AN EXAMINATION OF ATTENTIONAL BIAS FOR THREAT IN MOTOR VEHICLE ACCIDENT SURVIVORS WITH POSTTRAUMATIC STRESS

DISORDER

A Thesis

Submitted to the Faculty of Graduate Studies and Research

In Partial Fulfillment of the Requirements

For the Degree of

Master of Arts

in

Clinical Psychology

University of Regina

By

Sophie Duranceau

Regina, Saskatchewan

July, 2014

© Copyright 2014: S. Duranceau

UNIVERSITY OF REGINA

FACULTY OF GRADUATE STUDIES AND RESEARCH

SUPERVISORY AND EXAMINING COMMITTEE

Sophie Duranceau, candidate for the degree of Master of Arts in Clinical Psychology, has presented a thesis titled, An Examination of Attentional Bias for Threat in a Motor Vehicle Accident Survivors with Posttraumatic Stress Disorder, in an oral examination held on Friday, July 11, 2014. The following committee members have found the thesis acceptable in form and content, and that the candidate demonstrated satisfactory knowledge of the subject material. External Examiner: *Dr. Bradley C. Riemann, Rogers Memorial Hospital

Co-Supervisor: Dr. R. Nicholas Carleton, Department of Psychology

Co-Supervisor: **Dr. Gordon J. G. Asmundson, Department of Psychology

Committee Member: Dr. Christopher Oriet, Department of Psychology

Chair of Defense: Dr. Larena Hoeber, Faculty of Kineiology & Health Studies *via tele-conference **Not Present at defense

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Abstract

Theoretical models of anxiety suggest that cognitive vulnerabilities are involved

in the development and maintenance of posttraumatic stress disorder (PTSD; Elwood,

Hahn, Olatunji, & Williams, 2009). Attentional bias for threat has been identified as a

cognitive vulnerability which may facilitate the development and maintenance of PTSD

(Bomyea, Risbrough, & Lang, 2012). Several cognitive tasks have previously been used

to assess attentional bias for threat in anxiety pathologies (i.e., emotional Stroop task,

visual search task, dot probe task). The proposed investigation was designed to assess the

directionality (i.e., facilitated attention, difficulty in disengagement, avoidance) and time-

course of attentional bias for threat in motor vehicle accident (MVA) survivors using a

contemporary dot probe task. Participants included MVA survivors with high PTSD

symptoms (n = 18), MVA survivors with low PTSD symptoms (n = 46), and a control

group with no history of MVA or PTSD (n = 64) recruited across North America. Results

suggest that MVA survivors reporting high PTSD symptoms display a different

attentional pattern than individuals without such symptoms during the early stages of

cognitive processing. Specifically, MVA survivors with high PTSD symptoms 1) easily

disengage their attention from MVA-related threat and, contrary to individuals without

PTSD symptoms, 2) fail to engage with generally threatening stimuli. A lack of

engagement with threatening stimuli could interfere with the processing and re-appraisal

of threat, in turn contributing to the exacerbation of PTSD symptoms. Attention bias

modification programs could be useful for the treatment of PTSD. Comprehensive

results, methodological considerations, implications, and future research are discussed.

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Acknowledgements

First and foremost, I would like to thank my supervisor, R. Nicholas Carleton, for

his unconditional support, understanding, and guidance. His feedback has been

invaluable to me and without his encouragements I could not have come this far.

He has been an ideal supervisor and I look forward to pursuing my learning under his

mentorship. Second, I would like to thank my co-supervisor Dr. Gordon J. G. Asmundson

for his invaluable input and expertise. His commitment to research and, most of all,

work-life balance never ceases to amaze me. Last but not least, I would like to thank my

research committee, Drs. Chris Oriet and Brad Riemann. Through their insights,

recommendations, and support, they have all contributed to making me a better

researcher.

I am also grateful of the time and effort participants have put into completing my

study. Without their help, this research would not have been possible. I am extremely

grateful for the funding provided to me by so many sources. This project was supported

in part by a Social Sciences and Humanities Research Council of Canada Joseph-Armand

Bombardier CGS Master’s Scholarship (766-2012-0269) and a Bourse de maîtrise en

recherche B1 from the Fonds de Recherche du Québec – Société et Culture (167131).

I was also fortunate to receive scholarship funding from the Faculty of Graduate Studies

and Research, the Department of Psychology, and Dr. Carleton.

Special thanks to “the cohort” and my friends and family for their unconditional

support through graduate school. I would never have come this far without their help.

Finally, I would like to thank my partner, Simon Pelletier. Not once did he stop believing

in me…even during those handless hours spent making Excel tables together.

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Table of Contents

Abstract ................................................................................................................................ i

Acknowledgements ............................................................................................................. ii

Table of Contents ............................................................................................................... iii

List of Tables ..................................................................................................................... vi

List of Figures ................................................................................................................... vii

List of Appendices ........................................................................................................... viii

1.0 Literature Review...........................................................................................................1

1.1 Posttraumatic Stress Disorder ....................................................................................1

1.1.1 General History....................................................................................................1

1.1.2 Diagnostic History ...............................................................................................2

1.1.3 Vulnerabilities to Posttraumatic Stress Disorder .................................................6

1.2 Theoretical Framework of Attentional Bias for Threat in Anxiety Disorders ...........9

1.2.1 Beck and Clark’s Cognitive Model .....................................................................9

1.2.2 Cisler and Koster’s Integrative Framework of Attentional Bias for Threat ......13

1.3 Attentional Bias in Posttraumatic Stress Disorder ...................................................18

1.3.1 Emotional Stroop Task ......................................................................................18

1.3.2 Visual Search Task ............................................................................................22

1.3.3 Dot Probe Task ..................................................................................................24

1.4 Current Investigation, Purposes, and Hypotheses ...................................................27

1.4.1 Purposes .............................................................................................................28

1.4.2 Hypotheses .........................................................................................................29

2.0 Method .........................................................................................................................30

2.1 Environment .............................................................................................................30

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2.2 Recruitment ..............................................................................................................30

2.3 Participants ...............................................................................................................31

2.4 Measures...................................................................................................................32

2.4.1 Demographic Measures .....................................................................................32

2.4.2 Standardized Measures ......................................................................................32

2.4.3 Dot Probe Task .................................................................................................35

2.5 Procedure ..................................................................................................................37

2.6 Analyses ...................................................................................................................38

2.6.1 PTSD Status .......................................................................................................38

2.6.2 Preparation of Reaction Time Data ....................................................................38

2.6.3 Analyses .............................................................................................................40

3.0 Results ..........................................................................................................................41

3.1 Main Hypotheses ......................................................................................................42

3.2 Exploratory post hoc Analyses ................................................................................51

4.0 Discussion ....................................................................................................................55

4.1 Time Course of Attentional Biases for Threat .........................................................55

4.2 Group Differences in Attentional Bias ....................................................................61

4.3 Group Differences in Attentional Pattern ................................................................64

4.4 Methodological Implications ...................................................................................66

4.5 Clinical Implications ...............................................................................................68

4.6 Limitations and Future Directions ...........................................................................69

4.7 Conclusions ..............................................................................................................72

References ..........................................................................................................................74

Footnotes ............................................................................................................................99

v

Appendices .......................................................................................................................100

vi

List of Tables

Table 1. Participant Demographic Information as a Function of Group ...........................43

Table 2. Traumatic Events Endorsed and Event Referenced as the Most Traumatic as a

Function of Group ..............................................................................................................44

Table 3. Self-report Measures Mean Score as a Function of Group ..................................45

Table 4. Summary of Intercorrelations for Scores on the STAI, ACS, ERQ, and the

Orienting and Disengaging Indices for the Control Group ................................................47

Table 5. Summary of Intercorrelations for Scores on the STAI, ACS, ERQ, and the

Orienting and Disengaging Indices for the MVA-Low PTSD Symptoms Group .............48

Table 6. Summary of Intercorrelations for Scores on the STAI, ACS, ERQ, and the

Orienting and Disengaging Indices for the MVA-High PTSD Symptoms Group ............49

Table 7. Mean Orienting and Disengaging Indices as a Function of Group and Trial Type

............................................................................................................................................50

Table 8. Mean Non-Indexed Dot Probe Reaction Times as a Function of Group and Trial Type ..................................................................................................................................52

Table 9. Mean Traditional Bias Index as a Function of Group and Trial Type .................54

vii

List of Figures

Figure 1. Integrative Framework of Attentional Bias for Threat .......................................14

Figure 2. Mean Disengagement Bias Index at 100 ms SOA as a Function of Group Assignment and Threat Level ............................................................................................56

viii

List of Appendices

Appendix A. Demographic Measures ..............................................................................101

Appendix B. Attentional Control Scale ...........................................................................103

Appendix C. Alcohol Use Disorders Identification Test .................................................105

Appendix D. Emotion Regulation Questionnaire ............................................................107

Appendix E. Posttraumatic Stress Checklist-Stressor Specific Version ..........................108

Appendix F. Word List ....................................................................................................110

Appendix G. University of Regina Research Ethics Board Ethical Approval Forms .....111

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1.0 Literature Review

The present investigation was designed to assess the directionality and time

course of cognitive attentional bias for threat in motor vehicle accident (MVA) survivors

with Posttraumatic Stress Disorder (PTSD) symptoms using a contemporary dot probe

paradigm. First, the development of PTSD as a recognized psychological disorder will be

discussed. Second, an overview of the theoretical framework underlying attentional bias

for threat in anxiety disorders will be presented, including Cisler and Koster’s recent

integrative framework. Third, the discussion will focus on a review of the literature on

attentional bias for threat in PTSD and in MVA survivors more specifically. Findings

pertaining to attentional bias for threat in PTSD will be discussed in relation to the model

proposed by Cisler and Koster. Theoretical models of attentional bias for threat and past

empirical findings support the current investigation, including the methods and analyses.

Fourth, findings from the current investigation and their implications for future research

will be discussed in the context of research and clinical practice.

Wars begin when you will but they do not end when you please.

Niccolò Machiavelli, 1532 1.1. Posttraumatic Stress Disorder

1.1.1 General History

Written five centuries ago, Machiavelli's work offers observations of the political

and social landscape during Renaissance Italy. Unbeknownst to the author, his words also

underscore the lasting impact a traumatic event such as war may have on an individual.

The word “trauma” finds its origin in the ancient Greek word “wound” (Liddell & Scott,

1999) and initial accounts of traumatic stress symptoms can be found as early as in the

Antiquity literature. For five millennia, testimonies of wars and great civilian

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catastrophes have come with descriptions of traumatic stress symptoms such as intrusive

recollections of the event and the inability to find sleep (Birmes, Hatton, Brunet, &

Schmitt, 2003; Homère, 1975; Pepys, 1994; Trimble, 1981). Despite repeated reports of

traumatic stress symptoms in the literature, a nosology of trauma-related psychological

disorders only emerged in the 19th century.

In 1892, Oppenheim coined the term “Traumatischen Neurosen” to describe the

irritable mood and nightmares produced by a shaken nervous system following a railway

accident (Kraepelin, 1896). In 1896, Kraepelin renamed such a condition

“Schreckneurose” or “fright neurosis” and was the first to recognize that serious

accidents or injuries can lead to an independent clinical condition with an emotional

rather than a physical etiology (Kraepelin, 1896). Grinker and Spiegel (1945) later wrote

about the many problems that awaited a returnee from World War II with “combat

neuroses,” namely depression, agitation, sympathetic overactivity, difficulty

concentrating, and suspicion. In the same book, the authors noted that the symptoms

experienced by soldiers with combat neuroses mirrored the symptoms presented by any

man who failed to adapt to a stressful environment. A year later, Hans Selye introduced

the notion of the pituitary-adrenocortical response to stress and exposed that chronic

activation of the physical stress response could produce a “disease of adaptation” (Selye,

1950). For the first time, it was recognized that psychological symptoms which present

following a stressful event may be associated with the physiological response to stress.

1.1.2 Diagnostic History

The end of World War II fueled the dissemination of knowledge between the

American and the European scientific communities. A consensus quickly emerged

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regarding the need for a standardization of mental health disorders and the first

Diagnostic and Statistical Manual of Mental Disorders was published in 1952 (DSM-I;

American Psychological Association [APA], 1952). “Gross Stress Reaction” was

incorporated within the “Transient Situational Personality Disorders” category of DSM-I

and identified as an acute distress response (e.g., nightmares, increased arousal,

irritability) to extreme physical demand or emotional stress, such as in war combat or in a

civilian catastrophe (e.g., fire, earthquake, explosion; Wilson, 1994). Given the transient

nature of Gross Stress Reaction, persistence of symptoms was taken as a sign of a more

severe predispositional disturbance (i.e., neurosis and psychosis; Wilson, 1994).

The second installment of the DSM (DSM-II; APA, 1968) sustained a similar

view and “Adjustment Reaction of Adult Life” as a Transient Situational Personality

Disorder replaced Gross Stress Reaction in DSM-II. The provisional nature of

Adjustment Reaction of Adult Life was reiterated and a list of life stressors was provided

in appendices (e.g., motor vehicle accidents, railway accidents, water transport accidents,

air transport accidents; Wilson, 1994). The early classifications of DSM-I and DSM-II

rendered normal the short-term psychological symptoms experienced following an

extreme life stressor; however, due to the longer lasting nature of their symptoms,

veterans of the Vietnam War were still being diagnosed with schizophrenia and other

psychotic disorders (Ozer, Best, Lipsey, & Weiss, 2003). Accordingly, a new

classification was required to account for the continuing psychological distress

experienced by some individuals following trauma exposure.

By the early 1970s, Vietnam’s battlefields had become increasingly violent and

unpredictable (Honzell, 2008). Many veterans returned to the United States and reported

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experiencing recurrent nightmares, flashbacks, numbing of emotions, social withdrawal,

and hyperarousal to stimuli in the environment (Ozer et al., 2003). Around the same time,

a nurse at Boston City Hospital witnessed signs of re-experiencing, avoidance, and

hyperarousal in women who were sexually assaulted. Such a collection of symptoms was

recognized as “rape trauma syndrome” (Burgess & Holmstrom, 1974). The three distinct

clusters of symptoms (i.e., re-experiencing, avoidance/numbing, and hyperarousal)

experienced in “rape trauma syndrome” became Criterion B, C, and D respectively for

the DSM-III (APA, 1980) diagnosis of PTSD. Contrary to Gross Stress Reaction and

Adjustment Disorder of Adult Life, PTSD was recognized as a persistent psychological

condition caused by a traumatic event and was classified as an Anxiety Disorder.

DSM-III divided PTSD into five different criteria, all of which were necessary to

meet PTSD diagnosis. Notably, Criterion A stipulated that the traumatic event had to be

one that would cause distress in almost everyone. By recognizing that certain

extraordinary stressors could produce traumatic reactions in almost everyone, DSM-III

recognized certain traumatic reactions as appropriate, contrary to DSM-I and DSM-II

(Lifton, 1988). Rather than being caused by an individual predisposition, PTSD was

perceived as the consequence of normal feelings and behaviors that persisted long after a

traumatic event and lead to maladaptive functioning (Wilson, 1994). Such a view was

maintained in the revised version of the DSM-III installment (DSM-III-R; APA, 1987)

and the diagnostic criteria for PTSD were further clarified. Criterion A made an explicit

reference to the experiencing of traumatic events outside the range of normal human

experience (e.g., physical life threat, threat to psychological well-being, and disaster of

natural or human origin) and was extended to individuals hearing about such threats to

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significant others, or witnessing such traumatic events. The notion of delayed onset of the

disorder−when symptoms begin more than six months after the experience of a traumatic

event−also emerged for the first time.

Research and clinical knowledge about PTSD rapidly highlighted the fact that

many potentially traumatic stressors did not meet the DSM-III-R prerequisite of falling

outside the range of normal human experience (Spitzer, First, & Wakefield, 2007). As a

result, further changes to the PTSD diagnosis were made in the DSM-IV (APA, 1994).

Criterion A was divided into two components. Criterion A1 required the individual to

have experienced, witnessed, or been confronted with actual or threatened death or

serious injury, or threat to the physical integrity of oneself or others and resembled the

original concept of gross stress found in DSM-I (Spitzer et al., 2007). Criterion A2

specified that horror, fear, and helplessness must be experienced in response to the

traumatic event. Criteria B (re-experiencing symptoms), C (avoidance/numbing

symptoms), D (hyperarousal symptoms), and E (timeframe requirements) remained

relatively unchanged but a sixth criterion was added to the disorder. Criterion F required

that symptoms presented in criteria B, C, and D cause significant distress and impairment

in occupational, social or other aspects of functioning. The changes to DSM-IV were

accompanied by a distinction between acute and chronic PTSD. Acute PTSD referred to

the presence of symptoms for less than 3 months, after which point chronic PTSD could

be diagnosed.

The diagnosis of PTSD did not undergo any significant changes in the revised

version of DSM-IV (DSM-IV-TR; APA, 2000); however, PTSD as defined by DSM-IV-

TR was debated within the scientific community. The existence of the disorder itself has

6

been called into question (Scott, 1990; Summerfield, 2001; Young, 1995). The question

was supported by evidence that patients can display several symptoms consistent with

PTSD without experiencing a traumatic event (Bodkin, Pope, Detke, & Hudson, 2007;

Gold, Marx, Soler-Baillo, & Sloan, 2005; Mol et al., 2005), underscoring the non-

specificity of PTSD symptoms (McHugh & Treisman, 2007).

The recent publication of DSM-5 led to further changes to the diagnosis (APA,

2013). Criterion A had been qualified as vague, unreliable (Spitzer et al., 2007), and as

facilitating "conceptual bracket creep" (McNally, 2003); accordingly, it became more

explicit in DSM-5 and Criterion A2 was dropped (APA, 2013). Avoidance and numbing

symptoms have been consistently shown to represent two distinct symptom clusters (e.g.,

Asmundson, Stapleton, & Taylor, 2004; Asmundson et al., 2000) and are considered as

such in the DSM-5, with numbing symptoms being identified as “negative alterations in

cognitions and mood” (APA, 2013). The distinction between Acute and Chronic PTSD

was removed and a specifier was added for individuals presenting with high levels of

dissociative symptoms (i.e., depersonalization, derealization). Finally, PTSD was re-

categorized as a Trauma- and Stressor-related Disorder rather than as an Anxiety

Disorder (APA, 2013), even though PTSD remains highly correlated with anxiety

disorders (e.g., Ginzburg, Ein-Dor, & Solomon, 2010) and shares common vulnerability

factors with such disorders (e.g., Bomyea, Risbrough, & Lang, 2012).

1.1.3 Vulnerabilities to Posttraumatic Stress Disorder

Approximately 90% of individuals in the general population will experience a

traumatic event during their lifetime and men are 1.2 times more likely than women to be

exposed to such an event (Breslau et al., 1998). In the general population, the most

7

prevalent traumatic events encountered include death of a close friend or a loved one

(60%), violent assault (38%), MVAs (28%), and natural disasters (13%; Breslau et al.,

1998). Estimates suggest that 9.2% of individuals who experience such events will meet

full criteria for PTSD (Breslau et al., 1998). The discrepancy between the prevalence of

traumatic event exposure and the prevalence of PTSD suggests that individual differences

prior to, during, and following trauma exposure may play an important role in the

development of the disorder. Women appear to be twice as likely as men to develop

PTSD following trauma exposure (Kessler, Sonnega, Bromet, Hughes, & Nelson, 1995)

and the difference remains even after controlling for the type of traumatic event

experienced (Breslau, Chilcoat, Kessler, Peterson, & Lucia, 1999). Being from an ethnic

minority group has also been identified as a vulnerability for the development of PTSD

(Kessler et al., 1995), although ethnic differences may result from a larger proportion of

ethnic minorities being from lower socioeconomic status and less educated, two

vulnerabilities for PTSD (Brewin, Andrews, & Valentine, 2000). In line with twin studies

suggesting that genetic factors account for approximately 30% of the risk of developing

PTSD (Koenen, Nugent, & Amstadter, 2008; Koenen, Fu, et al., 2008), the personality

trait of neuroticism (Paris, 2000) and family history of psychopathology (Keane, Marx, &

Sloan, 2009) have been identified as vulnerability factors present prior to the occurrence

of a traumatic event. During trauma, peritraumatic emotional response (e.g., fear,

helplessness, horror, guilt, and shame) and peritraumatic dissociation (e.g., altered sense

of time, “blanking out”, and feeling disconnected from one’s body) both confer an added

risk of developing PTSD (Keane et al., 2009). Following trauma, lack of social support

8

further increases the likelihood of developing PTSD (e.g., Brewin et al., 2000; Keane et

al., 2009).

Some predispositional variables (e.g., sex, ethnicity, family history of

psychopathology) cannot readily be modified; however, cognitive risk factors may be

altered (e.g., Barlow, 2008). Cognitive models of PTSD suggest that individuals

developing PTSD present cognitive vulnerabilities defined as biases regarding the

probability of threat in the outside world (Elwood, Hahn, Olatunji, & Williams, 2009).

Cognitive vulnerabilities which have been implicated in the development and

maintenance of PTSD include, but are not limited to, a negative attributional style,

rumination, anxiety sensitivity, and a looming cognitive style (Elwood et al., 2009) which

can manifest itself through an attention bias for threat (Bomyea et al., 2012). Attentional

bias for threat–an asymmetrical distribution of attentional resources towards threatening

stimuli in the environment–has been implicated as a general vulnerability factor for

anxiety disorders (e.g., Bar-Haim, Lamy, Pergamin, Bakermans-Kranenburg, & van

IJzendoorn, 2007) and specifically for PTSD (Beevers, Lee, Wells, Ellis, & Telch, 2011;

Bomyea et al., 2012). The anxiety disorders literature consistently supports the existence

of a moderate attentional bias for threat in anxiety pathologies; however, the theoretical

framework underlying this bias is subject to ongoing research and debate (Bar-Haim et

al., 2007). In an attempt to clarify the nature of attentional bias for threat in anxiety

disorders, cognitive models of attentional bias for threat have been developed over the

past 25 years (e.g., Beck, Emery, & Greenberg, 1985; Eysenck, 1992; Wells & Matthews,

1994; Williams, Watts, MacLeod, & Mathews, 1988). Such models can be used as a

9

foundation to better understand the relationship that exists between attentional bias for

threat and PTSD.

1.2. Theoretical Framework of Attentional Bias for Threat in Anxiety Disorders

1.2.1. Beck and Clark’s Cognitive Model

The earliest theoretical model of attentional bias for threat in anxiety disorders

was developed almost 25 years ago (Beck et al., 1985) and later refined (Beck & Clark,

1997). In this three-stage information processing model, pathological anxiety is the

product of overestimating the threatening nature of stimuli in the environment and

underestimating one’s own coping abilities (Beck et al., 1985), leading to inaccurate

interpretations of external stimuli during the different stages of the information

processing sequence. The first stage, the orienting mode, is primarily one of automatic

processing (Beck, 1996). Automaticity is characterized by rapid, effortless, and primarily

unconscious processing requiring minimal higher-order capacity (Logan, 1988; McNally,

1995). During this stage, stimulus features are rapidly processed in order to identify

potentially threatening situations (Beck et al., 1985). In the context of threat, such early

and pre-attentive analysis solely seeks to classify stimuli in terms of emotionality (i.e.,

negative, positive, neutral) and relevance (i.e., personally relevant vs. irrelevant; Beck &

Clark, 1997). Demonstrations from investigations using subliminal presentations of

stimuli show that, in anxious individuals, the orienting mode has a propensity to detect

and allocate attentional resources to negative and personally relevant stimuli (Bradley,

Mogg, Millar, & White, 1995; Mogg, Bradley, Williams, & Mathews, 1993).

The identification of personally relevant negative stimuli activates the second

stage of information processing, also referred to as the primal threat mode (Beck, 1996).

The primal threat mode encompasses an array of rigid and reflective schemas ensuring

10

evolutionary survival; however, controlled processing begins to emerge during this stage

and allows for the interpretation of novel or complex situations (Beck & Clark, 1997).

The primal threat mode leads to primary cognitive appraisal of threat information and

coordinated cognitive, affective, behavioral, and physiological responses seeking to

minimize danger and maximize safety (Beck et al., 1985). As part of this goal-directed

strategy, cognitive processing is narrowed and focuses on potentially threatening

components of a situation, while positive features are selectively dismissed (Beck &

Clark, 1997). An overestimation of the threat probability and threat severity arises from

the above biased processing of information in the environment and leads to further

catastrophic thinking–a core component of anxiety disorders (Beck et al., 1985; Beck &

Clark, 1997; Clark, 1986). According to Beck and Clark’s model, in order to maintain

focus on the strategic goal of minimizing danger and maximizing safety the primal threat

mode activates negative automatic thoughts of threat and danger concurrently with the

semantic analysis of threat stimuli (Beck & Clark, 1997). Taken together, the previous

two stages of the information-processing sequence ensure that once the primal threat

mode is activated, it governs information processing and minimizes the use of more

constructive and reflexive modes of processing. The first two stages of the information

processing sequence may offer a strategic advantage in the presence of a significant

threat; however, repeated activation of the primal threat mode by minimally threatening

stimuli may lead to pathological anxiety, especially if secondary appraisal processes do

not occur.

The final stage of Beck and Clark’s schema-based information processing model

is secondary elaboration. Contrary to the more automatic orienting mode and primal

11

threat mode, secondary elaboration mainly involves schema-driven controlled processing.

During secondary elaboration, threat stimuli are appraised in the context of the self-in-

relation-to-the-world and coping resources are evaluated (Beck et al., 1985). The re-

appraisal of threatening situations through strategic processing allows for a decrease in

anxiety by reducing the probability or severity of the threat and increasing awareness of

one’s coping resources (Beck & Clark, 1997). A failure to appropriately complete such a

process results in one of two outcomes. First, the automatic primal threat mode may

continue to dominate information processing resources; second, escape and avoidance

behaviors may be adopted. The former results in an escalation of anxious thoughts,

feelings, and cognitions, whereas the latter offers temporary relief contrasted with a

resurgence of anxiety once safety signals are gone or escape is no longer possible (Beck

& Clark, 1997). Therefore, according to Beck and Clark’s schema-based information

processing model, initial automatic allocation of attentional resources to potentially

threatening stimuli is responsible for the initial anxious cognitions and emotions, whereas

inappropriate strategic appraisal of threatening stimuli is responsible for the maintenance

of clinical anxiety (Mathews, 1990; Zinbarg, Barlow, Brown, & Hertz, 1992).

Beck’s early cognitive model pioneered the field of attentional bias for threat

research and highlighted fundamental processes in the development and maintenance of

anxiety disorders. Beck’s postulation that a threat detection mechanism operates during

the early automatic stages of processing and leads to vigilance towards threat (Beck et al.,

1985) was integrated into most subsequent models of attentional bias for threat (Bar-

Haim et al., 2007; Eysenck, Derakshan, Santos, & Calvo, 2007; Mathews & Mackintosh,

1998; Mogg & Bradley, 1998; Ohman, 1996; Williams, Watts, MacLeod, & Mathews,

12

1997) and later empirically supported (Carlson & Reinke, 2008; Koster, Crombez,

Verschuere, Van Damme, & Wiersema, 2006). The notion that anxious individuals may

not only be hypervigilant to threat, but may also have a difficulty disengaging their

attention from threat during later strategic stages of processing, is also an idea originally

presented by Beck and Clark (1997) that was later supported by research on anxiety

disorders (Amir, Elias, Klumpp, & Przeworski, 2003; Cisler & Olatunji, 2010; Fox,

Russo, & Dutton, 2002; Koster, Crombez, Verschuere, & De Houwer, 2004; Yiend &

Mathews, 2001). By contrasting facilitated attention towards threat with difficulty

disengaging from threat, and automatic processing with strategic or controlled

processing, Beck and Clark’s model highlights the possibility that different components

of the attention bias for threat may occur at different stages of processing (Cisler &

Koster, 2010).

Despite support for assumptions underlying Beck and Clark’s model (e.g., Amir

et al., 2003; Carlson & Reinke, 2008; Cisler & Olatunji, 2010), some research has drawn

attention to the associated limitations (Cisler, Bacon, & Williams, 2009; Cisler & Koster,

2010; Fox et al., 2002; Koster et al., 2004). Beck and Clark’s model does not overtly

explain the mechanisms underlying attentional avoidance of threat stimuli in anxious

individuals (Koster, Verschuere, Crombez, & Van Damme, 2005). In addition, Beck and

Clark’s model does not directly integrate contemporary research into mediating

mechanisms of attentional bias for threat, such as attentional control (Derryberry & Reed,

2002; Eysenck et al., 2007) and emotion regulation (Gross, 1998; Koole, 2009). The need

for a revised theoretical framework of attentional bias for threat has led to the

development of several models (Bar-Haim et al., 2007; Eysenck et al., 2007; Mathews &

13

Mackintosh, 1998; Mogg & Bradley, 1998; Ohman, 1996; Wells & Matthews, 1994;

Williams et al.,1997) following Beck’s early model and Beck and Clark’s schema-based

information processing model (Beck et al., 1985; Beck & Clark, 1997). There is also a

lack of agreement amongst the many contemporary models of attentional bias for threat,

which have also not integrated all of the available evidence on attentional bias for threat

in anxious pathologies (Cisler & Koster, 2010). In an attempt to integrate contemporary

findings on attentional bias for threat and to reconcile already existing models of

attentional bias for threat, Cisler and Koster (2010) developed an integrative theoretical

framework.

1.2.2. Cisler and Koster’s Integrative Framework of Attentional Bias for Threat

The primary assumption underlying Cisler and Koster’s (2010) framework is that

attentional bias for threat can be divided into three distinct components: facilitated

attention, difficulty in disengagement, and attentional avoidance (Koster et al., 2004).

Each component would be subject to different mediating mechanisms and would occur at

a different stage of the processing sequence. Attentional bias for threat would be the

product of the interaction between the different attentional components and their

mediating mechanisms (see Figure 1).

Facilitated attention is defined as the speed at which attention is oriented towards

threat stimuli (Cisler & Koster, 2010). The amygdala is thought to be the neural structure

critically involved in this process (Ohman, 2005) and enhanced amygdala activity would

be at least partially responsible for the heightened activation of a threat detection

mechanism (Carlson, Reinke, & Habib, 2009). The threat detection mechanism is

predicted to operate during automatic processing and to primarily respond to threat of

14

Figure 1: Integrative Framework of Attentional Bias for Threat

Reprinted from Clinical Psychology Review, 30/2, Cisler, J. M. and Koster, E. H.

W., Mechanisms of attentional biases towards threat in anxiety disorders: An integrative

review, 203-216, Copyright (2010), with permission from Elsevier.

15

high intensity presented for a short duration (i.e., 100 ms or less; Carlson & Reinke,

2008; Carlson et al., 2009; Koster et al., 2004; Koster et al., 2006). Accordingly,

facilitated attention would operate outside of awareness.

Difficulty in disengagement from threat is defined as the degree to which one’s

ability to transfer attention from one threat stimulus to another stimulus–threatening or

otherwise–is impaired (Cisler & Koster, 2010). The prefrontral cortex is thought to be the

neural structure responsible for this difficulty in disengagement (Derryberry & Reed,

2002; Miller & Cohen, 2001) through its influence on attentional control. Attentional

control can be construed as an individual’s top-down ability to regulate allocation of

attentional resources and to inhibit the bottom-up influence of emotional distracters

(Eysenck et al., 2007; Posner & Rothbart, 2000). Anxious individuals devoid of such a

regulatory ability are thought to show a difficulty disengaging their attention from threat

stimuli (Derryberry & Reed, 2002). Accordingly, attentional control would be an effortful

cognitive mechanism used during higher-order strategic processing and would mediate an

individual’s ability to disengage attention from threat.

Attentional avoidance is a more recently identified component of attentional bias

for threat and defined as the preferential allocation of attentional resources at locations

opposite to the threat stimuli location (Cisler & Koster, 2010). Attentional avoidance is

primarily witnessed when threat stimuli are presented to high trait anxious individuals for

long periods of time (i.e., 1250 ms; Koster et al., 2006; Koster, Verschuere, et al., 2005;

Mogg, Bradley, Miles, & Dixon, 2004) and is thought to be mediated by the prefrontal

cortex (Kim & Hamann, 2007; Ochsner et al., 2004). Prefrontal cortical structures would

exert their influence on attentional avoidance by activating emotion regulation

16

mechanisms, allowing individuals to control which emotions they have as well as when

and how they express them (Gross, 1998). Attentional avoidance, or re-allocation of

attentional resources to distracting stimuli, would serve as a controlled strategy used to

regulate the negative affect brought on by threat stimuli (Cisler & Koster, 2010; Koster et

al., 2006; Mogg et al., 2004). Given that effortful avoidance strategies require higher-

order strategic processing, anxious individuals would only display patterns of attentional

avoidance after being exposed to threatening stimuli for a long enough period of time

(Cisler & Koster, 2010).

Based on empirical data, Cisler and Koster’s (2010) integrative framework of

attentional bias for threat hypothesizes a temporal interaction between the three different

components of attentional bias. Delayed disengagement can be observed in the absence

of facilitated attention (Rinck, Becker, Kellermann, & Roth, 2003; Yiend & Mathews,

2001) but the reverse usually does not hold (Koster et al., 2004; Koster, Crombez, Van

Damme, Verschuere, & De Houwer, 2005), suggesting that facilitated attention likely

precedes delayed disengagement. Accordingly, Cisler and Koster’s (2010) framework

proposes that facilitated attention makes it easier for a stimulus in the environment to

reach a "threat threshold" and, once that threshold is reached, a threat detection

mechanism and the amygdala become activated and come to dominate information

processing. As a result, higher-order cortical structures such as the prefrontal cortex are

no longer able to regulate allocation of attentional resources, leading to difficulty

disengaging attention from threat stimuli. Alternatively, delayed disengagement occurs in

the absence of facilitated attention if someone already has poor higher-order regulatory

abilities. Indeed, simply telling an individual with poor higher-order regulatory abilities

17

to briefly attend to a threat stimulus (e.g., “look out for the snake!”) could be enough to

activate a threat detection mechanism and the amygdala, even though a threat threshold

may not have been reached through facilitated attention (Cisler & Koster, 2010).

Cisler and Koster’s (2010) framework attempts to reconcile the somewhat

contradictory finding that delayed disengagement and attentional avoidance both occur

during later stages of processing. Attentional avoidance of a stimulus appears to exclude

the possibility of simultaneously demonstrating a difficulty disengaging attention from

that stimulus. Accordingly, in the original vigilance-avoidance hypothesis of attentional

bias for threat (Mogg et al., 2004), anxious individuals were thought to initially show

facilitated attention towards threat stimuli followed by avoidance of threat stimuli, but

difficulty in disengagement was not discussed. Reconciling the latter two components of

attentional bias for threat, Cisler and Koster’s contemporary theory suggests that overt

avoidance of a stimulus does not preclude covert attention towards that stimulus

(Weierich, Treat, & Hollingworth, 2008). For instance, an individual with a snake phobia

who encounters a snake may employ overt avoidance strategies such as looking away

from the snake; however, cognitive resources may still be covertly directed towards the

snake (e.g., rumination). Further, increased difficulty disengaging attention from a

threatening stimulus likely increases the need for avoidance of that stimulus, possibly

explaining why attentional avoidance would occur subsequent to difficulty in

disengagement.

According to Cisler and Koster’s (2010) framework of attentional bias for threat,

an overactive threat detection mechanism and an underactive attentional control

mechanism would underlie attentional bias for threat in individuals with anxiety

18

pathologies. The threat detection mechanism would be responsible for facilitated

attention to threat during automatic processing, whereas the attentional control

mechanism would be implicated in delayed disengagement from threat and attentional

avoidance of threat during higher-order processing. An attentional bias for threat could

occur in the absence of one component or another; however, the attentional bias for threat

is likely the end product of the interaction between the three different components.

1.3. Attentional Bias for Threat in Posttraumatic Stress Disorder

Several cognitive paradigms have been used in the anxiety disorders literature to

assess attentional bias for threat. In the following sections, research making use of the

emotional Stroop task, the visual search task, and the dot probe task to assess attentional

bias for threat is presented. For each paradigm, findings pertaining to anxious populations

in general, and to PTSD and MVA survivors specifically are discussed, as well as

methodological issues associated with the use of each paradigm.

1.3.1 Emotional Stroop Task

The emotional Stroop task involves naming the colours of a list of emotional (i.e.,

positive and negative) and neutral words. Longer latency to naming emotional word

colours has been argued to represent increased cognitive interference from emotional

words (i.e., interference effect; McNally, 1998). Past research has repeatedly shown that

individuals with anxiety pathologies are slower at naming colours of threatening words

associated with their clinical condition (e.g., “snake” for spider phobia, “heart attack” for

panic disorder, “germs” for obsessive-compulsive disorder; see Williams, Mathews, &

MacLeod, 1996 for review). There is evidence to suggest that the emotional Stroop

interference effect (i.e., slower colour naming) also exists in individuals with PTSD.

Research with individuals having experienced sexual assault (Cassiday, McNally, &

19

Zeitlin, 1992; Foa, Feske, Murdock, Kozak, & McCarthy, 1991), ferry disaster survivors

(Thrasher, Dalgleish, & Yule, 1994), and war veterans (Kaspi, McNally, & Amir, 1995;

McNally, Kaspi, Riemann, & Zeitlin, 1990; McNally, Amir, & Lipke, 1996; McNally,

English, & Lipke, 1993; Vrana, Roodman, & Beckham, 1995) has provided evidence that

individuals with PTSD experience interference from specific trauma-related words (e.g.,

“boat” for ferry disaster survivors), an effect not found in trauma survivors without PTSD

or in control groups.

The emotional Stroop task has been used to identify attentional biases for threat in

MVA survivors with PTSD in at least four investigations. In the first investigation, the

response latencies of MVA survivors with PTSD, MVA survivors without PTSD but with

a simple driving phobia, and MVA survivors with low anxiety were compared for strong

(e.g., smash, death, blood) and mild (e.g., traffic, bridge, intersection) MVA-related

threat words, positive words, and neutral words (Bryant & Harvey, 1995). The authors

found that MVA survivors with PTSD experienced interference from strong threat words,

an effect not found in MVA survivors with a driving phobia or with low anxiety (Bryant

& Harvey, 1995), despite research having previously shown that an emotional Stroop

interference effect can occur in individuals with simple phobias (e.g., Watts, McKenna,

Sharrock, & Trezise, 1986). The finding that MVA survivors with PTSD experience

interference from strong threat words was corroborated by a second investigation

comparing the response latencies for threat words and neutral words presented to MVA

survivors with PTSD, MVA survivors without PTSD, and control subjects having never

been exposed to a MVA or having met criteria for PTSD. Again, the MVA survivors

with PTSD experienced interference from threat words whereas the other two groups did

20

not (Harvey, Bryant, & Rapee, 1996). A third investigation compared the response

latencies of MVA survivors with PTSD and pain, MVA survivors with pain but no

PTSD, and MVA survivors with no pain and no PTSD for accident-related (e.g.,

wrecked), pain-related (e.g., ache), positive, and neutral words. Highlighting the

specificity of the attentional bias for threat, both MVA survivor with pain groups showed

response delays to pain-related words, whereas only MVA survivors with pain and PTSD

were slower to respond to accident-related words, and no interference effect was found

for MVA survivors with no pain and no PTSD (Beck, Freeman, Shipherd, Hamblen, &

Lackner, 2001). In a fourth investigation, successful psychological treatment did not

appear to reduce interference from trauma-related threat words in MVA survivors with

PTSD (Devineni, Blanchard, Hickling, & Buckley, 2004). The lack of effect of

psychological treatment on interference to trauma-related threat suggests possible

methodological issues with the emotional Stroop task, limited clinical utility for this task,

or that the presence of attention biases for threat may not be the only factor associated

with psychopathology.

The emotional Stroop interference effect repeatedly found in the PTSD literature

has generally been viewed as an indication of a robust attentional bias for trauma-related

threat words (e.g., Buckley, Galovski, Blanchard, & Hickling, 2003; Emilien et al., 2000;

McNally, 1998); however, recent work has called into question whether the biases

actually are robust. A review of peer-reviewed studies and dissertation abstracts

investigating the Stroop interference effect in PTSD suggests that the robustness of the

emotional Stroop interference effect may be overestimated. Only 44% of published

studies and 8% of dissertation abstracts supported the emotional Stroop interference

21

effect (Kimble, Frueh, & Marks, 2009). A meta-analysis of 26 studies on the emotional

Stroop task in PTSD suggested that the emotional Stroop interference effect for trauma-

relevant threat words exists in individuals exposed to trauma, regardless of PTSD status

(Cisler et al., 2011). The Stroop interference effect could, therefore, be due to the

personal relevance of trauma-related words rather than their threatening nature. Findings

from the broader Stroop task literature suggest that stimuli with strong personal relevance

can produce a Stroop interference effect regardless of stimuli emotionality (i.e., positive

vs. negative) and psychopathology (i.e., anxious vs. normal subjects; e.g., Dalgleish,

1995; Riemann & McNally, 1995). Accordingly, the specific cognitive mechanisms

underlying this interference effect warrant clarification.

An emotional Stroop interference effect for threatening words was traditionally

interpreted as facilitated attention towards threatening stimuli (MacLeod, 1991);

however, delayed responses to threat related words may result from mechanisms other

than facilitated attention (De Ruiter & Brosschot, 1994; MacLeod et al., 1986).

Individuals with PTSD may process threatening words and neutral words in a similar

fashion, but threatening words may result in negative affective states interfering with and

generally slowing down task performance (Algom, Chajut, & Lev, 2004; MacLeod et al.,

1986). The interference effect has been shown to diminish when the task requires a

manual rather than a vocal response (see MacLeod, 1991 for review), suggesting that the

emotionally-laden words may interfere with general motor response performance rather

than cognitive processing (Algom et al., 2004). In such a case, attentional control

mechanisms (Derryberry & Reed, 2002), rather than heightened threat detection

mechanisms (Williams et al., 1996), would modulate task performance.

22

Consistent with the idea that attentional control may modulate task performance,

contemporary research has found delayed reaction times to neutral words that follow

threat words but not to the threat words themselves (McKenna & Sharma, 2004). The

emotional Stroop interference effect may therefore result from disrupted slow and

effortful processing (i.e., attentional control) rather than disrupted fast and automatic

processing (i.e., facilitated threat detection). A recent meta-analysis supported the

emotional Stroop interference effect as only occurring in PTSD samples when word

stimuli are presented supraliminally and some degree of elaborate or effortful processing

can occur (Cisler et al., 2011). An earlier meta-analysis of studies using anxious samples

also found that the emotional Stroop interference effect likely reflects late controlled

processing (e.g., response selection; Schmidt & Besner, 2008) rather than early stages of

attentional processing (Bar-Haim et al., 2007). The interpretation difficulties surrounding

the emotional Stroop task has propagated the use of other paradigms, such as the visual

search task (Neisser, 1963) and the dot probe task (MacLeod et al., 1986), to investigate

attentional bias for threat in anxious samples and in PTSD more specifically.

1.3.2 Visual Search Task

The original visual search task requires participants to identify a target in a matrix

of identical stimuli (Treisman & Gormican, 1988). Variations of the task used in research

investigating attentional bias for threat require participants to identify a threatening target

in an array of neutral stimuli or to identify a neutral target in an array of threatening

stimuli. Faster reaction times for the identification of a threatening target within neutral

stimuli is believed to indicate facilitated attention to threat. Conversely, slower reaction

times for the identification of a neutral target within threatening stimuli is taken to reflect

23

attentional interference from threat (e.g., Byrne & Eysenck, 1995; Ohman, Lundqvist, &

Esteves, 2001). Using the visual search task, interference arising from difficulty in

disengaging attention from threatening stimuli has been demonstrated in individuals with

high trait anxiety (Byrne & Eysenck, 1995), social phobia (Gilboa-Schechtman, Foa, &

Amir, 1999), and generalized anxiety disorder (Rinck et al., 2003); however, results

pertaining to facilitated attention towards threatening stimuli are mixed. Some

investigations have shown facilitated detection of threat stimuli in anxious populations

(Byrne & Eysenck, 1995; Gilboa-Schechtman et al., 1999; Ohman, Flykt, & Esteves,

2001) and others have found no such effect (Fox et al., 2000; Rinck et al., 2003; Rinck &

Becker, 2005).

The visual search task has been used at least twice to assess attentional bias for

threat in PTSD. The first investigation was completed with 57 male Vietnam veterans

(Pineles, Shipherd, Welch, & Yovel, 2007). The results indicated that veterans reporting

PTSD were slower to identify a target within trauma-relevant threat words suggesting

difficulty disengaging attention from threat stimuli; however, there was no evidence for

facilitated attention towards threat stimuli. The results were replicated in a second

investigation assessing attentional bias for threat in women exposed to sexual assault

(Pineles, Shipherd, Mostoufi, Abramovitz, & Yovel, 2009). Women reporting PTSD

displayed difficulty disengaging their attention from threat stimuli but not facilitated

attention towards threat stimuli. In addition, difficulty disengaging attention was found

for trauma-specific threat stimuli but not generally threatening stimuli, suggesting

specificity of the attentional bias for threat in PTSD and supporting previous findings

from the Stroop task (Beck et al., 2001; Foa et al., 1991; McNally et al., 1990). Like the

24

emotional Stroop task (McKenna & Sharma, 1995), the visual search task appears to

produce an order effect such that participants habituate to threat words (Pineles et al.,

2009; Pineles et al., 2007). The dot probe task is less likely to produce habituation

(Staugaard, 2009) but can still distinguish facilitated attention and difficulty in

disengagement; as such, the dot probe task may be more appropriate for investigations of

attention biases for threat in PTSD.

1.3.3 Dot Probe Task

The dot probe task was designed to overcome some of the interpretation

difficulties associated with the emotional Stroop task (e.g., impaired cognitive processing

vs. impaired motor responding) and requires participants to engage in a neutral response

(i.e., press a key) when a neutral probe (e.g., “•”) appears on a computer screen

(MacLeod et al., 1986). In the original version of the task, participants were

simultaneously presented with one threatening word and one neutral word prior to the

appearance of the probe. An attentional bias for threat was inferred when a participant

was faster at identifying the probe on trials where it replaced a threatening word

(MacLeod et al., 1986). The assumption behind the task is that, if the participant’s visual

attention was directed towards the threatening word, a shift in attention allocation was not

required to identify the probe, resulting in shorter reaction times. Using the dot probe

task, research has shown that individuals with generalized anxiety disorder (Bradley,

Mogg, White, Groom, & Bono, 1999), social phobia (Asmundson & Stein, 1994), and

panic disorder (Asmundson, Sandler, Wilson, & Walker, 1992) display an attentional bias

for disorder-specific threat information. In a general review of the literature on anxiety

and attentional bias for threat, the dot probe task effectively identified an attentional bias

25

for threat in anxious populations relative to non-anxious populations (Bar-Haim et al.,

2007). Despite empirical support for the use of the dot probe task to investigate

attentional bias for threat, only two published investigations have used this paradigm with

PTSD samples.

Attentional bias for threat was investigated in PTSD with a dot probe task

completed by a sample of MVA survivors (Bryant & Harvey, 1997). The reaction time of

MVA survivors with PTSD, MVA survivors with subclinical PTSD, and MVA survivors

with low trait anxiety (i.e., < 30 on the Trait scale of the State-Trait Anxiety Inventory

[STAI]) and no history of PTSD were compared for strong MVA-related threat words

(e.g., mortality), mild MVA-related threat words (e.g., highway), positive words (e.g.,

friendly), and neutral words (e.g., blanket). A modified version of the dot probe task was

used wherein the probe was presented on the screen simultaneously with the threatening

word and the neutral word. MVA survivors with PTSD displayed an attentional bias for

mildly threatening words, a bias not found in MVA survivors with subclinical PTSD or

MVA survivors with no history of PTSD. An attentional bias for strong threat words was

not found, possibly due to the use of a modified version of the dot probe task (Bardeen &

Orcutt, 2011) or due to the cognitive avoidance of strong threat words (De Ruiter &

Brosschot, 1994). The results were originally interpreted has an indication of facilitated

attention towards trauma-relevant threatening words in MVA survivors with PTSD;

however, contemporary research has suggested that the dot probe task may better reflect a

difficulty in disengaging attention from threat (Koster et al., 2004; Koster et al., 2006;

Salemink, van den Hout, & Kindt, 2007).

26

The dot probe task has recently been modified to distinguish between facilitated

attention, difficulty in disengagement, and avoidance (Koster et al., 2004; Salemink et al.,

2007) of threatening stimuli. Using this new method, researchers have found evidence

that individuals with high anxiety display facilitated attention to threatening stimuli

presented for 100 ms (Carlson & Reinke, 2008), difficulty in disengaging attention from

threatening stimuli presented for 500 ms (Koster et al., 2004; Koster et al., 2006; Koster,

Vershuere, et al., 2005; Salemink et al., 2007), and avoidance of threatening stimuli

presented for 1250 ms (Garner, Mogg, & Bradley, 2006; Koster, Vershuere, et al., 2005;

Mogg et al., 2004). Accordingly, using a contemporary method for the dot probe task

with the presentation of stimuli at different exposure times should allow for time-course

analyses of attentional bias threat dimensions as defined by Cisler and Koster (2010).

The contemporary dot probe task has already been used to investigate attentional

bias for threat in undergraduate students with posttraumatic stress symptoms (Bardeen &

Orcutt, 2011). The investigation made use of a 100 ms and 500 ms stimulus onset

asynchrony (SOA; i.e., the duration of time between initial presentation of the stimulus

and presentation of the probe) to assess for facilitated attention to threatening images and

difficulty in disengagement from threatening images. Individuals reporting higher levels

of PTSD symptoms did not display facilitated attention to threatening stimuli at 150 ms;

however, consistent with previous research using the visual search task (Pineles et al.,

2009; Pineles et al., 2009), individuals reporting higher levels of PTSD symptoms did

display difficulty disengaging attention from threatening stimuli at 500 ms. Results from

the Bardeen and Orcutt (2011) investigation highlighted the importance of difficulty in

disengagement from threat in individuals with PTSD symptoms; nevertheless, the role of

27

facilitated attention remains unclear. An absence of facilitated attention to threatening

stimuli may have resulted from the use of a non-clinical sample or non-trauma specific

threatening stimuli. Alternatively, a SOA of 150 ms may have been long enough for

attentional shifts to occur, making such an exposure time inappropriate for the assessment

of facilitated attention (Bardeen & Orcutt, 2011). Furthermore, the investigation did not

assess cognitive avoidance, which is likely to occur at longer SOA (e.g., 1250 ms; Cisler

& Koster, 2010). Cognitive avoidance can be posited as one mechanism through which

PTSD is maintained (e.g., Salters-Pedneault, Tull, & Roemer, 2004); as such, an

integrative investigation assessing the avoidance component of attentional bias for threat,

in addition to the facilitated attention and difficulty in disengagement components of

attentional bias for threat, may provide useful insights for PTSD researchers and

clinicians.

1.4 Current Investigation, Purposes, and Hypotheses

The previous literature review of attentional bias for threat in anxiety

pathologies−including PTSD−highlights several discrepancies among past research

findings. In addition, based on a review of the current literature, clarifying the

directionality and time course of attentional bias for threat using a contemporary dot

probe method appears warranted. Cisler and Koster’s (2010) integrative framework

suggests that attentional bias for threat in PTSD (and anxiety pathologies as a whole) may

result from an interaction between stimulus threat level and stimulus exposure time;

however, such an interaction was never explored in research investigating attentional bias

for threat in MVA survivors. Furthermore, the limited available research on MVA

survivors (Bryant & Harvey, 1995, 1997; Harvey et al., 1996) makes it unclear whether

28

MVA survivors without PTSD also demonstrate an attentional bias for trauma-relevant

threat stimuli (Cisler et al., 2011). Given that attentional biases for threat are thought to

be involved in the development and maintenance of PTSD (Elwood et al., 2009), that

MVAs are one of the primary cause of PTSD in the general population (Blanchard &

Hickling, 2003), and that research on MVA survivors and attentional bias for threat is

sparse, a contemporary investigation of attentional bias for threat in MVA survivors is

warranted.

The current investigation was designed to assess the directionality and time

course of attentional bias for threat in MVA survivors reporting high PTSD symptoms

(MVA-High PTSD), MVA survivors reporting low PTSD symptoms (MVA-Low PTSD),

and a control group of people who have not experienced an MVA and do not report

PTSD symptoms (Control) using a contemporary detection dot probe task (Salemink et

al., 2007). Words of different threat level (i.e., neutral, mild threat, and strong threat;

Bryant & Harvey, 1995, 1997) were followed by a probe presented at different levels of

SOA (i.e., 100 ms, 500 ms, 1250 ms; Koster, Verschuere, et al., 2005). The different

presentation threat levels and SOA were included in an attempt to disentangle the

relationship between the cognitive mechanisms of facilitated attention to threat, difficulty

in disengagement from threat, and avoidance of threat.

1.4.1 Purposes

The current research had two main purposes. First, the current investigation

extended previous research by integrating stimulus threat level and SOA to

simultaneously assess all three components of attentional bias for threat (i.e., facilitated

attention, difficulty in disengagement, and avoidance) in individuals with PTSD

29

symptoms. To date, two similar investigations have been conducted; however, only one

of the two investigations employed exposure durations identical to the ones used in the

proposed investigation (Koster, Verschuere, et al., 2005) and the manipulation of

exposure duration rather than SOA may have induced a measurement confound. Further,

neither of the two investigations used a sample with PTSD symptoms (Koster et al.,

2006; Koster, Verschuere, et al., 2005), and both used picture rather than word stimuli.

The inherently abstract threat themes associated with anxiety in PTSD are more

reasonably represented by written words than by focused and refined pictures (Bar-Haim,

2010). Second, the proposed investigation used a contemporary dot probe task to assess

the directionality and time course of attentional bias for threat in a sample of MVA

survivors. The only investigation to have used a dot probe task to assess attentional bias

for threat in MVA survivors did not differentiate between mechanisms of facilitated

attention to threat, difficulty in disengagement from threat, and avoidance of threat

(Bryant & Harvey, 1997). Through the use of a contemporary method, the proposed

investigation evaluated the three different components of attentional bias for threat in

MVA survivors. A comparison between the MVA-High PTSD, MVA-Low PTSD, and

Control groups was used to help clarify the relationship that exists between exposure to

an MVA, PTSD symptoms, and attentional bias for threat.

1.4.2 Hypotheses

Details pertaining to the computation of attentional bias indices are presented in a

later section; however, based on Cisler and Koster’s (2010) framework of attentional bias

for threat, groups demonstrating an attentional bias for threat were expected to display the

following pattern of results.

30

1. Threat words presented at 100 ms SOA were expected to produce facilitated

attention (i.e., positive orienting index).

2. Threat words presented at 500 ms SOA were expected to produce difficulty in

disengagement (i.e., positive disengaging index).

3. Threat words presented at 1250 ms SOA were expected to produce avoidance

(i.e., negative orienting index).

In addition, the following hypotheses were made based on group assignment and stimulus

threat level.

4. The groups were expected to differ such that the orienting and disengaging

indices would be larger for the MVA-High PTSD group compared to the MVA-

Low PTSD group, and for the MVA-Low PTSD group compared to the Control

group.

5. The threat level of the words presented was expected to influence the size of the

effect such that the orienting and disengaging indices would be larger for strong

threat words compared to mild threat words.

2.0 Method

2.1 Environment

The proposed investigation was conducted at the University of Regina in the

Anxiety and Illness Behaviours Laboratory (AIBL). The investigation was completed

online using two tools. The SurveyMonkey online survey tool (www.surveymonkey.com;

SurveyMonkey, 2012) was used to assess self-report information and the Inquisit

software tool (www.millisecond.com; Millisecond Software Inc., Seattle, WA) was used

to assess attentional biases.

2.2 Recruitment

31

Participants were recruited across North America through online social media

advertising (www.facebook.com), community advertising (e.g., www.kijiji.ca, newspaper

advertising, posters), and the University of Regina psychology participant pool.

Participants recruited through the psychology participant pool received 1 credit for

participation. Participants were asked to voluntarily and anonymously complete an

Internet-based survey as well as an attention task as part of an experiment investigating

attentional processes following MVAs.

2.3. Participants

Participants included in the proposed investigation had to be between the ages of

18 and 65 years, report English as their first language, have no vision problems not

corrected by glasses or contact lenses, no history of traumatic brain injury, and no pattern

of problematic alcohol use. To be included in one of the MVA groups, participants

needed to report the experience of a MVA severe enough to warrant the filing of a police

report. To ensure that the DSM duration criterion for PTSD (APA 2000; 2013) could be

met, the MVA also had to have occurred more than a month prior to the completion of

the investigation. Subsyndromal PTSD symptoms have been associated with increased

impairment, comorbidities, and suicidality in community, veteran, and rescue worker

samples (Cukor, Wyka, Jayasinghe, & Difede, 2010; Marshall et al., 2001; Yarvis &

Schiess, 2008) and participants with probable subsyndromal PTSD have previously been

included in PTSD treatment experiments of MVA survivors (Maercker, Zöllner,

Menning, Rabe, and Karl, 2006). Accordingly, in the current investigation the MVA-

High PTSD group was comprised of participants self-reporting both full PTSD and

subsyndromal PTSD symptoms (see below; Weathers et al., 1991) in reference to a MVA

32

specifically. To be included in the Control group or the MVA-Low PTSD group,

participants needed to self-report the absence of full PTSD or subsyndromal PTSD

symptoms in reference to a MVA or any other traumatic event.

A total of 306 participants started the experiment; however, only 127 participants

(100 women, 27 men, Mage = 23.76, SD = 7.98, age range: 18-56 years) met basic

eligibility criteria, completed all measures, and were included in the current investigation.

Excluded from the investigation were 9 participants who did not report English as their

first language, 4 participants with vision problems not corrected by glasses or contact

lenses, 11 participants with a history of traumatic brain injury, 61 participants with a

probable alcohol use problem, 28 participants who did not meet group inclusion criteria

(i.e., high PTSD symptoms from an event other than a MVA), and 55 participants who

had not completed all measures. An additional 8 participants were excluded based on

their request to exclude their data from the experiment, as well as 3 outliers with mean

dot probe reactions times more than 3 SD above or below the mean.

2.4 Measures

2.4.1 Demographic Measures

The Demographic Measures questionnaire presented in Appendix A was used to

assess eligibility to participate in the investigation, in addition to providing demographic

data relevant to the investigation. The Demographic Measures included demographic

questions (e.g., age, sex), questions relevant to inclusion in the investigation (e.g., first

language, vision problems), and questions relevant to MVA history (e.g., “Were you in a

motor vehicle accident […]?”).

2.4.2 Standardized Measures

33

Attentional Control Scale (ACS; Derryberry & Reed, 2002; Appendix B). The

ACS is a 20-item measure requiring respondents to report on their perceived ability to

flexibly control attention. Items pertaining to attention shifting (e.g., “I can quickly

switch from one task to another”), focusing of attention (e.g., “When concentrating, I can

focus my attention so that I become unaware of what’s going on in the room around

me”), and the ability to flexibly control thought (e.g., “It is hard for me to break from one

way of thinking about something and look at it from another point of view”) are reported

on a 4-point Likert-type scale (1 = almost never to 4 = always). The initial psychometric

evaluation of the ACS has shown good internal consistency for this measure (Derryberry

& Reed, 2002) and internal reliability was good in the current sample (α = .85; Cohen,

1988). Higher scores on the ACS have previously been associated with the activation of

brain areas involved in top-down emotion regulation (Mathews, Yiend, & Lawrence,

2004); as such, the ACS was included in the current investigation to better characterize

the sample.

Alcohol Use Disorders Identification Test (AUDIT; Barbor, de la Fuente,

Saunders, & Grant, 1989; Appendix C). The AUDIT is a 10-item self-report

questionnaire comprised of items assessing alcohol consumption (e.g., “How often do

you have a drink containing alcohol?”) and adverse consequences of alcohol use (e.g.,

“Have you or someone else been injured as a result of your drinking?”) over the past 12

months. Items are reported on a 5-point Likert-type scale (for most items, 0 = never to 4

= daily or almost daily). The AUDIT has demonstrated internal reliability above .80 in a

number of studies (see Reinert & Allen, 2002 for review) and a total score of eight or

above has been shown to be a sensitive indicator of problematic drinking (Saunders,

34

Aasland, Babor, de la Fuente, & Grant, 1993). The AUDIT demonstrated adequate

internal reliability (α = 57; Cohen, 1988) in the current sample. The AUDIT was

included in the current investigation as a screening measure and to better characterize the

sample.

Emotion Regulation Questionnaire (ERQ; Gross & John, 2003; Appendix D). The

ERQ is a 10-item measure requiring respondents to self-report on their use of two

different emotion regulation strategies−cognitive reappraisal (“I control my emotions by

changing the way I think about the situation I’m in”) and expressive suppression (“I

control my emotions by not expressing them”). Items are reported on a 7-point Likert-

type scale (1 = strongly disagree to 7 = strongly agree). Expressive suppression has

previously been associated with increased PTSD symptomatology (Moore, Zoellner, &

Mollenholt, 2008) and, during later stages of processing, may be involved in the

avoidance component of attentional bias for threat. Both the ERQ reappraisal scale

(ERQ-R; α = .86) and the ERQ suppression scale (ERQ-S; α = .82) showed good internal

reliability in the current sample (Cohen, 1988). The ERQ was included in the current

investigation to better characterize the sample.

PTSD Checklist–Stressor Specific Version (PCL-S; Weathers et al., 1991;

Appendix E). The PCL-S is a 17-item self-report measure of PTSD assessing symptoms

in relation to a specific stressful experience (e.g., MVA). For each item, respondents are

required to indicate how much a particular symptom (e.g., “Feeling jumpy or easily

startled”) has bothered them over the past 30 days using a 5-point Likert-type scale (1 =

not at all to 5 = extremely). A total score can be obtained by summing all PCL-S items.

Alternatively, PCL-S items can be divided into four different subscales (APA, 2013;

35

Asmundson et al., 2000; Asmundson et al., 2004) assessing DSM-IV re-experiencing,

avoidance, numbing, and arousal PTSD symptoms. A total of 19 studies reported values

above .75 for the PCL-S internal consistency (see Wilkins, Lang, & Norman, 2011 for

review) and previous research demonstrated high convergent validity with the Clinician

Administered PTSD Scale in samples of MVA survivors (Blanchard et al., 1996). In the

current investigation, all MVA survivors completed the PCL-S in reference to their

MVA. Further, participants who indicated having experienced another event that was

more traumatic than a MVA also completed the PCL-S in reference to that event. Internal

reliability was good (Cohen, 1988) in the current sample for both the PCL-S completed in

reference to the MVA (PCL-S MVA; α = .86) and the PCL-S completed in reference to

any other traumatic event (PCL-S Other; α = .90). The PCL-S was included in the current

investigation as a grouping measure and to better characterize the sample.

STAI1 (Spielberger, Gorsuch, Lushene, Vagg, & Jacobs, 1983). The STAI is a

measure comprised of 40 items (e.g., “I feel nervous and restless”) requiring respondents

to self-report on their general level of anxiety (i.e., STAI-State) and their current level of

anxiety (i.e., STAI-Trait). Items are reported on a 4-point Likert-type scale (1 = almost

never/not at all to 4 = almost always/very much so). The STAI has demonstrated good

psychometric properties (Barnes, Harp, & Jung, 2002; Spielberger et al., 1983) and both

the STAI-State (α = .94) and the STAI-Trait (α = .93) showed good reliability in the

current sample. Individuals with higher anxiety scores are thought to perceive situations

as more dangerous and threatening (Spielberger, 1972 as cited in Barnes et al., 2002).

The STAI was included in the current investigation to better characterize the sample.

2.4.3 Dot Probe Task

36

The dot probe task software used to assess participant allocation of attentional

resources was previously shown to provide sensitive reaction time measures (De Clercq,

Crombez, Buysse, & Roeyers, 2003). The dot probe task was made accessible online,

allowing participants to be assessed from many locations. The dot probe task requires the

identification of a probe on a computer screen following the presentation of stimuli. An

attentional bias for threat is inferred based on the speed with which the probe is identified

(MacLeod et al., 1986). Accordingly, dot probe task reaction times were used to derive a

measure of attentional bias for threat in the current investigation.

The current investigation used 50 words as stimuli (i.e., 30 neutral words, 10

mildly threatening words, and 10 strongly threatening words: see Appendix F). The

valence associated with the threat and neutral words used in the current investigation has

been established in prior research with MVA survivors and healthy controls (Arnell,

Killman, & Fijavz, 2007; Bryant & Harvey, 1995, 1997). Positive words were not used in

the current investigation because attentional bias for threat (as opposed to positive

stimuli) is thought to underlie anxiety pathologies (e.g., Bar-Haim, 2007; Beck & Clark,

1997; Cisler & Koster, 2010). Furthermore, an attentional bias for positive stimuli has not

been reliably demonstrated in anxiety disorders (see Ruiz-Caballero & Bermudez, 1997);

as such, positive words appeared an unnecessary addition to participant burden in the

current research context. During the dot probe task, the words were presented in pairs

matched for character length. The word pairs consisted of two neutral words (N-N), one

neutral word and one mildly threatening word (N-MT), or one neutral word and one

strongly threatening word (N-ST). Word pairs appeared in a random sequence and each

word pair was presented for 100ms. A probe appeared 100 ms, 500 ms, or 1250 ms

37

following the onset of the word pair (i.e., SOA) and half of the N-N trials were not

followed by a probe (i.e., “filler” trials).

2.5 Procedure

Participants in the current investigation were presented with an online consent

form briefly describing the purpose of the investigation. Participants were asked to

provide consent by checking a “Yes” or “No” box. Participants were asked to fill out an

initial battery of online questionnaires. Upon completion of all the questionnaires,

participants were asked to follow a weblink to the dot probe task.

Instructions for the dot probe task were presented on the screen. Participants were

instructed to observe the black fixation cross in the middle of the screen and informed

that the black cross would be followed by the appearance of two words, one above the

other. Participants were told that for the majority of trials a probe (i.e., “•”) would appear

on the screen following the offset of the words. Participants were instructed to press the

space bar when the probe appears on the screen. Upon responding, the next trial would

start. Participants were also instructed that on some trials a probe would not appear

following the offset of the words. Participants were instructed not to press the space bar

and to wait for the next trial to start. Participants completed 10 practice trials prior to the

240 trial test phase. During the test phase, participants completed 80 trials (i.e., 20 filler

trials, 20 “N-N” words, 20 “N-MT” words, and 20 “N-ST” words) for each SOA

condition (i.e., 100 ms, 500 ms, and 1250 ms). The probe appeared in the location

previously occupied by a threatening word for half of the N-MT and half of the N-ST

trials. The probe appeared in the location previously occupied by a neutral word for the

other half of the N-MT and the N-ST trials, as well as for all the N-N trials. Each trial

38

started with a black fixation cross presented for 1500 ms. The order of the trials was

randomized for each participant. Following the dot probe task, participants were asked a

screening question (i.e., “Based on how distracted you were while completing the

computer task, should we include your data as part of our study?”) to control for careless

responding.

2.6 Analyses

2.6.1 PTSD status

Participant PTSD status was made based on PCL-S scores. In MVA survivors, a

total score of 44 and above indicates a probable diagnosis of PTSD (Blanchard, Jones-

Alexander, Buckley, & Forneris, 1996); however, a high total score can be obtained

without endorsing symptoms in a pattern coherent with a PTSD diagnosis (Ruggiero, Del

Ben, Scotti, & Rabalais, 2003). Accordingly, probable PTSD classification was limited to

respondents scoring on symptom clusters as per the delineations in DSM-IV. PTSD

classification required reporting above 3 on at least one re-experiencing symptom, three

avoidance and numbing symptoms, and two arousal symptoms, in addition to scoring

above 44 on all scales combined (Pineles et al., 2009; Pineles et al., 2007). Probable

subsyndromal PTSD classification was assigned for participants endorsing at least two

PTSD symptom clusters, including the re-experiencing cluster but not meeting probable

PTSD criteria (Blanchard, Hickling et al., 1996).

2.6.2 Preparation of Reaction Time Data

Reaction times of less than 100 ms or more than 2000 ms were excluded to

account for anticipatory responding and distraction (Salemink et al., 2007). Dot probe

task reaction times have traditionally been analyzed using a bias index (e.g., Bryant &

39

Harvey, 1997; Koster, Verschuere et al., 2005) computed by subtracting mean reaction

times to congruent trials from mean reaction times to incongruent trials (see below for

detailed description of congruent and incongruent trials). However, in line with

contemporary investigations assessing the different components attentional bias for threat

(Koster et al., 2004) and already established congruency and incongruency indices

(Asmundson, Carleton, & Ekong, 2005; Asmundson & Hadjistavropoulos, 2007),

orienting and disengaging indices (Salemink et al., 2007) were the primary measures of

interest in the current investigation. There were six orienting indices (i.e., mild threat

words vs. strong threat words, at each SOA condition, 100 ms vs. 500 ms vs. 1250 ms)

and six disengaging indices (i.e., mild threat words vs. strong threat words, at each SOA

condition, 100 ms vs. 500 ms vs. 1250 ms) that were computed.

The orienting index was computed by subtracting a participant’s mean reaction

time on trials on which the probe replaces a threat word in the presence of a neutral word

(N, dT; i.e., congruent trials) from trials when the probe replaces a neutral word in the

presence of another neutral word (N, dN).

Orienting Index = N, dN – N, dT

A positive orienting index indicates faster identification of the probe when it follows

threat words in the presence of neutral words and a negative orienting index indicates

slower identification of the probe when it follows threat words in the presence of neutral

words.

The disengaging index was computed by subtracting a participant’s mean reaction

time on trials on which the probe replaces a neutral word in the presence of another

40

neutral word (N, dN) from trials on which the probe replaces a neutral word in the

presence of a threat word (dN, T; i.e., incongruent trials).

Disengaging Index = dN, T – N, dN

A positive disengaging index indicates slower identification of probes that follow a

neutral word in the presence of a threat word, compared to probes that follow a neutral

word in the presence of another neutral word.

2.6.3 Analyses

All analyses were performed using SPSS Version 21.0 (SPSS, Chicago, IL).

Frequencies and descriptive statistics based on demographic measures and trauma history

were computed for the purpose of group assignment and to better characterize the sample.

Descriptive statistics for all variables included in the primary analyses were also used to

evaluate suitability of the data. Subsequently, Pearson correlations were used to analyze

relationships between psychological measures (i.e., STAI, ACS, ERQ, PCL-S) and each

of the orienting and the disengaging indices to assess for the presence of potential

covariates. Thereafter, one sample t-tests using one-tailed significance were used to

compare the strength of the orienting and disengaging indices to chance for each group.

The effect of group, SOA, and stimulus threat level on mean orienting and disengaging

indices was tested using two group (i.e., Control, MVA-Low PTSD, MVA-High PTSD)

× SOA (i.e., 100 ms, 500 ms, 1250 ms) × threat level (i.e., mild threat, strong threat)

mixed-model Analysis of Variance (ANOVA). Statistically significant main effects and

interaction effects were analyzed using pairwise contrasts. Exploratory analyses were

subsequently conducted and included a group (i.e., Control, MVA-Low PTSD, MVA-

High PTSD) × SOA (i.e., 100 ms, 500 ms, 1250 ms) × threat level (i.e., mild threat,

41

strong threat) mixed-model Analysis of Variance (ANOVA) exploring the effect of

group, SOA, and stimulus threat level on the traditional dot probe bias index (Koster,

Verschuere, et al., 2005). Exploratory analyses also included one sample t-tests using

two-tailed significance to compare the strength of the orienting and disengaging indices

to chance for each group. The exploratory analyses were not part of the original data

analytic plan and were used to clarify the results of the main analyses and inform future

research.

3.0 Results

A total of 63 participants (50 women, 13 men, Mage = 23.02, SD = 7.73, age range:

18-56 years) did not report the experience of a MVA or high PTSD symptoms in

reference to any traumatic event and were included in the Control group. In total, 64

participants reported having experienced a MVA and were further divided into two

groups. The MVA-Low PTSD group included 46 participants (35 women, 11 men, Mage =

24.69, SD = 7.39, age range: 18-53 years) and the MVA-High PTSD group included 18

participants (15 women, 3 men, Mage = 24.00, SD = 10.25, age range: 18-56 years). There

was a statistically significant difference, F(2, 124) = 3.25, p = .04, η2 = .05, between the

three groups on the total number of traumatic events experienced (Control, M = .79, SD =

1.12; MVA-Low PTSD, M = 1.13, SD = 1.17; MVA-High PTSD, M = 1.15, SD = .99);

however, Tukey’s HSD post hoc analyses indicated that the difference between the

MVA-High PTSD group and the Control group was only approaching statistical

significance (p = .05). There was no statistically significant difference (p > .05) between

the two MVA groups for the number of months elapsed since the MVA (MVA-Low, M =

49.24, SD = 42.88; MVA-High PTSD, M = 32.39, SD = 29.11). There was a statistically

42

significant difference, F(2, 65) = 29.57, p < .001, η2 = .48, between the groups on the

PCL-S total score in reference to a traumatic event other than an MVA (i.e., PCL-S

Other). Tukey’s HSD post hoc comparisons revealed that, for participants in the MVA-

High PTSD group having reported another event as more distressing than the MVA, the

mean PCL-S Other score was statistically significantly (ps < .001) higher than the mean

PCL-S Other score for participants in the Control group and the MVA-Low PTSD group.

As expected, the PCL-S total score in reference to the MVA (i.e., PCL-S MVA) was also

statistically significantly higher, t(20.40) = -6.58, p < .001, r = .82, in the MVA-High

PTSD group compared to the MVA-Low PTSD group. The groups were not statistically

significantly different (ps > .05) on the other self-reported variables (i.e., STAI-State,

STAI-Trait, ACS, ERQ-R, ERQ-S, AUDIT) with the exception of the ERQ-S, F(2, 124)

= 3.68, p = .03, η2 = .06. Tukey’s HSD post-hoc comparisons revealed that the mean

ERQ-S score was statistically significantly higher for the Control group compared to the

MVA-Low PTSD group (p = .02). Participant demographic information (i.e., ethnicity,

relationship status, education, employment status), trauma history, and mean scores on

self-report measures are presented as a function of group in Tables 1, 2, and 3.

3.1. Main Hypotheses

Indices of univariate Skew and Kurtosis for several variables included in the

current investigation indicated potentially problematic non-normality for the primary

analyses (i.e., Skew > 2.00, Kurtosis > 7.00; Tabachnick & Fidell, 2013); as such,

adherence to normality was maximized with bootstrapping per current best practices

(Preacher, Rucker, & Hayes, 2007). The intercorrelations between scores on the self-

report measures and orienting and disengaging indices on the dot probe task are presented

43

Table 1. Participant Demographic Information as a Function of Group

Control MVA-Low PTSD MVA-High PTSD

Variable n (%) n (%) n (%) Ethnicity Caucasian 48 (76.2) 39 (84.4) 12 (66.7) First Nations 3 (4.8) 1 (2.2) - - African 2 (3.2) 1 (2.2) - - Asian 2 (3.2) 2 (4.3) 1 (5.6) South Asian 1 (1.6) 1 (2.2) 1 (5.6) Other 4 (6.3) 2 (4.3) 1 (5.6) Rather Not Say 3 (4.8) - - 3 (16.7) Relationship Status Single 53 (84.1) 35 (76.1) 13 (72.2) Married/Common Law 8 (12.7) 9 (19.6) 5 (27.8) Divorced/Separated 2 (3.2) 1 (2.2) - - Rather Not Say - - 1 (2.2) - - Education High School 16 (25.4) 2 (4.3) 1 (5.6) Partial College Education 34 (54.0) 26 (56.5) 14 (77.8) 2-yr College Diploma 3 (4.8) 5 (10.9) 1 (5.6) 4-yr College/University 8 (12.7) 10 (21.7) 2 (11.1) Partial Graduate Education 1 (1.6) 1 (2.2) - - Completed Graduate Education 1 (1.6) 1 (2.2) - - Rather Not Say - - 1 (2.2) - - Employment Student 51 (81.0) 35 (76.1) 14 (77.8) Part-time 32 (50.8) 19 (41.3) 12 (66.7) Full time 10 (15.9) 10 (21.7) - - Unemployed 2 (3.2) - - - - Disabled 1 (1.6) - - 1 (5.6) Retired - - - - 1 (5.6) Notes. Table lists frequencies and percentages as a function of group assignment.

44

Table 2. Traumatic Events Endorsed and Event Referenced as the Most Traumatic as a Function of Group

Control MVA-Low PTSD MVA-High PTSD

Trauma Type n (%) n (%) n (%) Endorsed Traumatic Event Natural Disaster 5 (7.9) 4 (8.7) - - Accident Other than MVA 1 (1.6) 7 (15.2) 2 (11.1) War-related 1 (1.6) 2 (4.3) - - Unexpected Death 19 (30.2) 17 (37.0) 12 (66.7) Robbery - - 1 (2.2) - - Physical Assault 6 (9.5) 6 (13.0) 3 (16.7) Sexual Assault 2 (3.2) 3 (6.5) 2 (11.1) Witnessing Assault 3 (4.8) 4 (8.7) 3 (16.7) Illness 5 (7.9) 3 (6.5) 3 (16.7) Other 8 (12.7) 5 (10.9) 2 (11.1) No Trauma 33 (52.4) - - - - Most Traumatic Event MVA - - 20 (43.5) 7 (38.9) Natural Disaster 2 (3.2) - - - - Accident Other than MVA - - 3 (6.5) - - War-related - - 1 (2.2) - - Unexpected Death 16 (25.4) 10 (21.7) 8 (44.4) Robbery - - - - - - Physical Assault 4 (6.3) 1 (2.2) - - Sexual Assault 1 (1.6) 2 (4.3) - - Witnessing Assault 1 (1.6) 1 (2.2) 2 (11.1) Illness 1 (1.6) 1 (2.2) - - Other 6 (9.5) 7 (15.2) 1 (5.6) No Referenced Trauma 32 (50.8) - - - - Note. Table lists frequencies and percentages as a function of group assignment. MVA = Motor Vehicle Accident.

45

Table 3. Self-report Measures Mean Score as Function of Group

Control MVA-Low PTSD MVA-High PTSD

Questionnaire M SD S (SE=.30) K (SE=.60) M SD S (SE=.35) K (SE=.69) M SD S (SE=.54) K (SE=1.04) STAI-State 40.03 11.37 .04 -.59 39.41 10.34 .60 -.01 43.00 12.52 -.30 -.83 STAI-Trait 42.23 10.37 .16 -.63 40.33 10.23 .49 -.53 47.00 13.96 .05 -.39 ACS 51.17 7.90 .54 .32 51.59 9.26 .19 -.83 51.28 11.58 .53 .76 ERQ-R 27.29 7.37 -.06 -.30 26.85 7.53 -.18 -.48 27.67 9.20 .13 -.35 ERQ-S 14.13 5.73 .14 -.84 11.61 4.65 .48 -.65 12.89 5.62 .81 - .41 AUDIT 2.97 2.45 .17 -1.39 3.39 1.95 -.09 - .94 3.56 2.36 .12 -1.13 PCL-S MVAa Total MVA - - - - 20.70 4.00 1.72 3.83 33.72 1.89 .34 -1.47 Re-experiencing MVA - - - - 6.26 2.03 2.80 10.97 11.56 3.79 .49 -1.45 Avoidanceb MVA - - - - 3.54 .75 1.32 1.36 6.39 2.30 1.18 3.15 Numbingb MVA - - - - 4.37 .83 2.91 9.36 5.56 2.09 1.28 .97 Hyperarousal MVA - - - - 6.52 2.79 2.94 9.36 10.22 3.12 -.01 -.83

M SD S (SE=.42) K (SE=.82) M SD S (SE=.46) K (SE=.89) M SD S (SE=.66) K (SE=1.28)

PCL-S Otherc Total Other 22.35 5.77 2.12 5.08 21.46 2.75 .77 .99 37.91 11.87 .81 .17 Re-experincing Other 6.45 1.80 1.41 1.13 6.46 1.53 1.02 .40 11.18 4.29 .47 -1.59 Avoidance Other 3.94 .93 .67 -.41 4.08 .98 1.23 2.14 7.36 1.96 .44 -.25 Numbing Other 5.06 1.79 1.77 2.21 4.38 .80 2.16 4.07 8.18 3.57 .09 -1.55 Hyperarousal Other 6.90 3.35 3.09 10.91 .51 2.60 2.84 10.25 11.18 4.79 .56 -.27 Note. M = Mean; SD = Standard Deviation; S = Skew; K = Kurtosis, SE = Standard Error; STAI-State = State-Trait Anxiety Inventory-State Score; STAI-Trait = State-Trait Anxiety Inventory-Trait Score; ACS = Attentional Control Scale Score; ERQ-R = Emotion Regulation Questionnaire-Reappraisal Score; ERQ-S = Emotion Regulation Questionnaire-Suppression Score; AUDIT = Alcohol Use Disorder Identification Test Score; PCL-S = Posttraumatic Stress Disorder Checklist-Stressor Specific; MVA = Motor Vehicle Accident. aAll participants with a motor vehicle accident history completed the PCL-S in reference to that event. bMean scores are presented separately for the Avoidance and Numbing subscales as DSM-V makes a distinction between these two symptom clusters. However, the combined score was used for PTSD classification to remain consistent with previous literature making use of the PCL-S for DSM-IV. cA subset of the control group (n = 34), MVA-Low PTSD symptoms group (n = 26), and MVA-High PTSD symptoms group (n = 11) indicated having experienced a traumatic event other than a motor vehicle accident and completed the PCL-S in reference to another event.

46

as a function of group in Table 4, 5, and 6. Few statistically significant correlations were

found between the scores on the self-report measures and the attention bias indices and

none of the correlations supported a specific pattern replicated across the groups.

Accordingly, the self-report measures were not included in further analyses.

The mean orienting and disengaging indices are presented as a function of group

and trial type in Table 7. The statistical significance of the orienting and disengaging

indices was assessed using a series of one sample t-test with one-tailed significance.

Contrary to Hypothesis 1, the MVA-Low PTSD group and the MVA-High PTSD group

did not display a statistically significant facilitated attention bias at 100 ms SOA (all ps >

.05). The Control group (p = .09) and the MVA-High PTSD group (p = .06) demonstrated

an avoidance bias for mild threat words that was approaching statistical significance.

Contrary to Hypothesis 2, the MVA-Low PTSD group and the MVA-High PTSD group

also did not demonstrate a difficulty in disengagement bias at 500 ms SOA (all ps > .05)

and the Control group demonstrated a difficulty in disengagement bias towards mild

threat words that was trending towards statistical significance (p = .05). Contrary to

Hypothesis 3, the MVA-Low PTSD group and the MVA-High PTSD group did not

display an avoidance bias at 1250 ms SOA (all ps > .05).

The MVA-High PTSD group and the MVA-Low PTSD group did not display the

expected directionality for the orienting and disengaging indices; however, the indices

were still analyzed to assess for differences within groups (i.e., SOA, threat level) and

between groups using two separate mixed-model ANOVAs. Contrary to Hypothesis

4 and 5, the ANOVA for the orienting indices failed to demonstrate a statistically

significant main effect of group, SOA, or strength (all ps > .05) using Greenhouse-

47

Table 4. Summary of Intercorrelations for Scores on the STAI, ACS, ERQ, and the Orienting and Disengaging Indices for the Control Group

Measure 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 1. STAI-State - 2. STAI-Trait .82** - 3. ACS -.48** -.48** -

4. ERQ-R -.35** -.44** .12 - 5. ERQ-S .02 .10 .12 -.12 - 6. 100OM -.21 -.18 -.08 .09 .20 - 7. 100OS -.22 -.19 .01 .17 .07 .33** -

8. 100DM .06 .10 .01 .06 -.13 -.20 -.34** -

9. 100DS .03 .05 .10 .03 .08 -.24 .01 .40** - 10. 500OM -.06 -.14 -.12 -.03 .05 .07 -.27* -.14 -.31* - 11. 500OS -.02 .01 -.11 -.00 .00 .03 -.40** .14 .20 .37** - 12. 500DM .09 .12 .08 .09 .08 .01 .24 .27* .49** -.36** -.07 - 13. 500DS -.14 .000 .04 -.08 -.01 .45** .30* -.10 .11 -.16 -.07 .18 - 14. 1250OM -.07 -.12 .07 -.05 -.09 .02 -.34** -.35** -.41** -.47** .11 -.48** -.03 - 15. 1250OS -.08 -.19 .07 .08 -.32* -.32* -.42** .01 -.17 .21 -.04 -.51** -.19 .43** - 16. 1250DM -.01 .10 .08 -.01 .15 04 .51** .07 .34** -.52** -.21 .37** .08 -.64** -.45** - 17. 1250DS .03 .11 .23 .07 .10 .09 .37** .10 .20 -.48** -.33** -.39** .08 -.50** -.55** .58**

Note. The Posttraumatic Stress Disorder Checklist-Specific total score was not included in the correlations table for the control group providing that it was not completed in reference to a motor vehicle accident. STAI-State = State-Trait Anxiety Inventory-State Score; STAI-Trait = State-Trait Anxiety Inventory-Trait Score; ACS = Attentional Control Scale Score; ERQ-R = Emotion Regulation Questionnaire-Reappraisal Score; ERQ-S = Emotion Regulation Questionnaire-Suppression Score; AUDIT = Alcohol Use Disorder Identification Test Score; 100OM = Orienting Index 100 ms SOA Mild Threat; 100OS = Orienting Index 100 ms SOA Strong Threat; 100DM = Disengaging Index 100 ms SOA Mild Threat; 100DS = Disengaging Index 100 ms SOA Strong Threat; 500OM = Orienting Index 500 ms SOA Mild Threat; 500OS = Orienting Index 500 ms SOA Strong Threat; 500DM = Disengaging Index 500 ms SOA Mild Threat; 500DS = Disengaging Index 500 ms SOA Strong Threat; 1250OM = Orienting Index 1250 ms SOA Mild Threat; 1250OS = Orienting Index 1250 ms SOA Strong Threat; 1250DM = Disengaging Index 1250 ms SOA Mild Threat; 1250DS = Disengaging Index 1250 ms SOA Strong Threat; SOA = Stimulus Onset Asynchrony. * p < .05. ** p < .01.

48

Table 5. Intercorrelations for Scores on the STAI, ACS, ERQ, PCL-S, and the Orienting and Disengaging Indices for the MVA-Low PTSD Symptoms Group

Measure 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 1. STAI-State 2. STAI-Trait .83** 3. ACS -.24 -.31* 4. ERQ-R -.07 -.20 .28 5. ERQ-S .03 -.12 -.10 .17 6. PCL-S MVA .24 .17 .04 .04 .35* 7. 100OM .06 .08 .03 .27 .33* .18 8. 100OS .18 .17 .03 .21 .19 -.08 .51** 9. 100DM -.07 -.06 .14 -.21 -.42** -.20 -.52** -.01

10. 100DS -.04 -.05 .08 -.23 -.29 -.13 -.43** -.01 .39**

11. 500OM .05 .03 .18 -.22 -.15 -.01 -.31* -.12 .53** .16 12. 500OS -.17 -.28 .02 -.18 -.03 -.14 -.30* -.26 .13 -.17 .35* 13. 500DM -.11 -.04 .02 .06 -.06 -.17 -.16 -.06 .05 .24 -.40** -.45** 14. 500DS -.08 -.08 -.03 -.02 -.10 -.02 -.25 -.09 -.18 .15 -.48** -.22 .60** 15. 1250OM -.01 -.15 .09 -.20 -.18 -.08 -.48** -.17 .41** .56** .06 -.02 .20 .24

16. 1250OS .02 .01 .23 -.04 .03 -.11 .28 .13 .04 -.07 .02 -.01 -.09 -.21 .16 17. 1250DM -.18 -.07 -.24 .18 .13 -.05 .20 .13 -.31* -.13 -.32* -.11 .06 .05 --.54** -.43** 18. 1250DS -.27 -.03 -.14 -.11 .05 .13 .19 .03 -.24 -.17 -.20 -.25 .26 .38** -.43** -.27 .45**

Note. STAI-State = State-Trait Anxiety Inventory-State Score; STAI-Trait = State-Trait Anxiety Inventory-Trait Score; ACS = Attentional Control Scale Score; ERQ-R = Emotion Regulation Questionnaire-Reappraisal Score; ERQ-S = Emotion Regulation Questionnaire-Suppression Score; AUDIT = Alcohol Use Disorder Identification Test Score; PCL-S MVA = Posttraumatic Stress Disorder Checklist-Stressor Specific Total Score in reference to a motor vehicle accident; 100OM = Orienting Index 100 ms SOA Mild Threat; 100OS = Orienting Index 100 ms SOA Strong Threat; 100DM = Disengaging Index 100 ms SOA Mild Threat; 100DS = Disengaging Index 100 ms SOA Strong Threat; 500OM = Orienting Index 500 ms SOA Mild Threat; 500OS = Orienting Index 500 ms SOA Strong Threat; 500DM = Disengaging Index 500 ms SOA Mild Threat; 500DS = Disengaging Index 500 ms SOA Strong Threat; 1250OM = Orienting Index 1250 ms SOA Mild Threat; 1250OS = Orienting Index 1250 ms SOA Strong Threat; 1250DM = Disengaging Index 1250 ms SOA Mild Threat; 1250DS = Disengaging Index 1250 ms SOA Strong Threat; SOA = Stimulus Onset Asynchrony. * p < .05. ** p < .01.

49

Table 6. Intercorrelations for Scores on the STAI, ACS, ERQ, PCL-S, and the Orienting and Disengaging Indices for the MVA-High PTSD Symptoms Group

Measure 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 1. STAI-State 2. STAI-Trait .83** 3. ACS -.34 -.58* 4. ERQ-R -.57* -.69** .59* 5. ERQ-S -.01 -.03 -.08 .14 6. PCL-S MVA .17 .21 -.24 -.27 -.47* 7. 100OM .13 .02 .37 .13 -.42 .23 8. 100OS -.02 -.25 .49* .09 .10 .11 .17 9. 100DM -.17 .01 -.26 .14 .36 -.52* -.36 -.70**

10. 100DS .21 .25 -.38 -.24 .26 .06 -.58* -.36 .19

11. 500OM .05 .16 -.49* -.52* -.03 .19 -.40 -.10 .14 .14 12. 500OS -.08 -.01 -.09 -.25 -.04 .23 .23 .27 -.24 -.15 .53* 13. 500DM -.19 -.48* .48* .62** -.05 -.35 .17 .15 .19 -.43 -.30 -.43 14. 500DS -.30 -.30 .55* .40 -.19 -.22 .51* -.10 .08 -.41 -.70** -.35 .24 15. 1250OM -.07 .19 -.61** -.19 .03 .11 -.41 -.54* .31 .25 .03 -.24 -.43 .07

16. 1250OS -.13 -.13 -.18 .20 .35 -.24 -.73** -.20 .27 .44 .09 -.29 -.03 -.30 .48* 17. 1250DM -.07 .21 -.24 -.27 -.16 .37 .14 -.15 .03 .03 .55* .64** -.40 -.28 -.07 -.30 18. 1250DS -.29 -.12 .09 -.16 -.13 .35 .36 .35 -.25 -.22 .21 .68** -.22 -.10 -.37 -.59* .53*

Note. STAI-State = State-Trait Anxiety Inventory-State Score; STAI-Trait = State-Trait Anxiety Inventory-Trait Score; ACS = Attentional Control Scale Score; ERQ-R = Emotion Regulation Questionnaire-Reappraisal Score; ERQ-S = Emotion Regulation Questionnaire-Suppression Score; AUDIT = Alcohol Use Disorder Identification Test Score; PCL-S MVA = Posttraumatic Stress Disorder Checklist-Stressor Specific Total Score in reference to a motor vehicle accident; 100OM = Orienting Index 100 ms SOA Mild Threat; 100OS = Orienting Index 100 ms SOA Strong Threat; 100DM = Disengaging Index 100 ms SOA Mild Threat; 100DS = Disengaging Index 100 ms SOA Strong Threat; 500OM = Orienting Index 500 ms SOA Mild Threat; 500OS = Orienting Index 500 ms SOA Strong Threat; 500DM = Disengaging Index 500 ms SOA Mild Threat; 500DS = Disengaging Index 500 ms SOA Strong Threat; 1250OM = Orienting Index 1250 ms SOA Mild Threat; 1250OS = Orienting Index 1250 ms SOA Strong Threat; 1250DM = Disengaging Index 1250 ms SOA Mild Threat; 1250DS = Disengaging Index 1250 ms SOA Strong Threat; SOA = Stimulus Onset Asynchrony. * p < .05. ** p < .01.

50

Table 7. Mean Orienting and Disengaging Indices as a Function of Group and Trial Type

Control MVA-Low PTSD MVA-High PTSD

Attention Bias Index M SD S (SE=.30) K (SE=.60) M SD S (SE=.35) K (SE=.69) M SD S (SE=.54) K (SE=1.04)

100 MS Orienting-M -12.03 55.44 .35 2.37 -7.07 67.69 -.97 4.28 -21.39 44.12 -.37 1.72 Orienting-S 2.52 63.07 -.33 5.02 .27 44.37 .04 2.37 -6.09 49.87 .15 -.44 Disengaging-M 8.49 64.52 1.31 6.64 2.70 50.29 .79 1.58 -22.65 32.19 -.07 -.37 Disengaging-S 29.04 84.76 2.15 5.54 24.57 64.56 1.78 6.09 8.28 47.64 .89 2.02 500 MS Orienting-M 5.74 48.53 -.21 2.48 -2.06 57.85 .75 5.72 -6.25 33.69 .06 -.86 Orienting-S 7.68 63.40 .65 1.33 -5.37 60.16 -1.10 8.61 -5.92 51.33 -.81 2.32 Disengaging-M 14.66 64.57 2.52 12.30 7.59 51.28 .28 .51 -2.37 34.94 -1.73 4.22 Disengaging-S -6.25 55.94 .39 4.94 7.81 53.70 .37 3.28 -.27 35.96 -.37 -.25 1250 MS Orienting-M -4.55 47.39 -1.49 5.59 1.06 50.67 1.37 6.07 4.91 45.14 .38 -.56 Orienting-S -10.78 64.41 -4.01 23.07 -6.10 39.08 -.19 -.56 2.10 38.71 .34 .52 Disengaging-M -1.06 61.42 2.00 11.52 4.08 45.49 -.52 .48 -1.05 38.29 .20 .71 Disengaging-S 14.14 63.42 2.12 9.50 2.16 50.26 .49 4.02 -8.05 32.26 -1.37 2.46 Note. A positive orienting index indicates facilitated attention to threat and a negative orienting index suggests avoidance of threat. A positive disengagement index indicates difficulty in disengagement from threat and a negative disengagement index suggests facilitated disengagement from threat. M = Mean; SD = Standard Deviation; S = Skew; K = Kurtosis, SE = Standard Error; 100 MS = 100 ms SOA; 500 MS = 500 ms SOA; 1250 MS= 1250 ms SOA; Orienting-M = Orienting Index Mild Threat; Orienting-S = Orienting Index Strong Threat; Disengaging-M = Disengaging Index Mild Threat; Disengaging-S = Disengaging Index Strong Threat; SOA = Stimulus Onset Asynchrony.

51

Geisser correction. For the disengaging indices, the ANOVA using a Greenhouse-Geisser

correction demonstrated a statistically significant interaction effect between SOA and

threat level, F(1.90, 235.73) = 5.68, p = .005, η2p = .04. Pairwise contrasts indicated that

the disengaging indices for mild and strong threat differed between the 100 ms and the

1250 ms SOA conditions, F(1, 124) = 5.27, p = .02, η2p = .04. At the 100 ms SOA, the

disengaging index was negative for the mild threat level and positive for the strong threat

level whereas at the 1250 ms SOA the disengaging index was nearing baseline (i.e., zero)

for both levels of threat. Accordingly, the disengaging index for mild threat increased as

SOA increased and the disengaging index for strong threat decreased as SOA increased.

Although the main effect of threat level was approaching statistical significance (p = .06),

contrary to Hypothesis 4 and 5, the ANOVA for disengaging indices did not demonstrate

a statistically significant main effect of group, SOA, or threat level and no further

interaction effects were identified (all ps < .05).

3.2. Exploratory post hoc Analyses

The null hypothesis could not be rejected for all hypotheses; nevertheless,

unplanned exploratory post hoc analyses were conducted with the sample data to provide

additional support for the current results, as well as directions for future research. Dot

probe mean reaction times as a function of group, SOA, congruency, and threat level are

presented in Table 8. Dot probe mean reaction times were analyzed by computing the

traditional bias index (e.g., Asmundson & Hadjistavropoulos, 2007; MacLeod &

Mathews, 1988), which is more commonly used in the literature than the orienting and

disengaging indices, and which has been used in a previous investigation of attentional

bias in MVA survivors (Bryant & Harvey, 1997). The bias index was calculated by

52

Table 8. Mean Non-Indexed Dot Probe Reaction Times as a Function of Group and Trial Type

Control MVA-Low PTSD MVA-High PTSD

Trial Type M SD S (SE=.30) K (SE=.60) M SD S (SE=.35) K (SE=.69) M SD S (SE=.54) K (SE=1.04)

100 MS Incongruent-M 533.02 171.22 2.64 7.24 504.10 138.75 2.60 8.27 463.24 56.99 .53 .60 Incongruent-S 553.56 186.80 2.64 7.86 525.94 148.99 2.36 6.19 494.16 87.55 1.77 4.15 Congruent-M 536.55 144.59 2.50 7.07 508.47 149.49 2.79 8.71 507.27 79.10 1.03 .32 Congruent-S 522.00 172.43 3.35 12.33 501.13 122.04 3.34 15.30 491.97 60.61 .46 -.36 500 MS Incongruent-M 497.55 145.90 2.06 3.83 460.25 100.18 1.58 2.59 433.39 38.74 .82 -.14 Incongruent-S 476.64 132.89 3.12 11.87 460.47 94.01 1.23 2.27 435.49 46.57 .22 -1.14 Congruent-M 477.15 112.24 2.06 4.32 454.72 79.06 1.16 2.07 442.00 50.94 .70 .29 Congruent-S 475.21 104.65 1.80 3.55 458.03 104.02 1.62 2.97 441.68 51.09 1.07 1.19 1250 MS Incongruent-M 444.78 84.11 1.64 -2.57 425.92 55.46 .46 -.22 418.59 47.17 .21 .30 Incongruent-S 459.98 103.17 1.87 4.06 424.00 68.11 1.47 2.89 411.60 41.13 .27 -.26 Congruent-M 450.38 93.93 1.91 4.39 420.78 55.11 .84 1.21 414.74 54.13 .86 .51 Congruent-S 451.55 102.75 2.76 11.20 435.04 81.58 .81 -.05 439.93 85.58 2.20 6.39 Note. The probe appears behind the neutral word for incongruent trials and behind the threatening word for congruent trials. M = Mean; SD = Standard Deviation; S = Skew; K = Kurtosis, SE = Standard Error; 100 MS = 100 ms SOA; 500 MS = 500 ms SOA; 1250 MS = 1250 ms SOA; Incongruent-M = Incongruent Trial Mild Threat; Incongruent-S = Incongruent Trial Strong Threat; Congruent-M= Congruent Trial Mild Threat; Congruent-S = Congruent Trial Strong Threat; SOA = Stimulus Onset Asynchrony.

53

subtracting mean reaction times to congruent trials from mean reaction times to

incongruent trials (Koster, Verschuere, et al., 2005). Mean bias index scores as a function

of group, SOA, and threat level are presented in Table 9. Congruent with the attention

bias literature, the bias index was analyzed to assess for differences within groups (i.e.,

SOA, congruency, threat level) and between groups using a mixed-model ANOVA.

Using Greenhouse-Geisser correction, results demonstrated that there was a statistically

significant interaction effect between SOA and threat level, F(1.77, 219.77) = 6.68, p =

.002, η2p = .05. Pairwise contrasts suggested that the mean bias index for mild and strong

threat differed between the 100 ms and the 1250 ms SOA conditions, F(1, 124) = 7.38, p

= .008, η2p = .06. At the 100 ms SOA, the bias index was negative for the mild threat

level and positive for the strong threat level whereas at the 1250 ms SOA the bias index

was nearing baseline (i.e., zero) for both levels of threat. Accordingly, the bias index for

mild threat increased as SOA increased and the bias index for strong threat decreased as

SOA increased. The ANOVA did not indicate a statistically significant main effect of

group, SOA, or threat level and no further interaction effects were identified (all ps <

.05); however, the main effect of group was approaching statistical significance (p = .08).

Mean scores for the orienting and disengaging indices used in the main analyses

were widely dispersed in the current sample and did not reflect the directionality of

attention bias expected as per Hypotheses 1, 2, and 3. The scores were found on both

sides of zero based on group and trial type. Between group comparisons of the orienting

and disengaging indices using an ANOVA may have been impacted by a regression

towards the mean cancelling out possible differences between the groups. Accordingly,

the mean orienting and disengaging indices were further analyzed using an exploratory

54

Table 9. Mean Traditional Bias Index as a Function of Group and Trial Type

Control MVA-Low PTSD MVA-High PTSD

Trial Type M SD S (SE=.30) K (SE=.60) M SD S (SE=.35) K (SE=.69) M SD S (SE=.54) K (SE=1.04)

100 MS Bias-M -3.53 76.31 1.19 7.24 -4.37 59.97 .14 3.60 -44.04 44.22 -.03 -.03 Bias-S 31.55 106.21 1.81 5.62 24.83 78.07 1.75 4.82 2.19 55.02 .71 .37 500 MS Bias-M 20.40 65.44 .64 .98 5.53 60.33 -.76 3.82 -8.61 40.52 .44 -.74 Bias-S -9.89 39.42 -1.76 6.90 -.78 24.47 -1.13 3.23 1.54 21.97 .27 1.35 1250 MS Bias-M -5.60 48.19 -.69 -2.57 5.14 46.46 -.37 2.97 3.85 13.47 1.31 4.89 Bias-S 3.36 60.61 .56 1.89 -3.94 54.86 -.71 .92 -5.95 32.70 -1.90 5.86 Note. A positive bias index indicates faster reaction times when the probe appears behind the neutral word. A negative bias index indicates faster reaction times when the probe appears behind the threat word. M = Mean; SD = Standard Deviation; S = Skew; K = Kurtosis, SE = Standard Error; 100 MS = 100 ms SOA; 500 MS = 500 ms SOA; 1250 MS = 1250 ms SOA; Bias-M = Traditional Bias Index Incongruent Mild Threat; Bias-S = Traditional Bias Index Strong Threat; SOA = Stimulus Onset Asynchrony.

55

series of one sample t-tests with no a priori hypotheses and two-tailed significance. The

orienting and disengaging indices were not statistically significantly different (ps > .05)

from chance in any of the groups except for three indices. At 100 ms SOA, the Control

group, t(62) = 2.72, p = .03, r = .33, and the MVA-Low PTSD group, t(45) = 2.58, p =

.02, r = .36, displayed difficulty in disengagement from strong threat words; however, the

MVA-High PTSD group displayed “facilitated disengagement” for mild threat words,

t(17) = -2.99, p = .008, r = .59. The disengaging indices for the 100 ms SOA have been

presented as a function of group and threat level in Figure 2.

4.0 Discussion

The current investigation had two purposes. First, the investigation was designed

to clarify the directionality and time course of attentional bias for threat using a PTSD

sample and a contemporary detection dot probe task. The presentation of a probe at

different levels of SOA was used in an attempt to disentangle the relationship between

the cognitive mechanisms of facilitated attention to threat, difficulty in disengagement

from threat, and avoidance of threat. Second, the investigation was designed to evaluate

the three different components of attentional bias for threat in MVA survivors with high

PTSD symptoms, MVA survivors with low PTSD symptoms, and a control group with

no history of MVA or PTSD symptoms. The role of stimulus threat level in attentional

bias was also clarified through the use of mild and strong threat words.

4.1 Time Course of Attentional Bias for Threat

The first objective of the current investigation was to assess Cisler and Koster’s

(2010) framework of attentional bias for threat using a sample of individuals with PTSD

symptoms. Specifically, an attentional bias was expected for facilitated attention to threat

56

Figure 2. Mean Disengagement Bias Index at 100 ms SOA as a function of group assignment and threat level. A positive disengagement index indicates difficulty in disengagement from threat and a negative disengagement index suggests facilitated disengagement from threat. SOA = Stimulus Onset Asynchrony. * p < .05.

-30

-20

-10

0

10

20

30

40

Mild Strong

Mea

n D

isen

gage

men

t Ind

ex 1

00 m

s SO

A

Threat Level

Control

MVA-Low PTSD

MVA-High PTSD

*

* *

57

at 100 ms SOA, difficulty in disengagement from threat at 500 ms SOA, and avoidance

of threat at 1250 ms SOA. The current results did not support Cisler and Koster’s (2010)

framework regarding the time course and directionality of attentional bias for threat.

Contrary to the first hypothesis, the groups did not display facilitated attention to

threat at 100 ms SOA. Findings from the current investigation are inconsistent with past

investigations using the dot probe task (Carlson & Reinke, 2008; Mogg & Bradley, 2002;

Koster, Crombez, Verschuere, Vanvolsem, & De Houwer, 2007; Koster, Verschuere, et

al., 2005), yet consistent with one investigation making use of the spatial cueing task

(Fox, Russo, Bowles, & Dutton, 2001). The discrepancy may be due, in part, to dot probe

methodological considerations. All investigations finding a facilitated attention bias made

use of pictorial threat stimuli (i.e., images) whereas the spatial cueing task investigation

made use of semantic threat stimuli (i.e., words). Perhaps threatening words are not

salient enough to capture attention as defined by the facilitated attention construct.

Alternatively, two of the dot probe task investigations demonstrating a facilitated

attention bias made use of masked stimuli (Carlson & Reinke, 2008; Mogg & Bradley,

2002). Unmasked threat stimuli have longer stimulus exposure duration than masked

stimuli. Facilitated attention to unmasked threat stimuli may therefore occur at a time

point earlier than 100 ms (Carlson & Reinke, 2008). Furthermore, investigations of

masked threat stimuli may better allow for the detection of a facilitated attention response

generated by unconscious processes; however, the use of unmasked threat stimuli may

facilitate the use of conscious processes overshadowing the unconscious facilitated

attention response (Jolij & Lamme, 2005).

58

Contrary to the second hypothesis, the groups did not display difficulty in

disengagement from threat at 500 ms SOA, although the control group did display a trend

towards difficulty in disengagement from mild threatening words. The trend may have

resulted from the recognition of familiar words from a similar semantic category (i.e.,

MVA-related words) rather than from an attention bias. In the current investigation, the

difficulty in disengagement bias mainly appears to have occurred at 100 ms SOA.

Specifically, the MVA-High PTSD group displayed facilitated disengagement from mild

threat words and both the MVA-Low PTSD group and the Control group displayed

difficulty in disengagement from strong threat words. The current finding is incongruent

with several dot probe task investigations (Bardeen & Orcutt, 2011; Koster et al., 2004;

Koster, Verschuere, et al., 2005; Salemink et al., 2007) which have found a

disengagement effect at 500 ms and with a spatial cueing task investigation suggesting

that high trait anxious individuals display difficulty disengaging attention from threat at

100 ms (Koster et al., 2006). Nonetheless, the latter investigation does suggest that a

disengagement bias can occur at 100 ms.

Discrepancies in disengagement results between the current investigation and

previous research may be explained, in part, by method differences in the nature of the

threat stimuli used. Most investigations having found a difficulty in disengagement bias

at 500 ms made use of pictorial threat stimuli, as opposed to the semantic threat stimuli

used in the current investigation. Pictorial stimuli are processed in approximately 100-

150 ms (Thorpe, Fize, & Marlot, 1996), whereas semantic stimuli are processed in less

than 50 ms (Rayner, Inhoff, Morrison, Slowiaczek, & Bertera, 1981). In the current

investigation, the use of threatening words rather than threatening images may have

59

accelerated the attentional bias sequence such that by 100 ms participants were already

involved in more effortful cognitive processes (e.g., disengagement). Although

unexpected, the MVA-High PTSD group displaying facilitated disengagement from

threat at 100 ms is partly in line with previous investigations that found rapid

disengagement from threatening stimuli in anxiety samples (Koster et al., 2006; Garner et

al., 2006). The results also suggest that avoidance mechanisms may occur prior to 500 ms

and involve more rapid and automatic processes than previously suggested (Cisler &

Koster, 2010). Assuming that cognitive processing of stimuli mainly occurred at 100 ms

SOA, increased attentional resources may have been required earlier on. Consistent with

the current findings, increased need for attentional resources may have translated into

generally slower response times in the earlier SOA condition, which progressively

became faster as SOA increased.

Contrary to the third hypothesis, the groups did not display avoidance of threat at

1250 ms SOA; however, the High-PTSD group and the Control group both displayed a

trend towards avoidance of mild threatening words at 100 ms SOA. The current finding is

inconsistent with investigations that have demonstrated an avoidance bias during the late,

but not the early stages of processing (Garner et al., 2006; Koster, Verschuere, et al.,

2005; Mogg et al., 2004). Nonetheless, the use of word stimuli may have facilitated

processing and made it possible for avoidance to occur as early on as 100 ms. Further,

some investigations have found support for the avoidance of threat at earlier delays (e.g.,

200 ms; Koster et al., 2006; Koster et al., 2007) and other investigations have failed to

find an avoidance bias at longer delays (e.g., 1250 ms; Bradley, Mogg, Falla, &

Hamilton, 1998; Mogg, Bradley, Bono, & Painter, 2007). The tendency of the MVA-

60

High PTSD group to avoid MVA-related words is congruent with the current result

suggesting that they easily disengage their attention from such words. Reasons for the

control group displaying a tendency to avoid mild threat words are, however, less clear.

Previous investigations have suggested that the dot probe task can yield unreliable results

for healthy participants (Schmukle, 2005). Alternatively, participants in the control group

may have processed mild threat words more quickly due to their familiarity and their

grouping into one semantic category (i.e., MVA-related words). At 100 ms, attention may

have shifted away from the mild threat words in favor of the non-semantically related

neutral words.

The discrepancies found between the current results and the attentional bias

literature for anxiety disorders may also have been due to the manipulation of SOA rather

than stimuli exposure duration. In previous investigations, the presentation of stimuli for

varying amounts of time may have confounded results such that a participant’s response

would have been dependent on SOA, as well as the amount of time for which the stimuli

were presented. The attentional biases found at 500 ms and 1250 ms in investigations

manipulating exposure duration (e.g., Koster et al., 2004; Koster, Verschuere, et al.,

2005; Salemink et al., 2007) may have reflected the strategic cognitive mechanisms

associated with the presence of threatening stimuli in one’s visual field; in contrast, the

current results may better reflect the automatic cognitive mechanisms associated with the

initial processing of threat stimuli in one’s environment. Accordingly, Cisler and Koster’s

framework (2010) may provides a general framework for the directionality and time

course of attentional bias for threat; however, the specific time points (i.e., 100 ms, 500

ms, 1250 ms) at which each attention bias mechanism operates appears dependent on

61

several methodological factors (i.e., semantic vs. pictorial stimuli, masked vs. unmasked

stimuli, manipulation of exposure duration vs. SOA). Similarly, when processing

environmental cues, individuals may display an attentional bias for threat at different

time points or in different ways (i.e., avoiding vs. attending) depending on contextual

factors present at the time of cognitive processing. In other words, the attentional biases

may depend more heavily on idiosyncratic variables than previously thought.

4.2 Group Differences in Attentional Bias

Contrary to the fourth and the fifth hypotheses, the strength of the orienting and

disengaging indices did not differ based on group or threat level. Moreover, the

traditional bias index (e.g., Koster, Verschuere, et al., 2005; MacLeod & Mathews, 1988)

also suggested against between-group differences when accounting for SOA and threat

level. The result differs from previous literature that demonstrated group differences in

reaction time between individuals with PTSD and those without when assessed on several

attentional bias measures (e.g., Bryant & Harvey, 1995; Harvey et al., 1996; McNally et

al., 1990; Pineles et al., 2007, 2009). Specifically, current results are incongruent with

past research making use of a sample of MVA survivors and a dot probe task (Bryant &

Harvey, 1997); however, the previous Bryant and Harvey investigation cannot be directly

compared to the current investigation because of differences in the procedure used to

administer the dot probe task.

The majority of investigations highlighting reaction time differences between

individuals with PTSD and those without made use of the emotional Stroop task. The

robustness of the emotional Stroop effect in PTSD samples appears to have been

overestimated in the literature. Research suggests that only 44% of peer-reviewed

62

published studies report group reaction time differences to threat words and that these

studies tend to be published in higher impact journals (Kimble et al., 2009). Moreover, an

examination of dissertation studies suggests that 75% of dissertations do not find reaction

times suggestive of an attentional bias in individuals with PTSD specifically (Kimble et

al., 2009). A similar review of the literature has not been conducted on investigations

making use of the dot probe task. That said, contemporary studies using the dot probe

task with anxiety samples have produced inconsistent results (Bockstaele et al., 2014) and

the possibility that reaction time differences between individuals with and without PTSD

are weak or unreliable cannot be excluded.

Assuming that group differences do exist in samples of individuals with and

without PTSD, several explanations can be put forth to explain the current findings. The

MVA-High PTSD group included MVA survivors with subsyndromal PTSD. It is

possible that reaction times are highly sensitive to PTSD symptom severity such that only

individuals endorsing full PTSD symptoms display reaction times indicative of an

attentional bias (Bryant & Harvey, 1997). That said, subsyndromal PTSD in MVA

survivors is associated with increased anxiety (e.g., Blanchard et al., 1995) and several

investigations have found individuals with anxiety to display significantly different

reaction times to threatening stimuli compared to individuals without anxiety (e.g.,

Koster, Verschuere, et al., 2005; MacLeod & Mathews, 1988; see Bar-Haim et al., 2007

for review).

The MVAs experienced by current participants may have been qualitatively less

severe than MVAs experienced by participants in previous research. Previous

investigations have recruited MVA survivors with PTSD from community hospital

63

settings and, on average, participants reported having been hospitalized for up to two

weeks (Bryant & Harvey, 1995, 1997; Harvey et al., 1996). The current investigation

only required the experience of a MVA that was severe enough to warrant filing of a

police report. Accordingly, endorsement of a MVA was possible in the absence of a

hospital admission. Further, despite reporting high PTSD symptoms, more than half the

MVA-High PTSD group indicated having experienced an event that was more traumatic

than the MVA.

The time elapsed since the MVA could also have impacted reaction times on the

dot probe task. In previous investigations of MVA survivors identifying a significant

difference in reaction time between the groups, accidents had occurred less than 5 months

prior to the attentional bias assessment (Bryant & Harvey, 1997; Harvey et al., 1996).

Moreover, previous research conducting assessments 6-24 months following an MVA

failed to identify reaction times indicative of an attentional bias for threat (Devineni et al.,

2004). In the current investigation, over 30 months had elapsed since the MVA. Due to

the prominence of MVA related cues in the environment (e.g., roads, cars, reports of

accidents in the news), habituation to such cues may have naturally occurred over time

and weakened the strength of the attentional bias (Pineles et al., 2007, 2009), in turn

reducing group differences in reaction time.

Finally, the personal relevance of the threat stimuli, or lack thereof, could have

impacted the nature and strength of the attentional biases displayed by participants in the

current investigation. Previous research using the emotional Stroop task (Riemann &

McNally, 1995) and the dot probe task (Mogg, Bradley, Hyare, & Lee, 1998) suggests

that attentional biases may largely be produced by that personal relevance rather than the

64

valence of the stimuli used to assess the biases. The mild threat stimuli (e.g., highway) in

the current investigation may have been strongly personally relevant to the MVA-High

PTSD group; however, the mild threat stimuli may also have been relevant to participants

in the MVA-Low PTSD group and the Control group as a result of their familiarity (e.g.,

one may have to drive on a highway daily to get to work). As a result, differences in

attentional biases may not have emerged between the groups. Similarly, the strong threat

stimuli (e.g., blood) used in the current investigation may have been too general to

produce a distinct attentional bias in the MVA-High PTSD group.

4.3. Group Differences in Attentional Pattern

Results of the current investigation demonstrated the presence of orienting and

disengaging indices on both sides of zero depending on group and threat level. As a

result, direct comparisons of orienting and disengaging indices may have yielded a

regression towards the mean and cancelled out possible effects. Nonetheless, inferences

can still be made about potentially different patterns of attention between the groups.

In the current investigation, the MVA-High PTSD group displayed a markedly

different attention pattern than the control group and the MVA-Low PTSD group at 100

ms SOA. Specifically, the MVA-High PTSD group displayed facilitated disengagement

from mild threat words. No such effect was found for strong threat words. Conversely,

participants in the control group and the MVA-Low PTSD did not demonstrate a specific

bias for mild threat words but displayed difficulty disengaging their attention from strong

threat words. Providing that significant bias indices are different from zero and that non-

significant bias indices (i.e., when a group does not show a specific attention bias) equal

zero, the current results could be interpreted as suggesting that the attention bias indices

65

are significantly different between the groups; that said, additional research would

strengthen the validity of such interpretations.

Hypothesis five was not directly supported; however, the current results suggest

stimuli of different threat levels yield different attention patterns as a function of group.

The mild threat words used in the current investigation were directly related to motor

vehicles and road traffic but were not inherently threatening words. Conversely, the

strong threat words broadly related to motor vehicle accidents (e.g., crash, blood) but

better reflected the concept of general threat. Congruent with previous investigations, the

finding that MVA survivors with high PTSD symptoms easily disengage from mild threat

words but not strong threat words reflects an attentional bias for trauma-related threat but

not general threat (Beck et al., 2001; Bryant & Harvey, 1997, Foa et al., 1991; McNally

et al., 1990; Pineles et al., 2009). The current finding also strengthens previous

assumptions suggesting that strongly personally relevant stimuli produce larger

attentional biases than mildly personally relevant or neutral stimuli, irrespective of

valence (Riemann & McNally, 1995).

In line with cognitive models of anxiety disorders, avoidance of trauma-related

threat may provide temporary relief for MVA survivors with high PTSD symptoms;

however, avoidance likely also interferes with the re-appraisal of threat, resulting in a

rapid resurgence of anxiety and the maintenance of PTSD symptoms (Beck & Clark,

1997). The role of avoidance in PTSD is supported by clinical investigations suggesting

that the most effective psychological treatments for PTSD are interventions requiring the

client to engage with trauma-related threat (Bisson et al., 2007). Current findings are also

in line with a recent US military investigation suggesting that avoidance of threat is

66

associated with increased PTSD symptoms 4 months following combat exposure (Sipos,

Bar-Haim, Abend, Adler, & Bliese, 2013).

Although unexpected, the control group and the MVA-Low PTSD group both

displaying difficulty disengaging their attention from strong threat words may be a key

difference between individuals with and without PTSD. Theoretical models of attentional

bias in anxiety emphasize that attending to imminent threat during early stages of

processing may be a normal and adaptive response (Eccleston & Crombez, 1999;

Mathews & Mackintosh, 1998; Mogg & Bradley, 1998). Several investigations have

found evidence that control subjects engage with (i.e., avoidance or difficulty in

disengagement) strongly threatening stimuli presented for a short period of time (i.e., <

500 ms; Koster et al., 2004; Koster, Verschuere et al., 2005; Wilson & MacLeod, 2003;

Yiend & Mathews, 2001). Accordingly, individuals with PTSD may avoid trauma-related

threat information while also failing to preferentially engage with generally threatening

material in their environment. The current data does not allow for the establishment of

causality; however, an individual’s failure to adaptively engage with threat stimuli

present at the time of trauma may increase the risk of developing PTSD by interfering

with cognitive processing and memory consolidation of the trauma (e.g., McCleery &

Harvey, 2004; Van der Kolk, 1994). In parallel, previous research has shown that threat

avoidance during an acute stressor predicts higher levels of PTSD symptoms at 1 year

follow up (Wald et al., 2011). Threat avoidance prior to combat deployment has also

been shown to predict higher levels of PTSD symptoms at the time of deployment

(Beevers et al., 2011).

4.4. Methodological Implications

67

The attentional bias literature includes several discrepant findings. To date, no

single theoretical model appears to have fully captured the cognitive processes involved

in attentional bias for threat in anxiety pathologies and PTSD more specifically. As

highlighted by the current results, divergences may in part be explained by

methodological considerations. The current PTSD sample demonstrated a limited

attentional bias for semantic threat. The selected semantic threat stimuli appear to have

produced robust effects in previous research with the emotional Stroop task (Bryant &

Harvey, 1995; Harvey et al., 1996); however, threatening images may be a more sensitive

tool to detect attentional biases for threat using the dot probe task (Bardeen & Orcutt,

2011; Sipos et al., 2013; Wald et al., 2011) or the visual search task (Pineles, 2007,

2009). As previously argued, the qualitative nature of the threat stimuli used (i.e., images

vs. words, subliminal vs. supraliminal) may also impact the time course of attentional

bias for threat such that a specific SOA condition may produce different biases (e.g.,

facilitated attention and avoidance) in different investigations.

In the current investigation, no between group differences were found when

directly comparing the groups based on the orienting and disengaging indices, as well as

based on a more traditional bias index. Nonetheless, differences in attention patterns

emerged between individuals with high PTSD symptoms and those without when

evaluating the directionality of the orienting and disengaging indices compared to

baseline. The contemporary dot probe paradigm may be more sensitive to attentional bias

for threat and provide more precise results as to the directionality of the attentional bias

in MVA survivors with PTSD (Bryant & Harvey, 1997). Accordingly, the contemporary

68

dot probe task would benefit from being used in future investigations of attentional bias

for threat in anxiety pathologies.

4.5 Clinical Implications

The current investigation has potentially important treatment implications for

MVA survivors with PTSD and individuals with PTSD more broadly. Simple and cost-

efficient attention bias modification programs have been developed for the treatment of

anxiety pathologies (Bar-Haim, 2010) and may prove beneficial for the treatment of

PTSD. Attention bias modification programs have typically been used to re-train

attention away from threat in generalized anxiety disorder and social anxiety disorder

samples (e.g., Amir, Beard, Burns, & Bomyea, 2009; Amir, Beard, Taylor, Klumpp, &

Elias, 2009; Schmidt, Richey, Buckney, & Timpano, 2009); however, current results

suggest attention bias modification programs for individuals with PTSD may benefit

from being designed to re-train attention towards threat rather than away from threat.

Current results also reiterate the importance of using trauma exposure techniques in

traditional clinical interventions for PTSD (e.g., cognitive-behaviour therapy, prolonged

exposure therapy). Pending future research supporting the use of attention bias

modification programs for PTSD, governmental bodies such as Saskatchewan

Government Insurance may wish to integrate such programs in their post-MVA

rehabilitation policies.

Avoidance of threat during acute stress has been posited as a risk factor for the

development of PTSD (Beevers et al., 2011; Wald et al., 2011) and ensuring that

individuals attend to life threatening stimuli at the time of a MVA may help prevent the

development of PTSD. Replications and extensions of the current finding that individuals

69

without PTSD engage with strong threat words whereas individuals with high PTSD

symptoms do not may highlight the benefits of using attention bias modification

programs as a preventive strategy. Indeed, governmental bodies issuing driving licenses

may wish to incorporate the completion of such programs as a requirement for obtaining

or renewing a license.

4.6 Limitations and Future Directions

The current investigation has several limitations that provide directions for future

research. The sample size for the MVA-High PTSD group fell short of the originally

desired sample; moreover, the majority of participants in the MVA-high PTSD group met

criteria for probable subsyndromal PTSD but not full PTSD. The attention biases of

MVA survivors with subsyndromal PTSD may differ from those of both MVA survivors

without PTSD and MVA survivors with full PTSD (Bryant & Harvey, 1997). Future

research using a contemporary dot probe task should seek to recruit a larger sample and

distinguish between such groups.

The current sample was also self-recruited and the majority of MVA survivors

who participated in the current investigation reported no PTSD symptoms. There may

have been a self-recruitment bias such that only individuals with limited distress about

their MVA participated in the research. Recruitment of participants through online

community advertising and the psychology participant pool at the University of Regina

also may have resulted in a sample of participants who experienced MVAs less severe

than those traditionally reported by participants in MVA investigations (Bryant &

Harvey, 1995, 1997, Harvey et al., 1996). Future research should seek to recruit MVA

survivors in hospital settings in an attempt to ensure a minimum severity threshold for the

70

MVA. Participant recruitment in hospital settings would also help ensure that all

participants have recently experienced a MVA (e.g., within a year).

The current investigation used the PCL-S self-report measure to assess PTSD

DSM-IV-TR criteria (APA, 200). Several symptoms on the PCL-S are non-specific to

PTSD (e.g., difficulty sleeping) and may have been endorsed in the absence of a clinical

presentation for PTSD. The PCL-S has high convergent validity with the Clinician

Administered PTSD Scale in samples of MVA survivors (Blanchard et al., 1996);

however, a structured diagnostic interview would have been required to better support the

clinical status of participants. Comorbid diagnoses were also not assessed in the current

investigation but could have impacted the attentional bias for threat (e.g., Mogg &

Bradley, 2005). Future investigations making use of structured diagnostic interviews

should seek to control for comorbid diagnoses such as depression.

Important changes were recently made to the PTSD diagnostic criteria in DSM-5

(APA, 2013). A self-report measure (i.e., PTSD Checklist for DSM-5; Weathers, Litz, et

al., 2013) and a structured diagnostic interview (i.e., Clinician Administered PTSD Scale

for DSM-5; Weathers, Blake, Schnurr, Marx, & Keane, 2013) for DSM-5 PTSD

symptoms have been made available since the beginning of data collection for the current

investigation. The use of DSM-5 PTSD criteria likely would not have resulted in

markedly different PTSD groups in the current investigation; however, given changes to

the wording of PTSD symptoms, future research should rely on DSM-5 assessment tools.

Web-based data collection has been shown to be a valid approach for

questionnaire-based research (Gosling, Vazire, Srivastava, & John, 2004); however, there

does not appear to be research assessing the validity of an Internet administered dot probe

71

paradigm. Any difficulty associated with this administration channel is likely the result of

differences in the testing environments, not the Millisecond software (Millisecond

Software Inc., Seattle, WA). Specifically, there is a possibility that participants completed

the dot probe task while being exposed to environmental distractions despite attempts

made to control for environmental distractions in the current investigation (i.e.,

standardized instructions in regards to the testing environment, exclusion of outliers,

asking participants to report careless responding). The presence of strongly personally

relevant stimuli in the testing environment could have resulted in the participants

allocating more attentional resources towards the environmental distracters than towards

the stimuli presented on the computer screen. Accordingly, future research should seek to

replicate current results using a laboratory administered dot probe task. Future research

should also seek to increase ecological validity by having participants complete a dot

probe task in an MVA-related context (e.g., in car). The presence of MVA-related

contextual cues may provide a better assessment of the attentional biases present at the

time of driving a vehicle. Further, MVA-related contextual cues may increase the

personal relevance of the threat stimuli presented in the attentional bias task, in turn

increasing the size of the bias.

Finally, assumptions of directionality made based on the current investigation

would need to be verified using longitudinal design. Discrepant findings in the literature

on attentional bias and PTSD may result from a change in the directionality of attentional

bias over time. Future investigations of MVA survivors should seek to longitudinally

assess the directionality of attentional bias as has previously been done in military

samples (Beevers et al., 2011; Wald et al., 2011). Logistically, predicting which

72

individuals will become involved in a MVA is impossible; however, recruitment of

research participants in emergency room settings could allow for the assessment of

attentional bias immediately after the MVA and at multiple time points thereafter.

4.7. Conclusions

The current investigation was the first to assess the directionality and time course

of attentional bias for threat in a sample of MVA survivors. The dot probe task yielded

different results based on the procedure used to analyze the data. Direct comparisons of

the attention bias indices between the groups did not support the presence of group

differences. Nonetheless, a different attention pattern emerged between the groups when

evaluating the directionality of the orienting and disengaging indices compared to

baseline. Accordingly, the contemporary dot probe task appears to be a more sensitive

measure of attentional bias and should be used in future investigations.

Results of the contemporary dot probe task provided evidence that MVA

survivors with high PTSD symptoms display a different attention pattern than MVA

survivors with low PTSD symptoms and non-MVA survivors during the early stages of

cognitive processing (i.e., 100 ms). Specifically, MVA survivors with high PTSD

symptoms appear to easily disengage (i.e., avoid) their attention from MVA-related

stimuli, despite such stimuli not being inherently threatening. Furthermore, MVA

survivors with high PTSD symptoms fail to engage with generally threatening stimuli, a

seemingly normal response displayed by MVA survivors with low PTSD symptoms and

non-MVA survivors. Replication of the current results would support attention bias

modification treatment programs for MVA survivors with PTSD. The current

investigation does not allow for the establishment of causality; however, failure to engage

73

with threatening stimuli at the time of the MVA may facilitate development of PTSD,

which is further maintained by the avoidance of MVA-related stimuli. Such supposition

would have to be verified through the use of a longitudinal research design, but provides

initial direction for exploring attention bias modification programs as a tool to prevent

development of PTSD.

74

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Footnotes

1 The STAI was not included in an appendix to avoid copyright violation. All other measures included in the current investigation are available in the public domain and are included in the appendices.

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Appendices

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Appendix A. Demographic Measures

If you would like to participate, please provide your email address below. Your contact information will only be used for data collection purposes.

Were you in a motor vehicle accident more than one month ago (30 days) where enough damage occurred that required you to (or should have required you to) file a police report or call the police? Y/N If yes, how long ago did this accident occur? ___________ Was this accident your first accident? Y/N If no, how many accidents have you been involved in previously? ____________ Did you injure your head during the motor vehicle accident? __________ If yes, did you lose consciousness or “black out” as a result of the head injury? Have you ever experienced any of the following stressful life events?

o Natural disaster (e.g., earthquake, flood, tornado) o Any accident other than a motor vehicle accident where you or someone was

badly hurt (e.g., plane crash, drowning, explosion) o Living, working, or doing military service in a war zone o Sudden and unexpected death of close friend or a loved one o Robbery with the use of a weapon o Physical assault o Sexual assault o Witnessed a severe physical or sexual assault o Life threatening illness (e.g., cancer, life threatening virus, spinal cord injury) o Any other threatening life event (e.g., lost in wilderness, severe animal bite):

_______________ If yes, was the motor vehicle accident the most traumatic event? Y/N If another event was more traumatic, which event was the most severe? (USE ABOVE) __________________ Do you have any daytime vision problems that aren’t corrected by glasses or contacts? Y/N

Are you currently taking any psychoactive medication on a regular basis? Y/N If yes, please list all medication that you are currently taking. ______________ Have you consumed any caffeine, alcohol, or drug in the past 24hrs? Y/N If yes, please indicate what substance and how much. ____________________

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How old are you? Please indicate your sex. How many years (not necessarily consecutively) have you been in school? Please indicate your current occupation. Please indicate your marital status. Please indicate your ethnicity. Please indicate which city or town you currently live in. Please indicate your first language.

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Appendix B.

Attentional Control Scale (ACS)

Please rate as 1 for almost never; 2 sometimes; 3 often; and 4 would be always.

Almost never

Sometimes Often Always

1. It’s very hard for me to concentrate on a difficult task when there are noises around.

2. When I need to concentrate and solve a problem, I have trouble focusing my attention.

3. When I am working hard on something, I still get distracted by events around me.

4. My concentration is good even if there is music in the room around me.

5. When concentrating, I can focus my attention so that I become unaware of what’s going on in the room around me.

6. When I am reading or studying, I am easily distracted if there are people talking in the same room.

7. When trying to focus my attention on something, I have difficulty blocking out distracting thoughts.

8. I have a hard time concentrating when I’m excited about something.

9. When concentrating I ignore feelings of hunger or thirst.

10. I can quickly switch from one task to another.

11. It takes me a while to get really involved in a new task.

12. It is difficult for me to coordinate my attention between the listening and writing required when taking notes during lectures.

13. I can become interested in a new topic very quickly when I need to.

14. It is easy for me to read or write while I’m also talking on the phone.

15. I have trouble carrying on two conversations at once.

16. I have a hard time coming up with new ideas quickly.

17. After being interrupted or distracted, I can easily shift my attention back to what I was

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doing before. 18. When a distracting thought comes to mind, it is easy for me to shift my attention away from it.

19. It is easy for me to alternate between two different tasks.

20. It is hard for me to break from one way of thinking about something and look at it from another point of view.

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Appendix C.

Alcohol Use Disorders Identification Test (AUDIT)

Please circle the answer that is correct for you.

1. How often do you have a drink containing alcohol? Never Monthly or less Two to four times a month Two to three times a week Four or more times a week 2. How many drinks containing alcohol do you have on a typical day when you are

drinking? 1 or 2 3 or 4 5 or 6 7 to 9 10 or more 3. How often do you have six or more drinks on one occasion? Never Less than monthly Monthly Weekly Daily or almost daily 4. How often during the last year have you found that you were not able to stop

drinking once you had started? Never Less than monthly Monthly Weekly Daily or almost daily 5. How often during the last year have you failed to do what was normally expected

from you because of drinking? Never Less than monthly Monthly Weekly Daily or almost daily 6. How often during the last year have you needed a first drink in the morning to get

yourself going after a heavy drinking session? Never

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Less than monthly Monthly Weekly Daily or almost daily 7. How often during the last year have you had a feeling of guilt or remorse after

drinking? Never Less than monthly Monthly Weekly Daily or almost daily 8. How often during the last year have you been unable to remember what happened

the night before because you had been drinking? Never Less than monthly Monthly Weekly Daily or almost daily 9. Have you or someone else been injured as a result of drinking? No Yes, but not in the last year Yes, during the last year 10. Has a relative or friend, or a doctor or other health worker been concerned about

your drinking or suggested you cut down? No Yes, but not in the last year Yes, during the last year

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Appendix D.

Emotion Regulation Questionnaire (ERQ)

We would like to ask you some questions about your emotional life, in particular, how you control (that is, regulate and manage) your emotions. The questions below involve two distinct aspects of your emotional life. One is your emotional experience, or what you feel like inside. The other is your emotional expression, or how you show your emotions in the way you talk, gesture, or behave. Although some of the following questions may seem similar to one another, they differ in important ways. For each item, please answer using the following scale: 1---------------2---------------3---------------4---------------5---------------6---------------7 strongly neutral strongly disagree agree

1. ____ When I want to feel more positive emotion (such as joy or amusement), I change what I’m thinking about. 2. ____ I keep my emotions to myself. 3. ____ When I want to feel less negative emotion (such as sadness or anger), I change what I’m thinking about. 4. ____ When I’m feeling positive emotions, I am careful not to express them. 5. ____ When I’m faced with a stressful situation, I make myself think about it in a

way that helps me stay calm. 6. ____ I control my emotions by not expressing them. 7. ____ When I want to feel more positive emotion, I change the way I’m thinking

about the situation. 8. ____ I control my emotions by changing the way I think about the situation I’m

in. 9. ____ When I am feeling negative emotions, I make sure not to express them. 10. ____ When I want to feel less negative emotion, I change the way I’m thinking

about the situation.

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Appendix E.

PTSD Checklist – Stressor Specific Version (PCL-S)

The event you experienced was: _______________ on: _______________ Below is a list of problems and complaints that people sometimes have in response to stressful life experiences. Please indicate how much you have been bothered by that problem in the past month. Please rate as 1 for not at all; 2 a little bit; 3 moderately; 4 quite a bit, and 5 would be extremely.

Not at all

A little bit

Moderately Quite a bit

Extremely

1. Repeated, disturbing memories, thoughts, or images of the stressful experience?

2. Repeated, disturbing dreams of the stressful experience?

3. Suddenly acting or feeling as if the stressful experience were happening again (as if you were reliving it)?

4. Feeling very upset when something reminded you of the stressful experience?

5. Having physical reactions (e.g., heart pounding, trouble breathing, or sweating) when something reminded you of the stressful experience?

6. Avoid thinking about or talking about the stressful experience or avoid having feelings related to it?

7. Avoid activities or situations because they remind you of the stressful experience?

8. Trouble remembering important parts of the stressful experience?

9. Loss of interest in things that you used to enjoy?

10. Feeling distant or cut off from other people?

11. Feeling emotionally numb or being unable to have loving feelings

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for those close to you? 12. Feeling as if your future will somehow be cut short?

13. Trouble falling or staying asleep?

14. Feeling irritable or having angry outbursts?

15. Having difficulty concentrating? 16. Being “super alert” or watchful on guard?

17. Feeling jumpy or easily startled?

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Appendix F.

Word List

Strong Threat Mild Threat Neutral Emergency Speedometer Momentary Deathbed Intersection Relative

Blood Truck Sail Panic Driver Pause Smash Wheel Record

Mortality Highway Blanket Death Mirror Round

Trapped Accelerate Pasture Scream Freeway Giraffe Agony Traffic Curtain

- - Loop - - Fish - - Table - - Aisle - - Butter - - Staple - - Binder - - Glove - - Jacket - - Cable Planet Card Desk Gel Computer Cotton Justify Zipper Send Vote

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Appendix G.

University of Regina Research Ethics Board Ethical Approval Forms

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