Attitude Scale

http://www.indranet.com/business/verve/attitude.htm

A t t i t u d e mS c a l e m C h a r tATTITUDE SCALE

Short Form

Level State Emotion Attitude

Point of View

Perceived Condition

| Apparent Solution

Take Action

3SourceCreate Empower

Love Serenity Wonder

Compassion Serenity Trust Faith

Freedom Commitment

BE COMMITTEDExpand responsibility. Empower others.

2StabilityPersonal Power

Enthusiasm Cheerfulness

Enthusiasm Passion Opportunity Promote

MAKE OPPORTUNITIESStrengthen positive results.

1RiskConcentration

Mild Anxiety Caution

Hope Curiosity

Entice Attract

Discovery Explore

COMMUNICATE NOWDemonstrate integrity.

0 Goal-lessFormulation

Contentment Complacent

Impartial Indifference Neutral Independent

MAKE GOALSDetermine what is needed and start doing it.

-1 ResponsibleLiable

Guilt Embarassment

Reluctance Disappointment Self-conscious

Obligation Agreement

KEEP AGREEMENTSMake amends. Reestablish trust. Define boundaries.

-2 UncertainConfused

Frustration Confusion

Annoyance Ambivalence

Infringement Evasion

MAINTAIN CHOICEMake conscious choices.

-3 OppositionAdversary

Antagonism Anger

Outrage Arrogance

Attack Insult

Suppress Dominate

GO FOR ITStop having to be right.

-4 Pretend Unexpressed Suspicion, Conspiracy, Secrecy TELL THE

http://www.indranet.com/business/verve/attitude.htm

Disloyal Fear Pain

resentment, Covert hostility, Self-abasement, Fear, Regret

Dread, Apathy, Blame, Greed, Jealousy, Malice

Threat, Trap, Burden, Overwhelm, Betrayal

Protection Rescue Revenge

TRUTHStop pretending. Develop trust. Endure vunerableness. Imagine a good outcome.

Attitude Scales - Rating Scales to measure data

Scaling Techniques for Measuring Data Gathered from RespondentsThe term scaling is applied to the attempts to measure the attitude objectively. Attitude is a resultant of number of external and internal factors. Depending upon the attitude to be measured, appropriate scales are designed. Scaling is a technique used for measuring qualitative responses of respondents such as those related to their feelings, perception, likes, dislikes, interests and preferences.

Types of Scales

Most frequently used Scales

1. Nominal Scale 2. Ordinal Scale 3. Interval Scale 4. Ratio Scale

Self Rating Scales

1. Graphic Rating Scale 2. Itemized Rating Scales

a. Likert Scale b. Semantic Differential Scale c. Stapel’s Scale d. Multi Dimensional Scaling e. Thurston Scales f. Guttman Scales/Scalogram Analysis g. The Q Sort technique

Four types of scales are generally used for Marketing Research.

1. Nominal Scale

http://www.managementstudyguide.com/marketing_research.htm

http://www.managementstudyguide.com/attitude-scales.htm#theqsorttechnique

http://www.managementstudyguide.com/attitude-scales.htm#guttmanscalesscalogramanalysis

http://www.managementstudyguide.com/attitude-scales.htm#thurstonscales

http://www.managementstudyguide.com/attitude-scales.htm#multidimensionalscaling

http://www.managementstudyguide.com/attitude-scales.htm#stapelsscale

http://www.managementstudyguide.com/attitude-scales.htm#semanticdifferentialscale

http://www.managementstudyguide.com/attitude-scales.htm#likertscale

http://www.managementstudyguide.com/attitude-scales.htm#itemizedratingscales

http://www.managementstudyguide.com/attitude-scales.htm#graphicratingscale

http://www.managementstudyguide.com/attitude-scales.htm#ratioscale

http://www.managementstudyguide.com/attitude-scales.htm#intervalscale

http://www.managementstudyguide.com/attitude-scales.htm#ordinalscale

http://www.managementstudyguide.com/attitude-scales.htm#nominalscale

This is a very simple scale. It consists of assignment of facts/choices to various alternative categories which are usually exhaustive as well mutually exclusive. These scales are just numerical and are the least restrictive of all the scales. Instances of Nominal Scale are - credit card numbers, bank account numbers, employee id numbers etc. It is simple and widely used when relationship between two variables is to be studied. In a Nominal Scale numbers are no more than labels and are used specifically to identify different categories of responses. Following example illustrates -

What is your gender?[ ] Male[ ] Female

Another example is - a survey of retail stores done on two dimensions - way of maintaining stocks and daily turnover.

How do you stock items at present?[ ] By product category[ ] At a centralized store[ ] Department wise[ ] Single warehouse

Daily turnover of consumer is?[ ] Between 100 – 200[ ] Between 200 – 300[ ] Above 300

A two way classification can be made as follows

Daily/Stock Turnover Method

Product Category

Department wise

Centralized Store

Single Warehouse

100 – 20

0

200 – 300

Above 300

Mode is frequently used for response category.

2. Ordinal Scale

Ordinal scales are the simplest attitude measuring scale used in Marketing Research. It is more powerful than a nominal scale in that the numbers possess the property of rank order. The ranking of certain product attributes/benefits as deemed important by the respondents is obtained through the scale.

Example 1: Rank the following attributes (1 - 5), on their importance in a microwave oven.

a. Company Nameb. Functionsc. Priced. Comforte. Design

The most important attribute is ranked 1 by the respondents and the least important is ranked 5. Instead of numbers, letters or symbols too can be used to rate in a ordinal scale. Such scale makes no attempt to measure the degree of favourability of different rankings.

Example 2 - If there are 4 different types of fertilizers and if they are ordered on the basis of quality as Grade A, Grade B, Grade C, Grade D is again an Ordinal Scale.

Example 3 - If there are 5 different brands of Talcom Powder and if a respondent ranks them based on say, “Freshness” into Rank 1 having maximum Freshness Rank 2 the second maximum Freshness, and so on, an Ordinal Scale results.

Median and mode are meaningful for ordinal scale.

3. Interval Scale


Herein the distance between the various categories unlike in Nominal, or numbers unlike in Ordinal, are equal in case of Interval Scales. The Interval Scales are also termed as Rating Scales. An Interval Scale has an arbitrary Zero point with further numbers placed at equal intervals. A very good example of Interval Scale is a Thermometer.

Illustration 1 - How do you rate your present refrigerator for the following qualities.

Company Name

Less Known

12345

Well Known

Functions

Few

12345Many

Price

Low

12345High

Design

Poor

12345Good

Overall Satisfaction

Very Dis-Satisfied

12345

Very Satisfied

Such a scale permits the researcher to say that position 5 on the scale is above position 4 and also the distance from 5 to 4 is same as distance from 4 to 3. Such a scale however does not permit conclusion that position 4 is twice as strong as position 2 because no zero position has been established. The data obtained from the Interval Scale can be used to calculate the Mean scores of each attributes over all respondents. The Standard Deviation (a measure of dispersion) can also be calculated.

4. Ratio Scale

Ratio Scales are not widely used in Marketing Research unless a base item is made available for comparison. In the above example of Interval scale, a score of 4 in one quality does not necessarily mean that the respondent is twice more satisfied than the respondent who marks 2 on the scale. A Ratio scale has a natural zero point and further


numbers are placed at equally appearing intervals. For example scales for measuring physical quantities like - length, weight, etc.

The ratio scales are very common in physical scenarios. Quantified responses forming a ratio scale analytically are the most versatile. Rati scale possess all he characteristics of an internal scale, and the ratios of the numbers on these scales have meaningful interpretations. Data on certain demographic or descriptive attributes, if they are obtained through open-ended questions, will have ratio-scale properties. Consider the following questions :

Q 1) What is your annual income before taxes? ______ $Q 2) How far is the Theater from your home ? ______ miles

Answers to these questions have a natural, unambiguous starting point, namely zero. Since starting point is not chosen arbitrarily, computing and interpreting ratio makes sense. For example we can say that a respondent with an annual income of $ 40,000 earns twice as much as one with an annual income of $ 20,000.

Self rating scales

1. Graphic Rating Scale

The respondents rate the objects by placing a mark at the appropriate position on a line that runs from one extreme of the criterion variable to another. Example

0(poor quality)

1(bad

quality)

5(neither good

nor bad)

7(good

quality)

BRAND 1

This is also known as continuous rating scale. The customer can occupy any position. Here one attribute is taken ex-quality of any brand of icecream.

poor good

BRAND 2

This line can be vertical or horizontal and scale points may be provided. No other indication is there on the continuous scale. A range is provided. To quantify the responses to question that “indicate your overall opinion about ice-ream Brand 2 by placing a tick mark at appropriate position on the line”, we measure the physical distance between the left extreme position and the response position on the line.; the greater the distance, the more favourable is the response or attitude towards the brand.

Its limitation is that coding and analysis will require substantial amount of time, since we first have to measure the physical distances on the scale for each respondent.

2. Itemized Rating Scales

These scales are different from continuous rating scales. They have a number of brief descriptions associated with each category. They are widely used in Marketing Research. They essentially take the form of the multiple category questions. The most common are - Likert, Sementic, Staple and Multiple Dimension. Others are - Thurston and Guttman.

a. Likert Scale

It was developed Rensis Likert. Here the respondents are asked to indicate a degree of agreement and disagreement with each of a series of statement. Each scale item has 5 response categories ranging from strongly agree and strongly disagree.

5Strongly agree

4Agree

3Indifferent

2Disagree

1Strongly disagree

Each statement is assigned a numerical score ranging from 1 to 5. It can also be scaled as -2 to +2.

-2 -1 0 1 2

For example quality of Mother Diary ice-cream is poor then Not Good is a negative statement and Strongly Agree with this means the quality is not good.

Each degree of agreement is given a numerical score and the respondents total score is computed by summing these scores. This total score of respondent reveals the particular opinion of a person.

Likert Scale are of ordinal type, they enable one to rank attitudes, but not to measure the difference between attitudes. They take about the same amount of efforts to create as Thurston scale and are considered more discriminating and reliable because of the larger range of responses typically given in Likert scale.


A typical Likert scale has 20 - 30 statements. While designing a good Likert Scale, first a large pool of statements relevant to the measurement of attitude has to be generated and then from the pool statements, the statements which are vague and non-discriminating have to be eliminated.

Thus, likert scale is a five point scale ranging from ’strongly agreement’to ’strongly disagreement’. No judging gap is involved in this method.

a. Semantic Differential Scale

This is a seven point scale and the end points of the scale are associated with bipolar labels.

1UnpleasantSubmissiv

e

2 3 4 5 67PleasantDominant

Suppose we want to know personality of a particular person. We have options-

a. Unpleasant/Submissiveb. Pleasant/Dominant

Bi-polar means two opposite streams. Individual can score between 1 to 7 or -3 to 3. On the basis of these responses profiles are made. We can analyse for two or three products and by joining these profiles we get profile analysis. It could take any shape depending on the number of variables.

Profile Analysis

---------------/-------------------------/----------------------------/----------------------

Mean and median are used for comparison. This scale helps to determine overall similarities and differences among objects.

When Semantic Differential Scale is used to develop an image profile, it provides a good basis for comparing images of two or more items. The big advantage of this scale is its simplicity, while producing results compared with those of the more complex scaling methods. The method is easy and fast to administer, but it is also sensitive to small differences in attitude, highly versatile, reliable and generally valid.

b. Stapel’s Scale

It was developed by Jan Stapel. This scale has some distinctive features:-

a. Each item has only one word/phrase indicating the dimension it represents.b. Each item has ten response categories.c. Each item has an even number of categories.d. The response categories have numerical labels but no verbal labels.

For example, in the following items, suppose for quality of ice cream, we ask respondents to rank from +5 to -5. Select a plus number for words which best describe the ice cream accurately. Select a minus number for words you think do not describe the ice cream quality accurately. Thus, we can select any number from +5,for words we think are very accurate, to -5,for words we think are very inaccurate. This scale is usually presented vertically.

+5+4+3+2+1High Quality-1-2-3-4-5

This is a unipolar rating scale.

c. Multi Dimensional Scaling

It consists of a group of analytical techniques which are used to study consumer attitudes related to perceptions and preferences. It is used to study-

a. The major attributes of a given class of products perceivedby the consumers in considering the product and by which they compare the different ranks.

b. To study which brand competes most directly with each other.c. To find out whether the consumers would like a new brand with a combination of

characteristics not found in the market.d. What would be the consumers ideal combination of product attributes.e. What sales and advertising messages are compatible with consumers brand

perceptions.

It is a computer based technique. The respondents are asked to place the various brands into different groups like similar, very similar, not similar, and so on. A goodness of fit is

traded off on a large number of attributes. Then a lack of fit index is calculated by computer program. The purpose is to find a reasonably small number of dimensions which will eliminate most of the stress. After the configuration for the consumer’s preference has been developed, the next step is to determine the preference with regards to the product under study. These techniques attempt to identify the product attributes that are important to consumers and to measure their relative importance.

This scaling involves a unrealistic assumption that a consumer who compares different brands would perceive the differences on the basis of only one attribute.For example, what are the attributes for joining M.Com course. The responses may be -to do PG, to go into teaching line,to get knowledge, appearing in the NET. There are a number of attributes, you can not base decision on one attribute only. Therefore, when the consumers are choosing between brands, they base their decision on various attributes. In practice, the perceptions of the consumers involve different attributes and any one consumer perceives each brand as a composite of a number of different attributes. This is a shortcoming of this scale.

Whenever we choose from a number of alternatives, go for multi- dimensional scaling. There are many possible uses of such scaling like in market segmentation, product life cycle, vendor evaluations and advertising media selection.

The limitation of this scale is that it is difficult to clearly define the concept of similarities and preferences. Further the distances between the items are seen as different

d. Thurston Scales

These are also known as equal appearing interval scales. They are used to measure the attitude towards a given concept or construct. For this purpose a large number of statements are collected that relate to the concept or construct being measured. The judges rate these statements along an 11 category scale in which each category expresses a different degree of favourableness towards the concept. The items are then ranked according to the mean or median ratings assigned by the judges and are used to construct questionnaire of twenty to thirty items that are chosen more or less evenly across the range of ratings. The statements are worded in such a way so that a person can agree or disagree with them. The scale is then administered to assemble of respondents whose scores are determined by computing the mean or median value of the items agreed with. A person who disagrees with all the items has a score of zero. So, the advantage of this scale is that it is an interval measurement scale. But it is the time consuming method and labour intensive. They are commonly used in psychology and education research.

e. Guttman Scales/Scalogram Analysis

It is based on the idea that items can be arranged along a continuem in such a way that a person who agrees with an item or finds an item acceptable will also agree with or find acceptable all other items expressing a less extreme position. For example - Children should not be allowed to watch indecent programmes or government should ban these

programmes or they are not allowed to air on the television. They all are related to one aspect.

In this scale each score represents a unique set of responses and therefore the total score of every individual is obtained. This scale takes a lot of time and effort in development.

They are very commonly used in political science, anthropology, public opinion, research and psychology.

f. The Q Sort technique

It is used to discriminate among large number of objects quickly. It uses a rank order procedure and the objects are sorted into piles based on similarity with respect to some criteria. The number of objects to be sorted should be between 60-140 approximately. For example, here we are taking nine brands. On the basis of taste we classify the brands into tasty, moderate and non tasty.

We can classify on the basis of price also-Low, medium, high. Then we can attain the perception of people that whether they prefer low priced brand, high or moderate. We can classify sixty brands or pile it into three piles. So the number of objects is to be placed in three piles-low, medium or high.

Thus, the Q-sort technique is an attempt to classify subjects in terms of their similarity to attribute under study.

http://www.managementstudyguide.com/attitude-scales.htm

Modified Fennema-Sherman Attitude Scales

by Diana Doepken, Ellen Lawsky, and Linda Padwa

In an effort to study students' attitudes towards math, Elizabeth Fennema and Julia A. Sherman constructed the following attitude scale in the early 1970's. The scale consists of four subscales: a confidence scale, a usefulness scale, a scale that measures mathematics as a male domain and a teacher perception scale. Each of these scales consists of 12 items. Six of them measure a positive attitude and six measure a negative attitude.

This scale could give a teacher and an individual student useful information about that particular student's attitude(s) towards math. Because this scale was originally written twenty years ago and

http://www.managementstudyguide.com/attitude-scales.htm

the subtle meanings and connotations of words have changed in that time period, it is important that this scale not be used for research.

We also adapted the scale to provide tools to examine a student's attitude towards science. Following the scales is the scoring key.

Introductory note (for use with these scales)

Fennema-Sherman Mathematics Attitude Scales

Using this scale will help you and I find out how you feel about yourself and mathematics.

On the following pages is a series of sentences. You are to mark your answer sheets by telling how you feel about them. Suppose a statement says:

Example 1: I like mathematics.

As you read the sentence, you will know whether you agree or disagree. If you strongly agree, circle A next to Number 1. If you agree, but not so strongly, or you only "sort of" agree, circle B. If you disagree with the sentence very much, circle E for strongly disagree. If you disagree, but not so strongly, circle D. If you are not sure about a question or you can't answer it, circle C. Now, mark your sheet, then go on and do Example 2.

Do not spend much time with any statement, but be sure to answer every statement.

Work fast, but carefully.

There are no "right" or "wrong" answers. The only correct responses are those that are true for you. Whenever possible, let the things that have happened to you help you make a choice.

A Modified Fennema-Sherman Mathematics Attitude Scale1. I am sure that I can learn math. A B C D E

2. My teachers have been interested in my progress in math. A B C D E

3. Knowing mathematics will help me earn a living. A B C D E

4. I don't think I could do advanced math. A B C D E

5. Math will not be important to me in my life's work. A B C D E

6. Males are not naturally better than females in math. A B C D E

7. Getting a teacher to take me seriously in math is a problem. A B C D E

8. Math is hard for me. A B C D E

9. It's hard to believe a female could be a genius in mathematics. A B C D E

10.

I'll need mathematics for my future work. A B C D E

11.

When a woman has to solve a math problem, she should ask a man for help. A B C D E

12.

I am sure of myself when I do math. A B C D E

13.

I don't expect to use much math when I get out of school. A B C D E

14.

I would talk to my math teachers about a career that uses math. A B C D E

15.

Women can do just as well as men in math. A B C D E

16.

It's hard to get math teachers to respect me. A B C D E

17.

Math is a worthwhile, necessary subject. A B C D E

18.

I would have more faith in the answer for a math problem solved by a man than a woman.

A B C D E

19.

I'm not the type to do well in math. A B C D E

20.

My teachers have encouraged me to study more math. A B C D E

21.

Taking math is a waste of time. A B C D E

22.

I have a hard time getting teachers to talk seriously with me about math. A B C D E

23.

Math has been my worst subject. A B C D E

24.

Women who enjoy studying math are a little strange. A B C D E

25.

I think I could handle more difficult math. A B C D E

26.

My teachers think advanced math will be a waste of time for me. A B C D E

27.

I will use mathematics in many ways as an adult. A B C D E

28.

Females are as good as males in geometry. A B C D E

29.

I see mathematics as something I won't use very often when I get out of high school.

A B C D E

30.

I feel that math teachers ignore me when I try to talk about something serious. A B C D E

31.

Women certainly are smart enough to do well in math. A B C D E

32.

Most subjects I can handle OK, but I just can't do a good job with math. A B C D E

33.

I can get good grades in math. A B C D E

34.

I'll need a good understanding of math for my future work. A B C D E

35.

My teachers want me to take all the math I can. A B C D E

36.

I would expect a woman mathematician to be a forceful type of person. A B C D E

37.

I know I can do well in math. A B C D E

38.

Studying math is just as good for women as for men. A B C D E

39.

Doing well in math is not important for my future. A B C D E

40.

My teachers would not take me seriously if I told them I was interested in a career in science and mathematics.

A B C D E

41.

I am sure I could do advanced work in math. A B C D E

42.

Math is not important for my life. A B C D E

43.

I'm no good in math. A B C D E

44.

I study math because I know how useful it is. A B C D E

45.

Math teachers have made me feel I have the ability to go on in mathematics. A B C D E

46.

I would trust a female just as much as I would trust a male to solve important math problems.

A B C D E

47.

My teachers think I'm the kind of person who could do well in math. A B C D E

Science Attitude Scale as Modified from the Fennema-Sherman Attitude Scale1. I am sure that I can learn science. A B C D E

2. My teachers have been interested in my progress in science. A B C D E

3. Knowing science will help me earn a living. A B C D E

4. I don't think I could do advanced science. A B C D E

5. Science will not be important to me in my life's work. A B C D E

6. Males are not naturally better than females in science. A B C D E

7. Getting a teacher to take me seriously in science is a problem. A B C D E

8. Science is hard for me. A B C D E

9. It's hard to believe a female could be a genius in science. A B C D E

10.

I'll need science for my future work. A B C D E

11.

When a woman has to solve a science problem, she should ask a man for help. A B C D E

12.

I am sure of myself when I do science. A B C D E

13.

I don't expect to use much science when I get out of school. A B C D E

14.

I would talk to my science teachers about a career which uses math. A B C D E

15.

Women can do just as well as men in science. A B C D E

16.

It's hard to get science teachers to respect me. A B C D E

17.

Science is a worthwhile, necessary subject. A B C D E

18.

I would have more faith in the answer for a science problem solved by a man than a woman.

A B C D E

19.

I'm not the type to do well in science. A B C D E

20.

My teachers have encouraged me to study more science. A B C D E

21.

Taking science is a waste of time. A B C D E

22.

I have a hard time getting teachers to talk seriously with me about science. A B C D E

23.

Science has been my worst subject. A B C D E

24.

Women who enjoy studying science are a little strange. A B C D E

25.

I think I could handle more difficult science. A B C D E

26.

My teachers think advanced science will be a waste of time for me. A B C D E

27.

I will use science in many ways as an adult. A B C D E

28.

Females are as good as males in science. A B C D E

29.

I see science as something I won't use very often when I get out of high school. A B C D E

30.

I feel that science teachers ignore me when I try to talk about something serious.

A B C D E

31.

Women certainly are smart enough to do well in science. A B C D E

32.

Most subjects I can handle OK, but I just can't do a good job with science. A B C D E

33.

I can get good grades in science. A B C D E

34.

I'll need a good understanding of science for my future work. A B C D E

35.

My teachers want me to take all the science I can. A B C D E

36.

I would expect a woman scientist to be a forceful type of person. A B C D E

37.

I know I can do well in science. A B C D E

38.

Studying science is just as good for women as for men. A B C D E

39.

Doing well in science is not important for my future. A B C D E

40.

My teachers would not take me seriously if I told them I was interested in a career in science and mathematics.

A B C D E

41.

I am sure I could do advanced work in science. A B C D E

42.

Science is not important for my life. A B C D E

43.

I'm no good in science. A B C D E

44.

I study science because I know how useful it is. A B C D E

45.

Science teachers have made me feel I have the ability to go on in science. A B C D E

46.

I would trust a female just as much as I would trust a male to solve important science problems.

A B C D E

47.

My teachers think I'm the kind of person who could do well in science. A B C D E

Key to Modified Fennema-Sherman Scale for Math and Science

Key:

C = Personal confidence about the subject matter U = Usefulness of the subject's content M = Subject is perceived as a male domain T = Perception of teacher's attitudes

+ = Question reflects positive attitude - = Question reflects negative attitude

Question #

Category of Question

Attitude

1 C +

2 T +

3 U +

4 C -

5 U -

6 M +

7 T -

8 C -

9 M -

10 U +

11 M -

12 C +

13 U -

14 T +

15 M +

16 T -

17 U +

18 M -

19 C -

20 T +

21 U -

22 T -

23 C -

24 M -

25 C +

26 T -

27 U +

28 M +

29 U -

30 T -

31 M +

32 C -

33 C +

34 U +

35 T +

36 M -

37 C +

38 M +

39 U -

40 T -

41 C +

42 U -

43 C -

44 U +

45 T +

46 M +

47 T +

Scoring Directions:

Each positive item receives the score based on points

A = 5 B = 4 C = 3 D = 2 E = 1

The scoring for each negative item should be reversed

A = 1 B = 2 C = 3 D = 4 E = 5

Add the scores for each group, T, C, U, M, to get a total for that attitude.

The highest possible score for each group of statements is 60 points.

http://www.woodrow.org/teachers/math/gender/08scale.html

The value of Likert scales in measuring attitudes of online learners

Hilary Page-Bucci - February 2003

Attitude is an important concept that is often used to understand and predict people's reaction to an object or change and how behaviour can be influenced

(Fishbein and Ajzen, 1975)

http://www.woodrow.org/teachers/math/gender/08scale.html

Introduction

Although online learning has grown alongside the progress of digital technology over the last 15 years; the reasoning behind why students become absorbed, practise and achieve a variety of tasks and exercises, or why they avoid others are always of interest to the effectors and evaluators of the learning process.

By establishing the characteristics of distance and online learners; how they become motivated, how they feel about learning online; useful information will be found that would empower the teaching practices and thus ultimately enhance student retention and achievement.

A review of some of the literature available has revealed some research already undertaken in various areas of learning online, such as 'training effectiveness and user attitudes' (Torkzadeh et al, 1999). Torkzadeh et al suggest, " to achieve successful training we need to be cognizant of the user's attitudes towards computers. Further investigation revealed other factors that should be taken into consideration; Miltiadou (1999) suggests that 'it is important to identify motivational characteristics of online students'. By investigating and defining their motivation, it would lead to an understanding of 'self-efficacy beliefs about their own abilities to engage, persist and accomplish specific tasks' (Bandura, 1986; Stipek, 1988 cited by Miltiadou).

The concept of measuring attitude is found in many areas including social psychology and the Social Sciences; they can be complex and difficult to measure and there are a number of different measuring instruments that have been developed to assess attitude.

'Scaling is the science of determining measuring instruments for human judgment' (McIver 1981). One needs to make use of appropriate scaling methods to aid in improving the accuracy of subjective estimation and voting procedures (Turoff & Hiltz 1997). Torgerson (1958) pointed out that scaling, as a science of measuring human judgment, is as fundamental as collecting data on well-developed natural sciences. Nobody would refute the fact that all science advances by the development of its measurement instruments. Researchers are constantly attempting to obtain more effective scaling methods that could be applied to the less well developed yet more complicated social sciences. Scaling models can be distinguished according to whether they are intended to scale persons, stimuli, or both (McIver 1981). For example, Likert scale is a subject-centered approach since only subjects receive scale scores. Thurstone scaling is considered a method to evaluate the stimuli with respect to some designated attributes. It is the stimuli rather than the persons that are scaled (Togerson 1958). Guttman scaling is an approach in which both subjects and stimuli can be assigned scale values (McIver 1981). (Li et al, 2001)

The purpose of this study is to explore the particular method of measuring attitude known as Likert Scales (Likert, 1932), and determine their effectiveness and value in researching attitudes, views and experiences of online learners. These scales according to Taylor and Heath (1996) have become one of the dominant methods of measuring social and political attitudes.

Methodology and Measurement

The methodology used for this research will be by a critique of previous research methodologies. In order to establish the methodology of this research it is first necessary to clarify the term 'attitude'.

Attitude is an important concept that is often used to understand and predict people's reaction to an object or change and how behaviour can be influenced (Fishbein and Ajzen, 1975)

An attitude is a mental and neural state of readiness, organised through experience, exerting a directive or dynamic influence upon the individual's response to all objects and situations to which it is related (Allport, 1935 cited by Gross)

A learned orientation, or disposition, toward an object or situation, which provides a tendency to respond favourably or unfavourably to the object or situation.' (Rokeach, 1968 cited by Gross)

Three of the generally accepted components of the term 'attitude' (Triandis, 1971) appear in some of the above definitions, these are:

Affective - the person's feelings about the attitude object Cognitive - the person's beliefs or knowledge about the attitude object Behavioural - the person's inclination to act toward the attitude object on a particular way

By analysing these components, and as Gross (1968) suggests it is a 'hypothetical construct'; it becomes apparent that it cannot be directly measured and the use of only a single statement or question to assess it [attitude] will not be effective in gaining reliable responses.

Attitude scales attempt to determine what an individual believes, perceives or feels. Attitudes can be measured toward self, others, and a variety of other activities, institutions, and situations (Gay, 1996)

There are several types of scales that have been developed to measure attitude:

Thurstone Scales

This is described by Thurstone & Chave (1929) as a method of equal-appearing intervals. Thurstone scalling is 'based on the law of comparative judgment' (Neuman, 2000). It requires the individual to either agree or disagree with a large number of statements about an issue or object. Thurstone scales typically present the reader with a number of statements to which they have to respond, usually by ticking a true/false box, or agree/disagree, i.e. a choice of two possible responses. Although one of the first scaling methods to be developed, the questionnaires are mostly generated by face to face interviews and rarely used in determining attitude measurement today, thus the example below (figure 1) is irrelevant to online learners.

An example of a Thurstone Scale (figure1)

ATTITUDE TOWARD WAR

An individual is asked to check those items which represent his views.

1. A country cannot amount to much without a national honor, and war is the only means of preserving it. 2. When war is declared, we must enlist. 3. Wars are justifiable only when waged in defense of weaker nations. 4. Peace and war are both essential to progress. 5. The most that we can hope to accomplish is the partial elimination of war. 6. The disrespect for human life and rights involved in a war is a cause of crime waves. 7. All nations should disarm immediately.

(Droba, 1930)

figure 1

Source: http://online.sfsu.edu/~psych200/unit8/84.htm

Advantages DisadvantagesItems are weighted or valued rather than subjects

More difficult to construct than a Likert scale

Easier to construct than a Guttman scale

No more reliable than a Likert scale

Measures only agreement or disagreement

Guttman Scales (Cumulative scales)

Guttman developed this scale in the 1940s in order to determine if a relationship existed within a group of items. The items are ordered from low to high according to difficulty so that to approve or correctly answer the last item implies approval or success of all prior ones (e.g. self-efficacy scale). The respondent selects an item that best applies. The list contains items that are cumulative, so the respondant either agrees or disagrees, if he/she agrees to one, he/she probably agrees to the previous statements. Arguably this scale does not give enough variation of feelings

http://online.sfsu.edu/~psych200/unit8/84.htm

and perceptions, therefore the author suggests, this would not be appropriate for measuring attitude of online learners.

An example of a Guttman Scale (figure 2):

Please indicate what you think about new information technology (IT) by ticking ONE box to identify the statement that most closely matches your opinion (Wilson, 1997)

Agree

IT has no place in the office.

IT needs experts to use it in the office.

IT can be used in the office by those with training.

I'd be happy to have someone use IT to do things for me in the office.

I'd be happy to use IT if I was trained.

I'd be happy to teach myself to use IT.

figure 2:

Source: http://www.hb.se/bhs/nyutb/kurswebb/c-kurser/applirm/qdes4.htm

Advantages DisadvantagesReproducibility Difficult to construct

More one-dimensional than Likert scaling

Scalogram analysis may be too restrictive, only a narrow universe of content can be used

Cornell technique questionable

Results no better than summated Likert scales

Semantic Differential Scaling

This is concerned with the 'measurement of meaning', the idea or association that individuals attach to words or objects. The respondent is required to mark on a scale between two opposing

http://www.hb.se/bhs/nyutb/kurswebb/c-kurser/applirm/qdes4.htm

http://www.hb.se/bhs/nyutb/kurswebb/c-kurser/applirm/qdes4.htm

opinions (bipolar adjectives) the position they feel the object holds on that scale for them. It is often used in market research to determine how consumers feel about certain products.

Three main factors emerge from the ratings, these are:

The evaluative factor (good-bad, pleasant-unpleasant, kind-cruel); the potency factor (strong-weak, thick-thin, hard-soft); the activity factor (active-passive, slow-fast, hot-cold) (Osgood et al, 1957).

Although this scale is comparatively easy for the respondent to complete, the author argues that this would not be suitable for measuring attitude of online learners as it tends to relate more to material associations than cognizance of feelings.

An example of a Semantic Differential Scale (figure 3):

figure 3

Advantages DisadvantagesSimple to construct Analyses can be complex

Easy for subjects to answer

Allows for several types of analyses to take place

Likert Scale (Summated scale)

This was developed by Rensis Likert in 1932. It requires the individuals to make a decision on their level of agreement, generally on a five-point scale (ie. Strongly Agree, Agree, Disagree, Strongly Disagree) with a statement. The number beside each response becomes the value for that response and the total score is obtained by adding the values for each response, hence the reason why they are also called 'summated scales' (the respondents score is found by summing the number of responses). Dumas (1999) suggests, ' this is the most commonly used question format for assessing participants' opinions of usability'.

Two examples of Likert Scales (figures 4 & 5):

figure 4

figure 5Advantages DisadvantagesSimple to construct Lack of reproducibility

Each item of equal value so that respondents are scored rather than items

Absence of one-dimensionality or homogeneity

Likely to produce a highly reliable scale

Validity may be difficult to demonstrate

Easy to read and complete

Reliability and Validity

Likert scale measures are fundamentally at the ordinal level of measurement because responses indicate a ranking only.

As the number of scale steps is increased from 2 up through 20, the increase in reliability is very rapid at first. It tends to level off at about 7, and after 11 steps, there is little gain in reliability from increasing the number of steps (Nunally, 1978, cited by Neuman)

Interestingly, Dyer (1995) states,

'attitude scales do not need to be factually accurate - they simply need to reflect one possible perception of the truth. ……[respondents] will not be assessing the factual accuracy of each item, but will be responding to the feelings which the statement triggers in them'

In line with the above statement, when constructing a Likert scale a pool of statements needs to be generated that are relevant to the attitude (not necessarily fact), (figure 6). The number of choices on the scale should be evenly balanced to retain a continuum of positive and negative statements with which the respondent is likely to agree or disagree although the actual number of choices can be increased. This will help avoid the problem of bias (figure 7) and improves reliability as anyone who answers 'agree' all the time will appear to answer inconsistently.

figure 6

figure 7

As early as 1967, Tittle et al suggest,

The Likert Scale is the most widely used method of scaling in the social sciences today. Perhaps this is because they are much easier to construct and because they tend to be more reliable than other scales with the same number of items (Tittle et al, 1967)

But there still seems to be some contention within research as to whether Likert Scales are a good instrument for measuring attitude; Gal et al (1994) suggest 'Likert-type scales reveal little about the causes for answers........it appears they have limited usefulness'. Helgeson (1993) states that major reviews 'repeatedly point to two problems: lack of conceptual clarity in defining attitudes.....technical limitations of the instrument used to assess attitude' (Helgeson, 1993 cited by Gal et al 1994). The author suggests that some of these 'major' reviews have taken place prior to 1993, and along with the progress in technology, the reasons for measuring attitude may have also changed. It should also be taken into account that this type of scale is not developed to provide any kind of diagnostic information that shows underlying issues of concern to the individual respondents. There are so many questionnaires students are asked to complete in the course of their studies, the interface and usability should be taken into consideration. There are now also researchers who are in favour of using Likert Scales; Robson (1993) suggests, Likert Scales 'can look interesting to respondents and people often enjoy completing a scale of this kind. This means that answers are more likely to be considered rather than perfunctory; and Neuman (2000) who states, 'the simplicity and ease of use of the Likert scale is its real strength'.

Reservations on the use of a central Neutral Point

Arguments exist for including and not including a neutral point, and it would be reasonable to ask what effect adding a neutral point has on the responses you receive. Is it possible that some respondents may be neutral? In which case it could be argued that by not including a neutral point in a scale, the respondent is compelled to make a decision. Kline (cited by Eysenck, 1998) argues for a middle point, 'even though some participants will very often opt out by remaining indecisive'.

Differing with this opinion it has been suggested,

the traditional idea suggests that the qualitative results between the two scales are unaffected since if the respondents are truly neutral, then they will randomly choose one or the other, so forcing them to choose should not bias the overall results (Kahn et al,2000)

It is also suggested that the exclusion of a neutral point will draw the respondent to make a decision one way or the other. This, states Dumas (1999), 'means that by eliminating a neutral level it is providing a better measure of the intensity of participants' attitudes or opinions'. The author suggests that by preventing the respondent to remain neutral, thus causing them to either 'agree' or 'disagree' could reduce the reliability of the scale as the results will not necessarily be true.

Review of Literature

Torkzadeh et al (2001) describe the construction of a scale to measure an individual's self-perception and self-competency in interacting with the Internet. They consulted five practitioners and four academics and developed a five-point Likert-type scale (where 1 is strongly disagree to 5 is strongly agree) using a list of 24 items with objectives to explore responses relating to 'unidimensionality, reliability, brevity and simplicity of the factor structure'. The survey was administered at a university in the Southwest region of the United States to a total of 227 students, with an age range from 17 to 57 years.

They used two main criteria for eliminating items that were not considered valid and reliable; firstly if the correlation of each item with the sum of the other items in its category was less than 0.50. This was using the assumption that 'if all items in a measure are drawn from the domain of a single construct, responses to those items should be highly intercorrelated'. The second criterion was for determining reliability; Cronbach's alpha was used to examine each dimension to see if 'additional items could be eliminated without substantially lowering the reliability'. 'Items were eliminated if the reliability of the remaining items would be at least 0.90.'The resulting figures showed evidence of reliability and construct validity, overall reliability for the scale had a coefficient alpha reliability score of 0.96.The final recommendation after taking into consideration that this was their first exploratory model stated; 'the instrument should also be validated across other variables such as age, education level and profession in order to assess the generalisability of the scale to a more heterogeneous population' but this was not a reflection of the instrument itself. In conclusion, they stated the 'instrument is useful in its present form' although one must always be aware of the ever changing technologies on the World Wide Web and the need to keep up to date with progress.

"this instrument is short, easy to use, reliable and appropriate for use by academics and practitioners to measure Internet-related self-efficacy." (Torkzadeh et al, 2001)

Shaw et al (2000) used a questionnaire arranged in a Likert format to determine attitudes, views and experiences of a group of nutrition students using an asynchronous learning network. The data was obtained through an online 'IT Appreciation' questionnaire completed in class during week 12 of the course. 'The text match questions allowed students to express opinions in their own words and the multiple choice format consisted of 5 possible responses (some reversed to counteract response sets) to the given statement arranged in a Likert format' (Shaw et al, 2000).

It was concluded that the ALN paradigm could be considered a success as the majority of the respondents agreed with the statements that they had become more independent learners. But it was also noted that the largely positive responses to the Likert questions were contradicted by the student responses to the open ended questions.

From this it was decided that further study should determine the discrepancy between the responses to the Likert question and the open-ended questions; it was also considered a possibility that this could be due to the Hawthorne effect (behaviour may be altered because the respondents know they are being studied.) The author suggests therefore, that although the questionnaire was considered a success, the initial construction of the questionnaire along with how it is presented (i.e. online in the classroom with other students or away from the class situation) needs to be considered carefully. The apparent acquiescence could be because the questions some of the questions were single-sided, (although it was stated otherwise) or perhaps there was a large number of 'don't knows' or 'non-responses'; the results don't include any information on this.

Rovai (2002) used a Likert-type scale, referred to as the 'Classroom Community Scale' in his study of 314 distance learners using Blackboard as the mode of delivery. The research was 'to determine if a significant relationship exists between sense of community and cognitive learning in an online educational environment'; with the premise that if online learners feel an 'emotional connectedness' to a community, their learning and motivation will be increased. 20 statements were used (some reverse scored), with a five-point scale of responses: strongly agree, agree, neutral, disagree and strongly disagree. Cronbach's coefficient alpha was used to calculate the reliability which was .93. Content validity was examined by a panel of experts comprising three university professors of educational psychology. Although there is an in-depth discussion with regard to further research, and assumptions that the respondents were typical students that participate in online distance education, the overall conclusion showed that the Classroom Community Scale 'allowed for the hypothesised relationships between the sense of community and cognitive learning'. The author suggests, this Likert-type scale which has been adapted and renamed shows there is considerable scope for the use of Likert scales in an e-learning environment.

Conclusions

Moving questionnaires with Likert scales onto the World Wide Web brings a whole new meaning to questionnaires. They could almost be another source of activity for the online learner. A form of scale that is frequently used is the 'graphic scale', the respondent indicates his/her rating by placing a mark at the appropriate point on a line that runs from one extreme of the attribute to the other. To be a true Likert scale after the series of items has been developed using a graphic rating scale, it is then necessary to determine which items have the highest correlation with a specific criterion measure; only these will be included in the scale.

Although not a graphic scale, figure 8 shows an example of how a Likert scale could be presented in a web page. The use of radio buttons makes it easy to complete, and as there is only one choice, difficult to invalidate by ticking two boxes.

It was easy for me to remember how to perform tasks using spreadsheets

StronglyDisagree

Disagree

Neither

Agree

StronglyAgree

figure 8

Other methods of presenting Likert scales in a web page are by using slider controls (figures 9, 10, 11 & 12). A “slider control” (also known as a trackbar) is a window containing a slider and optional tick marks. They are useful when you want the respondent to select a discrete value or a set of consecutive values in a range. When the user moves the slider, using either the mouse or the direction keys, the control sends notification messages to indicate the change.

figure 9

Source: http://msdn.microsoft.com/library/default.asp?url=/library/en-us/shellcc/platform/ commctls/trackbar/trackbar.asp

figure 10

Source: http://msdn.microsoft.com/library/default.asp?url=/library/en-us/shellcc/platform/commctls/trackbar/trackbar.asp

http://msdn.microsoft.com/library/default.asp?url=/library/en-us/shellcc/platform/commctls/trackbar/trackbar.asp




figure 11

Source: http://archive.devx.com/dhtml/articles/nm061102/slider.html

figure 12

Source: http://archive.devx.com/dhtml/articles/nm061102/Hand.html

The slider moves in increments that you specify when you create it. For example, if you specify that the slider should have a range of five, the slider can only occupy six positions: a position at the left side of the slider control and one position for each increment in the range.

From a technical aspect, a basic knowledge of programming is useful if the designer of the survey or questionnaire wishes to include slider controls in a web page. Radio buttons (figure 8) require a knowledge of html making them an easier option for the less technically minded.

Although there is some question of the reliability of Likert scales and their analytical capacity, the general consensus is in favour of using Likert scales; this is reinforced by the majority of the latterly dated literature reviewed.

Maurer and Pierce (cited by Maurer and Andrews, 2000) investigated the effectiveness of a Likert scale measure of self-efficacy for academic performance. They suggested the Likert scale can be considered a measure of both magnitude and confidence, and they concluded, based on reliability, predictive validity, and factor analysis data, that a Likert scale measure of self-efficacy is an acceptable alternative to the traditional measure.

http://www.hkadesigns.co.uk/websites/msc/reme/likert.htm

Dysfunctional Attitude ScalePosted on October 1, 2009 by Peter

http://overcoming-depression.org/dysfunctional-attitude-scale/

http://overcoming-depression.org/author/admin/

http://www.hkadesigns.co.uk/websites/msc/reme/likert.htm

http://archive.devx.com/dhtml/articles/nm061102/Hand.html

http://archive.devx.com/dhtml/articles/nm061102/slider.html

This scale will give you an indication where your psychological strengths or emotional weaknesses lie. Please complete this questionnaire before my talk, as I will explain the ratings during my talk. You will not be asked to share any of your results with the group– they are for your eyes only!Example

Ring your scores

Agree Strongly

Agree Slightly Neutral

Disagree Slightly

Disagree Very Much

35. People who have the marks of success (good looks, social status, wealth, or fame) are bound to be happier than those who do not. 0 1 2 3 4

Fill in the questionnaire on the next page and transfer your Total Scores to the grid below.Value System Questions Total Scores

I. Approval 1 to 5 &nbsp

II. Love 6 to 10 &nbsp

III. Achievement 11 to 15 &nbsp

IV. Perfectionism 16 to 20 &nbsp

V. Entitlement 21 to 25 &nbsp

VI. Omnipotence 26 to 30 &nbsp

VII. Autonomy 31 to 35 &nbsp

Now plot your Total Scores on the diagram below to develop your ‘personal philosophy profile!’The meanings of these concepts ‘psychological strengths’ and ‘emotional vulnerabilities’ will be explained.

Dysfunctional Attitude Scale Questionaire

Ring your scores

Agree Strongly

Agree Slightly

Neutral

Disagree Slightly

Disagree Very Much &nbsp

1. Criticism will naturally upset the person who receives the criticism. 0 1 2 3 4 &nbsp

2. It is best to give up my own interests in order to please other people. 0 1 2 3 4 &nbsp

3. I need 0 1 2 3 4 &nbsp

Ring your scores

Agree Strongly

Agree Slightly

Neutral

Disagree Slightly


other people’s approval in order to be happy.

4. If someone important to me expects me to do something then I should do it. 0 1 2 3 4 &nbsp

5. My value as a person depends greatly on what others think of me. 0 1 2 3 4 &nbsp

I. Approval. Total Score → &nbsp

6. I cannot find happiness without being loved by another person. 0 1 2 3 4 &nbsp

7. If others dislike you, you are

0 1 2 3 4 &nbsp

Ring your scores

Agree Strongly

Agree Slightly

Neutral

Disagree Slightly


bound to be less happy.

8. If people whom I care about reject me, there’s something wrong with me. 0 1 2 3 4 &nbsp

9. It a person I love does not love me, it means I am unlovable. 0 1 2 3 4 &nbsp

10. Being isolated from others is bound to lead to unhappiness. 0 1 2 3 4 &nbsp

II. Love. Total Score → &nbsp

11. If I am to be a worthwhile person, I must be truly outstanding in at least one major

0 1 2 3 4 &nbsp

Ring your scores

Agree Strongly

Agree Slightly

Neutral

Disagree Slightly


respect.

12. I must be a useful, productive, creative person or life has no purpose. 0 1 2 3 4 &nbsp

13. People who have good ideas are more worthy than those who do not. 0 1 2 3 4 &nbsp

14. If I don’t do as well as other people, it means I am inferior. 0 1 2 3 4 &nbsp

15. If I fail at my work, then I am a failure as a person. 0 1 2 3 4 &nbsp

III. Achievement. Total Score → &nbsp

16. If you can’t do something

0 1 2 3 4 &nbsp

Ring your scores

Agree Strongly

Agree Slightly

Neutral

Disagree Slightly


well, there is little point in doing it at all.

17.It is shameful for a person to display his weaknesses. 0 1 2 3 4 &nbsp

18. A person should try to be the best at everything he undertakes. 0 1 2 3 4 &nbsp

19. 1 should be upset if I make a mistake. 0 1 2 3 4 &nbsp

20. 1f 1 don’t set the highest standards for myself, I am likely to end up a second-rate person. 0 1 2 3 4 &nbsp

IV. Perfectionism. Total Score → &nbsp

21. If I 0 1 2 3 4 &nbsp

Ring your scores

Agree Strongly

Agree Slightly

Neutral

Disagree Slightly


strongly believe I deserve something, I expect that I should get it.

22. It is necessary to become frustrated if you find obstacles to getting what you want. 0 1 2 3 4 &nbsp

23.If I put others people’s needs before my own, they should help me when I need something from them. 0 1 2 3 4 &nbsp

24. If I am a good husband (or wife), then my spouse is bound to love me. 0 1 2 3 4 &nbsp

Ring your scores

Agree Strongly

Agree Slightly

Neutral

Disagree Slightly


25. If 1 do nice things for someone, I can anticipate that they will respect me and treat me just as well as I treat them. 0 1 2 3 4 &nbsp

V. Entitlement. Total Score → &nbsp

26. I should assume responsibility for how people feel and behave if they are close to me. 0 1 2 3 4 &nbsp

27. If I criticize the way someone does something and they become angry or depressed, this means I have upset

0 1 2 3 4 &nbsp

Ring your scores

Agree Strongly

Agree Slightly

Neutral

Disagree Slightly


them.

28. To be a good, worthwhile, moral person, I must try to help everyone who needs it. 0 1 2 3 4 &nbsp

29. If a child is having emotional or behavioural difficulties, this shows that the child’s parents have failed in some important aspect. 0 1 2 3 4 &nbsp

30. I should be able to please everybody 0 1 2 3 4 &nbsp

VI. Omnipotence. Total Score → &nbsp

31. I cannot expect to

0 1 2 3 4 &nbsp

Ring your scores

Agree Strongly

Agree Slightly

Neutral

Disagree Slightly


control how I feel when something bad happens.

32. There is no point in trying to change upsetting emotions because they are a valid and inevitable part of daily living. 0 1 2 3 4 &nbsp

33. My moods are primarily created by factors that are largely beyond my control, such as the past, or body chemistry, or hormone cycles, or chance. 0 1 2 3 4 &nbsp

34. My happiness is

0 1 2 3 4 &nbsp

Ring your scores

Agree Strongly

Agree Slightly

Neutral

Disagree Slightly


largely dependent on what happens to me.

35. People who have the marks of success (good looks, social status, wealth, or fame) are bound to be happier than those who do not. 0 1 2 3 4 &nbsp

VII. Autonomy. Total Score → &nbsp


DYSFUNCTIONAL ATTITUDES SCALE, FORM A; NORMS FOR THE ROMANIAN POPULATION AbstractThe results obtained following administration of the Dysfunctional Attitudes Scale, Form A (Hollon & Kendall, 1980) to a Romanian sample are, on the whole, consistent with those obtained in earlier normative studies involving American samples. The scale was administered to a group of 701 adults and teenagers selected from the normal population. Internal consistency coefficients (Alpha Cronbach) ranged from .79 to .86, which are adequate for reporting reliable results. A pilot study examining validity revealed the DAS-A discriminated between groups with extreme scores on different measures of emotional distress. Norms for the Romanian version of the scale are also included.Key words: CBT, dysfunctional attitudes, reliability, validity, norms for the Romanian population.

http://jcbp.psychotherapy.ro/vol6no2/dysfunctional-attitudes-scale-form-a-norms-for-the-romanian-population/


Pages: 157-171

INTRODUCTIONAccording to DSM IV (2000), clinically depressed people experience extreme feelings of sadness and feel hopeless and helpless weeks on end. Most of the time, they loose interest in the activities they once enjoyed, and have problems sleeping and eating. Many of the persons affected by depression have difficulties concentrating and solving even the simplest of life problems and spend much time contemplating suicide and death. In the severe cases, elaborate plans are made to end one’s life. These symptoms are known to cause major adjustment difficulties that frequently end in life termination.

Among the most efficient methods of treating clinical depression are the cognitive-behavior interventions. The central element that differentiates cognitive-behavior therapies from other psychotherapeutic approaches is the cognitive conceptualization of mental problems. A cognitive conceptualization provides the framework for understanding how the patient’s problem developed and is maintained. Cognitive-behavior therapy is based on the cognitive model, which assumes that people’s emotions are caused mainly by the way they interpret and think about life events (Ellis, 1994; Beck, 1995). Aaron Beck’s perspective on clinical depression (Beck, 1967; Beck, Rush, Emery, & Shaw, 1979) is based on the assumption that depressive people hold negatively biased cognitive schemas that filter out positive information, while favoring negative data. A cognitive schema is a knowledge structure that interacts with newer data entries, selectively orienting attention, expectations, memory retrievals and interpretations (Williams, Watts, MacLeod, & Mathews, 1997). Cognitive schemas develop in time, drawing on personal experience and guiding the interpretation of ambiguous situations, as well as the memory encoding and retrieval of emotion-laden information (Williams et al., 1997). While schemas are cognitive structures within the mind, core beliefs are the specific contents of them (Beck, 1964).

According to the cognitive theory of depression (Beck et al., 1979), depressive schemas and core beliefs represent cognitive vulnerability and are activated by negative life events; once activated, they lead to the generation of negative automatic thoughts. Depressed people harbour negative thoughts about self, world and future, this cognitive triad underlying specific depressive symptoms (Beck, 1967, 1976, 1987). Once activated, dysfunctional schemas and core beliefs produce systematic errors in thinking. Among the most frequent (Beck, 1995):(1) “All or nothing thinking”- the tendency to view a situation in only two categories, instead of on a continuum; absolutistic thinking.(2) Arbitrary inference – the tendency to draw negative conclusions in the absence of supporting evidence.(3) Selective abstraction – the tendency to pay attention to one negative detail, instead of seeing the big picture.(4) Magnification/minimization – the tendency to unreasonably magnify the negative and/or minimize the positive when evaluating one’s self, another person or a situation.(5) Labeling – the tendency to evaluate oneself or another person globally, ignoring evidence that might support a less extreme conclusion.Dysfunctional attitudes reflect the content of stable cognitive schemas (Beck, Brown, Steer, & Weissman, 1991). Previous studies (Dent & Teasdale, 1988; Marton, Churchard, & Kutcher, 1993; Weich, Churchill, & Lewis, 2003) have showed that dysfunctional attitudes are associated with the presence of depressive symptoms.

The Dysfunctional Attitudes Scale (DAS – Weissman, 1979; Weissman & Beck, 1978) is a self-report instrument for assessing attitudes associated with depressive symptoms. Originally a 100-item scale, it was later transformed into two 40-item parallel forms (DAS-A and DAS-B).Using a group of 2.023 psychiatric outpatients diagnosed mainly with affective and anxiety disorders (less than 1.0% were diagnosed with a psychotic disorder), Beck, Brown, Steer and Weissman (1991) examined the factor structure of the original 100-item DAS and found that 66 of the 80 items retained loaded on nine first-order factors. The factors reflected themes of vulnerability, approval, perfectionism, need to please others, imperatives, need to impress others, avoidance of weakness, control over emotions, and disapproval. The factor solution was stable on cross-validation and invariant with respect to gender.

Factor analyses performed on the two 40-item parallel forms revealed different structures, for different target populations. For example, Cane, Olinger, Gotlib and Kuiper (1986) factor analyzed form A of DAS using a non-clinical group of 664 students and found just two factors, which they named “performance evaluation” and “approval by others”. A year earlier, in 1985, Oliver and Baumgart have administered both forms of DAS (A and B) to a group of 275 persons formed by hospital workers and their spouses and found a lack of factorial equivalence between the two forms. In 1984, Parker, Bradshaw and Blignault had administered DAS-A and DAS-B to two samples of Australian general practice patients (N = 117 and 126) and found four factors, which they named “Externalized Self-Esteem”, “Anaclitic Self-Esteem”, “Tentativeness”, and “Need for Approval”. Results obtained with samples of older adults indicate the factor structure established with younger adults does not replicate with this age group. Moreover, the factor structure with older adults seems to be uncertain: a single factor structure, two-factor structure, and three-factor structure are essentially of equal validity (Floyd, Scogin, & Chaplin, 2004).While the factor structure of DAS-A and DAS-B remains uncertain, pending future investigation, reliability coefficients (Alpha Cronbach = .89) are good (Weissman & Beck, 1978), as well as the correlation between the two forms (r=.81).

All things considered, DAS-A is one of the most efficient instruments for measuring the cognitive distortions associated with clinical depression.

The purpose of the present study is to offer a first translation of the scale and preliminary data for the Romanian population, the comprehensive investigation of the psychometric properties of the Romanian version being an objective for future studies.Implications and limits of the present study are discussed in the “Discussion” section.

ITEM DESCRIPTIONThe 40 items of DAS-A are phrased as statements usually underlying depressive idiosyncratic thinking. Each item elicits information on the individual’s dysfunctional beliefs, which act as schemas used to construct the world (Weissman & Beck, 1978). Ten items are phrased in a functional way, while the other 30 represent dysfunctional attitudes.For example, item 4 “If I do not do well all the time, people will not respect me” represents a dysfunctional attitude; at the same time, item 2 “Happiness is more a matter of my attitude towards myself then the way other people feel about me” represents adaptive thinking.Subjects assess each statement, considering the way they usually think, using a 7-point Likert scale, where:1 = Totally agree

2 = Agree very much

3 = Agree slightly

4 = Neutral

5 = Disagree slightly

6 = Disagree very much

7 = Totally disagree

DAS-A score indicates the extent to which dysfunctional attitudes are characteristic of a person’s thinking; the higher the score, the more dysfunctionalthe subject’s attitudes.

SCALE ADMINISTRATION AND SCORINGThe scale is a paper and pencil assessment instrument, which can be administered both individually and collectively. In case of group administration, it is recommended the groups do not exceed 15 persons; however, individual testing is the method of choice whenever possible. When – due to special circumstances – groups exceed 15 persons, the number of evaluators must increase so as there is at least one evaluator for every 15 persons.Materials needed for the scale administration include the 40 items along with instructions and writing tools.Testing environment has to be secure and noise free, properly furnished and illuminated so as to provide optimal testing conditions. The subject has to be adequately motivated and in good physical and mental condition.

The scale is administered without time limit. After all necessary materials and adequate environmental conditions are provided, subject is instructed as follows:„This inventory lists different attitudes or beliefs which people sometimes hold. Read each statement carefully and decide how much you agree or disagree with the statement. For each of the attitudes, show your answer by using the number code given below that best describes what you think. Be sure to choose only one number for each attitude. Because people are different, there is no right or wrong answer to these statements. To decide whether a given attitude is typical of your way of looking at things, simply keep in mind what you are like most of the time.”The DAS-A score is calculated by summing up the individual scores for the 40 items of the test. Every item of the DAS-A is scored from 1 to 7. Depending on the content, either „Totally agree”, or „Totally disagree” will be the anchor point.

For 10 items, scores will start at 1 = “Totally agree”, and move toward 7 = “Totally disagree”. The following items are scored in the adaptive way if a “Totally agree” response in given:

# 2 # 29

# 6 # 30

# 12 # 35

# 17 # 37

# 24 # 40

1 = Totally agree

2 = Agree very much

3 = Agree slightly

4 = Neutral




The other 30 items are scored in the reversed direction, so that 1 = “Totally disagree”, while 7 = “Totally agree”.

7 = Totally agree

6 = Agree very much

5 = Agree slightly

4 = Neutral




The highest possible score is 280 (7×40 items), while the lowest possible score is 40 (1×40 items). The higher the score, the more dysfunctional the subject’sattitudes.Omits will be coded as zero (missing data). However, if the individual omits a large proportion of the items, the test should be ignored.

METHODParticipantsA total of 701 subjects volunteered to participate in the study developed to assess the psychometric properties of the Romanian version of the DAS-A. University students participated in exchange for course credits, while the other subjects were selected from the respondents to public announcements. All subjects were properly informed about test procedure, use of data and confidentiality. For the underage subjects, a parent or legal guardian had to provide agreement. Because some of the subjects failed to provide data concerning gender, educational level, age, and marital status, descriptive statistics reported below will reflect these missing data.

Tables 1- 4. Descriptive statistics for subjects included in study.

Educational levelN = 701 100 %

Secondary school education =

Vocational school education =

High school education =

22

28

222

(3.1 %)

(4.0 %)

(31.7 %)

College education =

University – undergraduate education =

University – graduate education =

Other =

60

346

19

4

(8.6 %)

(49.3 %)

(2.7 %)

(0.6 %)

Age

N = 695

Missing data N=6

M= 34.42

Min.= 15

Max.= 73

Gender

N = 574

Missing data N=127

Male =

Female =

169

405

Marital status

N = 567

Missing data N=134

Married =

Single =

326

241

InstrumentsBeck Depression Inventory (Beck, Rush, Shaw, & Emery, 1979) was used as a measure of current depressive symptoms. BDI is a 21-item self-report measure of depression, with excellent psychometric properties (high internal consistency, retest reliability and convergent validity), as well as sensitiveness to clinical change (Beck, Steer, & Garbin, 1988).Attitudes and Beliefs Scale 2 (DiGiuseppe, Leaf, Exner, & Robin, 1988) was used as a measure of irrational beliefs. ABS2 is a 72-item scale consisting of a 4×3x2 matrix. The first factor consists of belief processes and has four levels representing demandingness (DEM), self-worth or self-downing (SD), low frustration tolerance (LFT) and awfulizing (AWF). The second factor includes content/context information and has three levels representing beliefs about affiliation, achievement and comfort. The third factor determines if the item is worded rationally or irrationally. Therefore, the scale allows the discrete evaluation of irrationality, rationality, demandingness, self-downing, frustration tolerance and awfulizing. The scale is a valid measure of the four irrational beliefs central to rational emotive behavior therapy/theory (REBT). It has high internal consistency and discriminative validity for both American (DiGiuseppe, Robin, Leaf, & Gormon, 1989) and Romanian populations (Macavei, 2002).Unconditional Self-Acceptance Questionnaire (Chamberlain & Haaga, 2001) is a 20-item self-report instrument that measures unconditional acceptance of self. It is based on Albert Ellis’s theory of personal acceptance, the items reflecting different aspects of this complex concept. The questionnaire allows for the calculation of a global score, with high values expressing unconditional self-acceptance, and low values expressing conditional acceptance of one’s personal worth. Empirical data (Chamberlain & Haaga, 2001; David, Schnur & Belloiu, 2002) suggest unconditional self-acceptance is a protective factor against emotional distress when facing negative life events.Profile of Emotional Distress (PED) is a 26-item self-report scale that measures functional and dysfunctional negative emotions, falling into depression/sadness and anxiety/concern categories. The scale was constructed by Opris and Macavei (2005) based on the Profile of Mood States,

Short Version (DiLorenzo, Bovbjerg, Montgomery, Valdimarsdottir, & Jacobsen, 1999) and Albert Ellis’s theory of emotional distress (Ellis, 1994) and has good psychometric properties (Opris & Macavei, in press). The scale allows for the calculation of a global score of distress, as well as discrete scores for functional emotions, dysfunctional emotions, anxiety, depression, concern and sadness.Profile of Mood States-Short Version (POMS-SV) is a 47-item instrument that measures transient levels of distress. This is a short version (Shacham 1983) of the classic mood adjective checklist (McNair, Lorr, & Droppelman, 1971) that allows for the assessment of six affective dimensions and provides a total distress score. Test-retest reliability for each of the subscales have been found to be consistent with the long version, and have been demonstrated to have good criterion validity (DiLorenzo, Bovbjerg, Montgomery, Valdimarsdottir, & Jacobsen, 1999).Automatic Thoughts Questionnaire is a 30-item self-report measure of depression related automatic thoughts, elaborated in 1980 by Hollon and Kendall. It consists of statements reflecting idiosyncratic depressive thinking (Beck, 1976, Beck, 1995).PROCEDUREAfter giving an informed consent, participants were interviewed and tested individually; persons under 18 years of age were allowed to participate following consent of a parent or legal guardian. They participated in an assessment interview, during which the tests and scales were administered. Measures were administered without time limit, in random order, to control for any application order effects. The interviews were conducted by licensed psychologists.All participants were debriefed and the ones in need of counseling or psychotherapy were offered low-cost therapy referrals.

RESULTSResults obtained using a non-clinical group of 701 adult subjects indicate there is no significant difference between groups according to gender (t = 2.30, p > .05).

Norms were developed using five normal classes, (the corresponding percentages are 6.7%, 24.2%, 38,2%, 24.2%, 6.7%). Thus, the first class includes 6.7% of subjects, those with the lowest level of dysfunctional attitudes. The fifth class also includes 6.7% of subjects, those with the highest level of dysfunctional attitudes. Because there is no significant difference between groups according to gender (t = 2.30, p> .05), same norms were elaborated for men and women.Table 5. Descriptive statistics for DAS-A.

DAS-A Female Male Combined

Scores M 131.32 136.50 125.92

S.D. 24.11 24.16 28.87

N 398 163 682

* Note: 121 persons miss data on gender

Table 6. Norms for the Romanian version of DAS-A.

Male and female

Classes Description Scores

I Very low level of dysfunctional attitudes £ 79

II Low level of dysfunctional attitudes 80-112

III Medium level of dysfunctional attitudes 113-142

IV High level of dysfunctional attitudes 143-169

V Very high level of dysfunctional attitudes ³ 170

ReliabilityReliability of a psychological instrument reflects the extent to which all items refer to the same construct. Reliability is most often expressed based on internal consistency coefficients and score stability in time (Anastasi, 1988).While the factor structure of DAS-A and DAS-B remains uncertain pending future investigation, reliability coefficients for the English version (Alpha Cronbach = .89) are good (Weissman & Beck, 1978).

For the Romanian version of DAS-A internal consistency was assessed using 682 subjects. Alpha Cronbach coefficient was .86, which indicates all items express the same construct described by A. Beck (1976) – dysfunctional attitudes associated with depression.Table 7. Descriptive statistics and Alpha Cronbach coefficients for DAS-A, according to gender.

DAS-A Adults (age – 15-73, m=34.42 )

Female Male Combined*

Global score M 131.32 136.50 125.92

S.D. 24.11 24.16 28.87

N 398 163 682

a .81 .79 .86

* The difference between N-combined and the sum of N-female and N-male is given by the missing date on gender for some of the subjects.

ValidityThe 40 items of DAS-A come from a 100-item pool, which served to the elaboration of two 40-item parallel forms of DAS (A and B) (Beck, Brown, Steer & Weissman 1991).

In order to assess discriminative validity of DAS-A, three sets of extreme score groups were created based on (1) Profile of Emotional Distress global score, (2) Profile of Mood State-SV global score, and (3) Profile of Emotional Distress, depression subscore. Extreme scores groups were generated by adding and subtracting 1 S.D. to and from the mean score of each test. The “medium” group includes all values between the two extremes.

Table 8. Descriptive statistics for the tests used to generate extreme score groups.

Instrument m S.D. N

Low score group

High score

group

Profile of Emotional Distress – global score 49.80 18.77 782 < 31 > 69

Profile of Emotional Distress – depression subscore 12.71 6.28 811 < 6 > 19

Profile of Mood State-SV global score 50.05 29.61 224 < 20 > 80

For all three measures of emotional distress mentioned above, differences between extreme groups were significant (see Table 9). Although the extreme groups have relatively few subjects, results represent an argument for the ability of DAS-A Romanian version to discriminate between subjects with high and low levels of negative emotions.

Table 9. Comparisons among extreme groups for three measures of emotional distress.

DAS-A

Groups m S.D. N F

Profile of Emotional Distress – global score

High 144.03 24.01 60

F(2,536) = 11.27,

p<.05 (all 3 groups)

Medium 132.23 23.93 422

Low 123.14 24.67 57

Profile of Emotional Distress – depression subscore

High 146.02 22.86 60

F(2, 552) = 10.37, p<.05 (all 3 groups)

Medium 131.01 24.21 460

Low 132.03 23.32 35

Profile of Mood State-SV global score

High 139.49 25.95 35

F(2, 212)= 17.36, p<.05 (all 3 groups)

Medium 109.97 31.34 151

Low 98.17 31.02 29

The Romania version of the DAS-A also correlates positively with other measures of dysfunctional thinking (e.g., Automatic Thoughts Questionnaire, Attitudes and Beliefs Scale 2), and negatively with unconditional self-acceptance (Unconditional self-acceptance questionnaire) (Table 10). At the same time, results indicate a positive association between dysfunctional attitudes and negative affect and a negative association

between dysfunctional attitudes and positive affect (Table 10). These preliminary results should encourage future studies into the psychometric properties of DAS-A.Table 10. Correlations (r-Pearson) between DAs-A score and the scores for other measures of dysfunctional/functional thinking and affect.

DAS-A

1 PED – global score (N= 539) .26

2 PED – sadness subscale (N= 555) .21

3 PED – depression subscale (N = 555) .27

4 PED – anxiety subscale (N= 554) .25

5 PED – concern subscale (N= 558) .19

6 PED – functional emotions (N= 551) .22

7 PED – dysfunctional emotions (N= 548) .28

8 BDI (N= 230) .50

9 USAQ (N= 234) -.69

10 ATQ (N= 231) .52

11 ABS2 – IB (N= 220) .77

12 POMS-SV – global score (N= 215) .47

13 POMS-SV – negative emotions (N= 220) .45

14 POMS-SV – positive emotions (N= 230) -.36

* all correlations are significant at p£.01

CONCLUSIONS AND DISCUSSIONThe growing interest in cognitive-behavior theory and method Romanian mental health professionals and clients have expressed during the last years has encouraged us to try to make available yet another instrument to be used in research and practice.

At the core of all cognitive-behavior therapies lies the assumption that our maladaptive emotions and behaviors are caused by the endorsement ofdysfunctional attitudes and beliefs. In an attempt to identify cognitions directly responsible for our reactions, different professionals stressed either the role of cold cognitions (schemas and automatic thoughts – Beck, 1976; Beck, 1995), or hot cognitions (evaluations – Ellis, 1994, Lazarus, 1991). Fortunately, recently some avant-garde CBT professionals have begun to point out the need to investigate and clarify the

relation between cold and hot cognitions and the way they interact to cause emotional and behavioral consequences (David et al., 2002; David, 2006). Along with ABS2 (Macavei, 2002), we hope the Romanian version of DAS-A constitutes a useful working instrument for all interested.Because time and resources did not allow for a comprehensive evaluation of Romanian version of DAS-A properties, data offered in this article should be used cautiously, pending future investigations.




Attitude Scale

Documents

Transcript of Attitude Scale