National Tolerance

National Tolerance

Lab Report

Word count: 1500

YOU MUST SUBMIT YOUR SPSS OUTPUT

The aim of this lab report is to present the psychometric properties of a new scale. Although the context is prejudice and tolerance, the lab report is on psychometrics, not your understanding of prejudice. As such, you only need to understand attitudes enough to construct your hypotheses and to have a rationale for creating or using the new scale. Please think logically about your argument and how you will validate this scale, at the conceptual level, rather than letting the statistics drive it. 

INTRODUCTION:

The introduction is on the development of the scale to assess prejudice towards Muslims in Australia, not on prejudice itself – why do we need this new scale, about attitudes/tolerance.

STARTER REFERENCES

The citation and the purpose for each are detailedbelow:

Paper #1

Griffiths and Pedersen (2009) present a multi-study paper on the function that attitudes towards outgroups serves in the Australian context. Of particular interest is the study presenting the attitudestowards Muslims scale, which is included in your data set as a variable that could be used forvalidation purposes.

Paper #2

Verkuyten and Yogeeswaran (2017) present a theory paper on the contributions of social psychology to intergroup understandings through a framework of tolerance. Of particular interest is theconceptual distinction between prejudice and tolerance in intergroup attitudes.

Paper #3

Anderson (2016) presents an empirical analysis of prejudice towards asylum seekers in Australia.

Although this is a different social group, it gives you an idea of which demographic and ideological factors tend to be related to out-group attitudes in an Australian sample and thus might be useful formaking predictions.

Paper #4

Anderson, Guan, and Koc (2016) present the psychometric properties for the academic adjustment scale. Although this is a non-related construct, it is a paper on scale validation – although not all ofthis is relevant to you, it will be useful for you to see how validation and reliability scales can beoperationalized.

AIM:

You are to present evidence for the psychometric properties of a new measure that assesses two dimensions of intergroup perceptions of Muslims in Australia. The Australian Muslim Attitude and Tolerance Scale (AMATS) has two subscales:

Attitudes subscale (AMATS-A) – an evaluative component in which lower scores reflect an individuals’ endorsement of modern prejudice against Muslims

Tolerance subscale (AMATS-T) – an evaluation-free component in which higher scores reflect an individuals’ ability not to interfere with matters that do not concern them, even if they find it questionable.

The Data File:

The data file first has the average score for each of the 2 subscales of the AMATS, followed by the participant demographics, then finally  followed by scale variables (averages) for each validation measure. The variables are detailed below:

  • AMATS_A – the average score of the 6 attitude items in the Australian Muslim Attitude andTolerance Scale.
  • AMATS_T – the average score of the 6 tolerance items in the Australian Muslim Attitude andTolerance Scale.
  • Age – years since birth. Missing data is coded as 99.
  • Birth – self-reported country of birth – open ended text. Missing data is coded as 99.
  • Religion – categorical self-reported religious affiliation. Note: this variable has been recoded as ‘Christian_not’ for use in analyses.
    1. Christian
    2. Jewish
    3. Muslim
    4. Hindu
    5. Buddhist
    6. No religion
    7. Agnostic
    8. Atheist
  • Political_orientation – self-reported political orientation as it relates to social issues on a scale ranging from 1 (progressive) to 5 (conservative).
  • Sex – self reported sex coded as male (1), female (2) or other (3). For ease of dichotomizing the sample, missing data has been coded as 99 or 3 (meaning that those identifying as ‘other’ will be excluded from any analyses using the gender variable).
  • Christian_not – a dummy coded version of the ‘Religion’ variable.
    • Those who reported having no religion or being atheist/agnostic were recoded as 0.
    • Those who reported being Christian remained as 1.
    • Those reporting any other religion were coded as 0 – missing data has been coded as 99 or 3 (meaning that those identifying as ‘other’ religions will be excluded from any analyses using the Christian_not variable).
  • National_Tolerance – The aggregated score for the five items used to measure an individuals levels of social tolerance. These items were taken from Smeekes, Verkuyten, and Poppe (2012), and were endorsed by participants on a scale ranging from 1 (strongly disagree) to 7 (strongly agree). In this sample, the religiosity variable yielded poor reliability (α = .58).
  • SDO – The aggregate score for the items in the social dominance orientation scale (Pratto, Sidanius, Stallworth, &Malle, 1994). This is individual difference measure of endorsing the need for outgroup differences through social hierarchies is measured on a scale ranging from 1 (strongly disagree) to 7 (strongly agree). In this sample, the SDO variable yielded acceptable reliability (α = .91).
  • Religiosity – The aggregate score for the items in the short-form of the religious fundamentalism scale (Altemeyer&Hunsberger, 2004). This is an individual difference quantification of religion (for an understanding of categorical vs. continuous religion variables, see Anderson, 2015), which is measured on a scale ranging from 1 (strongly disagree) to 7 (strongly agree). In this sample, the religiosity variable yielded acceptable reliability (α = .94).
  • National_identification – The aggregated score for the five items used to measure strength of national identification. These items were first used by Pedersen, Attwell, and Heveli (2005) to test for the role of national identification in Australians’ prejudice towards outgroup (see also Anderson, 2016; Anderson & Ferguson, 2017). In this sample, participants endorsed these items on a scale ranging from 1 (strongly disagree) to 7 (strongly agree); the national identification variable yielded acceptable reliability (α = .88).
  • ATMS – The aggregated score for the attitudes toward Muslims scale (Griffiths & Pedersen, 2009). In this sample, the ATMS yielded acceptable reliability (α = .96).

Finally, in order to allow you to calculate estimates of reliability, the 12 items of the AMATS are included in the data file.         

Measures

Original Scale – Psychometric properties to be established:

Australian Muslim Attitude and Tolerance Scale (AMATS)

Strongly Disagree Strongly Agree
Attitudes
Muslim people are as considerate as everyone else.
People who are Muslim do not respect women. ®
People who practice Islam are more aggressive than people who do not. ®
Muslims do not always behave appropriately in public. ®
Muslims are peaceful people.
Muslims are respectful of other people’s beliefs.
Tolerance
Islamic women should be allowed to wear head coverings.
Muslim people have the right to build Mosques in the community where they live.
Muslim people should be allowed time off work to observe their religious holidays.
Muslims should only practice their religion in private. ®
I would prefer not to have Mosques in my neighbourhood. ®
Halal certified food should not readily available in restaurants. ®

National Tolerance:

Adapted from Smeekes et al. (2012).

Strongly Disagree Strongly Agree
Muslims have the right to show and express their religion in public life.
The right to establish own Islamic schools should always exist in Australia.
Some Islamic holy days should become official Australian holidays.
Australian TV should broadcast more programs by and for Muslims.
In Australia, the wearing of a headscarf should not be forbidden.

National Identification:

Adapted from Pedersen et al. (2005).

Strongly Disagree Strongly Agree
I have a lot in

common with the average Australian.

I am similar to the average Australian person.
I often think about the fact that I am Australian.
The fact that I am Australian is an important part of my identity.
Being Australian is an important part of how I see myself.

Social Dominance Orientation

Taken from Pratto et al. (1994)

Strongly disagree Strongly agree
Some groups of people are simply inferior to other groups.
In getting what you want, it is sometimes necessary to use force against other groups.
It’s OK if some groups have more of a chance in life than others.
To get ahead in life, it is sometimes necessary to step on other groups.
If certain groups stayed in their place, we would have fewer problems.
It’s probably a good thing that certain groups are at the top and other groups are at the bottom.
Inferior groups should stay in their place.
Other groups must be kept in their place.
It would be good if groups could be equal.
Group equality should be our ideal. (R)
All groups should be given an equal chance in life. (R)
We should do what we can to equalise conditions for different groups. (R)
Increased social equality. (R)
We would have fewer problems if we treated people more equally. (R)
We should strive to make incomes as equal as possible. (R)
No group should dominate in society. (R)

Religiosity

Taken from Altemeyer and Hunsberger (2004)

Strongly Disagree Strongly Agree
God has given humanity a complete, unfailing guide to happiness and salvation, which must totally be followed.
No single book of religious teaching contains all the intrinsic, fundamental truths about life.
The basic cause of evil in this world is Satan, who is constantly and ferociously fighting against God.
It is more important to be a good person than to believe in God and the right religion.
There is a particular set of religious teachings in this world that are so true, you can’t go any “deeper” because they are the basic, bedrock message that God has given humanity.
When you get right down to it, there are basically only two kinds of people in world; the righteous, who will be rewarded by God; and the rest, who will not.
Scriptures may contain general truths, but they should NOT be considered completely, literally true from beginning to end.
To lead the best, most meaningful life, one must belong to the one, fundamentally true religion.
“Satan” is just a name people give to their own bad impulses. There really is no such thing as a diabolical “Prince of Darkness” who tempts us.
Whenever science and sacred scripture conflict, science is probably right.
The fundamentals of Gods religion should never be tampered with, or compromised.
All of the religions in the world have flaws and wrong teachings. There is no perfectly true, right religion.

 Attitudes Toward Muslim Australian Scale

Taken from Griffiths and Pedersen (2009)

Strongly disagree Strongly agree
The average Muslim is as reasonable as everyone else ®
Islamic schools should not be allowed in this country
Muslims do not respect freedom of speech
Islam is no threat to Australia’s freedom®
All Muslims are potentially terrorists
The majority of Muslims are law abiding citizens ®
The Muslims are a peace loving community ®
Islam is threatening Australia’s freedom
Muslims are respectful and sensitive toward other religions within Australia®
Muslims have a hatred of western values
Islam is a dangerous religion and should be banned in Australia
As a multicultural nation, Australians should accept that Muslims are entitled to express their religious identity freely. ®
Islamic beliefs and customs are not compatible with multicultural Australia
I do not want my family mixing with Muslim families
Muslims do not want to obey our laws
Muslims are just as friendly as other Australians ®

References

Altemeyer, B., &Hunsberger, B. (2004). A Revised Religious Fundamentalism Scale: The Short and Sweet of It. International Journal for the Psychology of Religion, 14(1), 47-54.

doi:10.1207/s15327582ijpr1401_4

Anderson, J. R. (2015). The social psychology of religion: Using scientific methodologies to understand religion. In B. Mohan (Ed.), Constructions of Social Psychology. Baton Rouge, CA: inScience Press.

Anderson, J. R. (2016). Implicit and explicit attitudes toward asylum seekers: Demographic and ideological correlates. Australian Psychologist, 1-11. doi:10.1111/ap.12229

Anderson, J. R., & Ferguson, R. (2017). Demographic and ideological correlates of negative attitudes toward asylum seekers: A meta-analytic review. Australian Journal of Psychology.

doi:10.1111/ajpy.12162

Anderson, J. R., Guan, Y., &Koc, Y. (2016). The academic adjustment scale: Measuring the adjustment of permanent resident or sojourner students. International Journal of Intercultural Relations, 54, 68-76. doi:10.1016/j.ijintrel.2016.07.006

Griffiths, B., & Pedersen, A. (2009).Prejudice and the function of attitudes relating to Muslim Australians and Indigenous Australians.Australian Journal of Psychology, 61(4), 228-238.

Pedersen, A., Attwell, J., &Heveli, D. (2005). Prediction of negative attitudes toward Australian asylum seekers: False beliefs, nationalism, and self-esteem. Australian Journal of Psychology, 57(3), 148-160. doi:10.1080/00049530500125157

Pratto, F., Sidanius, J., Stallworth, L. M., &Malle, B. F. (1994). Social dominance orientation: A personality variable predicting social and political attitudes. Journal of Personality and Social Psychology, 67(4), 741. doi:10.1037/0022-3514.67.4.741

Smeekes, A., Verkuyten, M., &Poppe, E. (2012). How a tolerant past affects the present: Historical tolerance and the acceptance of Muslim expressive rights. Personality and Social Psychology Bulletin, 38(11), 1410-1422.

Verkuyten, M., &Yogeeswaran, K. (2017).The Social Psychology of Intergroup Toleration.Personality and social psychology review, 21(1), 72-96. doi:10.1177/1088868316640974 

Solution 

A New Measure Of Tolerance And Attitudes Regarding Muslims In Australia: Reliability And Validity Correlates

Word count: 1547

Attitudes are beliefs held by individuals regarding the evaluations of objects as positive or negative (Allport, 1935). When extremely negative attitudes are based on stereotypes and overgeneralization, these lead to prejudice and discrimination. Given the global political climate and tensions between Eastern and Western cultures, Islamic worshippers tend to become targets of such prejudice were they represent a minority (Dunn, Klocker, &Salabay, 2007).

In Australia, according to the latest census, there has been a 15% increase in the number of Muslims which are part of the population (ABS, 2017). Therefore, careful consideration of factors which increase prejudice and discrimination against this group is needed. Griffiths and Pedersen (2009) argued that to consider the role of attitudes in prejudice requires localized approach and instruments, and accordingly devised a scale of measuring attitudes towards Muslims in the Australian context. However, this scale does not consider the role of tolerance, as a measure of non-evaluative beliefs with implications in resilience towards prejudice (Verkuyten&Yogeeswaran, 2017). More so, their scale includes some items which could be argued of pertaining to tolerance more than attitudes (e.g. item 2).

Tolerance is defined as “a specific attitude structure whereby competing groups maintain a positive action orientation toward one another in spite of openly conflicting values or interests” (Jackman, 1977). The role of tolerance, or lack thereof, has been extensively theorized and supported empirically in the literature (Verkuyten&Yogeeswaran, 2017). Therefore, the current study aimed to develop and validate a new scale with relevance towards Islamic prejudice in Australia, the Australian Muslim Attitude and Tolerance Scale (AMATS) which features two subscales: one related to attitudes towards Muslims and one related to tolerance of Muslims.

In order to measure the reliability of the AMATS, a test-retest procedure was conducted in order to assess the temporal stability of the instrument. It was hypothesized that each subscale will correlate significantly and positively at both times of measurement.

In order to measure the convergent validity of the AMATS, a Pearson correlation coefficient was computed for each subscale with the score of Griffiths and Pedersen’s (2009) measure. It was hypothesized that both subscales will correlate negatively with this measure, since low scores on the AMATS indicate a high level of prejudice and a low level of tolerance.

In order to measure the concurrent validity of the AMATS, a Pearson correlation coefficient was computed for each subscale with the score of a national identification measure. This criterion (Kaplan &Saccuzzo, 2017) was chosen since multiple studies (Pedersen, Attwell, &Heveli, 2005; Smeekes, Verkuyten, &Poppe, 2011), including a meta-analysis (Anderson & Ferguson, 2017), found national identification as positively associated with negative views towards out-groups. It was again hypothesized that both subscales will correlate negatively with this measure.

Methods

Participants

A convenience sample of 146 participants was recruited for this study. 74.1% of the sample is female (with 3.4% describing themselves as other than male or female), which is not representative of the population. The mean age is 26.72 years old (SD=11.39) and 42.2% of the sample is Christian, with the second and third most common religious views being that of Agnostic, with 23.8% , and Atheist, with 17.7% respectively. Only 2.7% of the sample declared themselves as Muslim. Additionally, 78.9% of the sample had Australia as the country of birth.

Instruments

Australian Muslim Attitude and Tolerance Scale (AMATS) is a self-report instrument which contains 12 items. It has two subscales: Attitudes – which measures an evaluative component where lower scores indicate a modern prejudice against Muslims, and Tolerance – which measures a non-evaluative ability of not interfering in Islamic cultural matters that do not concern the individual (as indicated by higher scores). The first 6 items pertain to the Attitudes subscale while the last 6 belong to the Tolerance subscale. Each item is answered on 7 point Likert scale ranging from “Strongly disagree” to “Strongly agree” and items 2, 3, 4, 10, 11, 12 are reversed scored. The score for each subscale is computed as the mean of the scores for the pertaining items.

National Identification (Pedersen et al., 2005) is a self-report instrument measuring the strength of national identification. It contains five items answered on 7 point Likert scales ranging from “Strongly disagree” to “Strongly agree” and the total score is computed as the mean of the scores of all items. Higher scores indicate stronger national identification. The reliability of this scale in the current sample was acceptable (α = .88).

Attitudes Toward Muslim Scale (ATMS) (Griffiths & Pedersen, 2009) is a self-report instrument measuring prejudice against Muslims. It contains sixteen items answered on 7 point Likert scales ranging from “Strongly disagree” to “Strongly agree” and the total score is computed as the mean of the scores of all items (items 1, 4, 6, 7, 9, 12, and 16 are reverse scored). Higher scores indicate more intense prejudice and intolerance against Muslims. The reliability of this scale in the current sample was acceptable (α = .96).

Procedure

The study features a mixed non-experimental design, where measurements for the validity analyses were taken at the same time, specific to a cross-sectional design, while a second measurement on the AMATS was taken at a later time for the reliability analysis, specific to a longitudinal design. Only 40 participants were available for the second measurement, indicating a drop-out rate of 72.6%. Participants completed the self-report measurements online after also completing a set of demographic questions. Confidentiality, anonymity, and the right to withdraw from the research were guaranteed during the initial briefing. 

Results

The descriptive statistics including mean and standard deviation for the main study variables are viewable in Table 1.

The correlation between Time 1 and Time 2 Attitudes subscale of the AMATS was statistically significant, r(38)=.753, p<.05. Thus, we fail to reject the null hypothesis that the two measures of AMATS attitudes taken at different times are unrelated. Since this result is statistically significant and the direction of the correlation is positive, this is reflective of the increased reliability of this subscale.

The correlation between Time 1 and Time 2 Tolerance subscale of the AMATS was statistically significant, r(38)=.823, p<.05. Thus, we fail to reject the null hypothesis that the two measures of AMATS tolerance taken at different times are unrelated. Since this result is statistically significant and the direction of the correlation is positive, this is reflective of the increased reliability of this subscale.

The correlation between the Attitudes subscale of the AMATS and the ATMS was statistically significant r(144)=-.893, p<.05. Thus, we fail to reject the null hypothesis that the measure of attitudes through AMATS is unrelated to the ATMS. Since this result is statistically significant and the direction of the correlation is negative as expected, this is reflective of the increased convergent validity of the AMATS Attitudes subscale.

The correlation between the Tolerance subscale of the AMATS and the ATMS was statistically significant r(144)=-.855, p<.05. Thus, we fail to reject the null hypothesis that the measure of tolerance through AMATS is unrelated to the ATMS. Since this result is statistically significant and the direction of the correlation is negative as expected, this is reflective of the increased convergent validity of the AMATS Tolerance subscale.

The correlation between the Attitudes subscale of the AMATS and the National Identification scale was statistically significant r(144)=-.186, p<.05. Thus, we fail to reject the null hypothesis that the measure of attitudes through AMATS is unrelated to National Identification. Since this result is statistically significant and the direction of the correlation is negative as expected, this is reflective of the increased concurrent validity of the AMATS Attitudes subscale.

The correlation between the Tolerance subscale of the AMATS and the National Identification scale was statistically significant r(144)=-.251, p<.05. Thus, we fail to reject the null hypothesis that the measure of tolerance through AMATS is unrelated to National Identification. Since this result is statistically significant and the direction of the correlation is negative as expected, this is reflective of the increased concurrent validity of the AMATS Tolerance subscale.

Discussion

The current study aimed to develop and empirically validate a new measure of prejudice against Muslims in Australia which would account for both attitudes and tolerance regarding this cultural minority. To this purpose, a test-retest reliability analysis, as well as convergent and concurrent validity analysis was conducted.

The results support both the reliability and validity of the instrument, with statistically significant correlations identified in the analyses for both subscales of the AMATS and in the expected direction. Regarding the reliability, even though significant, the correlation coefficients were rather low (coefficients of determination of .567 and .677) suggesting that the temporal reliability can be improved (Kaplan &Saccuzzo, 2017). Regarding convergent validity, the coefficients were both significant and high, suggesting that the AMATS is just as efficient as measuring the construct of prejudice as other similar measures. Finally, regarding concurrent validity, the coefficients of determination were very low, albeit significant (0.035 and 0.063). This might suggest that either the concurrent validity of the AMATS is low or that national identification is a poor criterion, since previous studies also failed to find associations with prejudice and negative attitudes (Anderson, 2016).

The current study is limited by an overrepresentation of female participants and future studies should aim to assess other forms of validity (predictive, discriminant) and reliability (internal consistency, split-half).

Table 1
Descriptive Statistics for Continuous Demographic and Main Study Variables (N=146)
Variable Minimum Maximum M SD
Age (N=145) 15 61 26.72 11.39
Social Political Conservatism 1 5 3.48 0.98
AMATS Attitudes Subscale 1 7 5.18 1.50
AMATS Tolerance Subscale 1 7 5.29 1.42
National Identification 1 7 4.52 1.40
ATMS 1 7 2.62 1.37

References

Allport, G. (1935). Attitudes.in (Ed.) Murchison, C., A Handbook of Social Psychology. Worcester, MA: Clark University Press, 789–844.

Anderson, J. R. (2016). Implicit and explicit attitudes toward asylum seekers: Demographic and ideological correlates. Australian Psychologist, 1-11. doi:10.1111/ap.12229

Anderson, J. R., & Ferguson, R. (2017). Demographic and ideological correlates of negative attitudes toward asylum seekers: A meta-analytic review. Australian Journal of Psychology. doi:10.1111/ajpy.12162

Australian Bureau of Statistics (2017).Census of Population and Housing: Reflecting Australia – Stories from the Census, 2016 . Retrieved from http://www.abs.gov.au/ausstats/abs@.nsf/Lookup/by%20Subject/2071.0~2016~Main%20Features~Religion%20Data%20Summary~25

Dunn, K. M., Klocker, N., &Salabay, T. (2007). Contemporary racism and Islamaphobia in Australia: Racializing religion. Ethnicities7(4), 564-589.

Griffiths, B., & Pedersen, A. (2009).Prejudice and the function of attitudes relating to Muslim Australians and Indigenous Australians.Australian Journal of Psychology, 61(4), 228-238.

Jackman, M. R. (1977). Prejudice, tolerance, and attitudes toward ethnic groups. Social Science Research6(2), 145-169.

Kaplan, R. M., &Saccuzzo, D. P. (2017). Psychological testing: Principles, applications, and issues. Nelson Education.

Pedersen, A., Attwell, J., &Heveli, D. (2005). Prediction of negative attitudes toward Australian asylum seekers: False beliefs, nationalism, and self-esteem. Australian Journal of Psychology, 57(3), 148-160. doi:10.1080/00049530500125157

Smeekes, A., Verkuyten, M., &Poppe, E. (2011).Mobilizing opposition towards Muslim immigrants: National identification and the representation of national history. British Journal of Social Psychology50(2), 265-280.

Verkuyten, M., &Yogeeswaran, K. (2017).The Social Psychology of Intergroup Toleration.Personality and social psychology review, 21(1), 72-96. doi:10.1177/1088868316640974

ANNEX 1. SPSS OUTPUT

Correlations
Time1_Attitudes Time2_Attitudes
Time1_Attitudes Pearson Correlation 1 ,753**
Sig. (2-tailed) ,000
N 107 40
Time2_Attitudes Pearson Correlation ,753** 1
Sig. (2-tailed) ,000
N 40 51
**. Correlation is significant at the 0.01 level (2-tailed).
Correlations
ATMS ATMS AMATS_A Attitudes Subscale
ATMS ATMS Pearson Correlation 1 -,893**
Sig. (2-tailed) ,000
N 146 146
AMATS_A Attitudes Subscale Pearson Correlation -,893** 1
Sig. (2-tailed) ,000
N 146 146
**. Correlation is significant at the 0.01 level (2-tailed).
Correlations
ATMS ATMS AMATS_T Tolerance Subscale
ATMS ATMS Pearson Correlation 1 -,855**
Sig. (2-tailed) ,000
N 146 146
AMATS_T Tolerance Subscale Pearson Correlation -,855** 1
Sig. (2-tailed) ,000
N 146 146
**. Correlation is significant at the 0.01 level (2-tailed).
Correlations
AMATS_T Tolerance Subscale National_identification National Identity
AMATS_T Tolerance Subscale Pearson Correlation 1 -,251**
Sig. (2-tailed) ,002
N 146 146
National_identification National Identity Pearson Correlation -,251** 1
Sig. (2-tailed) ,002
N 146 146
**. Correlation is significant at the 0.01 level (2-tailed).
Correlations
National_identification National Identity AMATS_A Attitudes Subscale
National_identification National Identity Pearson Correlation 1 -,186*
Sig. (2-tailed) ,025
N 146 146
AMATS_A Attitudes Subscale Pearson Correlation -,186* 1
Sig. (2-tailed) ,025
N 146 146
*. Correlation is significant at the 0.05 level (2-tailed).