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Evaluating Diversity and Inclusion Programs Designed to Change Social Attitudes

Donald Fischer, Adena Young-Jones and Sequana Tolon

Missouri State University

Fischer, D., Young-Jones, A & Tolon, S. (2014, April). Evaluating Diversity and Inclusion

Programs Designed to Change Social Attitudes. Paper presented at the 29th

annual meeting of the

Society for Industrial and Organizational Psychology, Honolulu, HI

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ABSTRACT

Malleability of racial attitudes of students in courses with objectives that involve understanding

and valuing diversity were assessed using both implicit and explicit measures. Support for the

malleability of overt bias assessed by explicit measures was tempered with mixed support for the

malleability of automatic bias assessed by implicit measures.

PRESS PARAGRAPH

Decreases in the overt expression of racist attitudes over the past half-century have been

accompanied by evidence of pervasive implicit racial bias. Diversity and inclusion programs

often endeavor to help participants learn about their own attitudes as a way of motivating

positive change. Despite the widespread use of these programs, empirical evidence supporting

their effectiveness has been lagging – one survey of colleges and universities reported that 81%

used diversity training to address racial discrimination without any evaluation of their

effectiveness. This study examined an intervention designed to change social attitudes and found

mixed evidence in support of its effectiveness.

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Diversity and inclusion initiatives are prevalent employment practices in both public and

private sector organizations. It is estimated that over half of all employers in the U.S. with more

than 100 employees, and over 75% of the largest of these, have diversity and inclusion programs

(Hays-Thomas & Bendick, 2013). Globalization and an increasingly diverse workforce are often

cited as factors that require cultural competence and inclusive climates to effectively manage

human capital and leverage competitive advantage (Cascio & Aguinis, 2011; Ployhart 2012;

Thomas, 2005). Diversity and inclusion initiatives address the problems of conscious and

unconscious discrimination and one’s perception “that he or she is an esteemed member of the

work group through experiencing treatment that satisfies his or her needs for belongingness and

uniqueness” (Shore et al., 2011). Within this context an expansive list of attributes define

diversity – gender and sexual orientation, race and ethnicity, age, weight, disability, religious

practice, family status, educational background, personality traits, work styles, and functional

specialties are all pertinent when defining the construct of diversity in the workplace (Hays-

Thomas & Bendick, 2013).

Interventions seeking to create climates which respect diversity and value inclusion

typically focus upon changing social attitudes (Wah, 2012; Wise, 2011). Likewise, the

curriculum in higher education often includes courses that target social attitudes in an effort to

develop egalitarian values and respect for diversity (Blaine, 2011). The pedagogy used in college

courses frequently reflects what is used by organizational change agents in diversity and

inclusion programs. These efforts often begin with the proposition that psychological health and

personal effectiveness are fostered by experiential openness and self-awareness: positive change

begins with accurate self-knowledge. Added to this proposition is the corollary that few of us

have accurate self-knowledge when it comes to our social attitudes and how these influence our

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behavior – many, if not most of us, do not accurately perceive the impact our behavior has upon

others. Indeed, it is hard to find a chapter in an adjustment text in Psychology that does not

include a self-assessment activity which encourages students to learn more about their current

status in order to identify the direction and nature of steps they might take to achieve positive

change (Nevid & Rathus, 2010; Santrock, 2006; Watson & Tharp, 2002). Similar to these

initiatives in the educational setting, when the focus is upon understanding and changing social

attitudes in the workplace, interventions often help participants confront accurate assessments of

the beliefs and feelings they associate with target-group members, along with the behavior these

beliefs and feelings foster (Wah, 2012; Wise 2011).

A decrease in the overt expression of racist attitudes over the past half-century has been

accompanied by evidence of pervasive implicit racial bias (Gaetner & Dovidio, 2005; Nosek et

al., 2007). In his engaging best seller Thinking Fast and Slow, Daniel Kahneman (2011) nicely

illustrates a well-established tenet of contemporary cognitive science: both automatic or intuitive

cognitive processes of which we are often unaware and effortful or deliberate cognitive

processes of which we are often painfully aware, influence the way we think, feel and act. Tony

Greenwald and others have illustrated how these automatic and effortful dynamics influence our

social attitudes and the ways we interact with others (Dovidio et al., 1997; Greenwald et al.,

2002). Corresponding to the automatic and effortful cognitive processes that Kahneman and

Greenwald describe, behavioral scientists distinguish between implicit and explicit measures,

where the latter are typically self-reports that provide an opportunity to reflect and deliberate

before responding and the former attempt to reduce the effects that such reflection and

deliberation might produce. In particular, Greenwald, McGhee, and Swartz (1998) suggest that

the Implicit Association Test (IAT), which is based upon reaction times in classification tasks, is

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resistant to self-presentation artifacts and independent of a person’s introspective ability or self-

knowledge. People who espouse egalitarian values and describe themselves as not the kind who

judge people according to their race, but rather according to individual merit on a case-by-case

basis, often have IAT scores that indicate a strong tendency to associate negative attributes with

Blacks (Greenwald, McGhee, & Swartz, 1998). Consequently, implicit measures like the IAT are

useful when assessing racial/ethnic attitudes, particularly in settings where demand

characteristics (e.g., referent group norms) motivate people to respond in socially acceptable

ways (Fazio & Olsen, 2003).

Considerable empirical evidence links explicit and implicit measures of negative social

attitudes with dysfunctional and harmful behavior, especially when the attitudes involve racial

and ethnic minorities. Gordon Allport’s classic The Nature of Prejudice (Allport, 1954), along

with Thomas Pettigrew’s half-century of work (Campbell & Pettigrew, 1959; Pettigrew &

Martin, 1979; Pettigrew, 2011), vividly illustrate how negative social attitudes can impede

effectiveness. Recent interest has focused upon the incremental contributions that implicit

measures can make regarding the prediction of individual conduct in social settings (Greenwald,

Poehlman, Uhlmann, & Banaji, 2009). For example, implicit measures of racial/ethnic attitudes

predict differences in police officers’ decisions to shoot or not shoot a suspect pulling an object

from his pocket (a wallet or weapon) in a simulation exercise that varies the race/ethnicity of the

suspect, better than explicit measures of racial/ethnic attitudes (Eberhardt, 2007). Perhaps of

more relevance to diversity and inclusion initiatives in organizational contexts are studies that

link IAT measures of racial attitudes with interpersonal space and collaboration initiatives with

Blacks (Amodio & Devine, 2006), discomfort and negative interactions with Blacks (Dovidio,

Kawakami & Gaertner, 2002), and negative evaluations of Black job applicants (Rooth, 2010;

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Ziegert & Hanges, 2005). These studies provide a rationale for organizations, including

universities, to be concerned about the nature and prevalence of negative racial attitudes among

members, and they provide an incentive for these organizations to use implicit measures when

assessing their endeavors to change these attitudes.

While it is easy to find empirical evidence linking social attitudes with interpersonal

behavior, it is not as easy to locate evidence for the effectiveness of diversity and inclusion

programs (including university courses) designed to change negative social attitudes, particularly

when the evidence includes implicit measures of relevant attitudes (Gregg, Seibt & Banaji 2006;

Joy-Gaba & Nosek, 2010). Many have lamented the lack of solid, evidence-based information to

guide practitioners and many have called for more program evaluation research (Kalev, Dobbin

& Kelly, 2006; Hite & McDonald, 2006). There are, however, some notable efforts being made

in this regard. For example, Lai et al. (2012) report a meta-analytic investigation of 18

interventions designed to reduce implicit racial bias. Interventions were organized into six

descriptive categories according to the most distinctive feature of each intervention’s design and

interventions in three of the six categories were found to be effective in reducing implicit racial

bias, with involvement (the degree to which an attitude is linked with the self) being a common

feature among the effective interventions. Phills et al. (2011) reported that interventions using

implicit “approach training” procedures to strengthen associations between the self and Blacks

were effective in reducing racial bias among non-Blacks. Another study reported by Rudman,

Ashmore, and Gary (2001) compared changes in the attitudes of students in an upper-division

prejudice and conflict seminar taught by a Black instructor, where the course content involved

relevant topics, with those in a research methods course taught by a White instructor, where the

course content did not involve relevant topics. They found support for the malleability of

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students’ attitudes on both explicit and implicit measures for students in the prejudice and

conflict course but not for students in the experimental methods course. However, Tolon,

Fischer, and Young-Jones (2013) were only partially successful when they attempted to replicate

and extend the findings of Rudman, Ashmore, and Gary (2001). They used multiple implicit and

explicit measures of racial attitudes in a repeated measures design to assess the effectiveness of

activities that were embedded in two undergraduate psychology courses – an adjustment course

taught by a Black instructor and a diversity course taught by a White instructor. A mid-term

assessment of racial attitudes toward Blacks was used to introduce a unit that examined racial

and ethnic attitudes in both courses. Assessment results were provided to students during a

feedback session designed to help students understand what their scores mean and how they

might use this information. A second assessment administered during the final week of classes

indicated some support for the effectiveness of the activities, but only as reflected in one of the

explicit measures. Tolon, Fischer, and Young-Jones (2013) identified several problems with their

design, including limited statistical power, technical glitches with the procedures used to assess

students’ attitudes, and the exclusion of relevant intervention activities from the pre-posttest

interval caused by the midterm pretest assessments. The present study attempts to address these

problems and, like previous efforts, help identify effective methods for developing attitudes that

respect diversity and contribute to inclusive organizational climates.

Hypothesis: Effectiveness of the assessment and intervention activities designed to

change racial attitudes will be evident in a pre-post change on both the explicit and implicit

measures of students’ attitudes. More specifically, White students will explicitly express less

resentment and hostility toward Blacks and greater desire to control their prejudicial reactions

toward Blacks on their posttest measures, relative to their pretest measures. Similarly, White

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students will implicitly express a stronger association of Blacks with positive evaluations and

mental strength on the posttest measures, relative to their pretest measures.

If the assessments and subsequent feedback activities are effective in helping students

confront undesirable aspects of their racial attitudes, their enhanced self-awareness should

motivate a desire to change, which should be reflected in the posttest assessments. We expect

other activities in the diversity course to further enhance students’ motivation to change the way

they consciously think about Blacks and try to control their expression of prejudicial behavior

toward Blacks. However, we expect these gains to be more evident in the conscious, deliberative

thinking of these students rather than in the implicit associations and automatic processes that are

experientially conditioned from childhood to the present. We expect this because of limited

exposure to positive, prosocial experiences with racially diverse others which a course with few

(at most two) Blacks per section provides (Pettigrew, 2011; Zajonc, 1968).

METHOD

Participants

Participants (N = 109) were recruited from a diversity course (The Psychology of Diverse

Populations) taught at a public university in the Midwest that has relatively few racial and ethnic

minority students (about 15%). Although all students were taught by the same instructor, they

were enrolled in five different sections distributed across three consecutive semesters.

Measures

Explicit Racial Prejudice. This measure combined the seven items of the Modern Racism

Scale (McConahay, 1986) with the four items of the Explicit Racial Resentment Scale (Wilson &

Davis, 2008). Higher scores indicate more negative attitudes toward Blacks.

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Motivation to Control Prejudiced Reactions Scale. This measure was the 17 item scale

developed by Dunton and Fazio (1997) to assess concern about acting prejudiced and the desire

to avoid dispute. Higher scores indicate greater motivation to control prejudicial behavior.

Racial Preference IAT. An IAT modeled after those used by Greenwald and others was

used to assess the degree of students’ implicit evaluative race bias. The seven block procedure

and scoring algorithm (D measure) recommended by Greenwald et al. (2003) was used with

images (cropped pictures of 12 faces: six Black male and female faces, and six White male and

female faces) and 16 word stimuli (see Table 1). The more negative the IAT effect, the stronger

the implicit association between negative valence and Blacks (relative to a positive valence with

Whites).

Racial Stereotyping IAT. An IAT modeled after that developed by Amodio and Devine

(2006) was used to assess the degree of students’ implicit racial stereotyping. The same seven

block procedure, scoring algorithm, and face stimuli described above were used with 12 word

stimuli to obtain this measure (see Table 1). The more negative the IAT effect, the stronger the

implicit association of mental strength with Whites (and physical strength with Blacks).

Procedure

The racial preference and stereotyping IATs were administered through a website hosted

by Millisecond, Inc., and InQsit software (Fortriede, 2005) was used to create a web-based

questionnaire for the explicit measures. All measures were self-administered by students in a

computer lab during the first week of the semester. A feedback session modeled after that used

by Tolon, Fischer, and Young-Jones (2013) was conducted in conjunction with the unit that

addressed racial and ethnic minorities. This activity provided a brief review of dual process

attitude theory, in addition to interpretive suggestions about what scores within various ranges

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might mean and how students might use this information.1 The same measures were

administered a second time during the final week of classes.2

RESULTS

Descriptive statistics for the study variables are presented in Table 2. These results

suggest that the measures provide adequate variance and internal consistency to support

additional analyses. Table 3 contains zero-order correlations for study variables. These results

provide evidence of convergent validity for both the explicit and implicit measures in that

measures within each category were significantly correlated on both the pretest and posttest.

These results also provide evidence of discriminant validity and dissociation between the two

types of measures in that only two of the twelve correlations involving an implicit and an explicit

measure were significant. With respect to sample demographics, median age was 22 years, 74%

were female and 85% were White.

Tests of Hypothesis

Only non-Black students (N = 100) were included in the sample used to test the

hypothesis because our predictions and measures target attitudes toward Blacks. Consistent with

our predictions, a multivariate analysis of variance for a repeated measures design produced a

significant within-subjects main effect for the pre-posttest factor (Wilks’ Lambda = .74, F (4,

282) = 8.16, p < .001, partial eta-squared = .26). Univariate analyses of the four dependent

measures produced significant within-subject main effects for pre-posttest differences on only

the Racial Prejudice measure (F (1, 95) = 28.48, p < .001, partial eta-squared = .23) and the

Motivation to Control measure (F (1, 95) = 7.08, p < .01, partial eta-squared = .07). An

examination of cell means (see Table 4) indicated that the pre-posttest difference was in the

predicted direction for both measures. Overall, students expressed less hostility toward Blacks

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and greater desire to control their prejudicial behavior on the posttest. In addition to these main

effects, there was a significant pre-posttest-by-section interaction effect (Wilks’ Lambda = .69, F

(16, 282) = 2.29, p < .01, partial eta-squared = .09). An examination of these effects revealed that

the pre-posttest differences were consistently more positive on the explicit measures compared to

the implicit measures (see Figures 1 – 4). This was most evident on the stereotype IAT measure

where two sections had smaller posttest means and two sections had larger posttest means,

relative to the pretest (F(4, 95) = 2.91, p < .05, partial eta-squared = .11).

DISCUSSION

This study used both implicit and explicit measures to investigate the malleability of

racial attitudes in the context of a university course. Overall, the results indicated a significant

change in students’ explicit racial prejudice and motivation to control their prejudice without a

corresponding significant change in their implicit attitudes. As such, the results only partially

replicate the findings of Rudman, Ashmore, and Gary (2001). Nevertheless, the strength of the

explicit findings represents evidence of the intervention’s effectiveness. Being aware of one’s

prejudices and motivated to regulate these beliefs is a necessary first step in the direction of

positive change for those seeking to create sustainable organizational climates that are inclusive

and value diversity. Oftentimes, at the onset of interventions to change social attitudes,

participants do not believe they are prejudiced against those who are different. Results from this

study provide evidence that, as a consequence of the intervention activities, students’ awareness

of their prejudicial attitudes was heightened. Thus, the explicit and conscious manifestation of

prejudice was addressed.

Although this study did not find consistent support for the malleability of automatic bias

assessed by implicit measures, the implicit assessments encouraged students to confront the

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possibility they are at risk of being prejudiced in ways they are not consciously aware. The idea

that one may be influenced in ways he or she is not aware may lead to greater concern about

monitoring one’s conduct and a heightened explicit desire to control prejudicial reactions. On the

other hand, this finding begs the question why the effects assessed by the implicit measures were

so variable across the five sections: three of the five sections showed positive change on the

racial preference IAT and two did not; two of the five sections showed positive change on the

stereotype IAT and three did not (see Figures 3 and 4). Perhaps, in accord with the findings of

Lai et al. (2012), the number of involved students (i.e., those self-identified with an attitude) in

the sections with positive change reached critical mass. Future research with interventions that

include confrontational components should assess students’ involvement so that its mediating

effects might be studied. Future studies might also profit from investigating how the “approach

training” interventions described by Phills et al. (2011) can be combined with intervention

activities like those used here as a way to leverage student involvement.

Regardless of their involvement, students expressed recognition of implicit beliefs

throughout the course, which they did not originally know existed; they also revealed motivation

to work through those implicit beliefs. This alone supports the effectiveness of the intervention

in terms of helping individuals understand that unconscious ideas exist and are important. When

people learn about their own implicit beliefs and the resulting impact it can have on behavior,

this can inspire them to try and deal with their deeply ingrained mindsets.

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Notes

1. Size limitations prevent a detailed description of the intervention activities within the

text of this paper; more information (PowerPoint presentation and course syllabus) is

available from the authors upon request.

2. The authors want to acknowledge the contributions of research team members Jacque

Byrket, Laccy Gillard, Teanna Lucas and Louis Oberdeiar, and express our gratitude

to them for making this research possible.

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Table 1.

Concept Labels (in italics) and Word Stimuli for the Implicit Association Tests

Race Evaluation Stereotype

Black White Positive Negative Mental Strength Physical Ability

6 faces 6 faces joy terrible math athletic

glorious nasty educated run

wonderful evil scientist boxing

love hurt smart dance

happy

laughter

horrible

failure

college

read

jump

rhythmic

pleasure

peace

awful

agony

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Table 2.

Descriptive Statistics for Study Variables

Variables N Mean SD Alpha

Pretest Measuresa

Racial Prejudice 109 2.11 .59 .84

Motivation to Control 109 4.46 .69 .78

IAT-Preferenceb 109 -.442 .37 .67

IAT-Stereotypec 109 -.188 .37 .74

Posttest Measuresa

Racial Prejudice 109 1.91 .55 .83

Motivation to Control 109 4.61 .69 .79

IAT-Preferenceb 109 -.432 .38 .60

IAT-Stereotypec 109 -.190 .37 .60

a All implicit measures are IAT effects expressed as D measures (Greenwald et al., 2003).

b Larger negative values indicate a stronger association of Black+negative (and White+positive).

c Larger negative values indicate a stronger association of Black+physical (and White+mental).

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Table 3.

Zero-order Correlations for Study Variables

Variables 1 2 3 4 5 6 7 8

Pretest Measures

1. Motivation to Control -

2. Racial Prejudice -.21* -

3. IAT-Preference -.03 -.23* -

4. IAT-Stereotype -.08 -.05 .22** -

Posttest Measures

5. Motivation to Control -.70** -.20* -.15 -.09 -

6. Racial Prejudice -.23* .77** -.13 -.07 -.33** -

7. IAT-Preference -.16 -.15 .47** -.18 -.11 -.21* -

8. IAT-Stereotype -.09 -.06 .36** .41** -.18 -.07 .28** -

Note: N = 109 (all students with complete data)

*p < .05; **p < .01

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Table 4.

Cell Means for Study Variables Used in the Analysis of Variance.

Pretest Posttest

Sectiona N

b RP

c MC

d IAT-P

e IAT-S

f RP

c MC

d IAT-P

e IAT-S

f

FA12-1 14 2.08 4.56 -.525 -.285 1.96 4.68 -.449 -.091

FA12-2 17 2.30 4.50 -.452 -.004 1.92 4.84 -.327 -.240

SP13-1 22 2.10 4.75 -.381 -.249 1.79 4.71 -.448 -.142

SP13-2 25 2.09 4.27 -.582 -.111 1.88 4.57 -.498 -.180

SU13-1 22 2.11 4.44 -.301 -.153 2.07 4.38 -.473 -.168

a FA12-1 = fall semester 2012, section 1; FA12-2 = fall semester 2012, section 2; SP13-1 =

spring semester, section 1; SP13-2 = spring semester 2013, section 2; SU13-1 = summer

semester 2013, section 1. b

Non-Black students with complete data. c RP = Racial Prejudice;

d MC = Motivation to Control;

e IAT-P = IAT-Preference;

f IAT-S = IAT-Stereotype.

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Figure 1. Cell means for the Racial Prejudice measure.

1.7

1.8

1.9

2

2.1

2.2

2.3

2.4

Pretest Posttest

FA12-1

FA12-2

SP13-1

SP13-2

SU13-1

24

Figure 2. Cell means for the Motivation to Control measure.

4.1

4.2

4.3

4.4

4.5

4.6

4.7

4.8

4.9

Pretest Posttest

FA12-1

FA12-2

SP13-1

SP13-2

SU13-1

25

Figure 3. Cell means for the IAT-Preference measure.

-0.65

-0.6

-0.55

-0.5

-0.45

-0.4

-0.35

-0.3

-0.25

-0.2

Pretest Posttest

FA12-1

FA12-2

SP13-1

SP13-2

SU13-1

26

Figure 4. Cell means for the IAT-Stereotype measure.

-0.3

-0.25

-0.2

-0.15

-0.1

-0.05

0

Pretest Posttest

FA12-1

FA12-2

SP13-1

SP13-2

SU13-1