A Dissertation Entitled the Role of Physician Social Identities In

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A Dissertation

entitled

The Role of Physician Social Identities in Patient-Physician Intergroup Relations

Yopina G. Pertiwi

Submitted to the Graduate Faculty as partial fulfillment of the requirements for the

Doctor of Philosophy Degree in Experimental Psychology

______Dr. Andrew L. Geers, Committee Chair

______Dr. Jason Rose, Committee Member

______Dr. Jon D. Elhai, Committee Member

______Dr. Matthew T. Tull, Committee Member

______Dr. Revathy Kumar, Committee Member

______Dr. Cyndee Gruden, Dean College of Graduate Studies

The University of Toledo May 2019

The Role of Physician Social Identities in Patient-Physician Intergroup Relations

Yopina G. Pertiwi

Submitted to the Graduate Faculty as partial fulfillment of the requirements for the Doctor of Philosophy Degree in Experimental Psychology

The University of Toledo May 2019

This study examined the role of the physician combined race/ethnic and gender identities on patient perceptions, emotions, attitudes, and behavioral tendencies toward the physicians. An integrative approach was utilized in examining this phenomenon with three prominent theories in intergroup relations and stereotyping and prejudice, i.e.,

Social Identity Approach, Stereotype Content Model, and Role Congruity Theory. Based on the Social Identity Approach, it was hypothesized that patient emotions, attitudes, and behavioral tendencies toward the physicians depended on the patient and physician’s social identity similarities. The Stereotype Content Model predicted that patient emotions and behavioral tendencies depended on patient perceptions of physician warmth and competence. Finally, the Role Congruity Theory suggested that patient evaluation and behavioral tendencies depended on the congruency between their expectations and the physician actual roles. MTurk workers completed a set of questionnaires measuring their perceptions, emotions, and attitude toward the physician, after seeing a White, Asian, or

Black physician profile. Subsequently, they imagined a slightly unpleasant visit experience to the physician office and predicted their behavioral tendencies. MIMIC

iii models were developed and tested based on the three theories. The findings showed a minimal effect of the physician social identities on patient perceptions, emotions, attitude, and behavioral tendencies across the three statistical models. Physicians were perceived similarly regardless of their social groups. Findings from each of the models’ analysis also showed the uniqueness of each theory in predicting patient-physician intergroup relations. The study has both theoretical and practical implications that are discussed in this document.

Keywords: patient-physician, intergroup relations, social perceptions, social identity, stereotypes, social role

To Ahmed: the perfect partner to defy the odds, and to Issa and Aisha: the best motivational trainers anyone could ever asked for. This work is for you.

Acknowledgments

Almost six year ago, I started the graduate school marathon to accomplish an ultimate personal goal. Today, I would have not reached the end of the race without an excellent team work. I am extremely grateful to Dr. Andrew Geers, for ‘adopting’ me into his lab and has become the best mentor I could ever asked for in graduate school. His expertise in the academic and professional work along with his faith and understanding that he has to his students have transformed me into a much better researcher, student, and, importantly, a person than I was when I first started this journey. I am thankful for

Dr. Rose, Dr. Elhai, Dr. Kumar, and Dr. Tull who served as committee members for this dissertation. Their feedback and suggestions have improved the quality of the study and made this a full-of-learning experience to me.

Accomplishing graduate school and dissertation work would have been too difficult to bear if not because of the friendship I’ve made along the way with Michelle,

Ashley, Fawn, Jacclynn, and many others who have definitely made significant contribution into where I am at right now. I am blessed with a supportive husband,

Ahmed, who has not only showered me with love but provided me with the means I needed during the most stressful period in my life. For my two children, I am truly blessed to have the opportunity to still be able to fight for an important accomplishment in my personal life, but at the same time to learn to be a loving mother. I hope, someday, both of you will look back to these days with a sense of pride and inspiration. For my family in Indonesia, I am thankful for their patience and support while their daughter and sister strive to achieve her dream. Finally, a special thanks to Brooke who has spent her valuable time reading this lengthy draft and provided me with constructive feedback.

Table of Contents

Abstract iii

Acknowledgments vi

Table of Contents vii

List of Tables xii

List of Figures xiii

List of Abbreviations xv

I. Patient-Physician Relationship based on Three Theoretical Perspectives 1

on Intergroup Relations and the Stereotyping and Prejudice

A. A Social Identity Approach to the Patient-Physician Intergroup 5

Relationship

a. Crossed Categorization Theory of Social Identity 7

b. Intergroup Emotions Theory of Social Identity 10

B. Stereotype Content Model and Patient-Physician Intergroup 14

Relationship

C. Role Congruity Theory and Patient-Physician Intergroup 21

Relationship

D. Summary 26

II. Preliminary Findings 28

A. Pilot Study 1: Exploring Patient-Physician Intergroup 28

Relationship

a. Perceptions of the Physicians, Behavioral Tendencies, 29

Participants Gender and Physician Race/Ethnicity

vii

b. Perceptions of the Physicians, Behavioral Tendencies, 30

Participant Gender, and Race-Concordance

c. Perceptions of the Physicians, Behavioral Tendencies, 31

Participant Gender, and Black vs. non-Black Physicians

d. Conclusion 32

B. Pilot Study 2: Investigating Relevant Emotions and Behavioral 33

Tendencies in Patient-Physician Interactions

a. Patient Emotions 34

b. Patient Behavioral Tendencies 35

c. Conclusion 37

III. Hypotheses and Proposed Models 38

A. Hypotheses and the Proposed Model of the Social Identity 38

Approach’s Prediction

B. Hypotheses and the Proposed Model of the Stereotype Content 40

Model’s Prediction

C. Hypotheses and the Proposed Model of the Role Congruity 42

Theory’s Prediction

IV. Method 44

A. Overview 44

B. Participants 46

a. Exploratory Factor Analysis 46

b. Main Study 46

C. Procedure 49

viii

D. Experimental Stimuli: Physician Profiles 52

E. Measures 53

a. Stereotypic Beliefs on Various Types of Occupation 53

b. Perceptions of the Physician 54

c. Emotions toward the Physician 55

d. Evaluation of the Physician (Outgroup Feeling 55

Thermometer)

e. Evaluation of the Physician (Semantic-Differential 56

Measure of Attitudes)

f. Facilitative Behavioral Tendency toward the Physician 56

g. Harmful Behavioral Tendency toward the Physician 57

F. Data Analytical Strategy 57

V. Results 62

A. Exploratory Factor Analysis 62

a. Facilitative Behavioral Tendency 63

b. Harmful Behavioral Tendency 63

B. Confirmatory Factor Analysis 64

a. Facilitative Behavioral Tendency 64

b. Harmful Behavioral Tendency 65

C. Social Identity Approach 66

a. Evaluating Group Differences on Dependent Variables 66

b. Correlations between Focal Variables 70

c. Test of the MIMIC Model 71

D. Stereotype Content Model 76

a. Evaluating Group Differences on Dependent Variables 76

b. Correlations between Focal Variables 80

c. Test of the MIMIC Model 82

E. Role Congruity Theory 84

a. Evaluating Group Differences on Dependent Variables 85

b. Correlations between Focal Variables 88

c. Test of the MIMIC Model 89

VI. Discussion 92

A. Social Identity Approach 92

a. Hypothesis 1 93

b. Hypothesis 2 95

c. Hypothesis 3 95

d. Hypothesis 4 96

e. Summary 96

B. Stereotype Content Model 97

a. Hypothesis 1 98

b. Hypothesis 2 98

c. Hypothesis 3 99

d. Hypothesis 4 99

e. Summary 100

C. Role Congruity Theory 100

a. Hypothesis 1 101

b. Hypothesis 2 101

c. Hypotheses 3 and 4 102

d. Summary 102

D. The Lack of Race Effect in the Present Study Findings 103

a. Context Matters 103

b. The Absence of Threat 105

c. The Lack of Choice 106

E. Implications 107

a. Integrating the Three Theoretical Views 107

b. Practical Implications 110

F. Limitations 110

References 113

Appendices

A. Pilot Study 1 Materials 142

B. Pilot Study 2 Materials 146

C. Main Study Materials 149

D. Consent Forms 176

List of Tables

Table 1. Description of patient and physician crossed categories.…………………..9

Table 2. Participant demographics based on race/ethnicity………………………...49

Table 3. Standardized factor loadings of the facilitative behavioral tendency scale..65

Table 4. Standardized factor loadings of the harmful behavioral tendency scale…..65

Table 5. Correlations between all focal variables in Social Identity Approach

model………………………………………………………………………69

Table 6. Correlations between all focal variables in Stereotype Content Model…...79

Table 7. Correlations between all focal variables in Role Congruity Theory………87

xii

List of Figures

Figure 1. Patient and physician crossed categories…………………………………..9

Figure 2. Illustration of patient-physician relationship based on the Social Identity

Approach………………………………………………………………….13

Figure 3. SCM and BIAS map predictions for emotions and behaviors in the warmth

by competence space……………………………………………………..19

Figure 4. The complex patient-physician intergroup relationship based on previous

SCM studies………………………………………………………………19

Figure 5. Illustration of patient-physician intergroup relations based on the

Stereotype Content Model and BIAS map……………………………….21

Figure 6. Illustration of patient-physician intergroup relationship based on the Role

Congruity Theory…………………………………………………………26

Figure 7. Patient emotions if they like or dislike a physician………………………35

Figure 8. Patient behaviors during positive interaction with a physician…………..36

Figure 9. Patient behaviors during negative interactions with a physician…………36

Figure 10. Proposed MIMIC model diagram of patient-physician intergroup relations

based on Social Identity Approach……………………………………….40

Figure 11. Proposed MIMIC model diagram of patient-physician intergroup

relationship based on the Stereotype Content Model…………………….41

Figure 12. Proposed MIMIC model diagram of patient-physician intergroup

relationship based on Role Congruity Theory………………..…………..43

Figure 13. Tested MIMIC model diagram of patient-physician intergroup relations

based on Social Identity Approach……………………………………….72

xiii

Figure 14. Modified MIMIC model diagram of patient-physician intergroup relations

based on Social Identity Approach with admiration and thermometer

evaluation…………………………………………………………………75

Figure 15. Modified MIMIC model diagram of patient-physician intergroup relations

based on Social Identity Approach with admiration and semantic-

differential evaluation…………………………………………………….75

Figure 16. Tested MIMIC model diagram of patient-physician intergroup relations

based on Stereotype Content Model……………………………………...82

Figure 17. Modified MIMIC Model of the patient-physician intergroup relations

based on the Stereotype Content Model……………………….…………84

Figure 18. Tested MIMIC Model based on Role Congruity Theory with outgroup

feeling themometer evaluation measure………………………………….90

Figure 19. Tested MIMIC Model based on Role Congruity Theory using semantic-

differential evaluation measure…………………………………………...91

xiv

List of Abbreviation

AAMC……. Association of American Medical Colleges ANOVA…... Analysis of Variance

BIAS……… Behavior from Intergroup Affect and Stereotypes

CFA………. Confirmatory Factor Analysis CFI………... Comparative fit index

DIF………... Differential Item Functioning

EFA……….. Exploratory Factor Analysis

FIML……… Full Information Maximum Likelihood

MANOVA... Multivariate Analysis of Variance MCAR…….. Missing Completely At Random MI…………. Multiple Imputation M.I………… Modification Index MIMIC……. Multiple Indicators Multiple Cause ML………... Maximum Likelihood MLM……… Maximum Likelihood with a mean-adjusted chi-square MTurk…….. Mechanical Turk

RMSEA…… Root mean square error of approximation

SCM………. Stereotype Content Model SD………… Standard Deviation SEM………. Structural Equation Modeling SPSS………. Statistical Package for the Social Sciences SRMR…….. Standardized root mean square residual

TLI………... Tucker-Lewis Index

Chapter One

Patient-Physician Relationship based on Three Theoretical Perspectives on

Intergroup Relations and the Stereotyping and Prejudice

In 1991, the Association of American Medical Colleges (AAMC) launched the

“3000 by 2000” initiative with a goal of enrolling three thousand students from underrepresented groups1 annually by the year 2000 (Nickens, Ready, & Petersdorf,

1994). The rationale behind this campaign was to promote diversity in medical colleges as a strategy to address health disparities and to improve quality of health care across the country (Beavers & Satiani, 2010; Grumbach & Mendoza, 2008; Ready, 2001; Terrell &

Beaudreau, 2003). This project, however, did not meet its numerical goal by the end year

2000 (Terrell & Beaudreau, 2003). In fact, minority groups are still underrepresented in the medical workforce. For instance, Blacks and African-Americans comprise only four percent of the physician workforce, even though Blacks and African-Americans comprise about 13 percent of the United States (U.S.) populations (Association of American

Medical Colleges, 2014).

A more diverse medical workforce does not mean a mere growth regarding quantity that may be shown by the increasing number of physicians and other health care

1 Before June 2003, the AAMC definition of underrepresented minority included only African-Americans, Mexican-Americans, Native-Americans, and mainland Puerto Ricans. These were the target groups of the “3000 by 2000” initiative. In June 2003, following the Supreme Court decision, AAMC adopted a new definition of ‘underrepresented in medicine’, which now includes any “racial and ethnic populations that are underrepresented in the medical profession relative to their numbers in the general population” (Association of American Medical Colleges, 2003). For the purpose of consistency and to be able to capture the stereotyping and prejudice phenomenon in medical setting more broadly, the term of “minority groups” or “minorities” will be used throughout this paper as defined by the United States Census Bureau (United States Census Bureau, 2015) as any racial and ethnic groups other than non-Hispanic White. This definition implies that Asians, even though not considered underrepresented in medicine, are included. It has been noted that Asians have undergone similar challenges as other minority groups in medical workforce (Yu, Parsa, Rogers, & Chang, 2013).

providers who belong to diverse race/ethnic background. Instead, a diverse medical education setting could also mean an enhanced cultural competence among health care professionals (Nivet, 2010). Physician cultural understanding and sensitivity, including their understanding about stigma, prejudice, and discrimination faced by patients (Stuber,

Meyer, & Link, 2008) has been suggested as an important aspect that is associated with patient perceptions toward medical encounters with physicians (Napoles-Springer,

Santoyo, Houston, Perez-Stable, & Stewart, 2005). Hence, much research on this topic has focused on enhancing physician cultural competence to improve the quality of health care (Boutin-Foster, Foster, & Konopasek, 2008; Flores, 2000; Michalopoulou,

Falzarano, Arfken, & Rosenberg, 2009; Tucker, Marsiske, Rice, Nielson, & Herman,

2011).

A diverse medical workforce is also regarded crucial in providing a better health care experience for minority population as reports have shown that physicians of minority background mainly serve patients from this type of population (see U.S. Department of

Health and Human Services, 2006 for review; Xu et al., 1997). Indeed, data from the

Commonwealth Fund 1994 National Comparative Survey of Minority Health Care showed that 88% of the White respondents sought care from White physicians, whereas

Black and Hispanic respondents preferred to see physicians of their race if they had the opportunity choose (Saha et al., 2000). This demographic similarity between patient and physician is an example of what is often termed as “concordance” in the medical literature, which is defined as “a state of agreement or harmony” related to the similarity of the patient and the physician, in terms of gender, social class, age, ethnicity, race,

language, sexual orientation, beliefs about roles, beliefs about health and illness, values, and actual health care decisions (Cooper & Powe, 2004).

Patient-physician race concordance is associated with an improved quality of the patient-physician relationship. Specifically, looking at the phenomenon from the patient side, patient-physician race concordance is linked with higher patient respect towards the physicians for White patients (Malat, 2001), better physician ratings for Black patients, higher satisfaction of overall health care for Hispanic patients (Saha, Komaromy,

Koepsell, & Bindman, 1999), higher trust towards the physician, and stronger intention to adhere to recommendations (Street, O'Malley, Cooper, & Haidet, 2008). From the physician point of view, patient-physician race concordance is associated with longer visits, higher ratings of patient positive affect (Cooper et al., 2003), and more physician participatory decision making styles (Cooper-Patrick et al., 1999).

Even though increasing the number of minority physicians and health care practitioners is inarguably essential for the many advantages it will bring to society, it needs to be carried out with caution. As a matter of fact, a majority of the patient- physician relationship studies have focused on the impact of physician behavior on the relationships (Beck, Daughtridge, & Sloane, 2002; Berry, 2007; Ha, Anat, & Longnecker,

2010; Stewart, 1995; Williams, Weinman, & Dale, 1998), and in doing so, have treated patients as passive individuals who hold no prior beliefs and expectations about the relationship and their care in general (Vermeire, Hearnshaw, & van Royen, 2001).

In reality, social interaction is a two-way street (e.g., Madon, Jussim, & Eccles,

1997; Madon, Willard, Guyll, & Scherr, 2011; Rosenthal & Jacobson, 1968/2003).

Patient perceptions toward physicians can also influence treatment outcomes. For

instance, patients’ liking of their physicians were linked with self-reported health, positive feelings, physician ratings, and visit satisfaction (Hall, Horgan, Stein, & Roter,

2002). On the contrary, patient derogative expressions that were viewed as threatening to the physician self-esteem and dignity were found to be associated with physician negative emotional experiences (Smith & Zimny, 1988). Moreover, as in the case of minority patients, physicians and other health care providers who are members of minority groups are not immune to the negative experiences and consequences of stereotyping and prejudice directed toward their groups (Beagan, 2003; Nunez-Smith et al., 2007).

Therefore, it is reasonable to study how diversity in the physician workforce could be associated with the patient-physician relationship by examining patient perceptions and potential behaviors toward the physicians in order to obtain a comprehensive understanding of the phenomenon.

The current study examined the complex association between physician social identities and the patient perceptions and potential behaviors toward the physicians in the context of the patient-physician relationship. Notably, instead of only looking at the phenomenon from one theoretical angle, such as race-concordance, the present work analyzed the topic from several theoretical points of view. By doing so, it is expected that this research will advance our integrative understanding of the intergroup relationship and its effect on social perceptions and behaviors (Eagly, 2004; Jost & Hamilton, 2005;

Koenig & Eagly, 2014; Oakes, Haslam, & Turner, 1994). In this dissertation, the patient- physician intergroup relationship and its association with patient social perceptions and behaviors were examined through three different theoretical lenses: (1) A Social Identity

Approach, (2) The Stereotype Content Model, and (3) Role Congruity Theory. Each of

these theoretical approaches is described in the next section along with the predictions regarding the anticipated reactions based on physician race/ethnic and gender identities.

Importantly, it is worth mentioning at the outset that the goal of this work was not to challenge or undercut the efforts to promote diversity in the medical workforce.

Instead, the goal was to provide a more comprehensive understanding of the intricacy of the patient-physician intergroup relationship. Furthermore, the findings from this research could raise a healthy dialogue about the negative experiences that minority physicians and practitioners may experience while fulfilling their duties to serve the communities that are typically undiscussed (Nunez-Smith et al., 2007).

A Social Identity Approach to the Patient-Physician Intergroup Relationship

Patient-physician race-concordance is considered advantageous in improving the quality of the patient-physician relationship and ultimately the health care experience in general (for review see U.S. Department of Health and Human Services, 2006). If the general race-concordance hypothesis (i.e., the patient-physician racial similarity is associated with improved patient-physician relationship and enhanced health care experience) is true, health care quality would depend on simply matching the patient and physician racial backgrounds. One aim of the current study was to investigate to what extent that this broad hypothesis was applicable, considering the complexity of intergroup relations in the society that may be translated into a specific social situation such as the patient-physician relationship. Further, as gender is another critical social identity that can be shared by patients and practitioners (e.g., Schieber et al., 2014; Schmittdiel,

Grumbach, Selby, & Quesenberry, 2000), the present research examined hypotheses related to both race and gender groupings.

At first glance, patient preferences in receiving services from physicians of a similar race may be explained through a social identity approach, stemming from the original social identity theory developed by Tafjel and colleagues in the 1970s (Tajfel,

1970; Tajfel & Turner, 1979, 1986). According to this view, individuals tend to categorize themselves and others into various social classifications, such as race, gender, and occupations. One of the basic premises of social identity theory is that individuals engage in this ingroup-outgroup categorization process in order to achieve or maintain a positive social identity which leads to a positive evaluation of their ingroup and a negative evaluation of the relevant outgroups (Tajfel & Turner, 1979, 1986). That is, a positive social identity is a result of comparisons that favor one’s ingroup over the relevant outgroups. Using the minimal group paradigm, Tajfel and colleagues found reliable evidence for ingroup favoritism and outgroup discrimination by simply making group categories salient to participants (Tajfel, 1970). Thus, concerning the race- concordance effects, the original social identity theory could lead to the prediction that patient preference of physicians with similar racial backgrounds and the improved patient-physician interaction in a racial concordance situation is because they categorize the physicians as ingroup members which leads them to positively evaluateof the physicians.

Up until this point, the primary race-concordance hypothesis seems to be closely linked with the original social identity theory proposed by Tajfel and colleagues (Tajfel,

1970; Tajfel & Turner, 1979). However, the problem with this explanation is that it tends to streamline the intricacy of social identities and categorization process into only two possible mechanisms (i.e., patient-physician race-concordance versus race-discordance).

In reality, people possess more than one social identity, and the activation of these various identities are not based on assigned group membership per se (Brewer, 2007;

Dovidio, Gaertner, Pearson, & Riek, 2005; Roccas & Brewer, 2002). Rather, it is contextual and depends on the individual’s perception of the identity fit and identity accessibility (Brewer & Gardner, 1996; Hogg & Williams, 2000; Turner et al., 1994).

Moreover, every individual perceives their identity importance differently, and this prioritization affects how one perceives ingroup and outgroup membership (Urada &

Miller, 2000; Urban & Miller, 1998). Based on this idea of social identity multiplicity, the original social identity theory has branched out into various, more specified, theoretical frameworks that expand on the initial postulation of the ingroup-outgroup categorization. As the proposed study involves activation of multiple social identities (i.e, race/ethnicity and gender), two re-formulations of social identity theory, i.e., the crossed categorization (Crisp & Hewstone, 1999) and intergroup emotions theory (Mackie,

Smith, & Ray, 2008; Smith, 1993), were used to develop hypotheses for the present study.

Crossed Categorization Theory of Social Identity. The crossed categorization theory suggests that intergroup relations are influenced by how individuals make sense about the multiple identities that they may share or not share with other individuals (Crisp

& Hewstone, 2000). For instance, in the context of this study, a participant might possess a variety of social identities, such as a woman, a graduate student, and a

Caucasian/White. When this participant interacted with a physician, she would categorize herself and the physician based on the extent to which she shared similar social identities with the physician. If the physician also happened to be a White woman, then the

participant would share more social identities with this physician than if the physician was a Black man.

At this point, different patterns of crossed categorization (i.e., additive, dominance, social inclusion, social exclusion, hierarchical ordering, and hierarchical derogation2) might occur which would affect intergroup relationships differently (Crisp &

Hewstone, 1999). Most studies, however, have found that the additive model (i.e., groups are evaluated based on category differentiation when two social identities are salient at the same time) is most likely to occur both in the laboratory-induced social identity context as well as in the actual social identity context (Crisp & Hewstone, 1999; Crisp,

Hewstone, & Rubin, 2001; Hewstone, Islam, & Judd, 1993; Migdal, Hewstone, &

Mullen, 1998; van Oudenhoven, Judd, & Hewstone, 2000). Thus, the White female graduate student would be more likely to see the White female physician as a ‘double ingroup’ member and evaluated the physician more positively than a Black male physician who was seen as a ‘double outgroup’ member. Figure 1 and Table 1 illustrate the possible crossed categorization patterns that would likely to occur in this study, where

2 The six crossed categorization models based on Crisp and Hewstone (1999): (1) Additive (category differentiation): when two categories are salient, members of double ingroups are evaluated most positively, followed by members of partial ingroup/outgroup, whereas members of double outgroups are evaluated least positively (II > IO = OI > OO). (2) Dominance: when only one category is salient, those who share membership in the salient/dominant category are evaluated more positively than those who do not share membership in this category (II = IO > OI = OO). (3) Social inclusion: when there is one category that is inclusive. Those who share membership in this inclusive category are evaluated more positively and those who do not share membership in this inclusive category are evaluated least positively (II = IO = OI > OO). (4) Social exclusion: when there is one category that is exclusive, only those who share membership in this exclusive category are evaluated positively, while others are evaluated less positively (II > IO = OI = OO) (5) Hierarchical ordering: when evaluations toward different categories depend on membership on the first category (II > IO > OI = OO). (6) Hierarchical derogation: when outgroup membership on the first category determines differentiation (II = IO > OI > OO)

participants (patients) might differentiate themselves from the physician by attending to racial and gender identities resulting into four different models from the participant perspectives.

Race Patient Race Physician Patient Gender Physician Gender Other Gender

Partial ingroup (race): Double ingroup: Identity intersection occurs in one category. Identity intersection occurs in two categories. .

Race Other Race Race Other Race Patient Physician Patient Gender Physician Gender Other Gender

Double outgroup: Partial ingroup (gender): No identity intersection. Identity intersection occurs in one category.

Figure 1. Patient and physician crossed categories.

Table 1.

Description of Patient and Physician Crossed Categories.

Category Patient Physician Race Gender Race Gender Double Ingroup White Male White Male Asian Male Asian Male Black Male Black Male Partial Ingroup White Female White Male (race) Asian Female Asian Male Black Female Black Male Partial Ingroup White Male Asian Male (gender) White Male Black Male Asian Male White Male Asian Male Black Male Black Male White Male Black Male Asian Male Double Outgroup White Female Asian Male White Female Black Male Asian Female White Male Asian Female Black Male Black Female White Male Black Female Asian Male Note. The highlighted columns show the intersecting identities.

Intergroup Emotions Theory of Social Identity. By integrating the social identity theory and the appraisal theory of emotions (e.g., Frijda, 1986), the intergroup emotions theory also moves beyond the idea of the pure ingroup favoritism and outgroup derogation as consequences of social identity and self-categorization (Mackie, Smith, &

Ray, 2008). Specifically, this theory argues that group members can experience distinct emotions depending on which ingroup and outgroup serve as the categorization target

(Mackie & Smith, 2015, 2017; Mackie et al., 2008; Smith, Seger, & Mackie, 2007). For example, the White female graduate student might feel quite happy with her graduate student status and proud about being a woman, but was particularly unhappy about being

White. At the same time, this individual might generally admire physicians, felt envious toward men, and guilty toward Blacks. Subsequently, these specific emotions produce a readiness for specific actions (Frijda, Kuipers, & terSchure, 1989). For instance, group- based emotions, such as anger and disgust, produce a readiness to act against a particular group and group-based emotions, such as admiration, trigger actions to move toward a group (Mackie, Devos, & Smith, 2000; Ray, Mackie, Smith, & Terman, 2012; for review, see Mackie & Smith, 2015, 2017; Mackie et al., 2008). Notably, studies have found the emotions of admiration, anger, and disgust mediate the effect of contact on prejudice

(Seger, Banerji, Park, Smith, & Mackie, 2016).

The specific group-based emotions have also been used to explain the effect of crossed categorization when two identities were made salient. Ray and colleagues (2012) have found that the additive effect of crossed categorizing two different identities on intergroup evaluations was also found in group-based emotions. Specifically, findings from an experiment in this previous study showed that the college students who were

unaffiliated with any Greek fraternity/sorority and who identified as Democrats (i.e., non-

Greek Democratic students) highly admired the other non-Greek fellow students (partial ingroup-non-Greek). At the same time, students in this group felt the most disgust toward their Republican college student counterparts (partial ingroup-non-Greek and double outgroup). Hence, their emotions toward the other non-Greek Democrats (double ingroup) were simply the result of the combination between admiration toward the other non-Greek students (partial ingroup-non-Greek and double ingroup) and the lack of disgust feeling toward the other Democrat students (partial ingroup-Democrats and double ingroup). By the same token, their emotions toward the Greek Republicans

(double outgroup) were the result of the combination between the lack of admiration toward the Greek students (partial-ingroup-Democrats and double outgroup) and the feeling of disgust toward the Republicans (partial ingroup-non-Greek and double outgroup). These findings, however, also implied that the emotions toward the two different partial ingroups (i.e., non-Greek Republicans: admired and disgusted; Greek

Democrats: not admired and not disgusted) were contextually specific and could not be predicted by the simple explanation of less intense emotional experience toward each of the partial ingroups. Furthermore, the authors also reported a significant positive correlation between admiration and outgroup evaluations as well as a significant negative correlation between disgust and outgroup evaluations. More importantly, these emotions mediated the relationship between the crossed categorization and the outgroup evaluations (Ray et al., 2012).

Drawing from research on the intergroup emotion theory, the current study examined the involvement of the emotions of admiration and disgust. These two

emotions were examined here as findings from a pilot study (described later in this document) suggested that admiration was most likely to occur in a situation where the patients liked the physicians and disgust was most likely to occur in a situation where patients disliked the physicians. Additionally, since the intergroup emotions theory suggests a relationship between emotions and behavioral tendencies (Mackie & Smith,

2015, 2017; Mackie et al., 2008; Mackie et al., 2000), behavioral tendencies were also included in the current study. Behavioral tendencies are defined as impulses or a readiness to act, which are comparable to intentions suggested in several attitude- behavior relations theories (e.g., Ajzen & Fishbein, 1980; Fazio, 1990; for review see

Mackie & Smith, 1998). Thus, the actual behaviors were not assessed in this study.

Furthermore, since intergroup evaluations have been reported as antecedents of intergroup behaviors (for review see Dovidio, Brigham, Johnson, & Gaertner, 1996;

Mackie & Smith, 1998) and have been traditionally measured as general intergroup attitudes (e.g., Haddock, Zanna, & Esses, 1993), this evaluative component was also included in the theoretical model as the antecedent of the behavioral tendencies.

In sum, based on the crossed categorization and intergroup emotion theories, the patient-physician intergroup relationship were hypothesized as following (see a visual depiction in Figure 2).

1. The pattern of patient-physician crossed categories would predict patient

emotions toward the physicians, where patients who shared two group

memberships with the physician (i.e., double ingroup) would be most likely to

admire the physician, followed by the patients who only shared one group

membership with the physician (i.e., partial ingroup race and partial ingroup

gender); patients who did not share any group membership with the physician

(i.e., double outgroup) would be most likely to feel disgust toward the physician,

followed by the partial ingroups.

2. Patient emotions would, in turn, predict patient evaluation of the physicians,

where admiration would be positively correlated with the evaluation and disgust

would be negatively correlated with the evaluation of the physicians.

3. Evaluation of the physicians would then predict behavioral tendencies toward the

physicians, where the evaluation would be positively correlated with facilitative

behavioral tendencies but negatively correlated with harmful behavioral

tendencies.

4. Evaluations of the physicians would mediate the relationship between patient

emotions and patient behavioral tendencies toward the physicians.

Double Positive Facilitative Admiration behavioral Ingroup evaluation tendencies

Patient- physician Partial crossed Ingroups categories

Less Harmful Double Disgust positive behavioral Outgroup evaluation tendencies

Figure 2. Illustration of patient-physician relationship based on the Social Identity Approach.

Stereotype Content Model and Patient-Physician Intergroup Relationship

Another approach to understanding social perception in the intergroup relationship phenomena is through examining the stereotypes and prejudices that individuals have toward particular groups. In this case, instead of explaining the intergroup phenomena by taking into account the ingroup-outgroup differentiation, the stereotyping and prejudice approach uses individual attribute-based attitudes toward a variety of groups (Brewer, 2010; Oakes et al., 1994). Using this approach to observe the patient-physician intergroup relations phenomenon is important considering the abundant amount of research that has been performed to understand stereotyping and prejudice in medical settings. Yet again, mainstream studies conducted on this topic have primarily focused on how such issues affect patients (e.g., Abreu, 1999; Balsa & McGuire, 2003;

Collett & Tyler, 2016; Green et al., 2007; Guagliardo, Teach, Huang, Chamberlain, &

Joseph, 2003; Sabin, Rivara, & Greenwald, 2008; Schulman et al., 1999), neglecting the effect of the other person at the other end of the relationship: the minority physicians and practitioners.

To date, the few studies that focused on minority physicians and medical students have revealed that they were not immune to the negative experiences of stereotypes and prejudice. For instance, Beagan’s (2003) qualitative study indicated that minority physicians and physician assistants have reported feeling invisible and unnoticeable when providing treatment to patients, as they were not seen as the typical physicians, i.e.,

White men. Occurrences, when patients refused care from minority physicians, have also been reported (Nunez-Smith et al., 2007). Furthermore, within the workforce itself,

physicians from minority groups still experience difficulty advancing their careers

(Beavers & Satiani, 2010; Yu, Parsa, Rogers, & Chang, 2013).

Additionally, findings from the stereotype threat studies have shown that stereotypes and prejudice can negatively impact minority group members in a variety of ways, ranging from underperformance in different academic tests (Nguyen & Ryan,

2008; Shih, Wout, & Hambarchyan, 2015; Steele & Aronson, 1995; Steele, Spencer, &

Aronson, 2002) to the chronic abandonment and self-disidentifying from the scientific domain (Woodcock, Hernandez, Estrada, & Schultz, 2002). Moreover, individuals who expect to be the target of prejudice experienced negative feelings toward interactions with the outgroup members (Tropp, 2003) and reported more negative experiences when interacting with the ethnic majority group members (Shelton, Richeson, & Salvatore,

2005). It is likely that stereotypes and prejudice affect minority physicians and health care practitioners similarly. Paul-Emile, Smith, Lo, and Fernandez (2016) have even suggested that it could lead to physician negative emotional experience and burnout.

In order to investigate how stereotyping and prejudice toward minority physicians influence patient-physician intergroup relationships, the Stereotype Content Model

(SCM) developed by Fiske and colleagues (Fiske, Cuddy, Glick, & Xu, 2002; Fiske, Xu,

Cuddy, & Glick, 1999) was used in this study. This theory was founded based on the assumption that people are good-enough perceivers, that when it comes to social interactions, we use our cognition to make simple and pragmatic social judgments, either by using a category-oriented approach in a situation when sufficient information is not available or an attribute-oriented approach in a situation when abundant information is accessible and categorization is impossible (Fiske, 1992, 1993b, 2004).

The SCM theory suggests that in any social interaction context, we evaluate others based on their intention and goals toward the interaction. Specifically, we through judge one’s warmth to determine his/her intention and one’s competence to determine his/her capability in creating and maintaining positive interaction goals (Cuddy, Fiske,

Glick, 2007; Cuddy et al., 2008; Fiske, 2010, 2012; Fiske, Cuddy, Glick, Xu, 2002;

Fiske, Cuddy, Glick, 2006; Kervyn, Fiske, Yzerbyt, 2015). These two dimensions of social perception, i.e., the warmth and competence, are deemed to be universal, as they are crucial for survival and adaptation in the social world (Cuddy et al., 2008; Fiske et al.,

2006). They originate from the social-cultural variables (Fiske, 1993a, 2010; Caprariello,

Cuddy, & Fiske, 2009; Fiske, Dupree, Nicolas, & Swencionis, 2016; Swencionis &

Fiske, 2016) and have been found across different settings and cultures (Asbrock, 2010;

Cuddy et al., 2009; de Paula Couto & Koller, 2012; Sibley et al., 2011). For example, in the medical arena, these two dimensions, as they pertain to practitioner evaluations, have commonly been found to be associated with positive health care outcomes (Beck et al.,

2002; Cvengros, Christensen, Cunningham, Hillis, & Kaboli, 2009; Mercado, Mercado,

Myers, Hewit, & Haller, 2012). Hence, this theory is relevant to be utilized in the current study.

As the name of the theory implies, the warmth and competence dimensions are believed to be the core of stereotype contents that we have towards different groups

(Fiske et al., 2002; Fiske et al., 1999; Fiske, 2012). The SCM predicts stereotype content by crossing the warmth and competence dimensions in a 2 x 2 matrix. For instance, some groups (e.g., ingroups, close allies, the middle class) are consistently perceived as highly warm and competent, whereas other groups (e.g., the homeless, poor people) are

consistently perceived as cold and incompetent (Fiske et al., 2002; Cuddy et al., 2008).

Other groups receive ambivalent stereotypes where they are perceived to be high in one dimension but low in another dimension (Cuddy et al., 2008; Fiske et al., 2002; Fiske et al., 1999; Lee & Fiske, 2006). For example, Asians tend to be evaluated as highly competent but cold (Asbrock, 2010; Lin, Kwan, Cheung, & Fiske, 2005; Sibley et al.,

2011) and older people have consistently been perceived as warm but incompetent across various cultures (Asbrock, 2010; Cuddy, Norton, & Fiske, 2005; de Paula Couto &

Koller, 2012).

The next important proposition of the SCM theory is that the perceived levels of warmth and competence predict distinct emotions toward others. Specifically, perceived high warmth-high competence predicts admiration, perceived low warmth-low competence predicts contempt, perceived low warmth-high competence predicts envy, and perceived high warmth-low competence predicts pity (Cuddy et al., 2008; Fiske et al., 2002; Fiske et al., 1999; Lin et al., 2005). Later, the SCM was extended into the

‘Behavior from Intergroup Affect and Stereotypes’ (BIAS) map that added behavioral components into the SCM original propositions (Cuddy et al., 2007, 2008). The BIAS map proposed that the perceived levels of warmth and competence predict behavioral tendencies via emotions. Specifically, as evaluation of warmth is considered primary in

SCM, it is associated with active behaviors (i.e., the behaviors that require individuals to take actions), where high warmth predicts active facilitation (e.g., help and protect) and lack of warmth predicts active harm (e.g., attack and fight). In contrast, as competence evaluation is considered as secondary (i.e., there is no immediate effect in social interaction), it is associated with passive behaviors, where high competence predicts

passive facilitation (e.g., cooperate and associate) and lack of competence predicts passive harm (e.g., exclude and demean; Cuddy et al., 2007, 2008). Figure 3 illustrates the specific relationship between these three components in the SCM and BIAS map model.

Relevant to the context of the current study, previous studies using the SCM theory have found that physicians tend to be perceived as warm and competent (Asbrock,

2010; Fiske & Dupree, 2014). Concerning race/ethnic groups, Whites were previously evaluated as warm and competent (Fiske et al., 2002), though later were slightly shifted to the low warmth-high competence quadrant (Cuddy et al., 2007). Blacks, on the other hand, were positioned in between the four quadrants (Fiske et al., 2002), but when the group was split based on the socio-economic status, poor Blacks moved down to the low warmth-low competence quadrant, whereas Black professionals moved up to the high warmth-high competence quadrant (Fiske et al., 2002; Fiske, Bergsieker, Russell, &

Williams, 2009). In contrast, as mentioned earlier, Asians have consistently been perceived as highly competent but low in warmth (Asbrock, 2010; Lin et al., 2005; Sibley et al., 2011).

Regarding gender, the findings have shifted throughout the years and mixed findings were found depending on the other identities attached to each gender. For instance, housewives who used to be perceived as warm but incompetent (Fiske et al.,

2002), were later moved to the high warmth-high competence quadrant (Cuddy et al.,

2007). Working women, on the other hand, were perceived as cold but competent, but working mothers were perceived as cold and incompetent (Cuddy & Fiske, 2004; Fiske,

2010). In contrast, men were generally perceived as cold but competent (Fiske et al.,

2002), yet working fathers were perceived as warm and competent (Cuddy & Fiske,

2004). In the current study, however, only male physicians were used as the perception target, as they are commonly considered the typical physician (Beagan, 2003).

High

Active facilitation

Pity Admiration W A R M Passive Passive T harm facilitation H

Contempt Envy

Active harm

Low COMPETENCE High Figure 3. SCM and BIAS map predictions for emotions and behaviors in the warmth by competence space. Source: Cuddy et al., 2007. High

Active facilitation

Pity Admiration W A  Physicians R  Black professionals M Passive  Working fathers Passive T harm facilitation H  Whites  Asians  Working men

Contempt Envy

Active harm

Low COMPETENCE High Figure 4. The complex patient-physician intergroup relationship based on previous SCM studies. Sources: physician: Asbrock, 2010; Fiske & Dupree, 2014; race/ethnicity: Cuddy et al., 2007; gender-based parental status: Cuddy & Fiske, 2004.

As depicted in Figure 4, it is possible that the perceptions toward the physicians may shift to different quadrants depending on their other identities that are attached to their professional identity. Therefore, using the SCM framework, the present study investigated the complexity of the patient perceptions toward a physician based on the physician social identities, such as race/ethnicity and gender. However, since all of the previous findings seemed to be grouped into either high warmth-high competence or low warmth-high competence quadrants, only two specific emotions were included in the present research predictions. Additionally, this implied that the physicians should not be perceived differently regarding competence levels, but might be perceived differently in terms of warmth. Therefore, the warmth component was primary in this study, which also suggests that the active behavioral tendencies were more relevant than passive behavioral tendencies (Cuddy et al., 2007, 2008). For this reason, as well as for maintaining consistency with the other theoretical models examined in this work, only the active facilitation behavioral tendency and the active harmful behavioral tendency were included in this model’s predictions. Following are the specific predictions constructed based on the Stereotype Content Model studies and theoretical framework as illustrated in

Figure 5.

1. The combination of physician race/ethnic and gender identities would predict

patient perceptions of physician warmth and competence levels, where White and

Asian male physicians would be perceived as cold and competent, and the Black

male physicians would be perceived as warm and competent.

2. The perceptions of physician warmth and competence levels would, in turn,

predict patient emotions toward the physicians, where perceived physician high

warmth and high competence levels would predict admiration and perceived

physician low warmth and high competence levels would predict envy.

3. Patient emotions toward the physicians would predict patient behavioral

tendencies toward the physicians, where admiration would predict active

facilitation and envy would predict active harm.

4. Patient emotions toward the physicians would mediate the relationship between

patient perception of the physician warmth and competence levels and the patient

behavioral tendencies toward the physicians.

Low (Active) White- Warmth, Envy harmful male High behavioral physician Competence tendency

Physician Asian- race/ethnicity male and gender physician

High (Active) Black- Warmth, Admiration facilitative male High behavioral physician Competence tendency Figure 5. Illustration of patient-physician intergroup relations based on the Stereotype Content Model and BIAS map.

Role Congruity Theory and Patient-Physician Intergroup Relationship

The role congruity theory was developed based on the social role theory that was first developed by Eagly in the 1980s to explain sex differences and similarities through the lens of the societal gender stereotypes (Eagly & Steffen, 1984; Eagly, Wood, &

Diekman, 2000; Eagly & Wood, 2012). Instead of seeing stereotypes and prejudice as

general attitudes toward different groups, the social role theory maintains that stereotypical beliefs about groups are deeply rooted in the division of labor that exists in the society. Furthermore, this theory suggests that these stereotypical beliefs are the products of the interplay between biological differences between members of different groups and the sociocultural factors including local economy, social structure, and ecology (Eagly & Chin, 2010a; Eagly & Wood, 1999, 2012; Eagly, 1997; Wood &

Eagly, 2010). Inferring from a sociological perspective (e.g., Bakan, 1966), the social role theory describes stereotypic beliefs as consisting of two dimensions: agency (e.g., masterful, assertive, competitive, and dominant) and communal (e.g., friendly, unselfish, concerned with others, and emotionally expressive; Eagly et al., 2000; Eagly & Wood,

2012). These two dimensions overlap with the two dimensions in the SCM theory in which agency is parallel to competence and communion is parallel to warmth (Koenig &

Eagly, 2014).

For instance, when occupational information was unavailable, an average woman was seen as more communal, and an average man as more agentic due to women’s typical role as homemakers and men’s typical employment in a paid workforce.

Nevertheless, when both the average woman and man were employed, women were seen as more agentic than men (Bosak, Sczesny, & Eagly, 2012; Eagly & Steffen, 1984).

Relatedly, this theory posits that stereotypical beliefs toward various groups alter along with the sociocultural changes in terms of the division of labor in the society (Diekman &

Eagly, 2000). Nevertheless, due to the pervasiveness of the stereotypical beliefs in the members of the society, these beliefs affect the division of labor all over again, unless there is a breakthrough, both from the society side by providing equal access to all

groups, and from the disadvantaged group members by entering the atypical workforce

(Eagly & Diekman, 2005; Koenig & Eagly, 2014).

A previous study on social role theory revealed that each racial group was expected to hold different typical social roles. For instance, White men were expected to work as business professionals, lawyers, politicians, and doctors; Black men as professional athletes, factory workers, and drug dealers; and Asians (no gender assigned) as dry cleaner workers, doctors, small business owners, and engineers (Koenig & Eagly,

2014). These expectations were reflected in the actual U.S. labor divisions, where 5.8% of Asian men in the country worked as healthcare practitioners and other technical occupations, and only 2.6% of the White men and 2.7% of the Black men held positions in the same domain. In contrast, 25.2% of the Black men worked in production, transportation, and material moving occupations, compared to only 16.1% of the White men and 12.8% of Asian men who worked in this sector in 2017 (U.S. Bureau of Labor

Statistics, 2018).

Extending the propositions of the social role theory, the role congruity theory suggests that stereotypical beliefs exist as a consequence of the interaction between the societal expectations (i.e., the expected roles that a certain group member should have) and the situational context (i.e., the actual roles possessed by a certain group member;

Eagly & Chin, 2010b; Eagly, 2004; Eagly & Diekman, 2005). For instance, both men and women could be viewed as more communal and less agentic if they worked part-time

(Eagly & Steffen, 1986) or employed in female-dominated occupations (e.g., nurse, social worker; Bosak et al., 2012). This contextual approach is also applicable to explain the stereotypical beliefs about passive older people in work context (Diekman &

Hirnisey, 2007). Similarly, Black men were also perceived as more dangerous when associated with being a prisoner than a lawyer in a prison setting (Barden et al., 2004) perhaps due to the stereotypical beliefs of Black man physical strength (Wilson,

Hugenberg, & Rule, 2017). In a political setting, candidate electability was found to be associated with voters’ perception of role congruity by reflecting on the current leader’s views and identities (Benstead, Jamal, & Lust, 2015).

Based on the role congruity theory, problems arise when there is a mismatch between the societal expectations and the actual social roles that the group members engage. Perceived role incongruity can lead to less favorable attitudes that can result in discriminatory behaviors against the individuals (Eagly & Diekman, 2005). For example, compared to men, women generally face more disapproval and challenges when they hold a leadership position due to the perceived incongruence between the agentic stereotypical beliefs associated with leadership roles and the women’s typical communal roles (Eagly & Chin, 2010b; Eagly & Karau, 2002; Eagly, Makhijani, & Klonsky, 1992;

Koenig, Eagly, Mitchell, & Ristikari, 2011; Paustian-Underdahl, Walker, & Woehr,

2014).

Just as any other attitude, this less favorable attitude toward individuals behaving incongruently from the expected social roles can be expressed in terms of affect, behaviors, and cognition (Eagly et al., 2000; Eagly & Diekman, 2005). Nevertheless, there has been no clear proposition regarding the relationship between these three components and attitude. The relationship between stereotypic beliefs (cognition) and attitude has been found to be stronger than the relationship between emotion and attitude

(Eagly, Mladinic, & Otto, 1991). However, although it has been proposed that the

stereotypic beliefs are associated with behaviors (Eagly et al., 2000; Eagly & Diekman,

2005) as per the author’s knowledge, there have been no studies conducted to explain the relationship between these variables from the position of the role congruity theory. In the present study, the patient-physician intergroup relationship was examined based on the patient perceptions of the role congruity/incongruity of each of the physician. As there was no clear proposition about how the emotions toward the target individuals could be affected by the perception of role congruity, unlike the previous two theoretical models, this variable was omitted from the prediction. Instead, the perception of role congruity was predicted to affect evaluative component of attitude towards the physician directly, and that this attitude would, in turn, trigger specific behavioral tendencies toward the physician. Following are the hypotheses constructed based on the Role Congruity Theory as illustrated in Figure 6.

1. The physician race/ethnic and gender identities would affect patient perceptions

of physician-social group role congruity, where White and Asian male physicians

would be perceived as role congruent and Black male physician would be

perceived as role incongruent.

2. The perceived role congruity would, in turn, affect patient evaluation of the

physicians, where role congruence would be positively correlated with evaluation

but negatively correlated with evaluation of the physicians.

3. Evaluation of the physician would then affect patient behavioral tendencies

toward the physicians, where evaluation would be positively correlated with

facilitative behavioral tendency but negatively correlated with harmful behavioral

tendency.

4. The relationship between patient perception of role congruity and patient

behavioral tendencies would be mediated by patient evaluations toward the

physicians.

White-male physician

Facilitative Role- Positive behavioral congruent evaluation tendencies Physician Asian-male race/ethnicity physician

Harmful Black-male Less positive Role- behavioral physician evaluation incongruent tendencies Figure 6. Illustration of patient-physician intergroup relationship based on the Role Congruity Theory.

Summary

The present study aimed to examine the complexity of the patient-physician intergroup relationship that could be influenced by physician social identities such as race/ethnic identity and gender identity. In doing so, three different prominent theories in intergroup relations as well as stereotyping and prejudice, namely the Social Identity

Approach, the Stereotype Content Model, and Role Congruity Theory, were utilized.

Each of these predicted the relationship between the physician social group memberships and patient perceptions as well as behavioral tendencies differently. For instance, the

Social Identity Approach predicts the relationship by taking into account the social identities of both perceivers and the target, whereas both SCM and Role Congruity

Theory examine group-based perception based on the target’s social group membership.

Additionally, if both the Social Identity Approach and Role Congruity Theory suggest that intergroup relations and social perception are context-specific, the SCM theory takes a general attribute-based approach in explaining these phenomena. At the same time, however, the three theoretical approaches do overlap in some of their propositions. For example, both the Social Identity Approach and SCM theories suggest that emotion is central to intergroup relations. Also, the three theories propose that behavioral responses in intergroup relations are to some extent associated with the group-based attitude that is reflected in outgroup evaluation, perception of warmth and competence, and stereotypic beliefs. Hence, it is asserted that examining the same phenomenon in a specific context in one single study would provide a more comprehensive look on the dynamics of intergroup relationship between patient and physician and its effects.

Chapter Two

Preliminary Findings

Pilot Study 1: Exploring Patient-Physician Intergroup Relationship

A pilot study was conducted to provide preliminary information about how the three different theories could contribute to the investigation of the patient-physician intergroup relationship phenomenon. The pilot study was also used to assess a methodological approach for examining patient-physician relationship issues. Due to the initial conceptualization of the study, however, the measures used were based solely on the Stereotype Content Model and BIAS map.

A total of 222 undergraduate students (Mage = 19.25 years old, 68.5% female,

61.7% White) at the University of Toledo were randomly assigned to one of four conditions, where they evaluated a profile of either a White, Black, Asian or Arab male physician.3 All of the information provided in the physician profiles were the same in all conditions except for the physician profile picture and the name of the physician. After seeing the physician profile, participants completed a measure of perceptions of the physician warmth and competence levels. Afterward, they were asked to imagine having a slightly uncomfortable interactive experience with the physician, and then completed a measure of trust and behavioral tendencies (i.e., facilitative: cooperate and recommend, harmful: argue and change). All measures used in this pilot study are presented in

Appendix A.

3 Arab physician was originally included in this preliminary study due to the high percentage of Arab population in the location where the study was conducted (i.e., Lucas county, Ohio; http://www.aaiusa.org/demographics). However, this ethnic group was not included in the main study due to a small sample size in the study population.

Perceptions of the Physicians, Behavioral Tendencies, Participant Gender, and Physician Race/Ethnicity. A 2 (Gender: male and female) x 4 (Physician race/ethnicity: White, Asian, Black, and Arab) between-subject multivariate analysis of variance (MANOVA) was utilized to compare perceptions of physician warmth and competence levels based on participant gender and physician race/ethnic background.

Results revealed a significant interaction effect of participant gender and physician

2 race/ethnicity on the perceptions of physician competence, F(3,213) = 3.58, p = .015, ηp

= .05, but not on the perceptions of physician competence warmth. Further simple effect analyses showed a significant main effect of the physician race/ethnicity on the perceptions of physician competence for male participants only, F(3, 65) = 3.12, p =

2 .032, ηp = .13, where the Asian physician (M = 4.42, SD = .40) was perceived as significantly more competent than the Black physician (M = 3.99, SD = .42), p = .045 .

Next, the 2 (Gender) x 4 (Physician race/ethnicity) between-subject MANOVA was used to examine the role of participant gender and physician race/ethnicity on trust and behavioral tendencies toward the physician after the unpleasant interaction. The multivariate analysis revealed only a significant main effect of participant gender, F(3,

211) = 2.67, p = .049, Wilks’Ʌ = .96, but the univariate analyses also revealed significant

2 main effects of physician race/ethnicity in predicting trust, F(3,213) = 3.13, p = .027, ηp

2 = .04, facilitative, F(3,213) = 3.09, p = .028, ηp = .04, and harmful behavioral tendencies,

2 F(3,213) = 2.77, p = .043, ηp = .04, toward the physician. Specifically, the White (M =

3.15, SD = 1.19) and Asian (M = 3.06, SD = 1.07) physicians were more trusted than the

Black physician (M = 2.46, SD = 1.18); and participants tended to be more facilitative to the White (M = 2.69, SD = .95) than the Black physicians (M = 2.20, SD = .82). In

addition, a significant main effect of gender was found in predicting harmful behavioral

2 tendency toward the physicians, F(1,213) = 7.35, p = .006, ηp = .04, whereas marginal

2 main effects of gender were found for trust, F(1,213) = 5.02, p = .064, ηp = .02, and

2 facilitative behavioral tendency toward the physicians, F(1,213) = 2.69, p = .086, ηp =

.01. Compared to the male participants (harmful behavioral tendency: M = 2.74, SD =

1.06; trust: M = 3.12, SD = 1.21; facilitative behavioral tendency: M = 2.64, SD = .96), the female participants (M = 3.13, SD = .98) had higher harmful behavioral tendency, but were less likely to trust (M = 2.80, SD = 1.22) and had lower facilitative behavioral tendency (M = 2.40, SD = .96) toward the physicians.

Perceptions of the Physicians, Behavioral Tendencies, Participant Gender, and Race-Concordance. A 2 (Gender: male and female) x 7 (Race-concordance:

White/White, White/Non-White, Asian/Asian, Asian/Non-Asian, Black/Black,

Black/Non-Black, Arab/Non-Arab)4 between-subject MANOVA was utilized to compare differences in predicting perceptions of physician warmth and competence levels. The multivariate analyses revealed no significant main or interaction effects, but the univariate analyses revealed a marginally significant interaction effect of gender and race-concordance on the perceptions of physician competence, F(6, 193) = 1.97, p = .072,

2 ηp = .06. Furthermore, the simple effect analyses based on participant gender revealed a significant effect of race-concordance on the perceptions of physician competence for

2 male participants only, F(6, 52) = 2.89, p = .017, ηp =.25, where White male participants who saw either a White (M = 4.55, SD = .55) or a non-White physician (M = 4.25, SD =

.42) and Asian male participants who saw a non-Asian physician (M = 4.56, SD = .26)

4 There was only 1 participant in the Arab-Arab race-concordant group, and thus, it was not included in this analysis.

were significantly more likely to perceive the physician as competent than Black male participants who saw a Black physician (M = 3.50, SD = .38).

The 2 (Gender) x 7 (Race-concordance) between-subject MANOVA was also used to predict trust, facilitative, and harmful behavioral tendencies toward the physician.

The multivariate analyses revealed only a significant main effect of race-concordance,

2 F(18, 501.12) = 1.67, p = .041, Wilks’Ʌ = .85, ηp = .05. The univariate analyses showed

2 a significant main effect of race-concordance on trust, F(6, 179) = 2.60, p = .019, ηp =

2 .08, facilitative, F(6, 179) = 2.18, p = .047, ηp = .07, and harmful behavioral tendencies,

2 F(6, 179) = 3.11, p = .006, ηp =.09 toward the physician. In this case, White (M = 3.28,

SD = 1.33) and Asian participants (M = 3.83, SD = .75) whose race were concordant with the physician were more likely to trust the physician than Black participants whose race were concordant with the physician (M =2.00, SD = .82). Also, Asian participants whose race was concordant with the physician had higher facilitative behavioral tendency (M =

3.42, SD = .38) toward the physician than Black participants whose race was concordant with the physician (M = 2.05, SD = .83), p = .084, and had lower harmful behavioral tendency toward the physician than Arab participants whose race were discordant with the physician (M = 3.63, SD = .69), p = .092.

Perceptions of the Physicians, Behavioral Tendencies, Participant Gender, and Black vs. non-Black Physicians. As the findings from the previous analyses tend to show a particular trend against the Black physician, the subsequent analyses were conducted to examine the differences of perceptions and behavioral tendencies toward the physician based on participant gender and whether the physician was Black or non-

Black. A 2 (Gender: male and female) x 2 (Black/non-Black physician: Black and non-

Black physician) between-subject MANOVA was used to accomplish this goal. The multivariate analyses showed a significant interaction effect of’ gender and Black/non-

2 Black physician, F(2, 216) = .53, p = .030, Wilks’Ʌ = .97, ηp = .03. The univariate analyses revealed a significant interaction effect of gender and the Black/non-Black

2 physician on competence, F(1, 217) = 7.15, p = .008, ηp = .03. Further analyses revealed that male participants who saw a non-Black physician (M = 4.34, SD = .51) were significantly more likely to perceive the physician as competent than those who saw a

Black physician (M = 3.99, SD = .42), F(1, 67) = 5.94, p = .017.

Next, the same 2 (Gender) x 2 (Black/non-Black physician) between-subject

MANOVA was used to predict trust and behavioral tendencies toward the physician. In this case, the multivariate analyses only showed a marginally significant effect of

2 Black/non-Black physician, F(3, 215) = 2.40, p = .069, Wilks’Ʌ = .97, ηp = .03, and no main effect of gender or the interaction term. The univariate analyses showed a

2 significant effect of Black/non-Black physician on trust, F(1, 217) = 7.12, p = .008, ηp =

2 .03 and facilitative behavioral tendency, F(1, 217) = 5.82, p = .017, ηp = .03.

Specifically, participants who saw a non-Black physician (trust: M = 3.02, SD = 1.21; facilitative behavioral tendency: M = 2.55, SD = .97) were more likely to trust and had higher facilitative behavioral tendency toward the physician than those who saw a Black physician (trust: M = 2.46, SD = 1.18; facilitative behavioral tendency: M = 2.20, SD =

.90).

Conclusion. Overall, findings from this study highlighted the complexity of the patient-physician intergroup relationship, where careful examination of this phenomenon with an integrative approach would be useful to obtain a comprehensive understanding of

the patient-physician relationship. For instance, the findings implied that participant social identities, both race and gender identities, could influence their perceptions and behavioral tendencies toward the physicians. Therefore, the general attribute-based perception such as what is proposed by the Stereotype Content Model, that does not take into account the perceiver’s identities, may not be the best approach to explain intergroup relations that occur in the specific context of patient-physician interactions. Nevertheless, even though simply matching a patient and physician race could, at least partially, explained the White and Asian participants’ ingroup favoritism as suggested by the

Social Identity Approach, it did not seem to fit in the situation where Black patients saw physicians of the same race. The findings, instead, seemed to support the idea of a contextually-based, social perception explanation and the influence of labor division that is deeply ingrained in the society as proposed by the Social Role/Role Congruity Theory.

This preliminary study, however, did not assess emotions. As such, the relation of emotion with other variables, that are central to the Social Identity Approach and the

SCM model, could not be examined. Therefore, in the present study, the variables central to all three theoretical approaches, such as emotion, evaluation, and role congruity were measured.

Pilot Study 2: Investigating Relevant Emotions and Behavioral Tendencies in

Patient-Physician Interactions

In order to adequately capture the relevant types of emotion and behavioral tendencies in the specific context of patient-physician interactions, a second pilot study was conducted. The study was purely exploratory, and thus, a survey with both closed- ended and open-ended questions was used (see Appendix B for this study materials).

Data from 123 undergraduate students at the University of Toledo (Mage = 20.53 years old, 78.5% female, 61.8% Whites) was analyzed. Of all the participants, 94.3% of them claimed that they visited a physician at least once a year, in which 49.6% of them visited racially concordant physicians, 33.3% visited racially discordant physicians, and the rest of them did not visit any physicians in the past one year or did not provide either the physician’s or their race/ethnicity information. In this study, participants were asked to respond based on their interaction with their physicians, their child’s physician, or the physicians of a minor for whom they acted as guardians. Participants then completed patient emotions toward physician measures followed by the open-ended questions about behavioral tendencies.

Patient Emotions. Patient emotions toward physicians were measured through two multiple-choice items, i.e., “What kind of emotions would you feel towards a physician if you like [dislike] a physician?” in which they could select at least one response from the following options: Admiration, Proud, Contempt, Disgust, Pity,

Sympathy, Envious, and Jealous. Due to the initial design of the study, the types of emotion used in this study were based on the typical types of emotion that are used in the

Intergroup Emotions Theory and the Stereotype Content Model’s studies (Cuddy et al.,

2007; Ray et al., 2012).

Results showed that admiration was selected by 78% of the participants when they were asked about the emotions they would feel toward a physician if they like the physician, followed by proud (43.1%) and contempt (35%). On the other hand, disgust was selected by 73.2% of participants when they were asked about the emotions that they would feel toward a physician if they dislike the physician, followed by contempt

(30.1%) and pity (20.3%). Figure 7 shows a direct comparison of the results from these two items.

Jealous

Envious

Sympathy

Pity

Disgust Emotions Contempt

Proud

Admiration

0 10 20 30 40 50 60 70 80 90 Responses (in %)

DISLIKE LIKE

Figure 7. Patient emotions if they like or dislike a physician.

Patient Behavioral Tendencies. In order to explore patient behavioral tendencies toward physicians, participants were asked to respond to two open-ended questions, i.e.,

“Write one behavior that you would do to a physician when you think that you had a positive [negative] interaction with the physician during the visit.” Participant responses were extracted into themes by two raters who worked in parallel, and went through several discussions between the raters to minimize discrepancies. Findings revealed that the four most frequent themes that emerged from patient behaviors during a positive interaction with a physician include being appreciative (30.9%), friendly (24.4%), loyal

(8.9%), and to recommend or write a good review about the physician (8.1%). The four most frequent themes of patient behaviors during a negative interaction with a physician include being uncooperative (21.1%), being unfriendly (17.9%), stop visiting the

physician or ask for another physician (17.1%), and being disrespectful or rude toward the physician (8.9%). Next, the emergent themes were coded by the two raters into four behavioral tendencies as proposed by the SCM and BIAS map models, i.e., active facilitation, passive facilitation, active harm, and passive harm. Figure 8 and Figure 9 present the emergent themes extracted from participant responses to the behavioral tendency items and the categorization of the themes.

30 Appreciative Friendly 25 Loyal 20 Recommend/good review

15 Communicative Truthful

Responses Responses %) (in 10 Polite 5 Cooperative Positive emotions 0 Active facilitation Passive facilitation Unidentified Unidentified/unclear Behaviors based on BIAS Map by emerging themes

Figure 8. Patient behaviors during positive interaction with a physician.

25 uncooperative

20 unfriendly gesture dismissive

15 avoidance stop visit/change

10 disrespectful/rude

complain Responses Responses (in%) 5 not recommend/bad review appreciative

0 friendly Passive Active harm Active Passive Unidentified polite harm facilitation facilitation communicative Behaviors based on BIAS Map by emerging themes

Figure 9. Patient behaviors during negative interactions with a physician.

Conclusion. The most important finding from this preliminary study was that admiration-pride and disgust-contempt were the two types of emotion that were most likely to occur during a patient-physician interaction. Unlike what is proposed by the

SCM model, envy-jealousy seemed to be the least likely to occur in this context.

Additionally, findings from this study have also provided valuable information regarding the specific patient behaviors that might occur during patient-physician interactions that could be categorized into different behavioral tendencies. These findings were vital in constructing the items for the behavioral tendency scales that were used in the main study.

Chapter Three

Hypotheses and Proposed Models

The present study aimed to obtain a comprehensive look on the role of physician social categories of gender and race/ethnicity on the important elements of patient- physician relationship such as patient perceptions, attitudes, emotions, and ultimately behavioral tendencies toward physicians. In order to accomplish this aim, hypotheses were constructed based on three prominent social psychological theories on intergroup relations as well as stereotyping and prejudice. These hypotheses were then tested using the multiple indicators multiple cause (MIMIC) structural equation modeling (SEM). A

MIMIC model was used in this study as it allows for estimating group differences on latent variables by regressing the effect indicators on one or more dichotomous cause indicators that represent group membership (Kline, 2011). Through this study, it is expected that the findings would provide useful information regarding which theoretical point of view would best explain the intergroup relations in a specific context of patient- physician interaction, or if integrative findings were obtained, how would these three different perspectives be used together to explain the phenomenon. Following are the alternative hypotheses and proposed models constructed based on the three approaches.

Hypotheses and the Proposed Model of the Social Identity Approach’s Prediction

Based on the Social Identity Approach, it was hypothesized that:

1. the pattern of the patient-physician crossed categories would predict patient

emotions toward the physicians,

2. patient emotions would then predict patient evaluation of the physician,

3. patient evaluation would then predict behavioral tendencies toward the physician,

and

4. patient evaluation of the physician would mediate the relationship between patient

emotions and patient behavioral tendencies toward the physicians.

To test these hypotheses simultaneously, a MIMIC model with one structural model and two measurement models (i.e., facilitative behavioral tendency and harmful behavioral tendency) was proposed. In this model, the cause indicator was the four variations of the crossed categories based on the interaction of the participant and physician race/ethnicity and gender, which include: double ingroup, partial ingroup

(race), partial ingroup (gender), and double outgroup. As illustrated in Figure 10, two dummy-coded variables were created for the proposed model, where the two partial ingroups were collapsed into one reference group, and then compared to the double ingroup in one variable and to the double outgroup in the other variable. Here, the two partial groups were initially planned to be merged as one variable as previous studies found extreme differences between the double ingroup and double outgroup (Ray et al.,

2012). However, as we will see in a later section, preliminary MANOVA showed a different effect for each of the four group memberships, which required the number of dummy coded variables in this model to be modified.

Figure 10. Proposed MIMIC model diagram of patient-physician intergroup relations based on Social Identity Approach.

Hypotheses and the Proposed Model of the Stereotype Content Model’s Prediction

Next, based on the Stereotype Content Model, it was hypothesized that:

1. the combination of the physician race/ethnic and gender identities would predict

patient perceptions of physician warmth and competence levels,

2. the perception of physician warmth and competence would then predict patient

emotions toward the physicians,

3. patient emotions toward the physicians would predict patient behavioral

tendencies toward the physicians, and

4. patient emotions toward the physicians would mediate the relationship between

patient perception of physician warmth and competence levels and patient

behavioral tendencies toward the physicians.

For the Stereotype Content Model prediction, the MIMIC model also consisted of one structural model and two measurement models. The exogenous variable, however, was the physician race and gender combination. Since the model predicted no significant difference between White and Asian physician conditions, these two groups were initially collapsed into one reference group, leaving only two grouping categories in this model, where a Black physician was compared to the reference group. Therefore, as illustrated in

Figure 11, only one dummy-coded variable was included in this initial model. However, as in the case of the Social Identity Approach model, the number of the dummy-coded variables in this model were also modified, based on the outcomes of the MANOVA.

Figure 11. Proposed MIMIC model diagram of patient-physician intergroup relationship based on the Stereotype Content Model.

Hypotheses and the Proposed Model of the Role Congruity Theory’s Prediction

Finally, based on the Role Congruity Theory, it was hypothesized that:

1. the physician race/ethnic and gender identities would affect patient perceptions of

the physician-social groups role congruity,

2. the perceived role congruity would affect patient evaluation of the physician,

3. patient evaluation of the physician would then affect patient behavioral tendencies

toward the physician, and

4. the relationship between patient perception of role congruity and patient

behavioral tendencies would be mediated by patient evaluation of the physician.

A MIMIC model consisted of one structural model and two measurement models

(i.e., facilitative behavioral tendency and harmful behavioral tendency) was also developed for this theory’s prediction. Similar to the SCM MIMIC model, the exogenous variable was the physician race and gender combination. The model also predicted no significant difference between White and Asian male physician conditions. Therefore, these two conditions were originally combined into one reference group, where the Black male physician condition was compared to the reference group as illustrated in Figure 12.

However, as the MANOVA outcomes showed different effects of the three group membership on the tested dependent variable, the number of dummy-coded variables in this model were later modified.

Figure 12. Proposed MIMIC model diagram of patient-physician intergroup relationship based on Role Congruity Theory.

Chapter Four

Method

Overview

Since all three models consisted of two new measurement models, an exploratory factor analysis (EFA) was conducted for each of the measurement models before analyzing the full MIMIC models. Hence, data were collected separately to conduct the

EFA. Participants in the EFA study completed only the second part of the main study that will be described in detail below.

The main study itself consisted of two parts. In the first part of the study, participants completed several demographic questions and a set of questionnaires that were used as a measure of role congruity along with several unrelated questionnaires.

Participants who were determined to be eligible based on the information they provided in the first part of the study were invited to participate in the second part of the study.

Here, they were randomly assigned to one out of nine conditions, where they evaluated a profile of either a White, Asian, or Black male physician (three physician photos were used for each racial group). Then, participants completed a set of questionnaires that measure their perceptions, emotions, and attitudes toward the physicians. After rating the physician, they were asked to imagine a slightly unpleasant experience of a first visit to the physician office and then predicted their behavioral tendencies toward the physician during the visit.

The three physician race/ethnic groups of White, Asian, and Black, were selected as the main focus for the present work based on several reasons. First, historically, the relationship between White and Black racial groups have been significantly studied to

illustrate the dynamic of intergroup relations in the U.S. (e.g., Allport, 1954/1979; Correll et al., 2011; Devine, 1989; Kinder & Sears, 1981; McConahay, Hardee, & Batts, 1981;

Ryan, 1996; Sears, Henry, & J, 2003; Weber et al., 2014; see Gamst, Liang, & Der-

Karabetian, 2011 for review; see Tropp & Pettigrew, 2005 for number of studies).

Meanwhile, the Asian-American racial group has also attracted scholars’ attention in the area of stereotypes, prejudice, and intergroup relations research, either as the main focus

(e.g., Committee of 100, 2001; Dhingra, 2003; Ho & Jackson, 2001; Liang, Li, & Kim,

2004; Lin, Kwan, Cheung, & Fiske, 2005; Sue, Bucceri, Lin, Nadal, & Torino, 2007) or as one of the ‘other minorities’ to illustrate the intricacy of intergroup relations in one single nation (e.g., Bikmen, 2011; Bikmen & Durkin, 2014; Rosenbloom & Way, 2004).

Second, Black and Asian American groups make a good contrast for comparison in the proposed study. Even though Asians are already considered overrepresented whereas

Blacks are still underrepresented in medicine (Nivet, 2010; Yu et al., 2013), both racial group members experience challenges as minority groups both in a larger social setting as well as in medicine (Beagan, 2003; Nunez-Smith et al., 2007; Yu et al., 2013). The gender of the physician was also limited to male only in order to control for this variable as a physician gender could also influence the patient-physician interactions. Moreover, although there is an increasing number of female medical students and faculty

(Association of American Medical Colleges, 2014), male physicians are still considered

‘typical physician’ (Beagan, 2003). That said, the participants included both male and female, which allowed for prediction testing based on multiple group identities.

Participants

Exploratory Factor Analysis. Participants were recruited through the Amazon

Mechanical Turk (MTurk). The data collection for this purpose was conducted after the main study data collection was completed, so that MTurk workers who have participated in the main study could be excluded from the participant recruitment. The participant recruitment for this study was also restricted only to those who lived in the U.S to maintain consistency with the main study sample characteristics. Later, they were also screened based on their U.S. citizenship. Initially, 380 MTurk workers participated in this study for an exchange of $0.15. However, 16 participants had more than 30% of missing data, 11 of them were not U.S. citizens, and nine of them did not respond to the citizenship question. Thus, data from these participants were excluded from further analysis, which left the total of 344 participants (65.7% female, 76.5% White, Mage =

36.66 years old) for the EFA. This total number of participants is beyond the suggested sample size for conducting EFA even for the scales with low communalities, a small number of factors, and only three indicators for each factor, which is 300 (Henson &

Roberts, 2006; MacCallum & Widaman, 1999).

Main Study. Participants for the main study were also recruited through the

Amazon MTurk. In addition to the affordability and the ability to collect data from a more diverse subject pool than the college student sample, MTurk workers were used in this study as there were evidence suggesting the similarity between the MTurk data and the data collected through direct recruitment (Bartneck, Duenser, Moltchanova, &

Zawieska, 2015), and that MTurk workers were more attentive in following instructions in the online surveys than the college student sample (Hauser & Schwarz, 2016). Also, by

using the MTurk population, I was able to collect the sufficient number of data from the race/ethnic minority groups, which was the issue that occurred from using the college student sample in Pilot Study 1. The data collection was conducted using TurkPrime, an

Internet-based research platform that allowed for excluding participants based on specific characteristics and can be integrated with the MTurk account (Litman, Robinson, &

Abberbock, 2017). The first part of the study was opened for MTurk workers who were

U.S. citizens, regardless of their race/ethnicity or gender. Participants in this part of the study received a small monetary reward that ranged between $0.50 and $1.25 after completing the survey. Based on the demographic information provided by participants in the first part of the study, participants who met specific characteristics (i.e., female and male U.S. citizens or permanent residents who identify themselves as either White,

Asian, or Black Americans and were living in the U.S. at the time of taking the surveys) were invited to participate in the second part of the study. In this part of the study, participants received a monetary reward that ranged between $1.00 and $1.25.

Initially, I planned to obtain 120 participants for each crossed category based on the Social Identity Approach (i.e., the theoretical model that required the highest number of participants compared to SCM and Role Congruity Theory), which means that 80 participants from each race and gender combination (i.e., female White, male White, female Asian, male Asian, female Black, and male Black) were needed. This original plan should result in a total of 480 participants. The sample size in the main study was determined based on the suggested sample size that was required for a MIMIC model to have adequate power in detecting the differential item functioning (DIF), which is 100 for

each focal-group (Woods, 2009; Woods & Grimm, 2011; Woods, Oltmanns, &

Turkheimer, 2009).

In total, the data from 677 participants were collected through this process.

However, 35 of the participants had more than 30% of missing data, 2 of them were neither U.S. citizens nor permanent residents, 1 of them reported personally knowing the physician shown in the profile, and 73 of them were not located in the U.S. based on the

IP address screening. Thus, these participants were excluded from further analysis which left the total of 566 participants (50.5% female, 41.7% White, Mage = 37.48 years old).

Table 2 presents participant demographic information based on their race/ethnicity backgrounds.

Table 2. Participant Demographics based on Race/Ethnicity.

White/Caucasian Black/African Asian Americans Americans Americans (n = 155) (n = 236) (n = 175) Gender Male 128 (54.2%) 77 (44.0%) 75 (48.4%) Female 108 (45.8%) 98 (56.0%) 80 (51.6%) Age M (SD) 40.55 (13.37) 37.42 (12.57) 32.86 (10.91%) 18 – 24 20 (8.5%) 24 (13.7%) 33 (21.3%) 25 – 34 79 (33.5%) 61 (34.9%) 68 (43.9%) 35 – 44 56 (23.7%) 44 (25.1%) 31 (20.0%) 45 – 54 29 (12.3%) 26 (14.9%) 12 (7.7%) 55 – 64 40 (16.9%) 11 (6.3%) 9 (5.8%) Above 65 12 (5.1%) 9 (5.1%) 2 (1.3%) Educational background Less than high school 2 (0.8%) 0 (0%) 0 (0%) High school graduate 29 (12.3%) 15 (8.6%) 7 (4.5%) Some college 59 (25.0%) 60 (34.3%) 28 (18.1%) Undergraduate degree 91 (38.6%) 73 (41.7%) 85 (54.8%) Master’s degree 41 (17.4%) 23 (13.1%) 33 (21.3%) Doctoral degree 11 (4.7%) 2 (1.1%) 2 (1.3%) College educated mother Yes 115 (48.7%) 104 (59.4%) 93 (60%) No 117 (49.6%) 68 (38.9%) 60 (38.7%) College educated father Yes 114 (48.3%) 69 (39.4%) 95 (61.3%) No 117 (49.6%) 92 (52.6%) 59 (38.1%) Subjective SES (society ladder) 8 – 10 (highest) 29 (12.2%) 23 (13.1%) 24 (15.4%) 4 – 7 (middle) 166 (70.4%) 119 (68.0%) 110 (71%) 1 – 3 (lowest) 39 (16.6%) 33 (18.9%) 12 (13.5%)

Procedure

In the first part of the study, participants completed the stereotypic beliefs about various race/ethnic and gender groups scale measuring their perceptions of various race/ethnic groups’ communion and agency that were used as one of the two measures of role congruity, along with other surveys unrelated to the main study and demographic questions (see Appendix C). The order of the surveys and the items on each survey were

randomized. At the end of the survey, participants received a code to be entered through the MTurk platform in order to obtain the monetary reward.

Based on the demographic information, only White, Black, and Asian individuals who also identified themselves as Americans, claimed their U.S. citizenship or permanent residency, and lived in the U.S. at the time of the survey were invited to participate in the second part of the study. In the second part of the study, invited participants were randomly assigned to one of the nine conditions (based on physician race: White photo 1,

White photo 2, White photo 3, Asian photo 1, Asian photo 2, Asian photo 3, Black photo

1, Black photo 2, and Black photo 3). Upon agreeing to participate in the study, participants read the following scenario:

Imagine a situation in which you have moved to a new place, and you have to

select a new primary care physician. You went online to look up a number of

physicians in the nearby hospitals. After a thorough search, you saw a physician's

profile as shown on the next page.

After reading the scenario, they were directed to the next page that showed a physician profile based on the assigned condition. Then, they completed a set of questions that measure their perceptions, attitude, and emotions toward the physician (the order of the measure presentation were randomized).

Afterward, participants read another scenario of a first visit with the physician they saw in the profile as follows:

Now imagine that you have decided you need to schedule an appointment with

this physician, you went on time at the appointed time to meet him. You waited

for 15 minutes in the hospital lobby until a nurse greeted you with a friendly smile

and took you to the physician office. The nurse examined your height, weight, and

blood pressure; then interviewed you about some of your health information and

the symptoms that you experienced. This procedure took approximately 15

minutes, then she asked you to wait longer until the physician came.

Twenty minutes after waiting by yourself in the office, the physician finally came

along with a resident. He seemed to be in a hurry, and without apologizing for

making you wait so long, he directly asked you to lie down on the bed for an

examination.

He asked about the symptoms that you had been experiencing, and while

conducting the examination, he also kept speaking to the resident, explaining

about your health condition. He did give you some chances to talk, but you still

felt that he did not pay enough attention to what you said and to your questions.

The whole meeting with the physician took approximately 9 minutes. At the end

of the visit, he ordered a battery of test which included a blood test and chest X-

ray. He told you that once he received the result of these tests, staff from his

office would call you up to schedule the next appointment.

After reading the second scenario, participants completed a behavioral tendency questionnaire, where the order of the items was randomized, followed by other unrelated surveys and demographic questions. Upon completion of the experiment, participants read a debriefing statement and received a code to enter through the MTurk platform to obtain the monetary reward.

Experimental Stimuli: Physician Profiles

As previously described, each of the participants in this study saw the profile of either a White, Asian, or Black physician, where three different photos were used for each physician race/ethnic group. Each of the physician profiles contained a headshot photo (approximately 3 in x 2 in) on the left side of the page, accompanied with physician name above the photo. On the right side of the page, the profile listed other information which included a fictitious hospital name, education and training background, years of experience, and the physician spoken language. Underneath the profile, an overall rating indicated by 1 to 5 stars were provided, along with eight specific ratings (i.e., ease of making an appointment, promptness, courteousness of the staff, accuracy of the diagnosis, bedside manner, time spent with the patient, follow-up after the visit, and the average wait time).

The physician photos were selected from a pool of real physician pictures found through Google search and from various hospitals around the U.S. All physicians in the pictures were male and wearing a white lab coat. Based on the picture quality, pose consistency, as well as their similarity in age, six pictures of each race/ethnic group were selected and rated by a group of 52 undergraduate students (80.8% female, 71.2% White,

Mage = 20.73 years old, SDage = 2.45). Here, participants rated the physician attractiveness, intelligence, friendliness, happiness, and competence based on the photos on the scale of 1 to 5 (1 = not at all, 5 = extremely), as well as their perceived age and race/ethnic group. From this pilot study, one Asian, three Black, and three White physician photos were mostly perceived as belonging to the age group of 40 to 60 years old and member of the race/ethnic group they were supposed to belong. Their mean traits

ratings were also comparable (i.e., from 1.60 to 2.27 for attractiveness, and from 3.10 to

4.06 for the other traits). Another Asian physician photo from this pilot study, with comparable ratings to the seven already selected photos, was chosen and then edited using Adobe Photoshop to appear older. Additionally, three more Asian physician photos were piloted with another group of 10 undergraduate students (90% female, 80% White,

Mage = 20.90 years old, SDage = 1.20), in which one Asian physician photo was selected based on the criteria used in the previous photo pilot study.

In the profile, all physicians were named David, but their last names were altered to be consistent with the physician race/ethnic group (i.e., Wang for the Asian physicians,

Smith for the Black physicians, and Miller for the White physicians). All other information listed on the profiles were identical.

Measures

Stereotypic Beliefs on Various Types of Occupation. The stereotypic beliefs items measured participant perceptions of various types of occupations that included physician and other occupations (i.e., salesperson, nurse, scientist, teacher) on communion/warmth and agency/competence levels in a 5-point scale (1 = not at all, 5 = extremely). This scale was constructed by combining the warmth and competence scale from SCM literature with the communion and agency scale from the Social Role Theory literature (Koenig & Eagly, 2014). For this measure, participants responded to the question: “Think about people who work in different types of occupation. In general, what are your impressions toward people who work in each type of those occupations?”.

The communion/warmth items included kind, nurturing, sincere, and warm; whereas the agency/competence items included capable, skillful, competent, ambitious, dominant,

assertive, intelligent, and daring. Specifically, for the physician occupation, the internal consistency of the expected physician communion/warmth scale was α = .88, and the internal consistency of the expected physician agency/competence scale was α = .87.

Participants completed this measure in the first part of the study, and then their responses in this phase were correlated to their responses on the ratings of the physician communion/warmth and agency/competence that they completed in the second part of the study.

Perceptions of the Physician. The perceptions of the physician were measured using items from the communion/warmth and agency/competence measures described earlier (Koenig & Eagly, 2014). Participants were asked to rate the physician in the following traits: kind, nurturing, sincere, and warm (communion/warmth) as well as capable, skillful, competent, ambitious, dominant, assertive, intelligent, and daring

(agency/competence). A 5-point scale (1 = not at all, 5 = extremely) was used. The internal consistency of the communion/warmth scale was α = .89, and the internal consistency of the agency/competence scale was α = .78.

In order to measure the perceptions of physician warmth and competence levels as required in the SCM model, participant responses in each dimension were aggregated.

The mean score of the communion/warmth items served as the perceptions of physician warmth score and the mean score of the agency/competence items served as the perceptions of physician competence score. Thus, for each dimension, the score ranged from 1 to 5, which means that the higher the score, the better the perception of physician warmth and competence levels.

In order to obtain the role congruity score as required in the role congruity theory’s predictions, participant responses in this section of the main study were correlated with their responses obtained in the first part of the study on the stereotypic beliefs about physicians. Therefore, the role congruity score of each dimension (i.e., communion and agency) ranged from -1 to +1. The closer the score is to +1 the higher the communion congruity and agency congruity scores.

Emotions toward the Physician. Participants were asked about their feelings toward the physician on a 5-point scale (1 = not at all, 5 = extremely). Three emotion types (i.e., admiration, disgust, and envy) were included in this scale along with other emotion types relevant to the intergroup emotion theory and the SCM theory that served as filler items. The three relevant emotion types were measured using two-item scale used previously in the SCM literature (Cuddy et al., 2007) which included proud and admire to measure admiration (r = .57, p < .001), disgust and contempt to measure disgust (r = .49, p < .001), and envious and jealous to measure envy (r = .67, p < .001).5 The scores obtained from the two items were combined and aggregated into a composite score that ranged between 1 and 5, for each of the emotion types.

Evaluation of the Physician (Outgroup Feeling Thermometer). Participants were asked to rate the physician using a modified version of the outgroup feeling thermometer (e.g., Turner, Hewstone, Voci, & Vonofakou, 2008) to measure evaluations of the physician. Participants read the following instructions:

5 Other emotion items that were also included in the emotion measure were pity, sympathy (Cuddy et al., 2007), angry, irritated, uneasy, afraid, guilt, satisfied, hopeful, happy, grateful, and respectful (Smith, Seger, & Mackie, 2007).

Below you will see something that looks like a thermometer. We would like you

to use the thermometer to indicate your overall attitude towards the physician

whose profile you have just seen. If you have a favorable attitude towards this

physician, you would give him a score somewhere between 50° and 100°,

depending on how favorable you are toward this physician. If you have an

unfavorable attitude towards this physician, you would give him a score

somewhere between 0° and 50°, depending on how unfavorable you are toward

this physician. However, you are not restricted to the numbers indicated -- feel

free to use any number between 0° and 100°. Please be honest.

Evaluation of the Physician (Semantic-Differential Measure of Attitudes). A semantic-differential measure of attitudes (Eagly et al., 1991) was also used as a measure of evaluation of the physician. Participants were asked to rate the physician on five 7- point semantic differential scales: bad-good, negative-positive, useless-valuable, unpleasant-pleasant, and awful-nice (α = .91). Each scale was scored from -3 to +3, and the evaluation score was represented by the mean score of the five scales and thus, the evaluation score would range from -3 to +3.

Facilitative Behavioral Tendency toward the Physician. Initially, 12 items were developed to construct the facilitative behavioral tendency scale based on the findings of Pilot Study 2. Participants responded to the statement: “After this visit, I would…” in a 5-point scales (1 = strongly disagree, 5 = strongly agree). However, later exploratory factor analysis and subsequent confirmatory factor analysis with one factor

(described in detail in the results section) showed only five items made a good model fit for this scale. The five items included: compliment him, make sure I keep this physician

as my primary care provider, leave a good comment about him, recommend this physician to my family and friends, and write a positive review about him. Items in this scale were treated as observed variables for the facilitative behavioral tendency latent variable in the original proposed model. The internal consistency of this scale was: α =

.90.

Harmful Behavioral Tendency toward the Physician. Similar to the facilitative behavioral tendency, 12 items were initially developed to measure the harmful behavioral tendency based on the findings of Pilot Study 2. Participants responded to the statement:

“After this visit, I would…” on a 5-point scale (1 = strongly disagree, 5 = strongly agree). Later, the exploratory factor analysis and subsequent confirmatory factor analysis with one factor (described in detail in the results section) showed that only four items made a good model fit for this scale. These items included: show my anger during the visit, write a complaint about him, speak to the clinic director to complain about him, and write a bad review about him. Similar to the facilitative behavioral tendency, all items on this scale were treated as observed variables for the harmful behavioral tendency latent variable in the original proposed model. The internal consistency of this scale was: α =

.81.

Data Analytical Strategy

First, all of the data were evaluated for the missing data pattern. Listwise deletion was conducted for cases that had more than 30% of missing data, then Little’s Missing

Completely at Random (MCAR) test was performed for the remainder of the data using the IBM Statistical Package for the Social Sciences (SPSS) 20. If the Little’s MCAR test was not significant, the data were MCAR and thus, the Full Information Maximum

Likelihood (FIML) estimation was used to handle the missing data. If the data were not

MCAR, Multiple Imputation (MI) was used to handle the missing data (Graham, 2009;

Little, 1988). These tests were performed for both the EFA and the main study data.

Then, for the main study, preliminary analyses were conducted in order to examine the relations between all focal variables in each of the three theoretical models using Pearson’s correlational analysis. A series of analysis of variance (univariate and multivariate) were performed to examine the effects of the main independent variables on all of the dependent variables in each model. Specifically, for the Social Identity

Approach theoretical model, a univariate analysis of variance (ANOVA) and MANOVA were conducted to examine the differences between four grouping categories (i.e., crossed categories: double ingroup, partial ingroup (race), partial ingroup (gender), and double outgroup) on emotions, evaluation, and behavioral tendencies toward the physicians. For the Stereotype Content Model’s prediction, a series of MANOVA were used to examine the differences between three grouping categories (i.e., experimental conditions: White, Asian, and Black male physicians) on perceptions, emotions, and behavioral tendencies toward the physicians. Finally, to examine the effects of the independent variable on the dependent variables in Role Congruity Theory’s prediction,

ANOVAs and MANOVAs were conducted to examine the differences between three grouping categories (i.e., experimental conditions: White, Asian, and Black male physicians) on role congruity, evaluation, and behavioral tendencies toward the physicians.

The outcomes of this preliminary analysis were critical in determining the number of dummy-coded variables required for each MIMIC model. For instance, if there was no

significant difference found between the partial ingroup (race) and partial ingroup

(gender) in the Social Identity Approach model, these two partial ingroup categories would be collapsed into one category as the reference group in this model, leaving only three grouping categories in the ‘crossed categories’ variable. If this were the case, there would be only two dummy-coded variables required for this model, where the double ingroup would be compared to the reference group in one variable, and the double outgroup would be compared to the reference group in another. Nevertheless, if differences were found between the four groups, three dummy-coded variables would be created with one of the groups being treated as the reference group. Similarly, outcomes from this stage of analysis also provided important information for the further grouping of the exogenous variables in both SCM and Role Congruity Theory MIMIC models.

Overall, results from these preliminary analyses provided directionality to each of the

MIMIC models.

Three separate structural equation modeling (SEM) were conducted to analyze the data based on the three theoretical perspectives. Since all of the three theoretical perspectives called for a categorical main predictor variable (i.e., exogenous variable),

MIMIC models were used. The MIMIC model allowed for the assessment of group differences on measurement invariance and latent mean by incorporating the categorical variable as a covariate instead of testing the model based on the groups separately. This way, each of the MIMIC models was identified as a whole model and did not require partitioning the model into different subsamples, unlike what would happen in a multigroup SEM (Gunzler & Morris, 2015; Kim, Yoon, & Lee, 2012; Kline, 2011;

Woods, 2009; Woods, Oltmanns, & Turkheimer, 2009). Before conducting the SEM

analysis, the univariate normality assumption was evaluated using SPSS 20. The

Maximum Likelihood (ML) estimation would be performed for testing the SEM model if the data were normally distributed (skewness < 2.00 and kurtosis < 7.00); whereas

Maximum Likelihood with a mean-adjusted chi-square (MLM) would be used if the univariate normality assumption was violated (Kline, 2011).

Prior to testing the MIMIC models, selection of the observed variables used in the two measurement models was performed using EFA. Thus, the number and types of the observed variables in each of the measurement models depended on the EFA results.

Once the selected observed variables were determined, each of the proposed full MIMIC models was modified and tested. Additionally, since both Social Identity Approach and

Role Congruity Theory models used evaluation as one of their endogenous variables, analyses were performed separately using each of the two evaluation measures (i.e., outgroup feeling thermometer and semantic-differential measure of attitudes) to compare results between the two if either measure was used.

The assessment of model fit was then conducted using several recommended fit indices. First, chi-square goodness of fit index was used, in which a significant value indicated a lack of acceptable model fit (Hu & Bentler, 1999). However, this index has a tendency to be significant with a larger sample size and thus, additional fit indices were used with the recommended cut-off points that ensure Type-II error with acceptable

Type-I error rates, such as the root mean square error of approximation (RMSEA), standardized root mean square residual (SRMR), comparative fit index (CFI), and

Tucker-Lewis Index (TLI). A well-fitting (adequate) model had RMSEA value of < .06

(.07 - .08), SRMR value of < .08 (.09 - .10), and CFI and TLI values of > .95 (.90 - .94)

(Hu & Bentler, 1999). If the MIMIC model had a lack of adequate fit, the model would be modified based on the modification indices information and theoretical basis. An evaluation of model fit would then be performed to the alternative model.

Chapter Five

Results

Exploratory Factor Analysis

As mentioned earlier, EFA was required to analyze the two behavioral tendency scales (i.e., facilitative and harmful) as these measures were never used in any previous research. Factor analysis is used in theory building and construct development, and an

EFA allows us to investigate the dimensionality of the measure, relationship between the factors of a measure, and the quality of the variables used in the measure that is data- driven (Henson & Roberts, 2006). In this study, the EFA was used in the development of both facilitative and harmful behavioral tendency measures with the aim of selecting the best items that could be used to measure both of the latent variables in the measurement models of each of the tested MIMIC models in the main study.

In this case, the final data, with the total of 344 participants, were first evaluated for the missing data pattern, which showed a significant value of the Little’s MCAR test,

Little’s MCAR test χ2 (337) = 402.76, p = .008. Hence, missing data were imputed using

MI with MPlus program, and since the highest missing data fraction was only γ = .009, the data were imputed 20 times to ensure equivalent outcomes if FIML approach was instead used and with < 1% tolerance of power falloff (Dong & Pen, 2013; Graham,

Olchowski, & Gilreath, 2007). Evaluation of the univariate normality assumption was also performed on all of the variables which showed that all data were normally distributed. Thus, ML estimations were used in the EFA for both facilitative and harmful behavioral tendencies.

Facilitative Behavioral Tendency. An EFA using ML estimation was first performed to the 12 facilitative behavioral tendency items imputed data. Following a theory-driven approach, all items were expected to load into one latent variable, and thus, the EFA was performed for one factor. Assessment of the model fit showed χ2 (54) =

285.80, p < .001, RMSEA = .11, SRMR = .05, CFI = .91, and TLI = .86, indicating a lack of adequate model fit. Then, items with communality greater than .60 were selected for the second EFA as suggested by Henson and Roberts (2006). The items included: compliment him, make sure I keep this physician as my primary care provider, leave a good comment about him, recommend this physician to my family and friends, and write a positive review about him. The second EFA showed a good model fit, where χ2 (43) =

7.60, p = .180, RMSEA = .04, SRMR = .01, CFI = .998, and TLI = .996. Therefore, these items were selected as the observed variables used for the measurement model of each of the three MIMIC models. For a comparison purpose, a two-factor EFA was also performed to the 12 facilitative behavioral tendency items imputed data. Although the 2- factor model had a better fit than the 1-factor model (χ2 (5) = 7150.481, p < .001,

RMSEA = .09, SRMR = .03, CFI = .96, and TLI = .94), one of the factors consisted less than three items, which would result in an unidentified model for this specific latent behavior in the larger MIMIC models. Therefore, further analyses in this study used the results obtained from the 1-factor EFA analysis.

Harmful Behavioral Tendency. A similar procedure was performed with the 12 items harmful behavioral tendency items imputed data. A 1-factor EFA was examined following a theory-driven approach, which showed a lack of adequate model fit, χ2 (54) =

565.398, p < .001, RMSEA = .17, SRMR = .11, CFI = .73, and TLI = .67. However,

since none of the items had communalities greater than .60, the items with greater than

.50 communalities were selected. With the sample size used in this analysis, this parameter is still in the acceptable range to ensure the quality of the EFA outcomes

(Henson & Roberts, 2006; MacCallum & Widaman, 1999). Therefore, four items were selected for the second EFA, which included: show my anger during the visit, write a complaint about him, speak to the clinic director to complain about him, and write a bad review about him. A good model fit was found using these items, χ2 (2) = 6.266, p = .043,

RMSEA = .08, SRMR = .02, CFI = .99, and TLI = .98. Thus, these items were used in the measurement model of each of the three MIMIC models. Similar to the procedure used for the facilitative behavioral tendency EFA, a two-factor EFA was also performed to the 12 harmful behavioral tendency items imputed data for a comparison purpose. It was found that the 2-factor model had a worse fit than the 1-factor model (χ2 (43) =

680.721, p < .001, RMSEA = .21, SRMR = .14, CFI = .66, and TLI = .48), and thus, further analyses in this study used the results obtained from the 1-factor EFA analysis.

Confirmatory Factor Analysis

Facilitative Behavioral Tendency. A confirmatory factor analysis (CFA) was conducted to evaluate the model fit for the facilitative behavioral tendency scale based on the EFA results, using data collected from the main study. The data were first tested for a missing data pattern, and the results showed a non-significant Little’s MCAR test value,

Little’s MCAR test χ2 (12) = 4.758, p = .966. Thus, FIML was used to estimate any missing data in the CFA. All of the data used in this analysis were also found to be normally distributed. Outcome of the CFA indicated an adequately fitting model for the facilitative behavioral tendency scale, χ2 (5) = 30.107, p < .001, RMSEA = .09, SRMR =

.02, CFI = .98, and TLI = .97. Table 3 shows the standardized factor loadings of each of the scale items.

Table 3. Standardized Factor Loadings of the Facilitative Behavioral Tendency Scale.

Items Standardized Factor Loadings compliment him .74 make sure I keep this physician as my primary care provider .77 leave a good comment about him .84 recommend this physician to my family and friends .84 write a positive review about him .79

Harmful Behavioral Tendency. The Little’s MCAR test showed a non- significant value for the data used in this scale, Little’s MCAR test χ2 (9) = 5.814, p =

.758. Thus, FIML was used to estimate missing data in the subsequent CFA. All of the data used in this analysis were also found to be normally distributed. Outcome of the

CFA indicated an adequately fitting model for the harmful behavioral tendency scale, χ2

(2) = 4.018, p = .134, RMSEA = .04, SRMR = .01, CFI = .997, and TLI = .99. The standardized factor loadings of each of the scale items are presented in Table 4.

Table 4. Standardized Factor Loadings of the Harmful Behavioral Tendency Scale.

Items Standardized Factor Loading show my anger during the visit .53 write a complaint about him .86 speak to the clinic director to complain about him .77 write a bad review about him .74

Social Identity Approach

Evaluating Group Differences on Dependent Variables. Analyses of variance were conducted to investigate differences between the four crossed categories (i.e., double ingroup (n = 131), partial ingroup race (n = 104), partial ingroup gender (n = 149), and double outgroup (n = 182)) on emotions (i.e., admiration and disgust), outgroup feeling thermometer evaluation, semantic-differential evaluation, and behavioral tendencies (i.e., facilitative behavioral tendency and harmful behavioral tendency). All of the dependent variables used in the analysis were normally distributed. In this analysis stage, the items that measure the two behavioral tendencies were combined into the facilitative behavioral tendency and the harmful behavioral tendency scales.

First, the one-way MANOVA with emotions as the dependent variables revealed a significant difference of emotions based on the crossing of categories between the participant and the physician gender and race/ethnicity, Wilks’Ʌ = .97, F(6, 1122) = 2.63,

2 p = .016, ηp = .01. The subsequent univariate analysis revealed a significant effect of

2 crossed categories on disgust, F(3, 562) = 4.89, p = .002, ηp = .03, but not admiration,

2 F(3, 562) = 1.06, p = .365, ηp = .01. The results mean that the crossing of categories between participant and physician gender and race/ethnicity relates to whether the participants feel disgusted to the physician or not. Results from the Tukey’s post hoc tests showed that participants in the double ingroup category (i.e., similar in both gender and race/ethnic identities with the physician, M = 1.57, SD = .97) felt more disgusted toward the physician than those in the double outgroup category (i.e., did not share any gender and race/ethnic identities with the physician, M = 1.32, SD = .64), p = .045. Similarly, significant differences were also found between partial ingroup gender (i.e., only shared

gender identity with the physician) and double outgroup, where participants in the partial ingroup gender category (M = 1.63, SD = .97) felt more disgusted toward the physician than those in double outgroup category (M = 1.32, SD = .64), p = .004. The finding was unexpected because prior work in the area of crossed categorization theory suggested that individuals would feel most positively toward others who share more identities with them and feel least positively toward others with a lack of identity intersection with them

(Crisp & Hewstone, 1999; Ray et al., 2012). The fact that the participants who only shared gender identity with the male physician also felt more disgusted toward the physician than those who did not share both gender and race/ethnic identities, indicated that both participant and the physician gender matter in relation to whether a patient would feel more or less disgusted toward the physician.

Next, two separate ANOVAs were conducted to examine the differences between the four types of crossed categories on the outgroup feeling thermometer evaluation and the semantic differential evaluation. When the outgroup feeling thermometer evaluation was the dependent variable, the ANOVA result showed a non-significant effect of the

2 crossed categories, F(3, 562) = .25, p = .858, ηp = .00. The same result was also found when the semantic-differential evaluation was the dependent variable, F(3, 562) = .72, p

2 = .543, ηp = .00.

Finally, the one-way MANOVA with behavioral tendencies as the dependent variables revealed a significant difference of behavioral tendencies based on the four

2 crossed categories, Wilks’Ʌ = .95, F(6, 1122) = 4.86, p < .001, ηp = .03. The subsequent univariate analysis revealed a significant effect of crossed categories on facilitative

2 behavioral tendency, F(3, 562) = 9.73, p < .001, ηp = .05, but not harmful behavioral

2 tendency, F(3, 562) = .14, p = .937, ηp = .00. This means that the crossing of categories between the participant and the physician gender and race/ethnicity relates to the tendency of the participant to behave more positively toward the physician even after the slightly unpleasant first visit experience. Here, participants in the double ingroup category (M = 2.23, SD = .85) had higher facilitative behavioral tendency toward the physician even after imagining the unpleasant first visit than those in the double outgroup

(M = 1.81, SD = .83), p < .001 and partial ingroup race categories (M = 1.93, SD = .75), p

= .032. Also, participants in the partial ingroup gender category (M = 2.22, SD = .88) had higher facilitative behavioral tendency than the double outgroup (M = 1.81, SD = .83), p

< .001 and the partial ingroup race categories (M = 1.93, SD = .75), p = .031. These results were in-line with the previous work on the crossed categorization theory and intergroup emotions theory of social identity which suggest that those who share more identities with each other would feel more positively toward each other, and as a consequence, would act toward the group they share (Mackie & Smith, 2015, 2017; Ray et al., 2012).

Overall, the outcomes from these analyses showed that there were some unique differences between the two partial ingroup categories (i.e., partial ingroup race and partial ingroup gender) that needed further investigation. Based on these results, the subsequent correlational and SEM analyses treated the two partial ingroup categories as separate categories, instead of a combined category as originally proposed. Consequently, in the latter analyses, three dummy coded variables were created, in which the double outgroup category served as a reference group, and the rest were compared to this reference group.

Table 5. Correlations between All Focal Variables in Social Identity Approach Model.

M SD 1 2 3 4 5 6 7 8 9 10 11 1) Age 37.48 12.85 2) Gender .12** 3) Double ingroup -.01 -.56*** 4) Partial ingroup .04 .47*** -.26*** race 5) Partial ingroup -.12** -.60*** -.33*** -.28*** gender 6) Admiration 2.77 1.06 -.07 -.05 .01 .02 .05 7) Disgust 1.47 .84 -.28*** -.16*** .06 -.05 .12** .33*** 8) Thermometer 73.54 14.80 .06 .01 -.03 .01 .02 .28*** -.18*** evaluation 9) Semantic 1.73 .90 .05 .05 -.01 .04 -.05 .33*** -.16*** .57*** evaluation 10) Facilitative 2.03 .86 -.13** -.22*** .13** -.06 .13** .36*** .47*** .08 .09* behavioral tendency 11) Harmful 2.38 .94 -.12** .02 .01 .00 -.01 .12** .35*** -.12** -.13** -.00 behavioral tendency Note: *p < .05, ** p < .01, *** p < .01

5. Here, for the gender variable, male was coded “0” and female was coded “0”; whereas, for the three dummy-coded variables (i.e., double ingroup, partial race, and partial gender), each of these variables were coded “1” and the rest of the categories were coded

“0”.

Table 5 shows negative correlation between age with disgust, facilitative behavioral tendency, and harmful behavioral tendency. These results indicated that the feeling of disgust to the physician as well as the facilitative and harmful behavioral tendencies toward the physician decreased with participant age. Gender was also negatively correlated with disgust and facilitative behavioral tendency, indicating that female participants felt less disgusted with the physician, but at the same time were less likely to behave in a facilitative way toward the physician. The findings were in-line with the MANOVA results, where participants in both double ingroup and partial ingroup gender felt more disgusted but at the same time had higher facilitative behavioral tendency toward the physicians compared to those in double outgroup category.

Admiration was also positively correlated with disgust, both of the evaluation measures (i.e., outgroup feeling thermometer and semantic-differential), and both of the behavioral tendencies (i.e., facilitative and harmful). These results implied that the more a participant admired the physician, the more likely he/she would feel disgusted towards the physician; but at the same time, the more likely he/she would evaluate the physician more favorably, and had higher facilitative and harmful behavioral tendencies toward the

physicians. Disgust, on the other hand, was negatively correlated with both evaluation measures, which means that the more a participant felt disgusted towards the physician, the less favorable their evaluation of the physician. However, disgust was also positively correlated with both facilitative and harmful behavioral tendencies, which means that the more a participant felt disgusted towards the physician, the higher their facilitative and harmful behavioral tendencies toward the physician would be.

The two evaluation measures were also positively correlated with each other, which means that those who evaluated the physician more positively using the outgroup feeling thermometer would also be likely to evaluate the physician more positively using the semantic differential evaluation. These two measures were also negatively correlated with a harmful behavioral tendency, indicating that the more positive the evaluation, the lower the harmful behavioral tendency toward the physician. However, only the semantic differential evaluation was positively correlated with the facilitative behavioral tendency, albeit a weak correlation, which indicated that the more positive the semantic differential evaluation, the higher the facilitative behavioral tendency toward the physician.

Test of the MIMIC Model. First, the model was modified based on the EFA and

CFA results. Hence, the facilitative behavioral tendency latent variable had five observed variables, whereas the harmful behavioral tendency variable had four observed variables.

All of the data used in this model were tested for the missing data pattern which showed non-significant Little’s MCAR test value, Little’s MCAR test χ2 (78) = 52.354, p = .961, and thus, FIML was used for the missing data estimation. Then, an SEM analysis was performed for each of the Social Identity Approach’s MIMIC models, one with the thermometer evaluation measure and one with the semantic-differential evaluation

measure as the evaluation variable (Figure 13). However, none of these two models was found to fit the data adequately. The fit indices for the MIMIC model that used thermometer evaluation measure were: χ2 (82) = 575.159, p < .001, RMSEA = .10,

SRMR = .13, CFI = .84, and TLI = .80; whereas the fit indices for the MIMIC model that used the semantic-differential evaluation measure were: χ2 (82) = 563.553, p < .001,

RMSEA = .10, SRMR = .13, CFI = .84, and TLI = .80.

Figure 13. Tested MIMIC model diagram of patient-physician intergroup relations based on Social Identity Approach. A close inspection of the modification indices in both models revealed that the pathway from disgust to facilitative behavioral tendency yielded a very high modification index (M.I. = 135.395 in thermometer evaluation model and M.I. = 136.480 in semantic- differential evaluation model). Based on this result, both models were modified in a way that was theoretically reasonable. First, the models were modified by freeing the direct path between disgust and the facilitative behavioral tendency. This is a possible

modification as theoretically, a group-based emotion, such as anger and disgust, could directly influence behavioral tendency (Mackie et al., 2000; Ray et al., 2012; Mackie &

Smith, 2015, 2017; Mackie et al., 2008). This modification did improve the models, but they still did not fit the data adequately. The fit indices for the modified MIMIC model that used thermometer evaluation measure were: χ2 (81) = 396.542, p < .001, RMSEA =

.08, SRMR = .10, CFI = .89, and TLI = .87; whereas the fit indices for the modified

MIMIC model that used the semantic-differential evaluation measure were: χ2 (82) =

563.553, p < .001, RMSEA = .10, SRMR = .13, CFI = .84, and TLI = .80.

Subsequently, another model modification was pursued to improve both of the models. In this case, each model was trimmed by taking away disgust from each of the

MIMIC models. Theoretically, this modification is also sensible as it is possible that the discrete emotion of disgust may not be an appropriate emotion to occur in the context of the patient-physician relationship. As Cottrell and Neuberg (2005) suggested, disgust is likely to occur in the context of intergroup relations when the outgroup members are perceived as a threat to the ingroup health or values by spreading contagious illness or moral harm. On the other hand, in the context of the patient-physician intergroup relations, a physician is more likely to be perceived as the individual who will help the patient to improve or maintain his/her health.

The results of the MIMIC model analysis when the two types of emotion were separated supported this idea. When admiration was the only type of emotion included in each of the two MIMIC models, both models improved and were adequately fitting the data. Here, the fit indices for the MIMIC model that included only admiration and used outgroup feeling thermometer evaluation measure were: χ2 (72) = 324.128, p < .001,

RMSEA = .08, SRMR = .09, CFI = .91, and TLI = .89; whereas the fit indices for the

MIMIC model that included only admiration and used the semantic-differential evaluation measure were: χ2 (72) = 314.634, p < .001, RMSEA = .08, SRMR = .09, CFI

= .91, and TLI = .89. On the contrary, when disgust was the only type of emotion included in the model, the fit indices of both models showed inadequate fit (i.e., MIMIC model with disgust and thermometer evaluation measure: χ2 (72) = 467.120, p < .001,

RMSEA = .10, SRMR = .11, CFI = .86, and TLI = .83; MIMIC model with disgust and semantic-differential evaluation measure: χ2 (72) = 458.055, p < .001, RMSEA = .10,

SRMR = .11, CFI = .86, and TLI = .83).

As shown in Figure 14, admiration toward the physician predicted outgroup feeling thermometer evaluation, which indicated that the more a participant admired the physician, the more likely he/she would evaluate the physician more favorably. The outgroup feeling thermometer evaluation then predicted the harmful behavioral tendency toward the physician, in which the more favorable the evaluation was, the lower the harmful behavioral tendency. The model indirect analysis also revealed a significant indirect effect from admiration to harmful behavioral tendency through thermometer evaluation, β = -.04, p = .007. From Figure 15, we can see that admiration also predicted semantic-differential evaluation, which then predicted both facilitative behavioral tendency and harmful behavioral tendency. The model indirect analysis in this case also revealed significant indirect effects from admiration to facilitative behavioral tendency through semantic-differential evaluation, β = -.03, p = .043, as well as from admiration to harmful behavioral tendency through semantic-differential evaluation, β = -.05, p = .003.

Figure 14. Modified MIMIC model diagram of patient-physician intergroup relations based on Social Identity Approach with admiration and thermometer evaluation.

Figure 15. Modified MIMIC model diagram of patient-physician intergroup relations based on Social Identity Approach with admiration and semantic-differential evaluation.

Stereotype Content Model

Evaluating Group Differences on Dependent Variables. Three separate one- way MANOVAs were conducted to investigate differences between the three physician profiles (i.e., White male physician (n = 215), Black male physician (n = 156), and Asian male physician (n = 195)) on perceptions (i.e., warmth and competence), emotions (i.e., admiration and envy), and behavioral tendencies (i.e., facilitative behavioral tendency and harmful behavioral tendency). All of the dependent variables used in these

MANOVAs were normally distributed.

Here, the one-way MANOVA with perceptions as the dependent variables showed a non-significant multivariate effect of physician profiles on perceptions of

2 physician warmth and competence, Wilks’Ʌ = .99, F(4, 1124) = 2.06, p = .084, ηp = .01.

However, the univariate analysis revealed a significant effect of physician profiles on the

2 perceptions of physician warmth, F(2, 563) = 3.30, p = .038, ηp = .01, but not the

2 perceptions of physician competence, F(2, 563) = 2.91, p = .055, ηp = .01. The result indicated that participant perceptions of physician warmth were related to which physician profile they saw during the experiment. Specifically, Black male physicians (M

= 3.42, SD = .85) were perceived as significantly warmer than White male physicians (M

= 3.22, SD = .79), p = .041; but Black male physician warmth (M = 3.42, SD = .85) was not significantly different from the Asian male physician warmth (M = 3.36, SD = .79), p

= .767. Although there was a difference between participant perceptions of the warmth of the Black and White male physicians, all of the means of the perception of warmth fell above the mid-point of the warmth scale (i.e., the scale ranged from 1 to 5) across groups.

Similarly, all of the means of the perception of competence fell above the mid-point of

the scale (Black male: M = 3.59, SD = .65, White male: M = 3.46, SD = .56, Asian male:

M = 3.56, SD = .52). This result was consistent with the previous findings that placed physicians in the high warmth-high competence quadrant (Asbrock, 2010; Fiske &

Dupree, 2014), but did not support the Pilot Study 1 findings where Black physicians were found at a more disadvantaged situation compared to other physicians.

Next, the one-way MANOVA with both types of emotions as the dependent variables and the physician profiles as the independent variable showed a statistically significant effect of the physician profiles, Wilks’Ʌ = .97, F(6, 1124) = 3.72, p = .005,

2 ηp = .01. The subsequent univariate analysis revealed a significant effect of physician

2 profiles on admiration, F(2, 563) = 6.71, p = .001, ηp = .02, but not on envy to the

2 physician, F(2, 563) = .00, p = .997, ηp = .00. The result indicated that the feeling of admiration toward the physician depended on which physician profile was assigned to during the experiment. Here, participants were significantly more likely to admire the

Black male physicians (M = 3.00, SD = 1.08) than the White male physicians (M = 2.60,

SD = 1.06), p = .001; but there was no difference between Black male physicians (M =

3.00, SD = 1.08) and Asian male physicians (M = 2.78, SD = 1.03), p = .125.

Furthermore, the data in this study showed that the means of admiration toward the White and Asian male physicians fell below the mid-point of the scale (i.e., the scale ranged from 1 to 5). This result was inconsistent with an SCM premise which suggests that the groups who are perceived as highly warm and competent would be admired (Cuddy et al.,

2008; Fiske et al., 2002). The data on envy to the physicians, however, showed support to the SCM proposition, where all of the means of this variable fell below the mid-point of the scale across groups (Cuddy et al., 2008; Fiske et al., 2002).

Finally, the one-way MANOVA with both types of behavioral tendencies as the dependent variables and the physician profiles as the independent variable was not

2 statistically significant, Wilks’Ʌ = .99, F(4, 1124) = 1.03, p = .390, ηp = .00. None of the univariate analysis showed significant effect either (facilitative behavioral tendency, F(2,

2 563) = 1.72, p = .180, ηp = .01, harmful behavioral tendency, F(2, 563) = .35, p = .708,

2 ηp = .00). The result means that participant behavioral tendencies toward the physician were not dependent on which physician profile that they saw during the experiment.

Overall, the outcomes from these MANOVAs indicated there could be particular patterns that needed more exploration, regarding the differences between the three groups of the physician profiles. Unlike what was expected, that the Black male physicians would differ from both White and Asian male physicians, the results suggested that the perceptions and emotions toward the Black male physicians were only different in comparison to the White male physicians and not to the Asian male physicians.

Accordingly, in the latter analyses, the three groups were treated separately. In other words, data from participants who were assigned to see the White and Asian male physicians were not merged, as it was planned. Therefore, in the subsequent correlational and SEM analyses, two dummy-coded variables were created, in which the Black male physician profile served as the reference group.

Table 6. Correlations between All Focal Variables in Stereotype Content Model.

M SD 1 2 3 4 5 6 7 8 9 10 1) Age 37.48 12.85 2) Gender .12** 3) White male physician .04 -.01 4) Asian male physician -.09* -.03 -.57*** 5) Warmth 3.23 .81 -.03 -.05 -.10* .04 6) Competence 3.53 .58 .09* .01 -.10* .04 .52*** 7) Admiration 2.77 1.06 -.07 -.05 -.13** .01 .58*** .47*** 8) Envy 1.38 .80 -.21*** -.24*** -.00 -.00 .11* .07 .34*** 9) Facilitative behavioral 2.03 .86 -.13** -.22*** -.08 .05 .28*** .17*** .36*** .46*** tendency 10) Harmful behavioral 2.37 .93 -.12** .02 .03 .01 .00 -.04 .12** .32*** -.00 tendency Note: *p < .05, ** p < .01, *** p < .01

6. Here, for the gender variable, males were coded “0” and female was coded “1”; for the two dummy-coded variables (i.e., White male physician and Asian male physician), each of these groups was coded “1” and the rest of the groups were coded “0”.

Table 6 shows age was positively correlated with competence and it was negatively correlated with envy, facilitative behavioral tendency, and harmful behavioral tendency. The findings implied that the perception of physician competence increased with age, but the feeling of envy and the facilitative and harmful behavioral tendencies toward the physician decreased with age. Gender was also negatively correlated with envy and facilitative behavioral tendency, which means that female participants were less likely to feel envious but at the same time had lower facilitative behavioral tendency toward the physician.

The White male physician variable was negatively correlated with the perceptions of warmth, competence, and admiration. The results indicated that in comparison to those who saw a Black male physician profile, participants who saw a White male physician profile were less likely to rate the physician as warm and competent and were less likely to admire the physician. On the other hand, the Asian male physician variable was not significantly correlated with any of the focal variables, which indicated that participant perceptions, emotions, and behavioral tendencies toward the physician were not related to whether the physician was an Asian male or a Black male. The results were consistent with the MANOVA findings.

The perception of the physician warmth was significantly and strongly correlated with the perception of physician competence. This finding was inconsistent with the

SCM premise, as it assumes that warmth and competence should be orthogonal of each other (Kervyn, Fiske, & Yzerbyt, 2013). On the other hand, this finding implied that the physician was regarded highly in terms of warmth and competence as discussed in the previous section.

As expected, the perception of physician warmth was also significantly correlated with admiration and facilitative behavioral tendency, which means that the more participants perceived the physician as warm, the more likely they would admire the physician and tended to show facilitative behaviors toward the physician. However, the perception of physician warmth was also found to be positively correlated with envy, which is inconsistent with the SCM assumption (Cuddy et al., 2008; Fiske et al., 2002).

Also as expected, the perception of physician competence was positively correlated with admiration and facilitative behavioral tendency, which means that the higher the perceived competence, the more likely the participant would admire the physician and had higher facilitative behavioral tendency to the physician.

The two emotion types in this model (i.e., admiration and envy) were also positively correlated with each other, meaning the more a participant admired the physician, the more likely he/she would envy the physician at the same time. This finding was somewhat expected as the SCM suggests that both emotions are related to high perceived competence levels. Both admiration and envy were also found to be positively correlated with facilitative and harmful behavioral tendencies. Although SCM suggests that envy could be related with both behavioral tendencies (i.e., passive facilitation and

active harm), admiration was not expected to be positively correlated with the harmful behavioral tendency (Cuddy et al., 2007).

Test of the MIMIC Model. As in the Social Identity Approach’s MIMIC model, the SCM MIMIC model was modified based on the EFA and CFA results. All of the data used in this model were tested for the missing data pattern which showed non-significant

Little’s MCAR test value, Little’s MCAR test χ2 (78) = 52.144, p = .989, and thus, FIML was used for the missing data estimation. Then, an SEM analysis was performed for the

Stereotype Content Model’s MIMIC model (Figure 16) which revealed a poor fitting model, χ2 (82) = 488.402, p < .001, RMSEA = .09, SRMR = .09, CFI = .88, and TLI =

.84.

Figure 16. Tested MIMIC model diagram of patient-physician intergroup relations based on Stereotype Content Model.

The examination of modification indices showed that the highest modification index was the correlation between warmth and competence variables (M.I. = 149.72), which was not assumed in the model. Based on this information, the model was then modified by freeing the covariance between the warmth and competence variables

(Figure 17), which resulted in an adequately fitting model, χ2 (81) = 314.508, p < .001,

RMSEA = .07, SRMR = .07, CFI = .93, and TLI = .91.

Figure 17 shows that compared to the Black male physicians, the White male physicians were perceived as less warm and less competent. The perception of the physician warmth also predicted both admiration and envy, but perception of physician competence only predicted admiration. The model indirect analysis revealed a significant indirect effect of the White male physician variable to admiration through warmth, β = -

.06, p = .016, and through competence, β = -.03, p = .039. This finding indicated that whether the physician was a Black or White male physician predicted admiration, and this relationship was mediated by the physician perceived warmth and competence levels.

Admiration toward the physician predicted facilitative behavioral tendency, whereas envy to the physician predicted both facilitative and harmful behavioral tendencies. The model indirect analysis also revealed significant indirect effects of warmth to facilitative behavioral tendency, both through admiration, β = .11, p < .001, and envy, β = .04, p = .044. On the other hand, the indirect effects of warmth to harmful behavioral tendency through admiration and envy were not significant, β = .01, p = .738 and β = .02, p = .050, respectively. In terms of the paths between competence and the behavioral tendencies, only the indirect effect of competence to facilitative behavioral tendency through admiration was found to be significant, β = .06, p < .001.

Figure 17. Modified MIMIC Model of the patient-physician intergroup relations based on the Stereotype Content Model. Role Congruity Theory

To analyze the role congruity theory’s predictions on the patient-physician intergroup relations, participant responses to the expected physician communion and agency levels, that they provided in the first part of the main study, were correlated with their responses from the second part of the study. The correlation indices resulted from this process then served as the communion congruity and agency congruity scores.

Nevertheless, since many participants provided a constant number (e.g., 4 in all items) in responding to the questionnaires, the Pearson’s correlation index was not able to be computed for those participants, resulting in the missing data of the communion and/or agency role congruity scores. Thus, in this part, only the data from participants that had both communion congruity and agency congruity scores were included in the further analysis, which left the data from only 296 participants, where 119 saw a White male

physician, 80 saw a Black physician, and 97 saw an Asian male physician profile. In terms of demographic, 44.3% of the participants were White, 47.3% were female, with a mean age of 38.03 years old (SD = 13.58). The number of participants in each of the focal group did not meet Wood’s (2009) recommendation for the MIMIC model, which is 100.

However, the total number of participants in the full MIMIC model met Jackson’s (2003)

N:q rule of 10:1 to be considered adequate sample for an SEM analysis, where N is the number of participants and q is the number of parameters. For the Role Congruity Theory

MIMIC model, there were 27 parameters, which would only require 270 participants in total based on this rule.

(i.e., outgroup feeling thermometer evaluation and semantic-differential evaluation), and behavioral tendencies (i.e., facilitative behavioral tendency and harmful behavioral tendency). All of the dependent variables used in the MANOVAs were normally distributed.

For the first MANOVA, the physician profiles were entered as the independent variable, whereas the communion congruity and agency congruity were entered as the dependent variables. The multivariate test revealed a non-significant effect of the

2 physician profiles in role congruity, Wilks’Ʌ = .996, F(4, 584) = .32, p = .867, ηp = .00.

Also, the univariate analyses revealed a non-significant effect of physician profiles on

2 communion congruity, F(2, 293) = .43, p = .653, ηp = .00, and on agency congruity, F(2,

2 293) = .11, p = .900, ηp = .00.

Next, two separate ANOVAs were conducted to examine the differences between the three physician profiles on outgroup feeling thermometer evaluation and semantic- differential evaluation. When outgroup feeling thermometer evaluation was the dependent variable, the ANOVA result showed non-significant effect of cross categories,

2 F(2, 293) = 2.05, p = .131, ηp = .01. The same result was also found when semantic-

2 differential evaluation was the dependent variable, F(2, 293) = .93, p = .397, ηp = .01.

Lastly, the MANOVA where the physician profiles were the independent variable, and the facilitative and harmful behavioral tendencies were the dependent variables, revealed a non-significant effect of physician profiles, Wilks’Ʌ = .99, F(4,

2 584) = .77, p = .543, ηp = .01. The univariate analyses also revealed a non-significant effect of physician profiles on facilitative behavioral tendency, F(2, 293) = 1.51, p =

2 2 .224, ηp = .01, as well as on harmful behavioral tendency, F(2, 293) = .14, p = .868, ηp =

.00. This result was consistent with what was found in the SCM’s MANOVA that used the same variables.

Overall, results from the MANOVAs showed that participant responses on all of the dependent variables in the Role Congruity Theory were independent of which physician profile they saw during the experiment. This finding was inconsistent with the

Pilot Study 1 result and the assumptions built on the Role Congruity Theory, where a

Black male physician might be at a disadvantaged position, relative to the Asian and

White male physicians, as there would be more incongruity between the expectation and the reality (Koenig & Eagly, 2014).

Table 7. Correlations between All Focal Variables in Role Congruity Theory.

M SD 1 2 3 4 5 6 7 8 9 10 1) Age 38.03 13.58 2) Gender .13* 3) White male physician .03 -.05 4) Asian male physician -.10 .00 -.57*** 5) Communion congruity .34 .52 .20** .07 .01 -.05 6) Agency congruity .16 .40 .05 .05 -.00 .02 .19** 7) Thermometer 73.25 14.47 .16** .06 -.09 -.01 .09 .17** evaluation 8) Semantic evaluation 1.68 .91 .11 .10 -.07 .01 -.04 .09 .53*** 9) Facilitative behavioral 2.08 .86 -.18** -.20** -.10 .03 -.18** .00 -.03 -.00 tendency 10) Harmful behavioral 2.36 .93 -.22*** -.10 -.03 .02 -.10 -.16** -.19** -.15** .14* tendency Note: *p < .05, ** p < .01, *** p < .01, N = 296.

Correlations between Focal Variables. Pearson’s correlational analyses were conducted to examine the relationship between independent variables, dependent variables, and demographic variables. To maintain consistency with the SCM’s analysis that used physician profiles as the exogenous variable, the three categories in the physician profile variable were transformed into two dummy-coded variables, where a

Black male physician profile served as the reference group. Results from the analyses are presented in Table 7. For the gender variable, male was coded “0” and female was coded

“1”; for the two dummy-coded variables (i.e., White male physician and Asian male physician), each of these groups was coded “1” and the rest of the groups were coded

“0”.

Table 7 shows that age was negatively correlated with communion congruity, facilitative behavioral tendency, and harmful behavioral tendency, but was positively correlated with outgroup feeling thermometer evaluation. The results indicated that communion congruity and the tendency of facilitative and harmful behaviors toward the physician decreased with age. However, the evaluation of the physician using outgroup feeling thermometer measure increased with age. Here, gender was only negatively correlated with facilitative behavioral tendency, indicating that female participants had lower facilitative behavioral tendency toward the physician.

Consistent with the MANOVA findings, neither the White male physician nor the

Asian male physician variables were correlated with any other variable. The result indicated that there was no difference between participants who saw a physician of any race, concerning their communion and agency congruity, physician evaluations, and behavioral tendencies toward the physician. The congruency between the expected

communion level and the actual ratings of the physician from the participants was positively correlated with the agency congruity. In other words, the participants who thought that the physician they saw in the profile met their expectations on the communion dimension, also thought that the physician met their expectation on the agency dimension. Consistent with the findings from the Social Identity Approach correlational analyses, the two evaluation measures were positively correlated. Both evaluation measures were negatively correlated with the harmful behavioral tendency, which supported the findings in the Social Identity Approach analyses. However, although the two behavioral tendencies were positively correlated, the correlation was weak.

Test of the MIMIC Model. Since not all of the data used in the previous CFA analysis could be used in testing the Role Congruity Theory MIMIC model, a separate

CFA analysis to confirm the EFA results on the behavioral tendency scales, was performed before testing the full MIMIC model. All of the data used in this model were tested for the missing data pattern which showed the non-significant Little’s MCAR test value, Little’s MCAR test χ2 (48) = 28.773, p = .987. Thus, an FIML was used for the missing data estimation. The CFA results were satisfactory, where both facilitative and harmful behavioral tendency CFA models were found to adequately fit the data (i.e., facilitative behavioral tendency: χ2 (5) = 15.258, p = .009, RMSEA = .08, SRMR = .02,

CFI = .99, and TLI = .97; harmful behavioral tendency: χ2 (2) = 1.500, p = .472, RMSEA

= .00, SRMR = .01, CFI = 1.00, and TLI = 1.00).

Then, two separate SEM analyses were performed to test the MIMIC models based on the Role Congruity Theory, one with the outgroup feeling thermometer

evaluation and one with the semantic-differential evaluation measure. The MIMIC model, which used the outgroup feeling thermometer evaluation as the evaluation measure, showed an adequate fitting model, χ2 (72) = 161.174, p < .001, RMSEA = .07,

SRMR = .07, CFI = .93, and TLI = .91. As Figure 18 shows, the agency congruity predicted the outgroup feeling thermometer evaluation, which predicted the harmful behavioral tendency. The model indirect analysis also revealed a significant indirect effect from the agency congruity to the harmful behavioral tendency through the outgroup feeling thermometer evaluation, β = -.08, p = .036. None of the other pathways showed a significant direct or indirect effect in this model.

Figure 18. Tested MIMIC Model based on Role Congruity Theory with outgroup feeling themometer evaluation measure. Similarly, the MIMIC model that used the semantic-differential as its evaluation measure was found to be adequately fitting the data, χ2 (72) = 153.029, p < .001, RMSEA

= .06, SRMR = .07, CFI = .94, and TLI = .92. Here, as Figure 19 shows, only the direct

effect of the semantic-differential evaluation for the harmful behavioral tendency was significant. None of the indirect pathways was significant in this model.

Figure 19. Tested MIMIC Model based on Role Congruity Theory with semantic- differential evaluation measure.

Chapter Six

Discussion

The present study was conducted based on three different theoretical points of view on intergroup relations, as well as stereotyping and prejudice, with the goal of examining the role of the physician social identities on the important elements of the patient-physician relationship, such as patient perceptions, attitudes, emotions, and behavioral tendencies toward physicians. For this study, three statistical models were developed and tested. This section provides a general discussion of the study findings based specifically on each model’s result as well as overall findings of the study. The possibility of developing an integrative theory that focuses on intergroup relations in the health-care settings is also discussed. Finally, the implications and limitations of the study are addressed at the end of the section.

Social Identity Approach

Based on the Social Identity Approach, it was hypothesized that: (1) the pattern of the patient-physician’s crossed categories would predict patient emotions of admiration and disgust toward the physicians, (2) patient admiration and disgust emotions would predict patient evaluations of the physicians, (3) patient evaluation would then predict the behavioral tendencies toward the physicians, and (4) patient evaluation of the physicians would mediate the relationship between patient emotions and the patient behavioral tendencies toward the physicians. A MIMIC model with one structural model and two measurement models (i.e., facilitative behavioral tendency and harmful behavioral tendency) was proposed, with the goal of testing the hypotheses simultaneously.

Additionally, in testing the MIMIC model, two different evaluation measures were used.

One measure was a single-item outgroup feeling thermometer commonly used in intergroup relations research (Turner et al., 2008). The other was a five-item semantic- differential measure of attitudes commonly used in role congruity literature (Eagly et al.,

1991). Therefore, two MIMIC models developed based on the Social Identity Approach were tested.

Hypothesis 1. In general, the patient-physician intergroup relations, based on the

Social Identity Approach’s predictions, were only partially supported. First, as noted above, the approach contents that patient-physician crossed categories would predict patient emotions of admiration and disgust toward the physicians. Contrary to the findings of Pilot Study 2, results from the testing of the MIMIC models suggest that the emotion of disgust did not appear to fit in the context of the patient-physician interaction.

One possible explanation of this finding is due to the different characteristics between the participants in Pilot Study 2 and the participants in the main study. In Pilot Study 2, participants were college-age students (Mage = 20.53 years old), whereas participants in the main study were older (Mage = 36.66 years old). Consequently, participants in the main study might perceive the physicians as more similar to their age than those in Pilot

Study 2. The perceived age similarity between patient and physician has also been previously found to predict an improved patient-physician relationships (Street et al.,

2008), which could also explain the negative correlation between disgust and age found in the main study.

The preliminary analyses also showed that the male participants were more likely than the female participants to feel disgust toward the physicians, who were also male, which indicated that patient-physician gender concordance was not necessarily associated

with an improved patient-physician relationship. This finding was consistent to the previous studies suggesting that male patients felt the most dissatisfied with male providers (Schieber et al., 2014; Schmittdiel et al., 2000).

Nevertheless, disgust did not add to the MIMIC model. It could be because the emotion of disgust is more likely to occur in a context where the outgroup member is suspected of carrying a contagious disease or will contaminate the group moral values

(Cottrell & Neuberg, 2005). Instead of being perceived as a threat, a physician might be perceived as an ‘ally’ to the patient, as they share the same goal: to maintain or improve the patient’s health (Alexander, Brewer, & Herrmann, 1999; Alexander, Brewer, &

Livingston, 2005). The emotion of admiration, on the other hand, is more likely to arise in this medical context, especially if the physician is considered to be an individual who possesses an exceptional ability (Keltner & Haidt, 2003). In sum, to answer the question of whether the crossed category patterns affect emotion, researchers should take into account the specific context where the situation took place and which type of emotion was likely to be aroused in the situation.

Once disgust was removed from the model and leaving only admiration in the equation, the models significantly improved, regardless of which evaluation measure was used. However, it appears that the crossed category patterns did not predict admiration toward the physician in this context which indicated that the participants admired the physician the same way regardless of whether they shared or did not share social identity with the physician. This result did not support the additive model of crossed categorization, which suggests that the double ingroup members would be the most positively evaluated and admired, whereas the double outgroup members would be the

least positively evaluated and least admired, and the partial group members would fall in between (Crisp et al., 2001; Ray et al., 2012). A limiting factor for this additive prediction may be in a situation when the target belongs to a high-status occupation, such as a physician in the context of this study, a point that I will return to later (Heikkila et al., 2015; Hugh et al., 2011; Turner & Nicholson, 2011).

Hypothesis 2. Using only admiration as the type of emotion in the models, the second hypothesis was supported. Admiration did predict patient evaluation of the physician, regardless of which evaluation measure was used. This result supports the assumption that affect predicts attitude, not only in the interpersonal context (Edwards & von Hippel, 1995; Murphy & Zajonc, 1993) but also in intergroup relations (Ray et al.,

2012).

Hypothesis 3. The third hypothesis was also supported. However, it seems as though the multi-item semantic-differential scale as a measure of the evaluation was more capable of capturing the relationship between evaluation and behavioral tendency than the single-item outgroup feeling thermometer measure (Diamantopolous, Sarstedt, Fuchs,

& Wilczynski, 2012). When the semantic-differential scale was used, a more positive evaluation predicted higher facilitative behavior tendency and a lower harmful behavioral tendency. When the outgroup feeling thermometer was used, a more positive evaluation only predicted a lack of harmful behavioral tendency. Regardless, patient evaluation of the physician predicted the two different behavioral tendencies in a way that was consistent with the crossed categorization and intergroup emotions predictions. Here, a more positive evaluation predicted facilitative behavioral tendency, whereas a less

favorable evaluation predicted a harmful behavioral tendency (Dovidio et al., 1996;

Mackie & Smith, 1993).

Hypothesis 4. The last hypothesis based on the Social Identity Approach’s prediction was also supported. Specifically, admiration predicted behavioral tendencies through evaluation, whenever the path between the evaluation and the behavioral tendency existed. Through evaluation, the more the participant admired the physician, the higher the facilitative behavioral tendency and the lower the harmful behavioral tendency, which was in-line with the assumption that admiration triggers action to move toward a group (Mackie & Smith, 2015, 2017; Mackie et al., 2008).

Summary. At least two findings need to be highlighted from testing the Social

Identity Approach’s predictions of the patient-physician intergroup relations. First, it appears that the specific situation that occurred in this study, where the outgroup member could be considered as an ‘ally’ or possessed a prestigious status, was crucial in defining the relationship between the ingroup and outgroup members. Therefore, this finding emphasized the determining factor of the context in the intergroup relations. Second, the fact that the participants and the physicians might share gender or race identity was overshadowed by another type of social identity (i.e., occupation), which was not considered in any of the crossed category groups in the tested model. As a consequence, no difference was found between the crossed categories included in the tested model.

Essentially, these two findings affirmed one of the Social Identity Approach premises that individuals possess multiple social identities and the activation of each of these identities is contextual, based on the individual’s perception of the identity fit and identity accessibility (Brewer, 2007; Hogg & Williams, 2000; Roccas & Brewer, 2002;

Turner et al., 1994). The activation of the specific identity in the particular contextual situation clarifies the perception and direction of the relationship between individuals who belong to different social groups. On a related note, these findings also suggest that improving health care quality may not be as simple as matching a patient’s and a physician’s race identity, as implied by the race-concordance hypothesis (Malat, 2001;

Saha et al., 1999; Saha et al., 2000; Street et al., 2008). Instead, patient expectations and perceptions of the contextual experience may add to the complexity of the patient- physician relationship that will eventually affect the treatment outcome (Vermeire et al.,

2001).

Stereotype Content Model

The hypotheses constructed based on the Stereotype Content Model were: (1) the combination of the physician race/ethnic and gender identities would predict patients perceptions of the physician warmth and competence, (2) the perceptions of the physician warmth and competence would predict patient emotions toward the physicians, (3) patient emotions toward the physicians would predict patient behavioral tendencies toward the physicians, and (4) patient emotions toward the physicians would mediate the relationship between the patient perception of the physician warmth and competence levels and the patient behavioral tendencies toward the physicians. In testing these hypotheses simultaneously, a MIMIC model was developed, but the result showed that this model did not fit the data adequately. In contrast to the assumption that warmth and competence are orthogonal (Kervyn et al., 2013), the physician perceived warmth and competence in this study were strongly correlated to each other. Thus, the correlation

between these two stereotype content dimensions were taken into account in the modified

MIMIC model, which was found to fit the data adequately.

Hypothesis 1. The first hypothesis was supported, but not exactly in the hypothesized direction. Following the assumption that a Black physician is considered a part of the Black professional group (versus the poor Blacks), it was hypothesized that a

Black physician would be placed in the high warmth-high competence quadrant, whereas the White and Asian physicians would be positioned in the low warmth-high competence quadrant (Cuddy et al., 2007). The present study finding did show a significant difference regarding the perceived warmth between the Black and White physicians, but in general, all of the physicians were perceived as highly warm and highly competent across race/ethnicity. Hence, this finding confirmed the superiority of the physician occupational status (Asbrock, 2010; Fiske & Dupree, 2014) over the physician race/ethnicity in the context of patient-physician intergroup relations.

Hypothesis 2. The second hypothesis was partially supported. A higher perception of warmth predicted both higher admiration and envy, whereas a higher perception of competence only predicted admiration. The relations between warmth, competence, and admiration were consistent with the SCM prediction which suggests that high warmth and high competence predict admiration. However, the relations between the two stereotype content dimensions and envy were inconsistent with the SCM theory which suggests that envy is predicted by lack of warmth and high competence (Fiske et al., 1999; Fiske, 2010). This finding was also inconsistent with the previous study finding implying that the physician perceived empathy is a predictor of both the physician perceived warmth and competence (Kraft-Todd et al., 2017). In this circumstance, it is

possible that the target person’s occupation as a physician mattered more to participants than their gender and race/ethnic background, a perception that might trigger jealousy due to the professional success commonly associated with being a physician (Clanton,

2006). Hence, in this case, the context triggered ambivalent emotions manifested in both admiration and envy to the physician, especially when competence is taken out of the context.

Hypothesis 3. The third hypothesis was supported. Cuddy and colleagues (2007,

2008) predicted that admiration elicits both active and passive facilitative behavioral tendencies, whereas envy triggers passive facilitative and active harmful behavioral tendencies. In the present study, it was found that admiration predicted higher facilitative behavioral tendency, whereas envy predicted higher facilitative behavioral tendency and higher harmful behavioral tendency.

Hypothesis 4. The final hypothesis based on the SCM theory was supported.

Findings from the present study showed that emotions did mediate the relationship between warmth and competence with behavioral tendencies. Specifically, both admiration and envy mediated the relationship between warmth and facilitative behavioral tendency, and envy mediated the relationship between warmth and harmful behavioral tendency (Cuddy et al., 2007, 2008). Admiration also mediated the relationship between competence and facilitative behavioral tendency (Cuddy et al.,

2007, 2008). However, since the path between competence and envy was not significant, envy did not mediate the relationship between competence and any of the behavioral tendencies. This result might be due to the measurement of both of the behavioral tendencies in this present study, which were only measured through active behavior items

and did not include the passive behaviors, following the findings from Pilot Study 2 and the BIAS map of the physician based on race/ethnicity and gender (see Figure 4).

Although this is consistent with the previous study findings with BIAS map (Cuddy et al.,

2007), it is interesting to note that envy did mediate the relationship between warmth and the active facilitative behavioral tendencies. These findings highlight the importance of the situational context.

Summary. In general, the predictions of the patient-physician intergroup relations that were constructed based on the SCM premises were mostly supported. For instance, the perception of warmth and competence predicted specific emotion which predicted behavioral tendencies, and the relationships between each dimension of the perception and behavioral tendencies were mediated by emotion. Nevertheless, the participant perceptions of the physician warmth and competence placed all physicians, regardless of their racial/ethnic backgrounds, in the high warmth-high competence quadrant, even though the Black physicians were perceived as warmer than the White physicians. This finding implied that physician differences in terms of race/ethnicity was not the dominant factor for the participants in evaluating the physician traits. Once again, the occupational stereotype of a physician (Asbrock, 2010; Fiske & Dupree, 2014) seemed to dominate over other social identities in this context.

Role Congruity Theory

Finally, based on the Role Congruity Theory, it was hypothesized that: (1) physician race/ethnic and gender identities would affect patient perceptions of the physician-social groups role congruity, (2) the perceived role congruity would then affect patient evaluation of the physician, (3) patient evaluation of the physician would then

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affect patient behavioral tendencies toward the physicians, and (4) the relationship between the patient perception of role congruity and the patient behavioral tendencies would be mediated by patient evaluation of the physicians. Similar to the testing of the

Social Identity Approach’s hypotheses, two MIMIC models based on the Role Congruity

Theory were developed and tested, with each using either the single-item outgroup feeling thermometer or the five-item semantic-differential measure of attitudes as the evaluation measure.

Hypothesis 1. The first hypothesis constructed based on the Role Congruity

Theory to explain the patient-physician intergroup relations was not supported in this study. Based on the previous study, a Black male would be perceived as the least likely to be a physician compared to a White male or an Asian male. Thus, Black male physicians would have the lowest communion and agency role congruity scores compared to the other two physician groups (Koenig & Eagly, 2014). However, findings from the present study showed physician race/ethnicity was not related to role congruity. Once again, the physician occupation seemed to obscure the fact that the physician belonged to a specific social group.

Hypothesis 2. Depending on which evaluation measure was used in the model, the second hypothesis was supported. When the outgroup feeling thermometer was used as the evaluation measure, the agency role congruity, but not the communion role congruity, predicted evaluation. Although both the physician communication ability and competence have previously been reported to be important elements in patient-physician relationship (Kraft-Todd et al., 2017; Paulsel, McCroskey, & Richmond, 2006; Stewart,

1995), this study suggests that the congruity between the stereotypic beliefs and the

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physician agency/competence was deemed as more important for the participants in their general evaluation. When the semantic-differential measure of attitude was used as the evaluation measure, however, none of the role congruity predicted evaluation.

Hypotheses 3 and 4. The third and the fourth hypotheses constructed based on the Role Congruity Theory were mostly exploratory, as no previous study made these specific predictions. However, the findings from the present study seemed to be consistent with the idea that role incongruity produces negative attitude-in-context which leads to contextual discrimination (Eagly & Diekman, 2005). The present study showed that when the relationship between agency role congruity and evaluation existed, the role congruity predicted a harmful behavioral tendency in the opposite trends. In other words, this finding suggests that the agency role incongruity in the patient-physician relationship context was associated with a higher tendency of behaving in harmful ways toward the physician.

Summary. Similar to what was found with the SCM model of the patient- physician intergroup relations, the physician race was not found to be related to role congruity. Regardless of the race, all of the physician communion and agency levels in the study appeared to be congruent with participant expectation of how communal and agentic a physician should be. Nevertheless, findings from this study implied that role incongruity carries negative consequences in intergroup relations (Eagly & Diekman,

2005) was supported. Specifically, the agency role incongruity predicted a harmful behavioral tendency to the physician, suggesting that it is vital for the patients to feel confident about the physician competence in performing their duties.

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The Lack of Race Effect in the Present Study Findings

The inspiration for conducting the present study came from the question related to the race-concordance hypothesis in patient-physician relationship. As discussed previously, race-concordance between patient and physician has been shown to have significant benefits in the patient-physician relationship (Cooper et al., 2003; Cooper &

Powe, 2004; Malat, 2001; Saha et al., 1999; Street et al., 2008). However, the idea that merely matching a patient and physician’s social identities by itself enhances the quality of health care seems too good to be true, especially when minority physicians still experience the negative consequences of targeted prejudice from their colleagues and patients (Beagan, 2003; Nunez-Smith et al., 2007). The pilot study conducted before the present study (i.e., Pilot Study 1) seemed to support this assertion, where the Black physician was found to be positioned at the most disadvantageous situation compared to physicians of other race.

By using the three different theoretical frameworks of intergroup relations and the stereotyping and prejudice, and with a more careful experimental design, the present study was conducted following a similar but more complex procedure as what was used in the Pilot Study 1. Nonetheless, findings from the present study showed a minimal effect of physician race on other variables associated with intergroup relations, such as attitudes, stereotype contents, role congruity, intergroup emotions, and behavioral tendencies. The following section includes possible explanations of this lack of race effect in the present study.

Context Matters. Upon examining the patient-physician intergroup relations using the predictions developed based on Social Identity Approach, Stereotype Content

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Model, and Role Congruity Theory, one aspect stands out: the physician context. Overall, findings of this study showed that in this context, the physician occupation, represented by their profile and attire (which perhaps highlighted its prestigious status within the society) overshadowed the physician social identities (Asbrock, 2010; Brase &

Richmond, 2004; Fiske & Dupree, 2014; Heikkila et al., 2015).

This phenomenon may be explained using image theory which suggests that different contexts trigger different stereotype contents, based on the perceived status equality, power equality, and goal compatibility (Alexander et al., 1999; Alexander et al.,

2005), which is also in-line with the Social Identity Approach’s premise on the identity fit and identity accessibility (Brewer, 2007; Hogg & Williams, 2000; Roccas & Brewer,

2002; Turner et al., 1994). Based on the image theory, an outgroup member would be considered as an ‘ally’ if the perceiver believes that they have equal status, equal power, and compatible goals; if the perceiver believes they have incompatible goals, the outgroup member is either pictured as an enemy (equal status-equal power), a barbarian

(lower status-higher power), a dependent (lower status-lower power), or an imperialist

(higher status-higher power; Alexander et al., 1999; Alexander et al., 2005). It is very likely that the participants in the present study believed the physician had compatible goals with them, that is, to maintain or improve the patient’s health. If the patient and physician relationship was founded based on the idea that they are allies, other elements in the interaction, such as the physician social identities, would matter less in this context.

Instead, the specific situation might trigger the participants to activate their identity as a patient over their other identities (Brewer, 2007; Roccas & Brewer, 2002) and as a

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consequence, chose to cooperate with the physician to achieve their health care goals

(Alexander et al., 1999; Alexander et al., 2005).

Although it is also possible that a physician could be considered as a figure of authority (Brase & Richmond, 2004), it is also possible that in the context of the present study, participants considered the physicians as their ‘ally’ due to their perceived similarity in terms of age (Street et al., 2008). However, from the data collected in this study, participant perceptions of the status and power equality with the physician could not be determined. To address this limitation, future studies should also examine the patient perception of status, power, and goal compatibility between themselves and the physicians. Future studies may also consider including other healthcare providers such as a nurse, physician assistant, nurse practitioner, or medical student as the outgroup member to examine whether the race or another social identity effect is superior to the professional identity when the outgroup member is less of an authority figure than a physician.

The Absence of Threat. Another possible factor that caused the lack of the race effect in the present study is the absence of threat initiated by the stimuli and scenarios used in the experimental design. Participants were only asked to imagine a relatively mundane scenario of evaluating a primary care physician without facing a threat to their health or life in general. Although the first visit experience was slightly unpleasant, it was not threatening. In contrast, the intergroup threat theory suggests that a situation may be perceived as threatening when an individual feels uncertain and unfamiliar with the situation, outnumbered, unsupported, or in a competitive situation with the outgroup member involved in the interaction (Stephan, Ybarra, & Rios, 2016). The threats should

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be perceived by the individual member of the ingroup as either realistic threats, which include actual physical or material harm, or symbolic threats, which include the loss of honor and the challenge to their self-identity or self-esteem (Stephan, Renfro, & Davis,

2008). The perception of threats is found to be important in predicting attitudes, emotions, and perceptions toward outgroup members in the intergroup relations context

(Barden et al., 2004; Cottrell & Neuberg, 2005; Kervyn, Fiske, & Yzerbyt, 2015; Stephan et al., 2016). Moreover, previous findings on race-concordance studies suggested that minority patients were prone to experiencing some forms of symbolic threats as they often felt less respected in race-discordant situation. In fact, physicians from majority race/ethnic group spent less time and showed less positive affect toward the minority patients (Cooper, et al., 2003; Malat, 2001; Schouten & Meeuwesen, 2006). In the present study, however, participants, including those from minority groups, could not experience the immediate reciprocal responses that the physicians would have toward them as the scenario used in the study stimuli was a “one-way street” interaction. Thus, unlike in an actual patient-physician interaction, participants in this study were unable to identify the possible threats during an interaction with a physician. Even though the Pilot

Study 1 findings showed the physician race effect using similar scenario with the present study, future studies should consider creating a scenario that is more threatening in the patient-physician interaction setting, such as including a physician history of negligence in the past or a physician rude behavior during the first visit, to examine whether the race or other types of social identity effect is accentuated when a threatening situation occurs.

The Lack of Choice. Previous studies have found that having a set of choices is associated with treatment efficacy (Geers et al., 2013; McCaffery et al., 2011), especially

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in the cultural setting where choices are valued as opportunity such as in the U.S. (Brown et al., 2015). Unfortunately, in the present study, the privilege of having more than one option of a physician was absent to the participants. Participants were only seeing one profile of a physician during the experiment, and thus, there was no decision-making process involved in the study setting. This limitation could be another reason for the lack of race effect in the present study. Saha and colleagues (1999) found that when choices were present, Black and Hispanic patients preferred to select physicians of the same race/ethnic group. A study conducted at the university student health center and the family physician clinic, where patients often had no liberty of selecting the provider on their own, also showed a minimal effect of the provider race and gender in patient attitudes, perceptions, emotions, and behaviors (Adams et al., 2019).

Thus, future studies should address this limitation by considering to provide options for the participants. For examples, the physician profiles could be altered not only in their race/ethnic background, but also in other aspects such as educational background, reviews, and experience. A software, such as MouseTrace, can be used in this kind of study, so that participant reaction time in the process of decision making while selecting the physician can be tracked (Jasper & Shapiro, 2002). When choices are present, it is possible that participants would have chosen physicians of the same race and those who experience the actual race-discordant situations might have rated their physicians differently, knowing that they could have selected other physicians.

Implications

Integrating the Three Theoretical Views. The three theories used to construct the predictions in the present study differ in their approach of explaining intergroup

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relations and social perceptions. The perception of ingroup and outgroup members’ identity is central in Social Identity Approach, and intergroup relations along with other variables associated with the interaction follows this categorization process that occurs in a specific and immediate context (Brewer, 2010). The Stereotype Content Model, on the other hand, uses the cognitive miser perspective, where group membership of the target, not the perceiver, is the key in the social categorization process that serves as a resource- saving device in social interaction (Fiske, 2004). Alternatively, the Role Congruity

Theory goes beyond the identity-based perception that cues the context or uses general group stereotypes to reduce cognitive load, by taking into account the actual labor division in the society that eventually affects expectations about different groups (Koenig

& Eagly, 2014).

However, findings from the present study seemed to open a possible venue that integrates the three theories into an even larger theoretical point of view that includes all relevant factors together. For example, both the Social Identity Approach and the

Stereotype Content Model include emotion as one of the predictors of behavioral tendencies. In the Social Identity Approach, however, evaluation or attitude mediates the relationship between emotion and behavioral tendencies. In the Stereotype Content

Model, emotion directly predicts behavioral tendencies. As the attitude literature suggests that emotion predicts attitude (Edwards & von Hippel, 1995; Murphy & Zajonc, 1993), it would be intriguing to explore whether attitude also mediates the relationship between emotion and behavioral tendencies within the SCM framework. On the other hand, whether crossed category patterns only directly affect emotion or indirectly affect emotion through perception of warmth and competence remain unexplored.

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Evaluation is also an overlapping variable in both the Social Identity Approach and Role Congruity Theory models. In the Social Identity Approach, evaluation is predicted by emotion; whereas in Role Congruity Theory, evaluation is predicted by role congruity. Hence, it would be intriguing to examine the relations between role congruity and emotion, and whether emotion mediates the relationship between role congruity and evaluation following the affective primacy hypothesis in attitude (Edwards & von Hippel,

1995; Murphy & Zajonc, 1993).

Between the Stereotype Content Model and the Role Congruity Theory, both take into account the importance of warmth/communion and competence/agency. However, while the SCM considers the perception of warmth and competence as the two dimensions of stereotype content, Role Congruity Theory also takes into account the expected level of the communion and agency instead of perceived communion and agency per se. Future research should also aim to investigate which variables are more primary than others in various intergroup settings.

In summary, all of the three theoretical models used in this study were very similar in the back half of the models. The starting point of the models was essentially the only different between the theories in predicting the patient-physician intergroup relations. In order to examine how these theories could be integrated in a more robust but parsimonious way, more research that attempts to translate these theoretical models into other settings is needed. By obtaining a more complete picture of how the theories are translated into different settings, researchers would be able to identify the important variables based on the different theories in predicting intergroup relations in general.

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Practical Implications. Overall, results from the present study conveyed both good news and caution to the medical society. On the one hand, findings from this study showed that, in this paradigm when participants were provided with a physician to evaluate, physicians were admired and regarded as both warm and competent, regardless of their gender and race/ethnic groups. These findings also confirmed the essential need of improving the cultural competence at the other side of the patient-physician intergroup relationships, that is, the physicians themselves, to enhance the quality of health care and minimize health disparity in the society (Boutin-Foster et al., 2008; Flores, 2000;

Michalopoulou et al., 2009; Napoles-Springer et al., 2005; Tucker et al., 2011).

On the other hand, this study also showed that patients are not passive individuals who receive treatment without any expectations (Vermeire et al., 2001), as their perceptions, emotions, and attitudes influence the way they respond to the physicians, both positively and negatively (Hall et al., 2002; Smith & Zimny, 1988). Therefore, it is essential to make sure that the patients are positively perceiving the physicians and are satisfied and happy while receiving care from a provider, so that both parties can maintain a healthy relationship and effective communication for a better quality health care.

Limitations

The present study has several limitations. First, due to the loss of data in the Role

Congruity Theory model analysis, a complete model comparison between the models developed based on the three different theoretical points of view was unable to be performed. The main issue stemmed from the inability to obtain correlation indices between perceptions of physician warmth/communion data collected in part 1 and part 2

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of the present study, due to the constant responses provided by many of the participants.

This problem might occur due to the limited number of items in the measure and that all items were following the same direction (none of them was reverse-coded). Future studies should consider using more items and varying the item directionality for the warmth/communion variable to minimize the possibility of losing too many data due to this issue since the correlation index is crucial for analyzing the model developed based on this theory.

Second, the physician gender used in this study was restricted to male only. Even though it was aimed to control the gender variable, further investigation about whether gender of the physician could affect patient-physician intergroup relations independent of the physician race could not be provided. Therefore, future studies should consider also using female physician profiles to see whether gender is more important than the race/ethnic background of the physician.

Third, the present study also suffered from data loss due to low data quality from

MTurk, in which many of the workers were not based in the U.S. despite the attempt to limit recruitment only for U.S. based workers using TurkPrime panel feature and the use of a two-stage study to reduce character misrepresentation by the MTurk workers

(Wessling, Huber, & Netzer, 2017). Although sufficient number of participants could still be obtained to conduct the main study analysis even after removing those low quality data, having more number of participants would have improved the ability to ensure the sufficient number of participants of each category across the three statistical models.

Thus, future studies should implement various procedures in their surveys, such as using captcha or random questions to filter out automated responses.

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Fourth, as has been discussed in the previous section, there are some limitations concerning the experimental stimuli used in the present study, such as the lack of context variation, threat, and choice. Future studies should at least consider adding more variations related to these three variables in order to obtain a better picture of the patient- physician intergroup relations. Future researchers may also consider varying the information provided in the physician profiles, not only in terms of race but also educational background, gender, and patient written reviews. Since the study was only limited to using three different race/ethnic groups, other minority race/ethnic backgrounds, such as Hispanic/Latino and Native Americans, or foreign-born physicians may also be considered to be added in the future study.

Lastly, the present study only examined the patient immediate attitude and evaluation of the physician. A longitudinal study with patients in the actual clinic where follow-up survey can be conducted could provide more information about how the patient-physician relationship develops through time across patient and physician social identities. Alternatively, a cross-sectional study could be conducted to obtain similar information by comparing the length of the patient-physician relationship.

Overall, despite the limitations, findings from this study have provided important information about patient-physician intergroup relations. More importantly, by examining this phenomenon using three prominent theories in intergroup relations as well as stereotyping and prejudice, this study has furthered our knowledge on how each of these theories explains a real-world intergroup interaction, both in its own way and together as an integrative approach.

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Appendix A

Pilot Study 1 Materials

Stage 1

Instruction: We would like you to evaluate a physician's profile in the following task. Please read the instructions carefully.

Imagine a situation in which you have moved to a new place and you have to select a new primary care physician. You went online to look up a number of physicians in the nearby hospitals. After a thorough search, you saw a physician's profile as shown below.

Please read the profile carefully.

>>RANDOM STIMULUS: (Participants were randomly assigned to see either one of the four physician profiles described in Pilot Study 1 section) Please read the profile carefully. The next tasks will be related to the physician’s profile and you will not be able to go back after this point. If you think you are ready, click continue.

After examining the physician’s profile, please indicate to what extent that you agree to the following statements. 1 = strongly disagree, 5 = strongly agree Preference: 1. How likely is it that you will see this physician?  I will never see this physician.  There is a possibility that I will not see this physician.  I cannot decide whether or not to see this physician.  I will be most likely see this physician.  I will definitely see this physician.

2. I will definitely schedule an appointment with this physician whenever I have health issues. 1 = strongly disagree, 5 = strongly agree

Based on the profile, how is your impression about this person’s characteristics? Using the following scale, please select the number that best represents your ratings. 1 = not at all, 5 = extremely 1. Competent 2. Confident

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3. Independent 4. Competitive 5. Intelligent 6. Tolerant 7. Warm 8. Good natured 9. Sincere

Stage 2 Now imagine that you have decided you need to scheduled appointment with this physician, you went on time at the appointed time to meet him. You waited for 15 minutes in the hospital lobby until a nurse greeted you with a friendly smile and take you to the physician’s office. The nurse examined your height, weight, and blood pressure, then interviewed you about some of your health information and the symptoms that you experienced. This procedure took approximately 15 minutes, then she asked you to wait longer until the physician comes. Twenty minutes after waiting by yourself in the office, the physician finally came along with a resident. He seemed to be in a hurry, and without apologizing for making you waiting so long, he directly asked you to lie down on the bed for an examination. He asked about the symptoms that you have been experiencing and while conducting the examination, he also kept speaking to the resident, explaining about your health condition. He did give you some chances to talk, but you still felt that he did not pay enough attention to what you said and to your questions. The whole meeting with the physician took approximately 9 minutes. At the end of the visit, he ordered a battery of test which includes blood test and chest X-ray. He told you that once he receives the result of these tests, a staff from his office will call you up to schedule the next appointment.

After this visit, please indicate your agreement to the following statements. 1. I will go on to schedule all the tests that the physician ordered for me in order to find out what is really wrong with my health. 2. I will trust his recommendation. 3. I will cooperate to his plan and recommendation. 4. I will definitely argue with him. 5. I will recommend this physician to my family and close friends. 6. I will change to a different physician.

Demographics What is your gender?  Male  Female

How old are you? ______years old.

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What is your race/ethnicity? (select one or more responses)  African American  Asian/Pacific Islander  Caucasian  Hispanic  Arab-American  Other, please specify: ______

How many years have you been in college? ______

What is the highest grade of school your father has completed, or the highest degree your father has received?  No schooling completed, or less than 1 year  Nursery, Kindergarten, or Elementary  High School (grades 9 - 12, no degree)  High School graduate (or equivalent)  Some college  Associate's degree (including occupational or academic degrees)  Bachelor's degree (BA, BS, AB, etc.)  Master's degree (MA, MS, MENG, MSW, etc.)  Professional school degree (MD, DDC, JD, etc.)  Doctorate degree (PhD, EdD, etc.)

What is the highest grade of school your mother has completed, or the highest degree your father has received?  No schooling completed, or less than 1 year  Nursery, Kindergarten, or Elementary  High School (grades 9 - 12, no degree)  High School graduate (or equivalent)  Some college  Associate's degree (including occupational or academic degrees)  Bachelor's degree (BA, BS, AB, etc.)  Master's degree (MA, MS, MENG, MSW, etc.)  Professional school degree (MD, DDC, JD, etc.)  Doctorate degree (PhD, EdD, etc.)

Your religion:  Catholic  Protestant  Islam  Buddhist  Hindu  No religious affiliation  Other, please specify: ______

How religious are you? 1 = not at all, 7 = extremely

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In which type of area did you grow up?  Rural  Suburban  Urban  Other, please specify

Think of the number below as representing a ladder where people stand in society (10=best off, 1=worst off). Some people are better off – they have more money, more education, and better jobs. Other people are worse off – they have less money, less education, and worse jobs. The higher up on the ladder you are, the closer you are to the people at the top and the lower you are, the closer you are to the people at the bottom. Think about yourself. Please select the number to indicate on which rung of the ladder you would place yourself.  10 (best off)  9  8  7  6  5  4  3  2  1 (worst off)

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Appendix B

Pilot Study 2 Materials

In this survey, you will be asked some questions related to your interaction with your own physician, you child's physician, or the physician of a child for whom you act as a guardian. Please read each instruction and question carefully, and take your time while answering the question.

The following questions ask about your feelings/emotions when interacting with a physician.

1. What kind of emotion would you feel towards a physician if you LIKE a physician?  Admiration  Proud  Contempt  Disgust  Pity  Sympathy  Envious  Jealous IS there any other emotions not mentioned above that you would feel towards a physician if you LIKE a physician? Name those emotions:______

2. What kind of emotion would you feel towards a physician if you DISLIKE a physician?  Admiration  Proud  Contempt  Disgust  Pity  Sympathy  Envious  Jealous IS there any other emotions not mentioned above that you would feel towards a physician if you LIKE a physician? Name those emotions:______

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The following questions ask about a specific behavior that you would do as a patient towards the physician based on your perception of the interaction itself.

1. Write one behavior that you would do to a physician when you think that you had a POSITIVE INTERACTION with the physician during the visit. 2. Write one behavior that you would do to a physician when you think that you had a NEGATIVE INTERACTION with the physician during the visit.

How often do you meet a physician in the past one year?  At least once a month  At least once in six months  At least once a year  Never

What kind of physician (what is the specialty of the physician) that you meet most frequently in the past one year? ______

Were you meeting the physician for yourself or for a minor whom you are a guardian?  For myself  For a minor  N/A

If you meet a physician, what do you think is the race/ethnicity of the physician?  White/Caucasian American  Asian/Pacific Islander  Native American  Arab American  African American  Hispanic/Latino  N/A  Other, please specify: ______

How old are you? ______years old.

How many years have you been in college? ______years.

Gender:  Male  Female  Prefer not to answer

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 Other, please specify: ______

Your race/ethnicity (you may select more than one options):  White/Caucasian American  Asian/Pacific Islander  Native American  Arab American  African American  Hispanic/Latino  N/A  Other, please specify: ______

Thank you for your participation in this study.

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Appendix C

Main Study Materials

PART 1 (Personality and Preferences Survey) Demographic Screening Questions (for eligibility to participate in Part 1  participants must be U.S. citizens, OR U.S. permanent residents, OR have been resided in the U.S. for at least 5 years, are currently living in the U.S., AND identified themselves as an American  will be advertised in the MTurk study requirement). Anyone who do not meet the criteria will be considered ineligible. 1. Are a U.S. citizen?  Yes  No 2. Were you born in U.S.?  Yes  No 3. If No, are you a U.S. permanent resident (i.e., green card holder)?  Yes  No 4. If No, have you been residing in the U.S. for at least 5 years?  Yes  continue to survey  No  if 1, 2, 3, 4 No  SORRY, YOU ARE NOT ELIGIBLE TO PARTICIPATE IN THIS STUDY Permanent resident and living in U.S. for at least 5 years:

 What is your nationality? ______ For how many years have you been living in the U.S.? ______years  In what year did you move to the U.S.? (yyyy) All: To what extent do you consider yourself an American?

 I am definitely an American  I am pretty much an American, but not totally  I am neither American nor my original nationality  I am only slightly American  I am definitely not an American  SORRY, YOU ARE NOT ELIGIBLE TO PARTICIPATE IN THIS STUDY Are you currently living in the United States?

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 Yes  No  SORRY, YOU ARE NOT ELIGIBLE TO PARTICIPATE IN THIS STUDY In which state do you currently live in the U.S.? ______In which city do you currently live in the U.S.? ______What is your race/ethnicity?

 Caucasian/European American  Black/African American  Asian American o Chinese o Japanese o Korean o Thai o Indian o Filipino o Pakistani o Indonesian o Vietnamese o Other, please specify: ______ Pacific Islander  Arab/Middle Eastern  Hispanic/Latinx(a,o)  Native American  Other, specify: ______

Now, you will be directed to the survey.

--- CONSENT FORM ---

Please enter your MTurk worker ID number in the box below. ______Please make sure that you enter the correct MTurk worker ID. This is a very crucial part in this study. Failure to provide a correct MTurk worker ID will result in rejection of work.

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QUESTIONNAIRES (Order of questionnaires and items were randomized) Stereotypic Beliefs toward Race Groups and Occupations Instructions: Think about members of the race/ethnic groups below. In general, what are your impressions toward the members of each of the race/groups below?

Using the options provided below (not at all/slightly/moderately/very/extremely), please select one that best represents your impressions toward members of each of the race/groups in general.

Not at all Slightly Moderately Very Extremely Caucasian/ Kind      European Nurturing      American Sincere      Warm      Capable      Skillful      Competent      Ambitious      Dominant      Assertive      Intelligent      Daring      Asian American Kind      Nurturing      Sincere      Warm     

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Capable      Skillful      Competent      Ambitious      Dominant      Assertive      Intelligent      Daring      Black/African Kind      American Nurturing      Sincere      Warm      Capable      Skillful      Competent      Ambitious      Dominant      Assertive      Intelligent      Daring      Hispanic/ Kind      Latino(a) Nurturing      American Sincere      Warm      Capable      Skillful      Competent     

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Ambitious      Dominant      Assertive      Intelligent      Daring      Native Kind      American Nurturing      Sincere      Warm      Capable      Skillful      Competent      Ambitious      Dominant      Assertive      Intelligent      Daring     

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Instructions: Think about who work in different types of occupation. In general, what are your impressions toward people who work in each type of the occupations below? Using the options provided below (not at all/slightly/moderately/very/extremely), please select one that best represents your impressions toward people who work in each type of occupations below in general.

Not at all Slightly Moderately Very Extremely Teacher Kind      Nurturing      Sincere      Warm      Capable      Skillful      Competent      Ambitious      Dominant      Assertive      Intelligent      Daring      Construction Kind      Workers Nurturing      Sincere      Warm      Capable      Skillful      Competent     

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Ambitious      Dominant      Assertive      Intelligent      Daring      Medical Kind      Doctors Nurturing      Sincere      Warm      Capable      Skillful      Competent      Ambitious      Dominant      Assertive      Intelligent      Daring      Businessmen/ Kind      women Nurturing      Sincere      Warm      Capable      Skillful      Competent      Ambitious      Dominant      Assertive     

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Intelligent      Daring      Politicians Kind      Nurturing      Sincere      Warm      Capable      Skillful      Competent      Ambitious      Dominant      Assertive      Intelligent      Daring     

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Identity Importance Instructions: Below is a list of different categories that we encounter in our daily life. Please rank these social categories that you think is the most important to the least important to you as an individual, using numbers from 1 (most important) to 10 (least important). For example, if you think that being an adult (age) is the most important thing for you, then you should type “1” inside the box that is provided next to the “age” category; on the same note, if you think that being a member of a sports team is the least important to you, then type “10” inside the box that is provided next to the “sports team member” category. Age (e.g., young adult, old adult) ______Political belief (e.g., conservative, moderate, liberal) ______Nationality (e.g., American, Canadian) ______Occupation (e.g., teacher, researcher, doctor) ______Gender (e.g., men, women) ______Race/ethnic group (e.g., White, Asian, Black, Hispanic) ______Socio-economic status (e.g., upper-class, middle-class) ______Living area (e.g., urban, rural) ______Education status (e.g., high school graduate, college student) ______Spiritual belief (e.g., Christian, Jew, Muslim, Agnostic, Atheist) ______Using the scale provided below (1=not important at all, 9=extremely), please select the option that best represents your response for each statement. How important is your nationality to you? How important is your race/ethnic group to you? How important is your gender identity to you? How important is your age to you?

Identification Instructions: Using the scale provided below (1=not at all, 9=very much), please select the option that best represents your response for each statement. 1. In terms of general attitudes and beliefs, I feel similar to other people of the same nationality.

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2. In terms of general attitudes and beliefs, I feel similar to other people of the same race/ethnicity. 3. In terms of general attitudes and beliefs, I feel similar to other people of the same gender. 4. I feel a sense of belonging with other people of the same nationality. 5. I feel a sense of belonging with other people of the same race/ethnicity. 6. I feel a sense of belonging with other people of the same gender. 7. In general, I think I would like other people of the same nationality. 8. In general, I think I would like other people of the same race/ethnicity. 9. In general, I think I would like other people of the same gender.

Quick Discrimination Index Using the options provided below (1=strongly disagree to 5=strongly agree), please select one that best represents your response to each statement. 1. I do think it is more appropriate for the mother of a newborn baby, rather than the father, to stay at home with the baby (not work) during the first year. 2. It is as easy for women to succeed in business as it is for men. 3. I really think affirmative action programs on college campuses constitute reverse discrimination. 4. I feel I could develop an intimate relationship with someone from a different race. 5. All Americans should learn to speak two languages. 6. It upsets (or angers) me that a woman has never been President of the United States. 7. Generally speaking, men work harder than women. 8. My friendship network is very racially mixed. 9. I am against affirmative action programs in business. 10. Generally, men seem less concerned with building relationships that women. 11. I would feel O.K. about my son or daughter dating someone from a different racial group. 12. In the past few years there has been too much attention directed toward multicultural or minority issues in education. 13. I think feminist perspectives should be an integral part of the higher education curriculum. 14. Most of my close friends are from my own racial group. 15. I feel somewhat more secure that a man rather than a woman is currently president of the United States. 16. I think that it is (or would be) important for my children to attend schools that are racially mixed.

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17. In the past few years there has been too much attention directed toward multicultural or minority issues in business. 18. Overall, I think racial minorities in America complain too much about racial discrimination. 19. I feel (or would feel) very comfortable having a woman as my primary physician. 20. I think the president of the United States should make a concerted effort to appoint more women and racial minorities to the country’s Supreme Court. 21. I think White people’s racism toward racial minority groups still constitutes a major problem in America. 22. I think the school system, from elementary school through college, should encourage minority and immigrant children to learn and fully adopt traditional American values. 23. If I were to adopt a child, I would be happy to adopt a child of any race. 24. I think there is as much female physical violence toward men as there is male violence toward women. 25. I think the school system, from elementary school through college, should promote values representative of diverse cultures. 26. I believe that reading the autobiography of Malcolm X would be of value. 27. I would enjoy living in a neighborhood consisting of a racially diverse population (i.e., African American, Asian American, Hispanic, White). 28. I think it is better if people marry within their own race. 29. Women make too big of deal out of sexual harassment issues in the workplace.

Need for Cognition Scale Instructions: For each of the statements below, please indicate to what extent the statement is characteristic of you. If the statement is extremely uncharacteristic of you (not at all like you) please write a "1" to the left of the question; if the statement is extremely characteristic of you (very much like you) please write a "5" next to the question. Of course, a statement may be neither extremely uncharacteristic nor extremely characteristic of you; if so, please use the number in the middle of the scale that describes the best fit. Please keep the following scale in mind as you rate each of the statements below: 1 = extremely uncharacteristic; 2 = somewhat uncharacteristic; 3 = uncertain; 4 = somewhat characteristic; 5 = extremely characteristic. 1. I would prefer complex to simple problems. 2. I like to have the responsibility of handling a situation that requires a lot of thinking. 3. Thinking is not my idea of fun. 4. I would rather do something that requires little thought than something that is sure to

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challenge my thinking abilities?

5. I try to anticipate and avoid situations where there is a likely chance I will have to think in-depth about something. 6. I find satisfaction in deliberating hard and for long hours. 7. I only think as hard as 1 have to. 8. I prefer to think about small, daily projects to long-term ones? 9. I like tasks that require little thought once I've learned them? 10. The idea of relying on thought to make my way to the top appeals to me. 1 I. I really enjoy a task that involves coming up with new solutions to problems. 12. Learning new ways to think doesn't excite me very much? 13. I prefer my life to be filled with puzzles that I must solve. 14. The notion of thinking abstractly is appealing to me. 15. I would prefer a task that is intellectual, difficult, and important to one that is somewhat important but does not require much thought. 16. 1 feel relief rather than satisfaction after completing a task that required a lot of mental effort? 17. It's enough for me that something gets the job done; I don't care how or why it works? 18. I usually end up deliberating about issues even when they do not affect me personally.

Demographic Questions Gender:

 Male  Female  Prefer not to say  Other: Age: ______years old. Occupations: ______If students, major: ______

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What is your race/ethnicity?  White/Caucasian  Black/African American  Middle Eastern (e.g., Lebanese, Egyptian, Iraqi)  South Asian (e.g.,  East Asian (e.g.,  South-East Asian Indian, Pakistani, Chinese, Japanese, (e.g., Thai, Bangladeshi, Sri Korean, Hong Kong, Vietnamese, Lankan, Nepali) Taiwanese) Filipino(a), Indonesian)  Hispanic/Latino(a,x)  Other: ______

Are you a U.S. citizen?

 Yes  No If NO: Are you a U.S. permanent resident (i.e., green card holder)?

 Yes  No If NO: What is your nationality? ______Are you a native English speaker?

 Yes  No If NO: What is your native language? ______Did you have any problems understanding any parts of the survey?

 Yes, which part? ______ No Are you currently living in the U.S.?

 Yes, in which state? ______ No Which one represents your political ideology?

 Conservative  Liberal  Moderate

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 Other: ______Your educational background:

 Less than high-school  High school graduate  Some college  Undergraduate  Master’s degree  Doctoral degree  Other: ______Did your mother go to college?

 Yes  No Did your father go to college?

 Yes  No

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Now, think of the numbers below as a ladder representing where people stand in society. Some people are better off – they have more money, more education, and better jobs. Other people are worse off – they have less money, less education, and worse jobs. The higher up on the ladder you are, the closer you are to the people at the top and the lower you are, the closer you are to the people at the bottom. Think about yourself. Please select a number to indicate on which rung of the ladder you would place yourself.

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PART 2 (Study about Interactions in Health Setting)

Only participants from Part 1 who identify themselves as Caucasian, Asian, or Black Americans WERE INVITED to participate in the main study. Instructions: We would like you to evaluate a physician's profile in the following task. Please read the instructions carefully.

Imagine a situation in which you have moved to a new place and you have to find a new primary care physician. You went online to look up a number of physicians in the nearby hospitals. After a thorough search, you saw a physician's profile as shown in the next page.

Please read the physician's profile carefully. You will be asked to review the profile right after you see the profile in the following page.

>>RANDOM STIMULUS: (Participants were randomly assigned to see either one of the nine physician profiles described in the Experimental Stimuli: Physician Profiles section)

Have you done reading through the profile? If not, please review the profile again. The next tasks will be related to the physician's profile and you will not be able to go back after this point. If you think you are ready, proceed to the next page.

Next, you will be asked a variety of questions about the physician's profile. Please respond to each question based on your initial impressions toward the physician.

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QUESTIONNAIRES (Order of questionnaires and items are randomized) Perceptions: Based on the profile, how is your impression about this physician’s character? Using the options provided below (not at all/slightly/moderately/very/extremely), please select one that best represents your impressions toward the physician whose profile you just read.

Not at all Slightly Moderately Very Extremely Kind      Nurturing      Sincere      Warm      Capable      Skillful      Competent      Ambitious      Dominant      Assertive      Intelligent      Daring     

Emotions: How do you feel toward this physician? Using the options provided below (not at all/slightly/moderately/very/extremely), please select one that best represents your feelings/emotions toward the physician whose profile you have just read.

Not at all Slightly Moderately Very Extremely Admire      Happy      Sympathy      Proud      Pity      Afraid      Envious      Angry     

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Not at all Slightly Moderately Very Extremely Satisfied      Uneasy      Jealous      Disgust      Irritated      Hopeful      Contempt      Grateful      Respectful      Guilty     

Evaluation 1 – Outgroup Feeling Thermometer Below you will see something that looks like a thermometer. We would like you to use the thermometer to indicate your overall attitude towards the physician whose profile you have just seen. If you have a favorable attitude towards this physician, you would give him a score somewhere between 50° and 100°, depending on how favorable you are toward this physician. If you have an unfavorable attitude towards this physician, you would give him a score somewhere between 0° and 50°, depending on how unfavorable you are toward this physician. However, you are not restricted to the numbers indicated -- feel free to use any number between 0° and 100°. Please be honest.

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Evaluation 2 – Semantic Differential Measure of Attitudes Using the scale below, please indicate what you think about this physician. -3 -2 -1 0 1 2 3 Bad Good Negative Positive Useless Valuable Unpleasant Pleasant Awful Nice

Next Step: First Visit

Now imagine that you have decided you need to schedule an appointment with this physician, you went on time at the appointed time to meet him. You waited for 15 minutes in the hospital lobby until a nurse greeted you with a friendly smile and take you to the physician’s office. The nurse examined your height, weight, and blood pressure, then interviewed you about some of your health information and the symptoms that you experienced. This procedure took approximately 15 minutes, then she asked you to wait longer until the physician comes.

Twenty minutes after waiting by yourself in the office, the physician finally came along with a resident. He seemed to be in a hurry, and without apologizing for making you waiting so long, he directly asked you to lie down on the bed for an examination.

He asked about the symptoms that you have been experiencing and while conducting the examination, he also kept speaking to the resident, explaining about your health condition. He did give you some chances to talk, but you still felt that he did not pay enough attention to what you said and to your questions.

The whole meeting with the physician took approximately 9 minutes. At the end of the visit, he ordered a battery of test which includes blood test and chest X-ray. He told you that once he receives the result of these tests, a staff from his office will call you up to schedule the next appointment.

Please make sure that you have read through the above scenario before continuing to the next page. Click continue when you're ready and after the arrow button reappears in this page to proceed to the next page.

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Behavioral Tendencies: (order of the items were randomized) Please indicate your agreement to the following statements

After this visit, I would …………………………. Strongly Disagree Uncertain Agree Strongly disagree agree thank him for his time.      compliment him.      show appreciation toward him.      smile and show positivity toward him.      make a conversation with him beyond my health      issue. try to crack jokes.      return to this physician for next appointment.      trust this physician.      make sure I keep this physician as my primary      care provider. leave a good comment about him.      recommend this physician to my family and      friends. write a positive review about him.      ask for another physician.      not return back for another appointment.      avoid this physician.      show my anger during the visit.     

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act rude towards this physician.      argue with this physician.      write a complaint about him.      speak to the clinic director to complain about      him. tell the clinic staff that I dislike this physician.      write a bad review about him.      not recommend this physician to anyone.      warn anyone who considers making appointment      with this physician.

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Intergroup Contact Questionnaire 1. How many friends do you have who are not of the same race/ethnicity as you? a. None b. One c. Two to five d. Five to ten e. Over ten 2. How often do you spend time with people who are not of the same race/ethnicity as you? a. Never b. Occasionally c. Sometimes d. Quite a lot e. All the time 3. How many people of the same race/ethnicity as you do you know who have friends of other race/ethnicity? a. None b. One c. Two to five d. Five to ten e. Over ten 4. Do you have any account in social media, such as Facebook, Twitter, Instagram, etc.? a. Yes b. No 5. How many friends do you have in your social media account(s) who are not of the same race/ethnicity as you? a. None b. One c. Two to five d. Five to ten e. Over ten 6. How often are you exposed to people of other race/ethnicity -- directly (e.g., having friendship and direct meeting) and indirectly (e.g., media, books, internet, etc.) -- ? a. Never b. Occasionally c. Sometimes d. Quite a lot e. All the time

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7. Overall, how would you rate your contact experience with people of other race/ethnicity? (1= Extremely negative, 5 = Extremely positive

Manipulation Checks

Please answer the questions below based on the physician profile that you saw at the beginning of the survey. What was the gender of the physician?

 Male  Female  Not sure How old was the physician?

 Between 30 to 45 years old  Between 46 to 60 years old  Above 60 years old What do you think was the race/ethnicity of the physician?

 Asian American  Black/African American  White/Caucasian American  Hispanic/Latino(a,x)  Other: ______What was the physician’s name?

 David Miller  David Smith  David Wang  David Wilson

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Demographic Questions

Gender:

 Male  Female  Prefer not to say  Other: Age: ______years old. Occupations: ______If students, major: ______What is your race/ethnicity?  White/Caucasian  Black/African American  Middle Eastern (e.g., Lebanese, Egyptian, Iraqi)  South Asian (e.g.,  East Asian (e.g.,  South-East Asian Indian, Pakistani, Chinese, Japanese, (e.g., Thai, Bangladeshi, Sri Korean, Hong Kong, Vietnamese, Lankan, Nepali) Taiwanese) Filipino(a), Indonesian)  Hispanic/Latino(a,x)  Other: ______

Are you a U.S. citizen?

 Yes  No If NO: Are you a U.S. permanent resident (i.e., green card holder)?

 Yes  No If NO: What is your nationality? ______Are you a native English speaker?

 Yes  No If NO: What is your native language? ______

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Did you have any problems understanding any parts of the survey?

 Yes, which part? ______ No Are you currently living in the U.S.?

 Yes, in which state? ______ No Your educational background:

 Less than high-school  High school graduate  Some college  Undergraduate  Master’s degree  Doctoral degree  Other: ______Did your mother go to college?

 Yes  No Did your father go to college?

 Yes  No

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

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Debriefing Statement: Study about Interactions in Health Setting

The purpose of the study today is to explore how physician characteristics may affect patients’ impressions and perceptions toward the physician. In the first section of this study, we asked you to see a profile of a physician who belongs to a specific social group. The goal of this part of the study was to examine your impressions toward the physician who is associated with a specific social group. Then, we asked you to imagine an interaction with the physician at the first visit and respond to several questions that measure your behavioral tendencies toward the physician Some of the responses that you provided to us today in this study will be linked to the responses you have provided earlier through the "Personality and Preferences Survey" that you completed prior to this study. This will allow us to examine whether some of your personal characteristics are associated with the responses you provided today while evaluating the physician who belongs to a certain social group. All the information we collected in today’s study will be confidential, and there will be no way of identifying your responses in the data archive. We are not interested in any one individual’s responses; we want to look at the general patterns that emerge when the data are aggregated together. Your participation today is appreciated. We ask that you do not discuss the nature of the study with others who may later participate in it, as this could affect the validity of our research conclusions. If you have any questions or concerns about the study right now, please take some time to discuss them with the researcher running the study session today. Further, you are welcome to talk to Yopina Pertiwi (yopina.pertiwi(at)rockets.utoledo.edu) or Prof. Andrew Geers, of the University of Toledo Psychology Department who are overseeing this study.

Thank you again for your participation.

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Appendix D

Consent Forms

Department of Psychology Mail Stop #903, 2801 W. Bancroft St. Toledo, Ohio 43606 Phone: 419-530-2508 Fax: 419-530-8402

ADULT RESEARCH SUBJECT - INFORMED CONSENT FORM (Personality and Preferences Survey)

Principal Investigator: Andrew Geers, Prof., 419-530-8530 Yopina Pertiwi, 419-530-4005

Purpose: You are invited to participate in the research project entitled, Personality and Preferences Survey which is being conducted at the University of Toledo under the direction of Prof. Andrew Geers and Yopina Pertiwi, M.A. The purpose of this study is to learn about personality, preferences, and opinions about different groups and types of occupations. For example, in one of the sections of the survey, you will be asked to rate how kind a salesperson is in general. In another section, you will be asked to rate how importance is your nationality to you.

Description of Procedures: This research study will be conducted using an online survey through Qualtrics survey platform and will take approximately 30 minutes to complete the study. You will be asked to complete several questionnaires related to your personal characteristics and opinions. In some cases, you may be invited to participate in another study.

Potential Risks: There are minimal risks to participation in this study, including loss of confidentiality.

Potential Benefits: The only direct benefit to you if you participate in this research may be that you will learn about how psychological study are run. Others may benefit by learning about the results of this research. You will also receive $.50 monetary reward for participating in this study.

Confidentiality: The researchers will make every effort to prevent anyone who is not on the research team from knowing that you provided this information, or what that information is. There is no part of the survey that will ask you to provide your names or any other identifying information. Your responses to the survey will be presented to others only when combined with other responses. However, although we will make every effort to protect your confidentiality, there is a low risk that this might be breached.

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Voluntary Participation: Your refusal to participate in this study will involve no penalty or loss of benefits to which you are otherwise entitled. In addition, you may discontinue participation at any time without any penalty or loss of benefits.

Contact Information: Before you decide to accept this invitation to take part in this study, you may ask any questions that you might have. If you have any questions at any time before, during or after your participation you should contact a member of the research team (Yopina Pertiwi, 419-530-4005, Prof. Andrew Geers, 419-530-8530).

THE UNIVERSITY OF TOLEDO SOCIAL, BEHAVIORAL & EDUCATIONAL INSTITUTIONAL REVIEW BOARD

The research project described in this consent has been reviewed and approved by the University of Toledo SBE IRB for the period of time specified below. {Fill in the appropriate information after approval has been granted} SBE IRB #: Number of Subjects: Project Start Date: Project Expiration Date:

By clicking on to the next page and beginning the survey, you are stating that you have read and accept the information above and are giving your consent to participate in this research. You are also confirming that you are 18 years old or over.

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Department of Psychology Mail Stop #903, 2801 W. Bancroft St. Toledo, Ohio 43606 Phone: 419-530-2508 Fax: 419-530-8402

ADULT RESEARCH SUBJECT - INFORMED CONSENT FORM (Study about Interactions in Health Setting)

Principal Investigator: Andrew Geers, Prof., 419-530-8530 Yopina Pertiwi, 419-530-4005

Purpose: You are invited to participate in the research project entitled, Study about Interactions in Health Setting which is being conducted at the University of Toledo under the direction of Dr. Andrew Geers and Yopina Pertiwi, M.A. The purpose of this study is to examine the judgment and decision making processes in a health setting.

Description of Procedures: This research study will be conducted using an online survey through Qualtrics survey platform and will take approximately 30 minutes to complete the study. You will be asked to evaluate a physician profile and making a judgment based on the profile. At the end of the survey, you will read a debriefing statement about the data, theory and research area under study

Potential Risks: There are minimal risks to participation in this study, including loss of confidentiality.

Potential Benefits: The only direct benefit to you if you participate in this research may be that you will learn about how psychological study are run. Others may benefit by learning about the results of this research. You will also receive $1.00 monetary reward for participating in this study.

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