completing the task (i.e., correctly identifying the colour), hence the quicker reaction
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times and less errors (Williams et al., 1988a, 1997). This information does not receive
any further elaboration, as evidenced by lower recall rates.
A similar explanation has been provided in past research wherein ‘low trait’
groups show a protective mechanism by selecting avoiding threatening information
(Johansson, Lundh, & Andersson, 2005; MacLeod & Rutherford, 1992). MacLeod and
Rutherford (1992), when examining high- and low-trait anxious individuals, found that
non-clinical individuals who score low on trait anxiety have almost a protective
mechanism wherein threatening information is avoided. When this group experiences
high state anxiety (i.e., stress from an upcoming exam), interference effects become more
pronounced, however they are avoiding rather than attending to the information. This
automatic avoidance of threatening information serves to maintain their low levels of
anxiety. Similarly, Johansson et al. (2005) found that when exposed to images of highly
attractive women before completing a Stroop task, body dissatisfied women reported an
interference effect while non-primed women showed a facilitation effect. These results
were explained as avoidance of threat related information, wherein body satisfied women
strategically divert processing resources away from threatening information. This in turn
may help to maintain their current levels of satisfaction by buffering against the any
negative impact of the media.
The progression from non-clinical yet symptomatic, to a full blown eating
disorder may shift attention back towards the negative emotion words. The increased
schema elaboration and increase in negative mood means that negatively valanced
information can longer be ignored. This suggestion is consistent with findings of Jones-
Chesters et al. (1998) who found that only women classified as Bulimic showed increased
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attention toward negative emotion information, and also showed more errors in colour-
naming. Clearly, more research is needed to test this idea.
It is not clear though how this avoidance of information can be explained in
combination with the increased memory for negative emotion material. Although
processing of this negative information is avoided, it may still produce schema activation
and activation of emotional nodes (Bower, 1981). This activation, even though the
information is avoided, may still make the negative emotion information
disproportionately more available. That is, even though the information is successfully
avoided, the residual activation renders the information available a short period later
during the incidental memory task. More research is needed to test this explanation, and
to further investigate the association between encoding and retrieval bias. Mathews and
MacLeod (2005), in their review of cognitive biases associated with emotional disorders,
conclude that while attention bias is generally supported in anxiety and depression, there
is inconsistent research on memory bias. To date, there is no research that has examined
memory bias for negative emotion information within the body image literature.
9.2.4 Physical Activity Words
This is the first study to use the category of physical activity words (e.g., “sport”,
“gym”) in an Emotional Stroop task. The inclusion of physical activity is theoretically
important for several reasons. First, physical activity is part of engaging in a healthy
lifestyle. Given the high rates of obesity worldwide, and the current focus by the
Queensland Government on healthy eating and regular exercise, it is important to
understand the whether cognitive bias extends to these words. Second, excessive exercise
is found in clinical groups (e.g., eating disorders, body builders) a means for weight
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control. Finally, the ideal body shape is becoming increasingly athletic and toned.
Therefore, an understanding of whether cognitive bias extends to physical activity words
is applicable to both clinical and non-clinical groups.
9.2.4.1 Integration of findings with past research for females. In the current study,
longer reaction times to colour name physical activity words was associated with a higher
recognition of any illness, and a trend for lower dietary restraint. Minimal interference
effects were noted for women who had, and had not, reported engaging in risky weight
management techniques recently. Comparisons of the interference indexes across the
groups identified in the cluster analysis revealed that the Athletic group showed the most
interference, although not significant. The other three groups also showed some evidence
of interference effects to the physical activity words, albeit to a smaller degree.
Therefore, the hypothesis that interference effects would only be found in symptomatic
individuals was not supported. However, it appears that interference effects for physical
activity words as not necessarily indicative of poorer functioning.
As a group, the women recalled significantly less physical activity words
compared to the matched neutral words. However, when the interference index was
correlated with the psycho-social variables, a higher percentage of physical activity
words recalled were consistently related to more focus on health and fitness. Significant
correlations revealed higher feelings of strength and fitness, a higher importance placed
on health and fitness, less illness, exercising to maintain a health lifestyle, but also high
anxiety. Both the Athletic group and the Symptomatic group showed a higher percentage
of physical activity words recalled, however the difference was non significant. Errors
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when colour naming the physical activity words was not significantly associated with any
of the body image, mood, or general well-being variables.
9.2.4.2 Integration of findings with past research for males. No evidence was
found of biased cognitive processing for physical activity words in men. The men did not
show any selective attention or memory for these words, and no significant associations
were found with the psycho-social variables. More errors when colour naming these
words was associated with a higher level of stress, but no other associations were noted
with body image or general well-being variables. Similarly, no differences emerged
between the three sub-groups in response to these words. For men, exercising does not
appear to be related to mood, body image, or general well-being, a finding consistent with
past research using questionnaire-based methodology (Boroughs & Thompson, 2002;
Tiggemann & Williamson, 2000). For instance, Tiggemann and Williamson (2000) found
that men’s exercising behaviour was not linked to body satisfaction or self esteem, like it
was in women. Therefore the hypothesis that interference effects would be found in
symptomatic individuals only, was not supported for physical activity words.
9.2.4.3 Theoretical Explanations. No significant processing biases were noted for
physical activity words in males or females, although the women showed reduced
memory for physical activity words. Within the male sample, the psycho-social variables
showed a complete lack of association with cognitive processing of exercise words. In the
female sample, higher recall of exercise words was related to the health and fitness
variables.
The women as a whole group showed reduced memory for the exercise words, but
it’s interesting to note that higher recall was consistently associated with feeling fit and
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healthy, and an importance of a healthy lifestyle. Alternatively, lower recall was
associated with poorer feelings of strength and fitness and lower importance on health.
Given the small number of women who were classified as Athletic, perhaps this reduced
recall of exercise words reflects that most women did not rate exercise as overly
important. Processing biases for physical activity words may are limited to women who
engage in regular exercise and report high levels of fitness. These women may have
highly developed schemas surrounding physical fitness, which allows increased
elaboration of this material. These findings are consistent with the “personal relevance”
hypothesis (Rogers et al., 1977) that only material that is personally relevant receives
biased processing. Thus, it appears that processing biases are found in some women, but
are limited to those who place increased importance on fitness. As this is the first study to
examine attention and memory bias for physical activity stimuli, further replication is
needed.
In theoretical terms, these findings suggested that males in the sample did not
have schemas developed around sporting activities / exercise, or these schemas are not
developed enough to influence cognitive processing. Even though a range of questions
were asked about exercising behaviours, reasons, and attitudes; and most of the sample
reported exercising in a typical week; this was not related to processing biases for
exercise stimuli. Men most frequently report exercising for health and fitness reasons
(Tiggemann & Williamson, 2000), but only a small proportion of men in the current
sample (n = 9) though were classified as “Health Conscious”. It may be that increased
attention and memory for physical activity words are only found in men who are more
athletic, engage in excessive exercise, or competitive sport; who have more highly
Cognitive Bias and Body Image 193
developed and elaborative schemas surround exercise. This claim is consistent with the
theoretical underpinnings of the research that biased processing is driven by schemas
(Beck 1967, 1991; Markus, 1977; Vitousek & Hollon, 1990), but that schemas need to
reach a certain level of activation before they influence processing (Bower, 1981). Future
research could examine whether words more specific to the type of exercise a person
does produces interference, as it has been noted that threat-specific words produce more
interference than general threat words (MacLeod & Rutherford, 1992). Alternatively,
exercise related words may only produce interference in elite athletes; a claim that
warrants further investigation.
9.2.5 Sex Differences in Cognition
Direct comparisons between males and females on attention, memory, and
number of errors revealed no significant differences. These findings suggest that body
image information is processed similarly between the sexes, a finding that is consistent
with some past research (Fairburn et al., 1981; Channon & Hayward, 1990), but
inconsistent with other findings (Unterhalter et al., 2007). In the current study, attentional
biases were not found in women, and were limited in men. Both groups recalled
significantly more experimental words, negative appearance words, and low calorie food
words, compared to matched neutral words. In addition, then men also showed increased
memory for negative emotion words, while the women showed poorer recall of physical
activity words.
Although no sex differences were observed, the pattern of findings was quite
different for men and women. For instance, in both groups facilitation effects for negative
emotion words were associated with poorer body image, but in women interference
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effects were associated with a larger number of body image variables, and also mood and
general well-being variables. Similarly, the males showed an enhanced recall for the
negative emotion words which was not found within the female sample. Within the male
sample, psycho-social variables were not related to recall; while in the female sample
lower recall was associated with poorer body image. The hypothesis that sex differences
would emerge in response to the stimuli was therefore not supported, with the cravat that
different patterns of associations between cognitive and psycho-social variables are
found. Therefore, it appears useful to consider males and females separately in analyses,
even if they appear similar at a surface level.
9.3 Summary of Chapter
The purpose of this chapter was to review the findings on processing biases in
men and women. Partial support was gained for the hypotheses that processing biases
would be found in symptomatic individuals only, across the six experimental categories
of words. In women, no evidence of attentional bias was found between groups; however
attentional bias was related to a range of body image and mood variables. Memory bias
was shown for negative appearance words, low calorie food words, and physical activity
words (lower recall). Again, memory bias was associated with a range of body image and
mood variables.
In men, attentional bias was found for negative emotion words and memory bias
was found for negative appearance words, negative emotion words, and low calorie food
words. However attention and memory bias was not consistently related the body image,
mood, and general well-being vulnerability factors. Although no differences emerged
between men and women for attention, memory, or number of errors, it is important to
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consider the different pattern of correlations between the cognitive and psycho-social
variables within each sex.
These findings were compared to previous research, however given the unique
nature of the study, and the number of refinements made over past research, direct
comparisons of the findings was difficult. The results were interpreted within the
theoretical approaches of the cognitive approaches of Vitousek and Hollon (1990),
Markus’ self schema theory (1977, 1987), and the applicability of the depression and
anxiety models of Williams et al. (1988a, 1997) and Beck (1967, 1991) was shown. It is
therefore concluded that the processing of certain types of body image information that is
personally relevant (Rogers et al., 1977) is driven by schemas (Markus, 1977, 1987;
Williamson et al., 2002; Vitousek & Hollon, 1990) but that schemas need to reach a
certain level of activation before they influence processing (Bower, 1981). Additionally,
the distinction noted between priming and elaboration noted in the anxiety literature
(Williams et al., 1988a, 1997) was also demonstrated for body image information.
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Chapter Ten: Overview, General Discussion, and Conclusions
10.1 Overview
The results from the current program of research have advanced our
understanding on the cognitive processing of body image and health related information
within the general community. Given the high rates of body dissatisfaction at both a
national and international level (Klemchuk, Hutchinson, & Frank, 1990), efforts to
understand factors associated in the maintenance of this problem are needed. The broad
aim of this project was to expand the literature on cognitive processes underlying body
image disturbance within males and females. Specifically, three phases of research were
undertaken to achieve this aim. In Phase One, a qualitative exploration was undertaken to
identify factors that males and females perceived as important components of their body
image. The outcome of this phase was an increased understanding of body image
concerns in non-clinical males and females. Factors identified as important determiners
of body image satisfaction were included as psycho-social variables in the Emotional
Stroop study (Phase Three). Phase Two involved the selection and careful matching of
an empirically supported set of stimuli to be used within an Emotional Stroop task. A
preliminary set of words was developed from a number of sources including past research
and based on the outcomes of Phase One. A study was undertaken to gather ratings on the
emotional valence, categorisation, and representativeness of the words. Words that
received the highest ratings on these categories were retained and matched to set of words
neutral in valance. This resulted in six categories of experimental words: positive
appearance / body shape words, negative appearance / body shape words, high calorie /
forbidden food words, low calorie food / non-forbidden words, negative emotion words,
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and physical activity words. In Phase Three, an Emotional Stroop task and incidental
memory task were developed. A national sample of women (N = 144) and men (N = 55)
from universities and the general community was recruited. This study was unique in
providing a multifaceted understanding of processing biases in males and females.
Overall, the results indicated that processing biases are found within the general
community, but are not always associated with negative functioning.
Detailed analyses of the results from each of the three phases of research have
been provided in previous chapters (Chapters Five, Six, Eight and Nine). Therefore, the
purpose of this final chapter is to provide an integration of the findings from each phase,
explore the theoretical and practical implications of these findings, and make suggestions
for future research.
10.2 Integration of Key Findings
The results from all phases of the current research indicate that body image
disturbance was a significant problem within the sample. Even though a clinical sample
was not sought, a substantial proportion of both males and females reported a range of
dysfunctional attitudes and behaviours such as appearance dissatisfaction, risky weight
management behaviours, and dietary restraint. Substantial evidence was also found of
processing biases within a non-clinical sample, however not all biased processing was
associated with negative body image. The findings point to the importance of considering
both attention and memory biases, given the widespread evidence of the later, but not the
former in the sample. In females, more interference for positive appearance words, low
calorie food words, and negative emotion words were associated with better functioning
on the psycho-social variables, and lack of risky weight management behaviours.
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Comparatively, quicker reaction times (or avoidance) of negative appearance words was
associated with poorer functioning on the psycho-social variables and engaging in
vomiting, fasting, and dieting to approve appearance. Interference on the food words was
not consistently associated with the psycho-social variables, and nor was attention for
physical activity words.
The women overall showed enhanced incidental memory for the negative
appearance words and low calorie food words, and lower recall of physical activity
words. Higher recall of the appearance words and low recall of negative emotion words
was associated with poorer mood and functioning. Higher recall of low calorie food
words was associated with better body image and self esteem, while higher recall of
physical activity words was associated with greater health and fitness. Recall of high
calorie food words was not consistently related to the psycho-social measures. This
relationship was not modified by sub-group, or engaging in risky behaviours.
Within the male sample, attentional bias was only noted for negative emotion
words, while memory bias was noted for negative emotion words, negative appearance
words, and low calorie food words. The general lack of associations between the psycho-
social variables, engaging in risky behaviours, and sub-group in association with the
cognitive variables suggests that processing biases in males are not linked to body image,
mood, or general well-being.
The sub-groups identified in both males and females support the non-
homogeneous nature of samples taken from the general community. While four distinct
groups emerged for females, and three groups for males, these groups did not consistently
differ on cognitive processing. At a mean level, a pattern emerged wherein increasing
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body image disturbance was associated with increasing interference effects, but these
differences did not reach significance. It may that the Emotional Stroop task was not
sensitive enough to detect the subtle differences in processing between these groups.
Most likely though that given the small mean differences a larger sample size would be
needed to provide enough power to detect a significant difference. This argument is
supported by the lower power levels reported in many of the analyses using the sub-
groups. Given the much larger sample size in the current study compared to past research,
the conclusion that past research has made that processing biases are not found within
non-clinical samples is called into question.
In the current study, a range of mood (depression, anxiety, and stress) and general
well-being variables (self esteem and social functioning) were included to expand our
understanding of the impact of cognitive biases beyond body image variables. Limited
associations were noted however between the cognitive and these psycho-social
measures. This suggests that within males and females from a non-clinical sample, body
image concerns are separate from general well-being. This may reflect the non-clinical
nature of the group, that is, any body image disturbance is kept compartmentalised, and
does not influence general feelings of worthiness as a person. This suggestion is
consistent with the findings of Tiggemann and Williamson (2000) that found the relation
between body dissatisfaction and self esteem was much stronger in women than in men.
This also provides an important implication regarding the distinction between clinical
samples. Perhaps one of the key distinctions between these two groups is how ‘far-
reaching’ are feelings of body dissatisfaction.
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These results were important is demonstrating that processing biases are found
within a non-clinical sample, and that not all biased attention and memory is indicative of
negative functioning. The theoretical implications of these findings are now explored.
10.3 Theoretical and Practical Implications
The results of this study were viewed within a number of theories that implicate
the role of schemas in biased processing. As there is much more information in the
environment available than can be processed at one point, a person must develop a way
of recognising and processing relevant information. It has been theorised that this
selective processing of information in one’s environment is guided by schemas. These
schemas guide processing based on information that is important to the person (Markus,
1977). That is, we notice in others what we hold important ourselves. For some
individual’s, increased importance placed on weight and appearance may serve to guide
their processing to this information when encountered. While all individuals’ hold
rudimentary schemas for appearance and weight, in some individual’s these schemas will
become highly associated with other facets of functioning (Markus, 1977, 1987;
Thompson et al., 1999; Vitousek & Hollon, 1990). Within this sample, evidence of the
general weight-related schemata was gained, that guides processing of information
relevant to cultural ideals and stereotypes associated with weight status (Vitousek &
Hollon, 1990). No evidence was found for weight-related self-schemata, however
Vitousek and Hollon (1990) note that this is restricted to those with clinical eating
disorders.
The lack of attentional bias within the current sample suggests that attentional
biases may not be stable within non-clinical groups, but are perhaps influenced by cues in
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the environment. For example, exposure to an attractive and thin model may activate
appearance and weight schemas. For those women who place a high importance on body
size and shape, this temporary activation may result in biased processing. These findings
suggest that body-related schemas must reach a critical level of activation before they
begin to affect processing. Unless these schemas are activated, through the use of primes,
they remain dormant and do not consistently affect processing of body-image and health
related material. The use of a prime prior to an Emotional Stroop task is an important
future research direction.
Schemas also drive biased memory (Vitousek & Hollon, 1990; Williams et al.,
1988a, 1997). Exposure to schema consistent material selectively directs processing and
increased elaboration for this information, making it disproportionately more available.
The pattern of findings suggests that processing biases within non-clinical samples are a
bias at the retrieval stage, rather than the encoding stage. This conclusion is limited in
past research that has only examined attention or memory, but not both. The model of
Williams et al (1988a, 1997) has particular importance to understanding the current
results. This model made the distinction between priming (encoding) and elaboration
(retrieval) and noted that one may occur in the absence of the other. In the current
sample, only consistent evidence of increased elaboration of the stimuli was found. This
suggests that processing biases are not automatic, but occurring at a later stage of
information processing (Faunce, 2002; Williams et al., 1988a, 1997), such as the memory
or elaboration stage, wherein strategic processing is used. Women and men in the sample
were able to distinguish between high and low calorie food words (showing biased
memory for only the latter), and also positive and negative appearance (again showing
Cognitive Bias and Body Image 202
biased memory for only the latter). This supports the notion made by Williams et al.
(1988a, 1997) that a pre-attentive decision mechanism selectively guides processing. This
is also consistent with Beck’s content specificity hypothesis (Beck & Clark, 1988) that
biased processing is restricted to self relevant information (Rogers et al., 1977), rather
than being pervasive.
These findings are also consistent with the work of Bower (1981) by showing that
emotional material grabs attention which interferes with task performance, supporting the
distinct way in which emotional information is processed. This may be related to a
survival mechanism wherein threatening information must be responded to rapidly. As
such, this material has a lowered threshold for awareness and the ability to interrupt on-
going activity (Sharma & McKenna, 2001). In today’s society, this ‘survival mechanism’
is on the look out for stimuli that signify being overweight and unattractive, and reflects
the current push in society for healthy eating.
Outcomes of this project are primarily theoretical. Researchers are limited in their
understanding of ‘abnormal’ if normal cognitive processing is not yet understood. This is
the first study to focus explicitly on understanding cognitive bias within non-clinical
samples. Additionally, the applicability of any research is guided by the strength of its
theoretical approach. This study used a strong theoretical background, in addition to a
number of significant methodological refinements, to improve our knowledge of how
body image information is processed.
These results also have important implications for understanding the maintenance
of emotional and eating disorders. Research shows that attentional bias takes time to
develop and also to eliminate (Williams & Nulty, 1986). For instance, these researchers
Cognitive Bias and Body Image 203
found that interference times were more related to previous depression status, than
recovery a year later. Inconsistent evidence is found for whether treatment changes
interference effects in eating disorders (Carter, Bulik, McIntosh, & Joyce, 2000; Cooper
& Fairburn, 1994). Interventions could aim to make positive constructs more available,
and focus on affect regulation as current mood has been shown to moderate attention for
negative information (Smith et al., 2006). This may help to reduce the chronic
accessibility of eating and weight related schemata in individuals with high levels of body
image disturbance.
The identification of empirically defined sub-groups may be useful at both
theoretical and practical levels. The identification of the these groups has helped to
advance the body image literature by demonstrating that non-clinical groups are not
homogeneous in nature, as is sometimes assumed in past research. A multidimensional
approach was taken in formation of groups by considering general well-being measures
in addition to the more typically used body image variables. According to Garner et al.
(1983), “the focus on a single symptom may obscure meaningful idiographic or subgroup
differences” (p. 18). Meaningful group differences emerged in the current study
highlighting how a combination of variables interact, rather than simply comparing
individuals who score high or low on one measure. This is the first study to compare such
groups on selective attention and memory.
At a practical level, knowledge of these groups will help at a descriptive level by
understanding the range of body image disturbance within non-clinical samples. A
number of researchers conceptualise Eating Disorders as occurring along a continuum
(e.g., Garner, Olmsted, & Garfinkel, 1983), with symptoms ranging from mild, moderate,
Cognitive Bias and Body Image 204
to severe. A much larger proportion of the population displays some Eating Disorder-like
symptoms rather than a ‘pure’ Eating Disorder (Drewnowski, Yee, Kurth, & Krahn,
1994), yet comparatively little research has examined the psychological characteristics of
non-clinical groups. The groups identified in the current study suggest both qualitative
and quantitative differences between the groups. An understanding of the distinction
between these groups may help to identify individuals who are ‘at risk’ or in the early
stages of the disorder. Given that milder cases generally respond better to treatment
(Garner et al., 1983), early detection is vital. In both the male and female sample from the
current study, large groups emerged that were characterised by high levels of body image
disturbance. Understanding the psychological make up of this group is the first step in
early detection.
Future research could compare these ‘dissatisfied’ groups to individuals classified
with Eating Disorders to improve our understanding of the progression to this disorder.
For example, an important distinction may be in how ‘far reaching’ the negative effects
of body dissatisfaction are. It has been shown that basing one’s self esteem around
feelings of attractiveness is associated with more dysfunctional eating behaviours (e.g.,
Wilksch & Wade, 2004).
An understanding of these classification issues will be helpful within health
psychology. Knowledge of the dietary and exercise behaviours and attitudes of the
general community will help public health campaigns to target their message more
efficiently. Further discussions around classification will aid the field of clinical
psychology in the treatment of eating and weight disorders, and the classification and
diagnosis of Eating Disorders. Currently, approximately one third of individuals with an
Cognitive Bias and Body Image 205
Eating Disorder are classified as Eating Disorder Not Otherwise Specified (Crow, Agras,
Halmi, Mitchell, & Kraemer, 2002). Increased descriptive information will lead to an
improved understanding and refinement of classifications, which should lead to
improvements in the treatment of body image disturbance (Sloan, Mizes, & Epstein,
2005).
10.4 Strengths, Limitations, and Suggestions for Future Research
10.4.1 Strengths of the Research
The innovative design of this project substantially adds to the current research in a
number of ways. Significant developments over previous research were made in two
main areas: sample characteristics, and methodological refinements.
10.4.1.1 Sample characteristics. This is the first study to explore processing
biases in males with stimuli specifically designed to reflect male body image. Few studies
have included male participants, and these studies have tested attention bias in males for
stimuli that largely represent female concerns. In the current study, lists of words were
developed that would be equally relevant to both males and females (e.g., “attractive”,
“muscular”). Further, no study to date has examined memory bias for body image and
health related information in males. Given the high incidence of male body image
disturbance (Pope et al., 2000), this represents a significant gap in the current literature.
Thus, this study substantially contributes to the knowledge regarding processing biases in
males.
Additionally, this study has also contributed to the existing literature by collecting
data from a large representative sample. Much of the past research examining processing
biases has used a small convenience sample of university students. This study has
Cognitive Bias and Body Image 206
gathered data from a large number of participants (198 in total), half of whom were
recruited from the general community. This sample increases the generalisability of the
findings.
Finally, participants in the current study were examined on a large number of
vulnerability factors. Past research has been criticised for simply comparing participants
high and low on a particular measure (Faunce, 2002). The outcomes of the qualitative
study in Phase one clearly indicated that body image is influenced by a multitude of
factors, even within a non-clinical sample. This is the first study to compare empirically
derived sub-groups on attention and memory bias. Although few differences emerged
between these groups, the recognition of the heterogeneous nature of “normal” women
and men need to be noted.
10.4.1.2 Methodological refinements. A number of significant methodological
refinements were included in the current study, based on limitations identified in past
research. In the current study, a more rigorous set of words were developed. This is the
first study that has included a category of physical activity words, and adds to the limited
research that has separated positive appearance from negative appearance words.
Similarly, it adds to the limited research that has examined low calorie food words and
negative emotion words. The importance of separating these word categories is evidenced
by the distinct pattern of processing biases associated with each of these categories. The
outcome from this phase of the research is an empirically selected set of words that future
research can utilise. One frequent criticism of previous Stroop research is the poor
selection of word stimuli (e.g., Dobson & Dozois, 2004; Faunce, 2002; Lee & Shafran,
2004). Particular attention needs to be paid to the lexical characteristics of words, as
Cognitive Bias and Body Image 207
shorter and more common words are responded to more rapidly that longer or less
common words (Larsen et al., 2006). Recently attempts have been made to standardise
lists of body image words (Cassin & von Ranson, 2005). While this list is an important
first step, more research is needed to develop a set of words that encompass multiple
facets of body image disturbance, and are applicable for males and females. The
outcomes of Phase Two are important in addressing this limitation.
This study also makes significant contributions to the memory bias literature. Few
studies have examined memory bias for body image and health information in men and
women from the general community. Many cognitive theories identify memory bias as
important in the maintenance of pathology (e.g., Williams et al., 1988, 1997; Vitousek &
Hollon, 1990). This the first study to date that has examined both attention and memory
bias for males and females using extensive word stimuli. An examination of attention,
memory, and error rates allows for an increased understanding of the full range of
processing biases, and links between biased attention and memory. Additionally, an
explicit memory task was used based on the recommendations of Russo et al. (2006),
who suggest this is a more sensitive measure of biased memory than a recognition test.
Given the limited research that has examined either implicit of explicit memory bias and
body image disturbance, more research is needed.
Based on problems identified in past research regarding the presentation of the
Stroop task, a computerised version was used. This allows for greater randomisation of
the words, and is a more sensitive measure of response time to each individual word.
Additionally, a button press response was used, based on problems with inaccurate
recording identified with voice response.
Cognitive Bias and Body Image 208
The refinements listed have been identified by other researchers are important
advancements in the use of the Emotional Stroop task (Dobson & Dozois, 2004; Faunce,
2002; Johansson et al., 2005; Lee & Shafran, 2004). Therefore, this study significantly
contributes to the current knowledge by exploring a wider range of processing biases in a
larger, more representative sample, using a more robust Emotional Stroop task. Despite
the numerous strengths of this study, some limitations should be noted.
10.4.2 Limitations of the Research
As with any study on body image, the somewhat sensitive nature of the topic may
have influenced the type of person who participated. Perhaps women who were
particularly concerned with their appearance avoided the study. However, discussions
with the participants suggested the opposite, particularly from the general community.
Women especially, were interested in the study because of their own struggles with body
image problems. Most participants knew the study was examining some aspect of body
image, however a cover story was provided for the first part of the task (cognitive
measures) to try and reduce demand characteristics. Participants were instructed that the
first task was simply looking at speed of information processing and reaction time.
However, it is granted that the knowledge that the study was examining body image may
have influenced their responses. This is not an easy issue to resolve, particularly when
calling for participants from the general community who are not used to the use of
deception in research. Discussions with the participants afterwards however, revealed that
they were unaware of the true purpose of the cognitive task. If participants were aware of
the nature of the study it would be expected that more interference effects and memory
bias would be found rather than the selective biases found in the current results.
Cognitive Bias and Body Image 209
Despite attempts to collect data from a representative sample, almost three times
as many women than men participated in the study. It remains unclear why this
discrepancy emerged. Perhaps women are simply more likely to take part in
psychological research than men. Additionally, very few men take psychology units in
Queensland and these units are a major source of recruitment. It should be noted
however, that 55 men were still recruited; a sample size that far exceeds that used in
similar past research.
An additional limitation of the current study may be the use of the same set of
word stimuli for males and females. Although the words were carefully selected to reflect
concerns relevant to both sexes (e.g., “attractive”, “ugly”, “gym”), it is granted that a
separate set of stimuli developed specifically for each sex may have been more sensitive
to detect processing biases. As some research has concluded that interference effects
relate to how personally relevant the material is to the person (Rogers et al., 1977;
Unterhalter et al., 2007), this warrants further research. However, the categories of words
used in the current study did produce processing biases, which provides support for their
relevance.
A limitation relevant to all Emotion Stroop studies is the objective versus
subjective frequency of words (Faunce, 2002). Words in the current study were carefully
matched on objective frequency of occurrence within the English language; however it is
acknowledged that subjective frequencies of body image words may be higher in some
groups. For example, dieters are bound to be exposed more to food words, and
individuals highly dissatisfied with their appearance will think more about negative
appearance. This is a difficult limitation to overcome. Future research needs to develop
Cognitive Bias and Body Image 210
more creative ways to test processing biases, such as colour naming pictures instead of
words (Ben-Tovim, Paddick, & McNamara, 1995).
A further limitation relates to the lexical equivalence of the words used. Larsen et
al (2006) have outlined the importance of lexical equivalence of word lists in Emotional
Stroop tasks. Word frequency and word length are noted as key factors in lexical decision
time, with less frequent or longer words taking longer to name then more frequent or
shorter words. Therefore, word frequency and word length influence word recognition,
which in turn affects naming speed. In the current study, attempts were made to control
the lexical equivalence of word lists by ensuring that all lists were matched on word
frequency and word length. However, while these control measures were implemented,
the lexical access of the word lists was not directly tested. Therefore, differences in
reaction times between the word lists may have been due to differences in word
recognition rather than emotional impact. While researchers typically use length and
frequency as indicators of word recognition, more research is needed to examine the
lexical characteristics of word lists in the Emotional Stroop task, particularly the use of
body image words.
Finally, the use of the Emotional Stroop task has been criticised by some (Faunce
& Job, 2000; Placanica et al., 2002), yet praised by others (MacLeod, 1992; Williams et
al., 1996). Many researchers acknowledge a number of conceptual and methodological
issues still to be addressed when using the Emotional Stroop task (Dobson & Dozois,
2004; Lee & Shafran, 2004). These researchers argue that alternate methodologies, such
as dot probe task, are a more sensitive method for the detection of processing biases.
Future research needs to explore the utility of both the Emotional Stroop and dot probe
Cognitive Bias and Body Image 211
task in more detail within the body image literature. Both tasks have been used more
extensively within the depression and anxiety literature and future research could benefit
from the application of the methodological refinements noted in this literature.
10.5 Summary of Chapter
The purpose of this final chapter was to understand the current research in a
broader sense by examining the theoretical and practical implications of the findings.
This research has substantially added to the existing literature on cognitive theories of
body image disturbance. Collectively, the results have expanded our understanding of
processing biases found in males and females from the general community. Using an
enhanced methodology it was demonstrated that some evidence of processing biases are
found within non-clinical samples, and that not all processing bias are associated with
negative functionality. This study is the first step in the development of a stronger
theoretical base from which intervention programs can be developed to reduce the
incidence of body image disturbance. A rigorous set of experimental procedures has been
developed that future research may utilise to help achieve this aim.
Cognitive Bias and Body Image 212
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Appendix A: Information and Consent forms used in the Qualitative Study of Phase One.
QUT Letterhead
Participant Information Sheet
“The application of a cognitive information processing approach to the understanding of body image and body image disturbance in non-clinical samples”
Ms Kate Mulgrew School of Psychology and Counselling Dr. Nathan Moss Queensland University of Technology Dr. Doug Mahar Beams Rd CARSELDINE 4034 Description
The purpose of this research is to asses what factors people think influence their body image, or physical attractiveness. This study is part of a larger project that is looking at the way people process information related to their bodies. We are interested in hearing from people from the general public. It doesn’t matter if you currently have, or have had, an eating or weight disorder of any kind. We would like to invite you to participate in this research. Your assistance would involve participating in two tasks. The first task is a semi-structured interview with the Chief Investigator (Kate Mulgrew). In the interview, you will be asked questions about what factors you think influence the way you view your body (for example, the media, friends, family etc.).This interview will take approximately 30-45 minutes. The second task involves rating a series of words. You will be provided with a list of words and asked to rate them on a few dimensions. This task is only expected to take about 20 minutes. Expected benefits
Although this project will not have any direct benefits for you personally, it is intended that the results will expand the current state of knowledge about body image in the general community. The incidence of body dissatisfaction is very high within Australia. It is hoped that the results from this study will help to inform treatment and intervention programs aimed at reducing the incidence of body dissatisfaction.
Risks
There are no risks associated with your participation in this project. This project has received ethical clearance from the Queensland University of Technology research office.
Confidentiality
You have a number of rights as a participant in this study. One of these is confidentiality. All responses will be kept completely confidential, and no one outside the research team will have access to the results. Any published material will be de-identified, meaning that there is no way that individual’s will be able to be identified from their responses.
Cognitive Bias and Body Image 238
Voluntary participation
Your participation in this project is completely voluntary. If you do agree to participate, you can withdraw from participation at any time during the project without comment or penalty, even if you have previously given your consent. Your decision as to whether to participate in this project will in no way impact upon your current or future relationship with QUT.
Questions / further information
If you should have any further questions about this project, or your participation in this project, the Chief Investigator (Kate Mulgrew) may be contacted via email: [email protected] or phone: 3864 4685.
Concerns / complaints
Please contact the Research Ethics Officer on 3864 2340 or [email protected] if you have any concerns or complaints about the ethical conduct of the project.
Thank you for your participation.
Cognitive Bias and Body Image 239
Participant Information Sheet
“The application of an information processing approach to the understanding of body image and body image disturbance in non-clinical samples”
Ms Kate Mulgrew School of Psychology and Counselling Dr. Nathan Moss Queensland University of Technology Dr. Doug Mahar Beams Rd CARSELDINE 4034
Statement of consent
By signing below, you are indicating that you:
• have read and understood the information sheet about this project; • have had any questions answered to your satisfaction; • understand that if you have any additional questions you can contact the research
team; • understand that you are free to withdraw at any time, without comment or penalty; • understand that you can contact the research team if you have any questions about
the project, or the Research Ethics Officer on 3864 2340 or [email protected] if you have concerns about the ethical conduct of the project;
• agree to participate in the project. Name
Signature
Date / /
Cognitive Bias and Body Image 240
Appendix B: List of Questions and Prompts for Interviews in Phase One.
Demographic information
Participants name:
Date of birth:
Highest level of education:
Country of Origin:
Topic 1: Participant’s definition of body image
Ask participants how they define body image.
Topic 2: Subjective assessment of their body image / body satisfaction
Ask how they would rate their body image / level of body satisfaction. Are they happy
with their bodies / appearance? How happy / unhappy?
Topic 3: Factors that influence their body image
Ask generally what factors they see as influencing their body image.
Ask what factors influence their physical appearance / weight satisfaction / body shape
satisfaction? (ie, make distinction between the various components of body image – link
to the components they mentioned in topic 1).
Prompts:
Media: television, magazines, advertising (billboards etc.)
Social support networks: friends, family, partner, children, siblings etc
Situations: e.g., tyring clothes on
Emotional states: e.g., when feeling sad about something else
Ask if there are times when these things don’t affect them. Or, are there times when they
affect them more.
Topic 4: Which factors are most influential in determining participant’s body image
Ask them to identify which of the previously mentioned factors are most influential in
affecting their body image. Identify top three.
Cognitive Bias and Body Image 241
Appendix C: Non-copyrighted questionnaires used in Phase Three.
Demographic form
1. Are you male or female (please circle)?
2. How old are you currently? ……………………………………………………
3. How tall are you? ………………………………………………………………
4. How much do you weigh? …………………………………………………….
5. Please indicate your highest and lowest adult weight:
Highest adult weight (excluding pregnancy)……………………………..
Lowest adult weight……………………………………………………….
6. What is the highest education that you have completed? ……………………..
7. What country were you born in? ………………………………………………
7a. If you weren’t born in Australia, how long have you been living here?
…………………………………………………………………………….
8. Which ethnic group would you most closely associate with? ………………………
9. Which best describes your marital status?
Single Married / de facto Dating
Divorced / Separated / Widowed Other (please specify) …………….
10. Have you ever been diagnosed with an eating disorder, or believed you had an eating
disorder? If yes, please give details on when this was, how old you were, the type of eating
disorder, treatment etc..
………………………………………………………………………………………………………
………………………………………………………………………………………………………
………………………………………………………………………………………………………
………………………………………………………………………………………………………
………………………………………………………………………………………………………
Cognitive Bias and Body Image 242
………………………………………………………………………………………………………
………………………………………………………………………………………………………
………………..
11. Do you have any medical conditions that would impact on your eating or weight? If yes,
please provide a brief explanation.
………………………………………………………………………………………………………
………………………………………………………………………………………………………
………………………………………………………………………………………………………
……………………………………………………………
12. Do you currently engage in any form of physical exercise? If yes:
What type of exercise do you do? ……………………………………………….
How long, on average, do you spend exercising in a typical week? ……………..
13. How hungry are you currently? Please indicate from one to five, where one = not at all hungry
and five = extremely hungry:
…………………………………
14. Please indicate in hours in minutes how long it has been since you last ate a full meal.
…………………………………
Cognitive Bias and Body Image 243
Cognitive Bias and Body Image 244
Appendix D: Information and Consent forms used in Phase Three.
PARTICIPANT INFORMATION for QUT RESEARCH PROJECT
“Colour perception, health, and speed of information processing”
Research Team Contacts
Ms Kate Mulgrew Dr. Nathan Moss (07) 3138 4881 (07) 3138 4660
[email protected] [email protected]
Description
This project is being undertaken as part of PhD project for Kate Mulgrew. The purpose of this project is to examine the factors involved with the perception of colour and how this effects reaction times. We are also interested in how your current health affects this relationship. The research team requests your assistance to take part in this study. Participation
Your participation in this project is voluntary. If you do agree to participate, you can withdraw from participation at any time during the project without comment or penalty. Your decision to participate will in no way impact upon your current or future relationship with QUT (for example your grades).
Your participation will involve a once off, 45 minute session, at a time convenient to you. The first set of tasks looks at speed of information processing, where you will be asked to respond as quickly as possible to various stimuli, and your reaction time will be recorded. The second task involves completing some standardized questionnaires about your current state of health. All data will be completely confidential, and your name will not be attached to any of your data. As the data is non-identifiable, it should be noted that it will not be possible to withdraw your data once submitted. Expected benefits
While the project may not benefit you directly, it is expected that the results from this study will be able to help others, and help researchers identify important factors in understanding reaction time, colour perception, and health. Risks
There are no risks beyond normal day-to-day living associated with your participation in this project.
QUT provides for limited free counselling for research participants of QUT projects, who may experience some distress as a result of their participation in the research. Should you wish to access this service please contact the Clinic Receptionist of the QUT Psychology Clinic on (07) 3138 4578. Please indicate to the receptionist that you are a research participant. Confidentiality
Cognitive Bias and Body Image 245
All comments and responses are anonymous and will be treated confidentially. The names of individual persons are not required in any of the responses. Consent to Participate
We would like to ask you to sign a written consent form (enclosed) to confirm your agreement to participate.
Questions / further information about the project
Please contact the researcher team members named above to have any questions answered or if you require further information about the project. Concerns / complaints regarding the conduct of the project
QUT is committed to researcher integrity and the ethical conduct of research projects. However, if you do have any concerns or complaints about the ethical conduct of the project you may contact the QUT Research Ethics Officer on (07) 3138 2340 or [email protected]. The Research Ethics Officer is not connected with the research project and can facilitate a resolution to your concern in an impartial manner.
Cognitive Bias and Body Image 246
CONSENT FORM for QUT RESEARCH PROJECT
“Colour perception and speed of information processing”
Statement of consent
By signing below, you are indicating that you:
• have read and understood the information document regarding this project
• have had any questions answered to your satisfaction
• understand that if you have any additional questions you can contact the research team
• understand that you are free to withdraw at any time, without comment or penalty
• understand that you can contact the Research Ethics Officer on (07) 3138 2340 or [email protected] if you have concerns about the ethical conduct of the project
• agree to participate in the project
Name
Signature
Date / /
Cognitive Bias and Body Image 247
Appendix E: Overview of cluster analytical technique and sub-group formation.
Overview of Cluster Analysis
Cluster analysis is a statistical technique applied to multivariate data designed to
identify homogenous sub-groups (Aldenderfer & Blashfield, 1984). Conceptually, it is
similar to factor analysis in that it searches for underlying latent variables. However, in a
cluster analysis, this procedure is applied to variables rather than individual cases. The
outcome of a cluster analysis is set of homogenous groups.
There are many different variants of cluster analysis, and the exact type of
methodology employed depends on the nature of the data and questions being asked.
Only a brief discussion of cluster analysis is provided here, but for a full discussion of
cluster analytical techniques the interested reader is directed to Aldenderder and
Blashfield (1984), Hair, Black, Babin, Anderson, and Tatham (2006) or Lange, Iverson,
Senior, and Chelune (2002). Based on the recommendations of these sources, a
hierarchical cluster analysis using an average linkage method and squared Euclidian
distance measure was used on standardised scores. This selection is briefly explained
below.
Consideration of the type of cluster analytical technique to use revealed that a
hierarchical cluster was most appropriate. A hierarchical cluster analysis is the most
commonly used technique within psychological research, and is particularly useful for
exploratory data analysis (Aldenderder & Blashfield, 1984; Hair et al., 2006; Lange et al.,
2002). A non-hierarchical analysis may be used when there is existing theoretical advice
on what sub-groups may form. Given the exploratory nature of the current research, a
hierarchical cluster analysis was deemed more appropriate. A hierarchical cluster analysis
Cognitive Bias and Body Image 248
works by forming groups in successive steps. At the first stage, each individual forms
their own cluster, thus the number of clusters equals the number of participants. The next
step of a hierarchical cluster groups together the two most similar cases into a cluster.
This process continues until there are N-1 clusters available. The relative ease of
interpretation of this method (the user is not required to possess knowledge of advanced
multivariate statistics) is accompanied however, by two disadvantages. Despite a number
of recommendations from researchers (e.g., Aldenderder & Blashfield, 1984; Hair et al.,
2006; Lange et al., 2002), there is no clear method of determining how many meaningful
clusters exist. Second, only one pass of the data is made, meaning that an individual case
remains in the cluster it was first assigned to (some type of cluster analysis make multiple
passes of the data). However, despite these limitations, hierarchical cluster analysis has
been noted as a useful exploratory technique (Lange et al., 2002). Given the potential
problems with this method, Lange et al recommend a two-stage approach wherein a
hierarchical cluster is run to ascertain how many clusters exist in the data, followed by
another type of cluster analysis known as a k-means cluster, where the user is able to
specify the number of clusters to emerge, and goodness-of-fit measures can be examined.
A researcher must also decide upon an appropriate algorithm to assign the
individuals to their respective clusters. An average linkage method was deemed most
appropriate based on the recommendations of Lange et al. This method assigns new cases
based on the average distance from all individuals already in the cluster. The new case is
assigned to the cluster with the greatest similarity measure. The benefit of this method
over other clustering algorithms is that selection of cases into a cluster is not based on
extreme scores of any individual already within the cluster.
Cognitive Bias and Body Image 249
The selection of a proximity measure involves consideration of how the similarity
between cases and clusters is to be measured. A squared Euclidean distance measure was
used, which assesses how far points are away from each other. In addition, scores were
standardized to account for differences in magnitude between measures.
According to Aldenderder and Blashfield (1984) the use of external validation of
clusters serves to corroborate the cluster solution. If clusters differ significantly on other
key variables that were not originally used to generate the clusters, this adds support to
the distinction between sub-groups.
Based on these recommendations from the literature, a hierarchical cluster
analysis using an average linkage method and squared Euclidian distance measure was
used. It should be noted that the cluster analysis was used simply to provide some basic
empirical support for the types of sub-groups within the non-clinical sample. While it is
recognised that cluster analysis has a number of limitations, this procedure was deemed
more useful than simply comparing individuals on a median split, as past research has
typically done. Instead of defining groups by one variable, a cluster analysis allows for a
more comprehensive understanding, as multiple variables are taken into account.
Results of the Cluster Analysis for Women
Core body image concerns, as assessed by the BAQ were entered as six variables
into the cluster for the 143 women. Missing variables on the BAQ were replaced with the
mean of the respective sub-scale. In order to determine how many clusters were
meaningful, a number of indicators were examined. First, the dendrogram was examined
to determine where a ‘break’ in the clusters occur. This dendrogram shows the clustering
process from beginning to end. A large gap indicates that the distance between clusters
Cognitive Bias and Body Image 250
before merging is large (i.e., there is little similarity between them). Based on the
dendrogram, a two or three cluster solution appeared most applicable. The Icicle plot was
also examined to ensure that no clusters contained only a few individuals. Lange et al
recommend that any cluster containing fewer than 5% of the total cases should be
excluded. The two cluster solution split the sample into a large group (n = 90), and
slightly smaller group (n = 53). The three cluster solution further subdivided the latter
group, with a group with 36 cases, and a group with 17 cases. The four cluster solution
retained the groups with 36 cases and 17 cases, and then further subdivided the N = 90
group into a group with 62 cases and 28 cases. Thus, no groups contained less than 5% of
the sample.
The fusion coefficients in the agglomeration schedule were also examined. These
values reflect how similar the clusters are that have just been joined. A large increase in
the values indicates that two clusters have been merged that are relatively dissimilar (Hair
et al., 2006). Large increases were evident in the agglomeration coefficients between a 4
and a 3 cluster solution. Additionally, the fusion coefficients were plotted against the
number of clusters, which forms a graph similar to a scree plot found in a factor analysis.
As in factor analysis, the graph is examined for a ‘flattening’, which indicates that
clusters have been joined despite being dissimilar. Examination of the graph revealed a
flattening in the curve around the four cluster solution.
In order to examine the usefulness of a two, three or four cluster solution, scores
on key variables were examined for each cluster, within each cluster solution. A two
cluster solution appeared to split the sample into two groups that seemed to reflect a
Cognitive Bias and Body Image 251
‘dissatisfied’ and ‘non-dissatisfied’ group. Scores on each of the six sub-scales of the
BAQ are shown in Table A1 for the two cluster solution.
Table A.1
Means and Standard Deviations for BAQ Sub-Scales for a Two Cluster Solution in
Women.
Cluster 1 (n = 90) Cluster 2 (n = 53)
BAQ sub-scale M SD M SD
Attractiveness 14.54 2.08 12.24 2.39
Disparagement 12.98 2.72 20.72 3.31
Feeling fat 34.76 7.39 50.96 6.61
Salience 18.52 3.85 26.83 4.42
Lower body fatness 10.39 3.12 14.94 2.99
Strength / fitness 18.33 4.06 16.20 3.63
Compared to cluster one, cluster two contained women with lower feelings of
attractiveness, higher feelings of loathing of her body, and higher feelings of fatness and
lower body fatness. Additionally, these women in cluster two appeared to place more
importance on appearance in their lives, and report lower feelings of fitness. Thus, the
two cluster solution appears to identify those women with poorer body image attitudes.
The three cluster solution is shown in Table A2. This solution further divided the
previously identified cluster two into a further two sub-groups.
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Table A.2
Means and Standard Deviations for BAQ Sub-Scales for the Three Cluster Solution in
Women
Cluster 1
(n = 90)
Cluster 2
(n = 36)
Cluster 3
(n = 17)
BAQ sub-scale M SD M SD M SD
Attractiveness 14.54 2.08 11.52 2.13 13.76 2.25
Disparagement 12.98 2.72 20.67 3.14 20.82 3.76
Feeling fat 34.76 7.39 49.72 6.28 53.58 6.71
Salience 18.52 3.85 25.02 3.93 30.64 2.62
Lower body fatness 10.39 3.12 14.30 2.77 16.29 3.07
Strength / fitness 18.33 4.06 14.80 3.11 19.17 2.83
The three cluster solution appeared to identify a smaller group of women with
more dysfunctional body image attitudes. The differences between the groups reflected a
dimensional, rather than categorical approach, wherein each group reported increasing
body image concerns. Cluster one shows the least symptomatic scores on all subscales,
while Cluster Two reports moderate levels of body image disturbance, while scores in
Cluster Three represent the most dysfunctional profile.
Descriptive information for the four cluster solution is shown in Table A3. This
solution further subdivides the largest, asymptomatic group seen in previous solutions.
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Table A.3
Means and Standard Deviations for BAQ Sub-Scales for the Four Cluster Solution in
Women
Cluster 1
(n = 62)
Cluster 2
(n = 28)
Cluster 3
(n = 36)
Cluster 4
(n = 17)
BAQ sub-
scale
M SD M SD M SD M SD
Attractiveness 14.08 2.18 15.57 1.39 11.52 2.13 13.76 2.25
Disparagement 13.84 2.70 11.07 1.58 20.67 3.14 20.82 3.76
Feeling fat 35.65 7.18 32.79 7.59 49.72 6.28 53.58 6.71
Salience 19.14 3.56 17.14 4.17 25.02 3.93 30.64 2.62
Lower body
fatness
11.05 3.16 8.92 2.52 14.30 2.77 16.29 3.07
Strength /
fitness
16.41 3.09 22.60 2.31 14.80 3.11 19.17 2.83
Examination of the profiles within the four cluster solution revealed four distinct
groups. Cluster one and two show similar means on most of the BAQ subscales. These
groups are characterised by higher feelings of attractiveness, little loathing of one’s body,
low feelings of fatness and low importance of appearance in one’s life. Cluster one and
two differ however on Lower Body Fatness and Strength / Fitness, with Cluster two
showing higher feelings of strength and fitness and less feelings of lower body fatness.
Cluster three and four appear to reflect groups of women with highly dysfunctional body
Cognitive Bias and Body Image 254
image attitudes. In particular, the means in Cluster four are similar to, or more
dysfunctional, than the scores found in Anorexic samples (Ben-Tovim & Walker, 1992).
Based on the available evidence, the four cluster solution was deemed most
appropriate. The highly dysfunctional attitudes reported in cluster four appeared quite
distinct from the group of women with whom they were originally grouped with in the
two cluster solution. Within the three cluster solution, the scores of cluster four are
substantially higher than the other sub-groups, thus it appears important to consider this
group uniquely.
Based on these scores, cluster one and two appear to reflect a group with very
little body image concerns. The distinguishing features between cluster one and two are
the high reports of strength and focus on fitness (and perhaps corresponding lower body
fatness) within cluster two. Hence these clusters were named “normal” and “athletic”
respectively. Cluster three appears to reflect a group that experiences moderate level of
dissatisfaction, and were therefore labelled “dissatisfied”. Cluster four, having the most
dysfunctional profile closely representing scores of Eating Disordered samples, were
therefore labelled “symptomatic”.
One criticism of cluster analysis has been that the use of different cluster
techniques can result in alternate group formations (Aldenderder & Blashfield, 1984;
Hair et al., 2006; Lange et al., 2002). In an attempt to overcome this limitation, the cluster
analysis was re-run using a different algorithm. A Wards’ method was used, as some
researchers recommend the use of this algorithm (e.g., Francis, 2004). Using this Ward’s
method, a similar result emerged to the previously described cluster solution, supporting
the four cluster solution.
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Results of the Cluster Analysis for Men
The measure used for the cluster analysis in females, the BAQ, was developed
specifically to encompass women’s body image concerns, thus it was not deemed useful
to categorise males. Instead, the MBSRQ was used. A full description of the MBSRQ
was given in the Stroop Method section. Briefly, the MBSRQ is one of the few
measurement tools available that adequately assess a wide variety of male body image
concerns. Additionally, this scale reports excellent psychometric properties, and
normative data is available. Six subscales of the MBSRQ were used in the cluster
analysis for males: the Appearance Evaluation and Orientation subscales, the Fitness
Evaluation and Orientation subscales, the Health Orientation subscale, and the
Overweight Preoccupation Subscale. These subscales were selected to cover feelings of
attractiveness, general health and fitness, importance placed on appearance and fitness,
and dietary restraint; key variables that emerged in the qualitative study of Phase One. As
cluster analysis requires a complete data set, missing data was replaced with the mean of
the subscale.
Core body image concerns, as measured by the six subscales of the MBSRQ, were
entered for the 54 men. A hierarchical cluster analysis using a Ward’s Method and
squared Euclidian distance measure was run on standardised scores. In order to determine
how many clusters were meaningful, a number of indicators were examined. Inspection
of the agglomeration schedule and the dendrogram revealed that a two or a three cluster
solution appeared most applicable, based on the change in the similarity scores between
the clusters. The Icicle plot was examined to ensure that no cluster contained fewer than
Cognitive Bias and Body Image 256
5% of the total cases. This started to occur with a four cluster solution, where only two
cases comprised a cluster.
In order to examine how meaningful the two and three cluster solutions were,
scores on the six subscales of the MBSRQ were examined. The two cluster solution
appeared to divide the sample into a larger group with better body image, and a smaller
group with poorer body image. Compared to cluster two, cluster one reported higher
satisfaction, but lower investment, with appearance; higher feelings of fitness and
importance placed on being fit; lower fat anxiety; and higher feelings of being healthy.
Scores on each of the MBSRQ subscales are shown below in Table A4.
Table A.4
Means and Standard Deviations for the MBSRQ Sub-Scales for a Two Cluster Solution in
Males
Cluster 1
(n = 35)
Cluster 2
(n = 19)
MBSRQ subscale M SD M SD
Appearance Evaluation 3.76 0.52 2.52 0.57
Appearance Orientation 3.03 0.66 3.40 0.64
Fitness Evaluation 4.17 0.56 3.47 0.78
Fitness Orientation 3.51 0.83 3.16 0.42
Overweight Preoccupation 1.66 0.67 2.46 0.80
Health Orientation 3.55 0.79 3.12 0.77
Cognitive Bias and Body Image 257
The means for the MBSRQ subscales are shown in Table A5 for the three cluster
solution. The three cluster solution kept the n = 19 group with poorer body image, but
further subdivided the larger group.
Table A.5
Means and Standard Deviations for the MBSRQ Sub-Scales for a Three Cluster Solution
in Males
Cluster 1
(n = 26)
Cluster 2
(n = 19)
Cluster 3
(n = 9)
MBSRQ subscale M SD M SD M SD
Appearance Evaluation 3.69 0.55 2.52 0.57 3.97 0.37
Appearance Orientation 2.85 0.51 3.40 0.64 3.54 0.78
Fitness Evaluation 4.06 0.55 3.47 0.78 4.48 0.50
Fitness Orientation 3.22 0.76 3.16 0.42 4.35 0.32
Overweight Preoccupation 1.34 0.33 2.46 0.80 2.58 0.53
Health Orientation 3.33 0.74 3.12 0.77 4.18 0.58
The three cluster solution appeared to identify a smaller group of men who could
be described as extremely driven by health and fitness. Compared to the n = 26 cluster
they were originally grouped with, this n = 9 cluster reported similar feelings of
attractiveness, but a much larger importance and investment placed on appearance. This
group also reported higher feelings of fitness, and placed more importance on regular
exercise. They report the highest levels of fat anxiety, and highest levels of being health
Cognitive Bias and Body Image 258
conscious. That is, this group appears to reflect men who are engaging in a health
lifestyle, and feel good because of it, but are also concerned about becoming overweight.
Given how distinct this small cluster was that emerged in the three cluster
solution, it was deemed useful to examine this group separately. To check the validity of
this cluster solution, the cluster analysis was re-run with an alternate clustering method
(between groups). The results of this cluster analysis revealed a similar solution, but the
group differentiation was not as clear compared to using the Ward’s method. Ultimately,
the purpose of a cluster analysis was to provide some empirical support for group
comparisons. Thus, the three cluster solution using the Ward’s method was used.