Race and Stereotypes Matter When You Ask About Conduct Problems: Implications for Violence Risk Assessment in Juvenile Justice Settings

Abstract

We examined the impact of stigma priming on self-reported severe conduct problems in two studies conducted with African American adolescents involved in the juvenile justice system. Data-collection interviews were conducted in a secure detention setting following arrest. In Study 1 (N = 193), stigma was primed by manipulating the ordering of surveys. Adolescents who completed a questionnaire about racial identity attitudes prior to questions about severe conduct reported substantively more problematic behaviors than control group peers (β = 0.43). In Study 2 (N = 264), stigma was primed by manipulating whether adolescents were interviewed by an African American or European American mental health professional. Racial group membership of the interviewer did not have a substantial effect on self-reported conduct problems (β = −0.04). Although the studies were not without limitations, they highlight the need for more research on the degree to which interview methods and context influence self-reported severe conduct behavior in forensic settings.

Keywords

African American adolescents racial identity stereotype threat stigma priming violence risk assessments

Negative stereotypes of African Americans that were crystallized when slavery was legal in the United States are reflected in contemporary racism (Altman, 1997; Cokley & Vandiver, 2012), and exemplified in the extant literature on unconscious bias (e.g., Dovidio & Gaertner, 2000) and stereotype threat (Steele & Aronson, 1995). They are also reflected in negative stereotypes that some African Americans hold about themselves (Worrell, Vandiver, Schaefer, Cross, & Fhagen-Smith, 2006). Based on these findings, we examined the degree to which stigma shapes responses to questions about severe conduct problems posed to African American youth involved in the juvenile justice system. The guiding hypothesis is that the priming of stigma and negative stereotypes will affect responding in psychological evaluations (Steele & Aronson, 1995).

The influence of stereotypes on self-reported conduct problems may be particularly salient in violence risk assessments. These types of evaluations include an examination of potentially criminal behaviors, and resulting risk estimates are used to inform high stakes judicial decisions. For example, “triers of fact” (i.e., judges) use risk estimates as a basis for decisions such as the need for pre- and posttrial secure detention, secure rehabilitation, and the extension of juvenile court custody beyond the maximum age (Grisso, 1998/2013). If adjudication is overly restrictive relative to a youth’s actual level of risk, the probability of an unfavorable developmental outcome increases (e.g., conviction as an adult; Andrews & Dowden, 2007; Petitclerc, Gatti, Vitaro, & Tremblay, 2013).

These data are of particular import to African Americans, as this group is most likely to receive overly restrictive sanctions. African Americans are twice as likely as European Americans to be rated as a high risk for future violence (Angwin, Larson, Mattu, & Kirchner, 2016) and are disproportionately sanctioned with high-intensity interventions in the juvenile courts (C. A. Mallett & Stoddard-Dare, 2010). For these reasons, considering sources of error in violence risk assessments among African Americans is prudent, and scrutinizing methods of soliciting self-reported criminal behavior provides one such opportunity. We briefly review the use of self-reported conduct problems in violence risk assessments and the role of racial identity in stigma priming before introducing the first study.

Self-Reported Conduct Problems in Violence Risk Assessments

Best practices in violence risk assessments incorporate multiple methods of data collection. Although unstructured, clinical interviews with adolescents yield some information that is pertinent to risk estimates, structured and standardized assessments have also been shown to be useful (Hoge & Andrews, 2010). Because few standardized assessments were specifically developed with the intention of providing an index of future harm to others, psychologists often employ personality tests (e.g., the Psychopathy Checklist–Youth Version [PCL-YV]; Forth, Kosson, & Hare, 2003), standardized interview schedules (e.g., the Diagnostic Interview Schedule for Children; Schwab-Stone et al., 1993), and standardized rating and checklist measures (e.g., the Conners Comprehensive Behavior Rating Scales [CBRS]; Conners, 2008) in their evaluation procedures. Of all the data used in violence risk assessment, it can be argued that none have as much influence on a relative risk estimate as a youth’s endorsement of criminal behaviors (Grisso, 1998/2013).

Indeed, risk instruments as well as broader psychological assessments used in the evaluation of violence risk, all include items that require youth to endorse or deny involvement in serious criminal activity. Here are some paraphrased examples of questions from the PCL-YV, the CBRS-Self Report, the Structured Assessment of Violence Risk in Youth (SAVRY; Borum, Bartel, & Forth, 2006), and the Youth Level of Service/Case Management Inventory (Hoge & Andrews, 2011): Do you threaten others often? Have you ever gotten in trouble with the police? Do you enjoy breaking the law? Have you mugged someone? Do you break into houses, cars, or buildings? Have you threatened anyone with a weapon? These types of questions about criminal involvement are commonly used in estimating violence risk, but the content of the questions also reflects societal stereotypes of African Americans as criminals (e.g., Vandiver, Fhagen-Smith, Cokley, Cross, & Worrell, 2001). For that reason, responses to these questions may be affected by stereotype avoidance (Steele & Aronson, 1995). In order to test this hypothesis, we set the stage with discussions of stereotypes, the activation of stereotypes (i.e., stigma priming and stereotype threat), and both the effect of activating stereotypes on self-reported behaviors as well as the mechanisms for doing so (e.g., manipulation of question order and race of the evaluator).

Characterization of African Americans as Criminals

The characterization of the African American as criminal has been a societal archetype since the enslavement of Africans in colonial America (Kennedy, 1997). However, it was the post–Civil Rights rebranding of young African American males as criminal predators that led to the mass overincarceration of this group (Mauer, 1997). By the 1990s, majorities of both African Americans and European Americans perceived the former as aggressive and violent (Sniderman & Piazza, 1993), and 80% of African Americans believed they were perceived as criminals by European Americans during this period (Sigelman & Tuch, 1997). The overestimation of African American involvement in violent crime has continued into the 21st century (e.g., Chiricos, Welch, & Gertz, 2004).

To a large extent, the image of the African American as criminal can be credited to the disproportionate portrayal of African Americans as perpetrators in television news (Chiricos & Eschholz, 2002; Dixon & Linz, 2000) and news magazines, including Time and Newsweek (Barlow, 1998). Dixon and Linz (2000) showed that African Americans accounted for 21% of actual arrests in Orange County, CA, but made up 36% of arrests broadcast on the local news between 1995 and 1997. In a similar study, Dixon and Azocar (2006) reported that African American adolescents accounted for only 18% of arrests, but 39% of perpetrator news stories in Los Angeles. The portrayal of negative African American stereotypes in entertainment programs is another popular cultural trend (Graves, 1999; Lichter, Lichter, Rothman, & Amundson, 1987), most recently manifested in reality TV (Tyree, 2011), although it should be noted that depictions of African Americans in both character-driven TV shows (Monk-Turner, Heiserman, & Johnson, 2010) and prime time commercials (Mastro & Stern, 2003) have improved over the past decade.

Unfortunately, some American TV viewers appraise positive portrayals of African Americans as fictitious and negative portrayals as authentic (Punyanunt-Carter, 2008). For these reasons, posing questions about severe conduct behaviors to African Americans is akin to asking them whether or not they engage in the behaviors that are perceived as common stereotypes of their group. How African Americans respond to such questions might be shaped by the degree to which they endorse negative stereotypes, and whether or not negative stereotypes are on their minds at the time of questioning. To organize an experiment aimed at answering this important question, we turn to the racial identity and priming literatures.

Racial Identity Attitudes, Problem Behaviors, and Stigma Priming

Cross’s (1971; Cross & Vandiver 2001) nigrescence theory is one of the most frequently cited models of Black racial identity. The expanded nigrescence model (NT-E; Cross & Vandiver, 2001), which is the most recent iteration of the theory postulates that African Americans hold several different racial identity attitudes to some degree. Assimilation attitudes focus on national rather than ethnic-racial identification. Miseducation attitudes reflect the endorsement of negative stereotypes, and self-hatred attitudes are negative feelings about being African American. Anti-White attitudes are strong negative emotional responses to the dominant group. Afrocentric attitudes reflect the belief that African Americans should live by historical Black principles, and multiculturalist inclusive attitudes indicate African American self-acceptance alongside an acceptance of all cultures. NT-E is operationalized with the Cross Racial Identity Scale (CRIS; Vandiver et al., 2000).

Worrell, Andretta, and Woodland (2014) administered the CRIS during forensic mental health screenings in a sample of 477 African American youth and identified five racial identity profiles: (a) Conflicted-Self-Hatred, marked by juxtaposed prominence of both Afrocentric and self-hating attitudes; (b) Multiculturalist, reflecting an acceptance of self and other cultures; (c) Low Race Salience, characterized by low scores across all six subscales indicating little attention to race; (d) Conflicted Anti-White, categorized by elevated self-hatred, anti-White, and Afrocentric attitudes; and (e) Miseducation-Pro-Black, reflecting the endorsement of both negative stereotypes of African Americans (miseducation) and Black self-acceptance (Afrocentric attitudes). Comparisons across profiles showed that adolescents with Conflicted-Self-Hatred profiles self-reported substantially higher levels of depression, anxiety, and obsessive-compulsive behaviors on the CBRS Self-Report (CBRS-SR; Conners, 2008) than peers with Multiculturalist and Low Race Salience profiles. In this study, more than 50% of the sample had racial identity profiles marked by the endorsement of negative stereotypes.

In the present study, we hypothesized that administration of the CRIS prior to asking risk assessment questions would prime negative stereotypes and affect subsequent response patterns about involvement in severe conduct behaviors. The CRIS includes five items that require respondents to appraise deleterious stereotypes about African Americans (e.g., African Americans are too quick to turn to crime, . . . too many Blacks “glamorize”/idealize the drug trade, . . . etc.) and indicate the degree to which they endorse the stereotypes. We contend that the process of responding to these negative stereotypes will make them salient for respondents and affect their responses to subsequent questions about personal involvement in behaviors that are representative of negative stereotypes about African Americans (e.g., use of a weapon, breaking and entering, gang membership). These hypotheses are in keeping with the behavioral priming literature, which we review next.

In one of the first studies on behavioral priming, Bargh, Chen, and Burrows (1996) showed that priming can shape behavior. Specifically, young adults (race and ethnicity unknown) who were exposed to rude words in a word scrambling game (e.g., intrude) were subsequently more likely to present with rude behavior (e.g., interrupt a conversation). Stigma priming refers to an event that activates or makes salient a negative stereotype specific to an individual’s demographic group (e.g., gender, race/ethnicity, sexual orientation). Stigma priming has been shown to have an adverse effect in stigmatized populations, including impairments in cognitive functioning, business acumen, and feelings of belonging in school (Mello, Mallett, Andretta, & Worrell, 2012; Stone, Harrison, & Mottley, 2012; Tellhed & Björklund, 2011). Stigma priming has also been shown to increase in-group identification, perceived discrimination, and the degree to which an individual anxiously expects discrimination (Eccleston & Major, 2006; Jetten, Branscombe, Schmitt, & Spears, 2001; Mendoza-Denton, Downey, Purdie, Davis, & Pietrzak, 2002). In fact, Andretta et al. (2015) showed that making racial identity attitudes salient had a substantive effect on behavioral self-report scores in a sample of African Americans with juvenile court contact.

The Effect of Question Order and Evaluator’s Race on Self-Reported Behaviors

Although many methods have been used to make stereotypes salient, survey-based studies have relied on the ordering of information to operationalize this social-priming phenomenon. Ordering matters because individuals self-report based on what information is accessible in the moment (Higgins, 1996), and what is accessible at the moment of judgement is strongly influenced by context (Schwarz, 1999). To provide an example, if attitudes about racial identity are made accessible, self-reports that immediately follow may reflect racial-identity related representations in memory. R. K. Mallett et al. (2011) tested this hypothesis by administering adolescents the Multigroup Ethnic Identity Measure (MEIM; Phinney, 1992) either before or after administering the following question: “To what extent do you experience a sense of exclusion or a sense of belonging at your school” (Sidanius, Van Laar, & Levin, 2004)? European Americans were not affected by the ordering of the MEIM and the question. In contrast, African American, Native American, and Latinx students reported higher belonging uncertainty when the MEIM preceded the question about school belonging. That is, making cultural attitudes accessible through ordering (i.e., priming) changed the response to the question about school belonging.

The ordering of surveys is likely not the only vehicle for priming negative stereotypes in assessment situations. It is also possible that the racial group membership of the assessor makes stereotypes active, and stereotype threat provides a theoretical framework for this hypothesis. To provide an example, given the history of stereotypes in the United States as outlined above, a European American evaluator’s racial group membership might cause an African American adolescent to fear confirmation of negative stereotypes during questioning about severe conduct problems.

Only a few stereotype threat (ST) studies have included a manipulation of the research confederate’s racial group membership, though the extant literature suggests that this stimulus is enough to activate ST. Blascovich, Spencer, Quinn, and Steele (2001) had a European American or African American confederate administer a test of cognitive abilities to college students. African Americans assessed by a European American administrator had higher levels of blood pressure and poorer overall performance on testing than same-race peers assessed by an African American administrator. In an ST study on math performance, Inzlicht and Ben-Zeev (2000) tasked college women with problem solving and paired participants with either female or male partners. Women working with many male partners performed the worst, and these authors attributed the poor performance to gender stereotypes about mathematics ability activated by the sex composition of the work groups.

To date, there are no studies in forensic settings that involved manipulating the racial group membership of the evaluator in a psychological assessment situation. However, some researchers have begun to address ST in forensic-related situations. In an ST study on police encounters, Najdowski et al. (2015) reported that young African American adults believed they are perceived by officers as criminals due to race alone. Najdowski et al. also reported that African Americans fear confirmation of negative stereotypes during contact with police. However, Najdowski et al.’s study was conducted in a college setting, and results may not generalize to a forensic population, to an actual forensic setting, or to adolescents. What is known is that arousal associated with the fear of confirming negative stereotypes compromises individuals’ ability to resist pressure from police to confess to crimes (Davis & Leo, 2012). ST also places individuals at risk of presenting with nonverbal behaviors that are likely to be interpreted as suggestive of guilt (Najdowski, 2011).

The Current Studies

As noted previously, violence risk assessments rely, in part, on soliciting individuals to self-report involvement in criminal behaviors. For African American youth, questions about criminal behaviors are inextricably tied to stereotypes about their group, and it is that connection that makes self-reported behaviors vulnerable to contextual, priming conditions. Therefore, manipulations of context, including questions about racial identity or the racial group membership of the evaluator, could affect the results of violence risk assessments and associated judicial decisions. Using archival data provided by a large district court, the purpose of the present studies was to examine these hypotheses. In Study 1, we examined how priming racial identity attitudes affected subsequent endorsement of the eight Severe Conduct items included on the CBRS-SR, each of which has potential criminal implications. In Study 2, we assessed if the race of the evaluator influenced these self-reported behaviors.

For both studies, we relied on both the conceptualization and associated survey of severe conduct problems as outlined in the user manual for the CBRS (Conners, 2008). These items are a set of low-incidence mental health referral issues that, when endorsed, require immediate attention (e.g., using a weapon; see Measures section). Severe conduct behaviors are so hazardous they are considered precursors to Antisocial Personality Disorder and psychopathy in adulthood and are estimated to occur in less than 2% of the school-age population in the United States (American Psychiatric Association, 2013). Because CBRS severe conduct item scores were not originally intended to be explained by a latent variable, a thorough exploration of item scores was undertaken to assess the viability of a severe behavior construct (see Measures section and Supplementary Material available in the online version of the article).

Study 1

The purpose of Study 1 was to examine the effect of priming on self-reported severe conduct scores. We hypothesized that primed individuals would report substantially higher levels of engagement in severe conduct than peers in a control group (Andretta et al. (2015).

Method

Participants

Participants included 226 (76% male) African American youth arrested in a mid-Atlantic city; however, 33 were excluded due to problematic response styles. Response style was appraised using the CBRS-SR software package, which provides scores for positive impression, negative impression, and inconsistency index scales (Conners, 2008). In the current study, two participants were excluded due to positive impression management, four due to negative impression management, and 27 due to inconsistent responding. Ages ranged from 12 to 18 years (M = 15.38 years, SD = 1.46), and grade level ranged from 3rd to 12th with a mode of 9th (n = 57, 31%). Police Service Area data were available for 204 participants. Seventy percent of the participants were living in the Police Service Areas with the lowest average household incomes in the city, the highest rates of adults without a high school diploma, and rates of interpersonal violence from 13 to 27 people per 1,000. Nationally, approximately 3.87 people per 1,000 experience interpersonal violence. Roughly half of the sample were arrested on misdemeanor charges (n = 101, 52%), with the others being charged with a felony (n = 92, 48%).

Measures

The current study included two sets of scores from the CBRS-SR (Conners, 2008). The CBRS-SR was used to assess both severe conduct and internalizing disorders. The self-report survey includes 177 items that load on 10 specific DSM-V scales. Response options ranged from not true at all/never to very much true/very often on a 4-point Likert-type scale. In a large normative sample (n = 1,357), Conners (2008) reported adequate internal consistency estimates for nine scores (α ≥ .82) with the estimate for Manic Episode being a little lower (α = .74). CBRS-SR scores accurately classified 75% of previously established diagnoses in individuals in a clinical group (n = 700), with classification rates ranging from 66% to 85%.

Severe conduct

The CBRS-SR (Conners, 2008) includes sets of critical items or items that when endorsed by an adolescent to indicate that immediate attention is required. One set of eight critical items is labeled Severe Conduct, which were subjected to exploratory factor analysis (see Supplemental Materials). Because of the results of exploratory factor analysis, we assessed severe conduct in the primary analyses using a composite score of six of the eight Severe Conduct items, which tapped knowledge of where to get a weapon, frequency of carrying weapons, use of weapons to hurt people, burglary, and robbery (see Table S1 in the Supplemental Materials). Two of the eight items—fire-setting and meanness to animals—were dropped due to inadequate factor coefficients observed in a large sample of African Americans involved in the juvenile justice system.

Internal consistency estimates for the severe conduct composite scores in the current study were low (i.e., in the .50-.70 range; see Table 2). As these items were not initially designed to be combined, we used them as an observed score and not a latent variable, recognizing that the results need to be interpreted with some caution (see Supplemental Materials). The severe conduct composite scores were not skewed, but were kurtotic, with many ratings falling between seldom and occasionally.

Internalizing disorders

Participants with a T score ≥70 on one or more of the six CBRS-SR scales assessing internalizing disorders—Major Depressive Episode, Manic Episode, Generalized Anxiety Disorder, Separation Anxiety Disorder, Social Phobia, and Obsessive-Compulsive Disorder—were classified as having an internalizing disorder (coded 1). Andretta et al. (2014) reported acceptable reliability estimates for all six of theses scales in a large sample of African Americans involved in the juvenile justice system (N = 1,040, α ≥ .75, ω^h ≥ .75).

Age and Charge

Dates of birth were used to develop a continuous variable for age. Charges were provided by the arresting officers, and a dummy variable was developed (misdemeanor = 0, felony = 1).

Racial Identity Attitudes

The CRIS (Vandiver et al., 2000) was used to prime racial identity attitudes. It includes 40 items: six 5-item subscales and 10 filler items. The six subscales assess the racial identity attitudes described in the Introduction: (a) assimilation, (b) miseducation, (c) self-hatred, (d) anti-White, (e) Afrocentricity, and (f) multiculturalist inclusive. Worrell et al. (2014) reported supportive reliability (α ≥ .72) and structural validity (comparative fit index = .943, nonnormed fit index = .937, root mean square error of approximation = .032, 90% CI [.027, .038]) evidence for CRIS scores in African American youth involved in the juvenile justice system. Studies outside of forensic settings have also yielded evidence of strong psychometric properties in both adolescents and adults (Gardner-Kitt & Worrell, 2007; Sussman, Beaujean, Worrell, & Watson, 2012; Vandiver, Cross, Worrell, & Fhagen-Smith, 2002; Worrell & Watson, 2008). CRIS response options range from 1 (Strongly disagree) to 7 (Strongly agree) and mean scores for the six subscales are calculated; no items are reverse-scored.

Endorsement of negative stereotypes

The endorsement of stereotypes was assessed using one Miseducation item from the CRIS. This item assessed the degree to which an individual endorsed negative stereotypes about criminal behaviors specifically: “African Americans are too quick to turn to crime to solve their problems.”

Procedure

The present study included archival CRIS and CBRS-SR data collected at a mid-Atlantic city court’s intake facilities shortly following arrest and also used by Worrell et al. (2014). In the city where the study occurred, the CBRS-SR is a court-ordered mental health screener administered to all youth immediately following arrest to aid the trier of fact in determining clinical eligibility for a juvenile mental health diversion program. The CRIS was added to the intake screening protocol by Worrell et al. (2014) as part of a program evaluation focused on meeting the unique needs of a 95% African American juvenile justice population. The stakeholders, who approved the dissemination of archival data before we proceeded with submissions, oversee the mental health screening of youth at the city’s courts, and include representatives from the Office of the Attorney General, the Department of Behavioral Health, District of Columbia Public Schools, Public Defender Services, Court Social Services Division, and the presiding Family Court judge. Informed assent was gained prior to each interview. Parental consent was not sought because screenings were conducted by order of the court.

When Worrell et al. (2014) collected CRIS and CBRS-SR data, these authors used two different survey orders which were re-conceptualized as priming in the present study. Some youth were asked to report on racial identity attitudes using the CRIS prior to reporting on their engagement in severe conduct using the CBRS-SR. Other youth were asked about racial identity attitudes after reporting on their engagement in severe conduct. Randomization of the order of administering the CRIS and CBRS-SR was based on the following algorithm, where “A” represents administration of the CRIS prior to the CBRS-SR, and “B” represents administration of the CRIS after the CBRS-SR: A, B, B, A, B, A, A, B, B, A. In the present study, Worrell et al.’s (2014) randomization of ordering yielded two groups: (a) a primed or experimental group and (b) a control group.

Interviews were conducted by one of two, European American, postdoctoral fellows of child and adolescent forensic psychology, both of whom were completing their fellowships at the court where the study occurred. To control for reading differences, all CBRS-SR and CRIS items were read to participants, and this procedure has been shown to yield internally consistent and structurally valid scores (Andretta et al., 2014; Worrell et al., 2014).

The screenings were conducted in one of two interview rooms in secure detention settings. Each interview began with the clinician introducing himself and inquiring about the juvenile’s well-being. Next, the clinician indicated that he was a psychologist using a standardized protocol:

I am psychologist who works with the court. It is my job to interview youth to see who might need a little more support in their life, so that they do not end up coming back to court. I will be asking you questions about thoughts, feelings, and behaviors. The process should take about 25 minutes. You should know that if you report a plan to hurt yourself or someone else, I will need to share that information with the court. I am also obligated to share information regarding drug use.

At this point in the interview, the clinicians paused to evaluate understanding and then provided a few final directions: “You may refuse to participate, and your refusal will not be shared with the judge or the government/DA/prosecuting attorney (i.e., Office of the Attorney General).”

Results

Data Analytic Strategy

Because stereotypes about severe conduct behaviors are typically about African American males, we controlled for gender differences (Correll, Urland, & Ito, 2006; Ito & Urland, 2003). We also controlled for age because Bongers, Koot, van der Ende, and Verhulst (2003) showed that externalizing behaviors decrease across the course of adolescence, though more so in males than females. The association between mental illness and criminal behaviors is less clear. Mental illness is not necessarily a strong predictor of criminal behavior among adolescents (Grisso, 1998/2013), but over half of African American youth with court contact meet diagnostic criteria for a mental health disorder (Abram, Teplin, McClelland, & Dulcan, 2003; Andretta et al., 2014). Thus, we controlled for internalizing disorders. We did not control for externalizing behaviors because of the theoretical overlap with severe conduct. Charge severity (i.e., misdemeanor or felony) was also included as a covariate of self-reported criminal behavior as this variable classifies those with more serious and less serious charges.

We also included interaction terms in our equations for each of the primary covariates. Specifically, we were interested in ascertaining whether or not the effect of priming was modified by gender, internalizing disorders, or the endorsement of negative stereotypes. We did not include interaction terms for age or charge because these covariates were not central to the analysis, but instead used for the sole purpose of controlling for potentially confounding effects.

Descriptive statistics and correlations are shown in Tables 1 and 2, and these statistics were conducted with STATA 14 (StataCorp, 2015). A hierarchical regression model was employed to examine the effect of racial identity attitudes on the endorsement of severe conduct behaviors. The model was developed in a SEM framework using the MLR estimator in Mplus Version 7 (Muthén & Muthén, 1998-2015), which is robust to nonnormality (Wang & Wang, 2012). Ferguson’s (2009) recommendations for the interpretation of standardized beta coefficients as effect sizes were used: a β ≥ |.20| was interpreted as practically significant, a β ≥ |.50| as a moderate effect, and a β ≥ |.80| as a large effect, and we also reported confidence intervals for the effect sizes.

Table 1.

Correlation of Study 1 Variables.

	1	2	3
1. Severe conduct	—
2. Age	−0.06	—
3. Stereotypes	0.12	0.05	—
4. Internalizing	0.29**	−0.06	0.09

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

Table 2.

Descriptive Statistics for Self-Reported Severe Conduct Scores in Study 1.

Severe Conduct Scores in Stigma Priming Experiment
	n	M	SD	Skewness	Kurtosis	α	α ≥ [95% CI]	ω^h
Entire sample	193	.18	.33	2.15	7.71	.62	.55	.64
Control group	97	.13	.26	2.66	11.06	.59	.47	.60
Primed group	96	.24	.37	1.75	5.72	.63	.52	.68
Males
Control group	75	.12	.25	3.18	14.92	.68	.58	—
Primed group	72	.28	.39	1.60	5.25	.61	.49	—
Females
Control group	22	.17	.30	1.47	3.94	.42	.02	—
Primed group	24	.14	.30	2.32	7.54	.72	.54	—

Note: n = number of participants; M = mean; SD = standard deviation; α = alpha or internal consistency; CI = confidence interval; ω^h = omega coefficients based on the standardized coefficients from confirmatory factor analyses.

Primary Analyses

In Step 1, age, gender, charge, and having an internalizing disorder were entered (see Table 3). The likelihood that an individual meets diagnostic criteria for at least one internalizing disorder had a substantive (Ferguson, 2009) and positive effect on severe conduct scores. The other three variables made minimal contributions to the model, and the model accounted for 16% of the variance in severe conduct behaviors.

Table 3.

The Effect of Priming Racial Identity Attitudes on Self-Reported Severe Conduct Scores.

Predictor	Step 1				Step 2
Predictor	β [95% Bootstrap CI]	b	p value	R ²	β [95% Bootstrap CI]	b	p value	R² (ΔR²)
				.16				.22 (.06)
Stigma priming	—	—	—		.43 [.12, .70]	.40	.02
Stereotypes	—	—	—		.16 [.01, .28]	.04	.05
SP × stereotypes	—	—	—		−.23 [−.60, .18]	−.05	.31
Internalizing	.40 [.20, .53]	.39	.001		.38 [.07, .59]	.40	.04
SP × Internalizing	—	—	—		−.03 [−.35, .33]	−.04	.88
Gender	−.10 [−.23, .05]	−.11	.27		.05 [−.14, .24]	.05	.73
SP × Gender	—	—	—		−.23 [−.42, .02]	−.32	.13
Age	.08 [−.04, .21]	.02	.31		.11 [−.04, .23]	.03	.24
Charge	−.04 [−.20, .14]	−.03	.73		−.03 [−.20, .14]	−.03	.78

Note: SP = stigma priming; β = standardized beta; b = unstandardized beta; R² = variance explained; Δ = change. Internalizing = likely suffers an internalizing disorder as evidenced by a T score of 70 or greater on one or more CBRS-SR internalizing scale(s). Dichotomous variables were coded as follows: (a) priming (0 = no, 1 = yes); (b) charge (0 = misdemeanor, 1 = felony), (c) internalizing (0 = no illness, 1 = illness present); (d) gender (0 = male, 1 = female).

In Step 2, both the degree to which individuals endorsed negative stereotypes about African Americans that were specific to conduct problems and the priming condition were added to the model. Three interaction terms—stigma priming with gender, internalizing behaviors, and endorsement of stereotypes—were also added to the model. Individuals who were primed with the CRIS reported substantively higher levels of severe conduct when compared with control group peers (Hedges’s g = −.34, 95% CI [−.63, −.06]; see Tables 1 and 2). Although the endorsement of negative stereotypes had a small positive effect on severe conduct scores, the interaction between the endorsement of negative stereotypes and priming was practically although not statistically significant (Ferguson, 2009). Individuals who were primed and endorsed stereotypes reported markedly less involvement in severe conduct. Priming was not associated with age, charge, or suffering from an internalizing disorder.

Discussion

Results suggested that asking questions about racial identity prior to an assessment of severe conduct behaviors will influence African American clients to endorse higher levels of severe conduct than when questions about racial identity are not introduced. These data have important implications for violence risk assessment methods and point to some potential pitfalls in well-intentioned approaches to employing culturally appropriate evaluations. Specifically, building rapport with clients through conversations around race and associated attitudes might counterintuitively place African Americans in the very psychological predicament clinicians seek to avoid.

Specific attention to the direction of self-reported behavior differences observed in Study 1 is also warranted. Stigma priming was associated with higher levels of self-reported severe conduct behaviors, a stereotype confirming response. In contrast, Steele and Aronson (1995) reported that stigma priming resulted in stereotype avoidant responses in college students: When compared with peers in a control group, individuals in the primed condition reported lower levels of behaviors associated with African Americans, such as aggression, belligerence, and enjoyment of both rap music and basketball. Steele and Aronson (1995) opined that the priming condition activated a commonly employed, adaptive function in collegiate African Americans: to avoid being “perceived through a race-class stereotype as a potentially menacing Black [person]” (p. 803). However, the sociocultural context of a university campus is far different than a forensic setting, and, in fact, these populations likely have a starkly different set of life experiences. The difference in context may explain why responses to stigma priming appear to differ between collegiate and forensic populations.

Additionally, there is a growing body of data suggesting that responses to priming in college students is not generalizable to forensic populations. In a study of African American adolescents involved in the justice system (Andretta et al., 2015), individuals in a stigma priming condition reported comparatively high levels of stereotypical behaviors associated with oppositional defiance. These authors concluded that adolescents responded to priming in a manner consistent with Ferguson’s (2001) theory on coping mechanisms in disenfranchised, African American communities: Individuals are taught to stand up for themselves, which, in this instance, manifested in endorsing defiance to authority.

Scholars have previously argued that priming activation is dependent on acknowledgment of stereotypes (Schmader, Johns, & Barquissau, 2004). The present study contributed to our understanding of this hypothesis by showing that priming is also affected by the endorsement of negative stereotypes. The findings suggested that individuals who do not endorse stereotypes about criminal behaviors are most vulnerable to the stigma priming phenomenon. It might be that youth who feel African Americans are too quick to turn to crime were not affected by the priming event because the stereotype is consistent with their own beliefs. This hypothesis is worth exploring further.

Study 2

Shapiro and Neuberg (2007) argued that scientists have both defined and applied ST in vastly different ways. They further surmised that a singular and broad umbrella term might set researchers up to misinterpret for whom, and under what conditions, the effects of ST are applicable. They proposed the multithreat framework (MTF), and accounted for six, qualitatively distinct stereotype threats differentiated by two dimensions. These authors opined that the source of threat, which might be the self, out-group members, or in-group members, comprised one dimension of ST. The second dimension of ST was the target of the threat, either the self or one’s group. Shapiro, Williams, and Hambarchyan (2013) provided support for MTF theory by showing that different stereotype threats are selectively responsive to interventions. For instance, role model interventions protected against group-as-target stereotype threats, but not self-as-target stereotype threats.

Based on the MTF framework, in Study 2, we examined own-reputation ingroup threat (i.e., African American evaluator) and own-reputation outgroup threat (European American evaluator), where manipulation of the evaluator’s race was the priming event. Further still, we hypothesized that own-reputation outgroup threat would yield higher self-reported severe conduct scores. Own-reputation outgroup threat arises if the source of the threat is an outgroup member and the target of the threat is self. Own-reputation ingroup threat arises if the source of the threat is an ingroup member and the target of the threat is self. We hypothesized that African American youth involved in the justice system would report higher levels of severe conduct to a European American than an African American evaluator. This hypothesis was based on the findings by Blascovich et al. (2001), where ST was engendered by the presence of an European American confederate, but not an African American confederate.

Method

Participants

Participants in Study 2 consisted of an independent sample of 339 African American adolescents arrested in in a mid-Atlantic city, which did not include an overlap with Study 1 participants. Seventy-five participants were dropped from analyses due to problematic response styles as indicated by CBRS-SR results: (a) positive impression management = 3, (b) negative impression management = 9, and (c) inconsistent responding = 63. Of the 264 remaining participants, 173 (65%) were male. Ages ranged from 10 to 18 years (M = 15.31 years, SD = 1.53), and grade levels ranged from 4 to 12 with a mode of 9th (n = 83, 31% with 19 unknown). About half of the participants (49%; n = 130) were charged with misdemeanor crimes and 51% (n = 134) were charged with felonies. The majority of the youth were from the two areas of the city with the lowest average household incomes ranges and were living in the areas of the city with the most adults without a high school diploma. The youth were also predominantly from the areas of the city with the two highest rates of violent crimes.

Measures and Procedure

The same measures employed in Study 1 were employed in Study 2 with one exception: Data on racial identity attitudes were not collected. As previously described, all youth at the host court receive a mental health screening immediately following arrest to determine clinical eligibility for a mental health diversion program. To control for reading differences, the CBRS-SR items were read aloud, and youth responded to each item orally. Interviews were conducted by one of two European American postdoctoral fellows, an African American postdoctoral fellow, or an African American intern from a local PhD program in clinical psychology. Interviewers were not randomly assigned. Instead, interviewers screened all the youth arrested during their shift at the juvenile intake facility where they were stationed. Interviewers used the standardized introduction to mental health screenings described in Study 1. Consent was not needed because every youth is provided a screening by court order, and interviewers were hired by the court to do the interviews. That is, the primary reason for the data collection was to serve the court, and data collection methods were not changed to meet the needs of the study. Informed assent was gained prior to each interview.

We were granted access to the archival data by Court stakeholders, which included representation from the following agencies and representatives: (a) Office of the Attorney General, (b) the Department of Behavioral Health, (c) District of Columbia Public Schools, (d) Public Defender Services, (e) Court Social Services Division, and (f) the presiding Family Court judge. These same stakeholders also approved the use of the archival data for research purposes before we proceeded with journal submissions.

Results

Descriptive statistics and correlations are shown in Tables 4 and 5. Analyses were developed in a SEM framework using the MLR estimator in Mplus Version 7 (Muthén & Muthén, 1998-2015). Severe conduct scores were kurtotic but not skewed. The internal consistency and factor saturation of self-reported criminal behavior scores were higher than in Study 1, but still lower than ideal.

Table 4.

Correlation of Study 2 Variables.

	1	2
1. Severe Conduct	—
2. Age	−0.06	—
4. Internalizing	0.29	−0.06

p < .05, **p < .01.

Table 5.

Descriptive Statistics for Self-Reported Severe Conduct Scores in Study 2.

	n	M	SD	Skewness	Kurtosis	α	α>[95% CI]	ω^h
Entire Sample	264	.18	.35	2.58	10.22	.67	.62	.68
African American Ev.	103	.26	.39	2.20	8.30	.67	.58	.68
European American Ev.	161	.13	.30	2.93	11.89	.66	.59	.67

Note: Ev. = Evaluator. n = number of participants, M = mean; SD = standard deviation; α = alpha or internal consistency; CI = confidence interval; ω^h = omega coefficients based on the standardized coefficients from confirmatory factor analyses.

Results of a hierarchical regression showed that age, charge, mental health, and gender explained 19% of the variance in severe conduct scores, and adding the interviewer condition (i.e., racial group membership of the evaluator variable scored 0 or 1) did not explain additional variance in scores (see Table 6). Moreover, the racial group membership of the evaluator did not have an effect on self-reported severe conduct scores (see Tables 5 and 6). The interactions between the race of the evaluator and gender of the participant and the race of the evaluator and mental health did not contribute to self-reported severe conduct behaviors.

Table 6.

The Effect of Evaluator’s Race on the Endorsement of Severe Conduct Behaviors.

Predictor	Step 1				Step 2
Predictor	β [95% Bootstrap CI]	b	p value	R ²	β [95% Bootstrap CI]	b	p value	R² (ΔR²)
				.19				.19 (.00)
Evaluator race	—	—	—		−0.04 [−.25, .23]	−0.03	0.81
Internalizing	−.19 [−.38, −.01]	−.13	.30		−0.07 [−.54, .31]	−0.05	0.85
Ev × Internalizing	—	—	—		−0.05 [−.25, .23]	−0.03	0.81
Gender	.23 [.03, .37]	.16	.15		0.32 [−.04, .77]	0.23	0.44
Ev × Gender	—	—	—		−0.13 [−.65, .27]	−0.11	0.74
Age	−.10 [−.26, .11]	−.02	.45		−0.10 [−.26, .12]	−0.02	0.44
Charge	.28 [.14, .43]	.20	.12		0.29 [.13, .43]	0.20	0.13

Note. Ev = evaluator race; CI = confidence interval; ST = stereotype threat activated by race of the evaluator; β = standardized beta; b = unstandardized beta; R² = variance explained; Δ = change; Internalizing = likely suffers an internalizing disorder as evidenced by a T score of 70 or greater on one or more CBRS-SR internalizing scale(s). Dichotomous variables were coded as follows: (a) admin (0 = African American, 1 = European American); (b) charge (0 = misdemeanor, 1 = felony), (c) internalizing (0 = no illness, 1 = illness present); (d) gender (0 = male, 1 = female).

Discussion

Contrary to the hypothesis, African American adolescents involved in the juvenile justice system reported similar levels of severe conduct to European American and African American evaluators in this study. Therefore, we concluded that the race of the evaluator did not evoke different levels of threat. One possible explanation for this finding may be that the socioeconomic status of the clinicians yielded similar appraisals of the African American and European American evaluators by the participants, thereby attenuating ST effects. The African American evaluators were young adults who had completed an undergraduate degree and were either in the process of completing or had already completed graduate study in psychology. In contrast, participants hailed from areas of the city characterized by the lowest percentage of adults with a high school diploma, the lowest average household incomes, and the highest levels of interpersonal violence. Therefore, it is possible that the African American evaluators presented themselves in a manner that was not consistent with participants’ current set of life circumstances and more in keeping with their expectations of “the other.” Studies on African American appraisals of clinicians’ cultural sensitivities provide some insight into why that might have occurred.

Thompson, Bazile, and Akbar (2004) conducted a qualitative study on perceptions of mental health providers among African Americans in a community clinic setting. These authors reported that African Americans in low income situations preferred to be paired with an African American clinician. And, in fact, many studies have shown that racial congruence between client and therapist has a beneficial effect on therapeutic outcomes among African Americans (Meyer & Zane, 2013). Nevertheless, Thompson et al. also reported a curious counterexample that has implications for the Study 2 results.

African Americans from low socioeconomic backgrounds perceived African American clinicians as too far removed from their culture. This group also appraised African American clinicians to be just as likely as European American clinicians to be insensitive to their life experiences. For example, one of Thompson et al.’s (2004) participants made the following statement:

I don’t think it would matter what ethnicity the person was. Even if they were the same ethnicity, it’s not going to guarantee that they understand. They grow up in a middle-class neighborhood and they don’t know anything about where I am. (p. 24)

In fact, African American clients reported limiting their discussion about experiences of racism, discrimination, and exposure to community violence with their African American clinicians due to apprehensions about understanding (Thompson et al., 2004). It might be important to expand on Thompson et al.’s study by examining how African Americans involved in the juvenile justice system perceive African American psychologists.

General Discussion

In the present study, we employed two different but associated theoretical frameworks. In Study 1, stigma priming had an effect on self-reported severe conduct behaviors, but in Study 2, interviewer race did not result in an effect on these scores. Of course, replications of Study 1’s findings are needed before definitive conclusions can be drawn. Thus, we encourage researchers interested in this topic to study stigma priming and other phenomena related to ST in future studies. It is also important to point out that these results do not suggest that stigma priming may be more important in forensic mental health evaluations than the race of the interviewer. A claim of this magnitude requires further study, especially given Thompson et al.’s (2004) findings with regard to clinician socioeconomic status.

There are many opportunities for further research on the deleterious effects of stereotypes in juvenile justice settings. For example, a study on the degree to which identification with the African American community offsets the harmful effect of stigma priming in violence risk assessments would be useful. Similarly, studies on how African Americans interpret feedback from psychological evaluators and how that appraisal affects responses to questions about criminal behaviors would also provide valuable information on behavior in these settings. Researchers can also examine the degree to which African Americans involved in the juvenile justice system differ with regard to their race-based rejection sensitivity (Mendoza-Denton et al., 2002). And it will be interesting to understand how the socioeconomic status of arrested youth affect interactions with, and perceptions of, clinicians on court-mandated assessments. As is evident, there are many questions that remain to be answered in this arena.

Limitations and Conclusion

The present set of studies had several limitations. First, the data were archival which limited the questions that could be asked and the measures that could be used. Thus, research questions were developed based, in part, on what data were available. This shortcoming is associated with both the difficulty and ethical considerations in conducting research in forensic settings and research using forensic mental health evaluations generally. Another limitation is that all data in the present study were self-reported with the exception of the charge placed on youth by arresting police officers. Further still, endorsement of negative stereotypes was captured using one item, which limited the degree to which scores on this item could be relied on.

Another limitation is the fact that the examination of differences between self-reported severe conduct scores evoked by European American and African American evaluators were developed across a limited number of clinicians. Therefore, results could have been shaped by factors other than ST, including the clinicians’ unique abilities to develop rapport with youth. Notwithstanding the limitations, the present study provides evidence to motivate psychological scientists to continue to examine if and how negative stereotypes introduce measurement error into violence risk assessments.

Supplemental Material

Supplementary_Materials_ST.edited – Supplemental material for Race and Stereotypes Matter When You Ask About Conduct Problems: Implications for Violence Risk Assessment in Juvenile Justice Settings

Supplemental material, Supplementary_Materials_ST.edited for Race and Stereotypes Matter When You Ask About Conduct Problems: Implications for Violence Risk Assessment in Juvenile Justice Settings by James R. Andretta, Frank C. Worrell, Katara M. Watkins, Ryan M. Sutton, Adrian D. Thompson and Malcolm H. Woodland in Journal of Black Psychology

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Supplemental Material

The online supplemental material is available at

References

Abram

K. M.

Teplin

L. A.

McClelland

G. M.

Dulcan

M. K.

(2003). Comorbid psychiatric disorders in youth in juvenile detention. Archives of General Psychiatry, 60, 1097-1108. doi:10.1001/archpsyc.60.11.1097

Altman

(1997). The encyclopedia of African American heritage. New York, NY: Facts on File.

American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). Washington, DC: Author.

Andretta

J. R.

Thompson

A. D.

Ramirez

A. M.

Kelly

Barnes

M. E.

Woodland

M. H.

(2014). A study on the psychometric properties of Conner Comprehensive Behavior Rating Scales Self-Report scores in African Americans with juvenile court contact. Journal of Forensic Psychology Practice, 14, 1-23. doi:10.1080/15228932.2014.863051

Andretta

J. R.

Worrell

F. C.

Ramirez

A. M.

Barnes

M. E.

Odom

Brim

Woodland

M. H.

(2015). The effects of stigma priming on forensic screening in African American youth. The Counseling Psychologist, 43, 1162-1189. doi:10.1177/0011000015611963

Andrews

Dowden

(2007). The Risk-Need-Responsivity Model of assessment and human service in prevention and corrections: Crime-prevention jurisprudence. Canadian Journal of Criminology and Criminal Justice, 49, 543-550. doi:10.3138/cjccj.49

Angwin

Larson

Mattu

Kirchner

(2016). Machine bias: There’s software used across the country to predict future criminals. And it’s biased against Blacks. ProRepublica. Retrieved from https://www.propublica.org/article/machine-bias-risk-assessments-in-criminal-sentencing

Bargh

J. A.

Chen

Burrows

(1996). Automaticity of social behavior: Direct effects of trait construct and stereotype activation on action. Journal of Personality and Social Psychology, 71, 230-244. doi:10.1037/0022-3514.71.2.230

Barlow

M. H.

(1998). Race and the problem of crime in Time and Newsweek cover stories, 1946 to 1995. Social Justice, 25, 149-183.

10.

Blascovich

Spencer

S. J.

Quinn

Steele

(2001). African Americans and high blood pressure: The role of stereotype threat. Psychological Science, 12, 225-229. doi:10.1111/1467-9280.00340

11.

Bongers

I. L.

Koot

H. M.

van der Ende

Verhulst

F. C.

(2003). The normative development of child and adolescent problem behavior. Journal of Abnormal Psychology, 112, 179-192. doi:10.1037/0021-843X.112.2.179

12.

Borum

Bartel

P. A.

Forth

A. E.

(2006). SAVRY: Structured Assessment of Violent Risk in Youth, professional manual. Lutz, FL: Psychological Assessment Resources.

13.

Chiricos

Eschholz

(2002). The racial and ethnic typification of crime and the criminal typification of race and ethnicity in local television news. Journal of Research in Crime and Delinquency, 39, 400-420.

14.

Chiricos

Welch

Gertz

(2004). Racial typification of crime and support for punitive measures. Criminology, 42, 359-389.

15.

Cokley

K. O.

Vandiver

B. J.

(2012). Ethnic and racial identity. In Altmaier

E. M.

Hansen

J. C.

(Eds.), The Oxford handbook of counseling psychology (pp. 291-325). New York, NY: Oxford University Press.

16.

Conners

C. K.

(2008). Conners Comprehensive Behavior Rating Scales. Toronto, Ontario, Canada: Multi-Health Systems.

17.

Correll

Urland

G. R.

Ito

T. A.

(2006). Event-related potentials and the decision to shoot: The role of threat perception and cognitive control. Journal of Experimental Social Psychology, 42, 120-128. doi:10.1016/j.jesp.2005.02.006

18.

Cross

W. E.

Jr. (1971). Toward a psychology of Black liberation: The Negro-to-Black conversion experience. Black World, 20, 13-27.

19.

Cross

W. E.

Jr. Vandiver

B. J.

(2001). Nigrescence theory and measurement: Introducing the Cross Racial Identity Scale (CRIS). In Ponterotto

Casas

Suzuki

Alexander

(Eds.), Handbook of multicultural counseling (pp. 371-393). Thousand Oaks, CA: Sage.

20.

Davis

Leo

R. A.

(2012). Interrogation-related regulatory decline: Ego depletion, failures of self-regulation, and the decision to confess. Psychology, Public Policy, and Law, 18, 673-704. doi:10.1037/a0027367

21.

Dixon

T. L.

Azocar

C. I.

(2006). The representation of juvenile offenders by race on Los Angeles area television news. Howard Journal of Communications, 17, 143-161. doi:10.1080/10646170600656896

22.

Dixon

T. L.

Linz

(2000). Overrepresentation and underrepresentation of African Americans and Latinos as lawbreakers on television news. Journal of Communication, 50, 131-154.

23.

Dovidio

J. F.

Gaertner

S. L.

(2000). Aversive racism and selection decisions: 1989 and 1999. Psychological Science, 11, 315-319. doi:10.1111/1467-9280.00262

24.

Eccleston

C. P.

Major

B. N.

(2006). Attributions to discrimination and self-esteem: The role of group identification and appraisals. Group Processes & Intergroup Relations, 9, 147-162. doi:10.1177/1368430206062074

25.

Ferguson

A. A.

(2001). Bad boys: Public schools in the making of Black masculinity. Ann Arbor: University of Michigan Press.

26.

Ferguson

C. J.

(2009). An effect size primer: A guide for clinicians and researchers. Professional Psychology: Research and Practice, 40, 532-538. doi:10.1037/a0015808

27.

Forth

A. E.

Kosson

Hare

R. D.

(2003). Manual for the youth version of the Hare Psychopathy Checklist–Revised (PCL-YV). Toronto, Ontario, Canada: Multi-Health Systems.

28.

Gardner-Kitt

D. L.

Worrell

F. C.

(2007). Measuring nigrescence attitudes in school-aged adolescents. Journal of Adolescence, 30, 187-202.

29.

Graves

S. B.

(1999). Television and prejudice reduction: When does television as a vicarious experience make a difference? Journal of Social Issues, 55, 707-727. doi:10.1111/0022-4537.00143

30.

Grisso

(2013). Forensic evaluations in juveniles (2nd ed.). Sarasota, FL: Professional Resource Press. (Original work published 1998)

31.

Higgins

E. T.

(1996). Knowledge activation: Accessibility, applicability, and salience. In Higgins

E. T.

Kruglanski

A. W.

(Eds.), Social psychology: Handbook of basic principles (pp. 133-168). New York, NY: Guilford Press.

32.

Hoge

R. D.

Andrews

D. A.

(2010). Evaluation of risk of violence in juveniles. Oxford, England: Oxford University Press.

33.

Hoge

R. D.

Andrews

D. A.

(2011). Youth Level of Service/Case Management Inventory 2.0 (YLS/CMI 2.0): User’s manual. Toronto, Ontario, Canada: Multi-Health Systems.

34.

Inzlicht

Ben-Zeev

(2000). A threatening intellectual environment: Why females are susceptible to experiencing problem-solving deficits in the presence of males. Psychological Science, 11, 365-371. doi:10.1111/1467-9280.00272

35.

Ito

T. A.

Urland

G. R.

(2003). Race and gender on the brain: electrocortical measures of attention to the race and gender of multiply categorizable individuals. Journal of Personality and Social Psychology, 85, 616-626. doi:10.1037/0022-3514.85.4.616

36.

Jetten

Branscombe

N. R.

Schmitt

M. T.

Spears

(2001). Rebels with a cause: Group identification as a response to perceived discrimination. Personality and Social Psychology Bulletin, 27, 1204-1213. doi:10.1177/0146167201279012

37.

Kennedy

(1997). Race, crime, and the law. New York, NY: Random House.

38.

Lichter

S. R.

Lichter

L. S.

Rothman

Amundson

(1987). Prime-time prejudice: TV’s images of Blacks and Hispanics. Public Opinion, July-August, 13-16.

39.

Mallett

C. A.

Stoddard-Dare

(2010). Predicting secure detention placement for African American juvenile offenders: Addressing the disproportionate minority confinement problem. Journal of Ethnicity in Criminal Justice, 8, 91-103. doi:10.1080/15377931003761011

40.

Mallett

R. K.

Mello

Z. R.

Wagner

D. E.

Worrell

Burrow

R. N.

Andretta

J. R.

(2011). Do I belong? It depends on when you ask. Cultural Diversity and Ethnic Minority Psychology, 17, 432-436. doi:10.1037/a0025455

41.

Mastro

D. E.

Stern

S. R.

(2003). Representations of race in television commercials: A content analysis of prime-time advertising. Journal of Broadcasting & Electronic Media, 47, 638-647. doi:10.1207/s15506878jobem4704_9

42.

Mauer

. (1997). Race to incarcerate. New York, NY: New Press.

43.

Mello

Z. R.

Mallett

R. K.

Andretta

J. R.

Worrell

F. C.

(2012). Stereotype threat and school belonging in adolescents from diverse racial/ethnic backgrounds. Journal of At-Risk Issues, 17, 9-14.

44.

Mendoza-Denton

Downey

Purdie

V. J.

Davis

Pietrzak

(2002). Sensitivity to status-based rejection: Implications for African American students’ college experience. Journal of Personality and Social Psychology, 83, 896-918. doi:10.1037//0022-3514.83.4.896

45.

Meyer

Zane

(2013). The influence of race and ethnicity in clients’ experiences of mental health treatment. Journal of Community Psychology, 41, 884-901. doi:10.1002/jcop.21580

46.

Monk-Turner

Heiserman

Johnson

(2010). The portrayal of racial minorities on prime time television: A replication of the Mastro and Greenberg study a decade later. Studies in Popular Culture, 32, 101-114.

47.

Muthén

L. K.

Muthén

B. O.

(1998-2015). Mplus user’s guide (7th ed.). Los Angeles, CA: Muthén & Muthén.

48.

Najdowski

C. J.

(2011). Stereotype threat in criminal interrogations: Why innocent Black suspects are at risk for confessing falsely. Psychology, Public Policy, and Law, 17, 562-591. doi:10.1037/a0023741

49.

Najdowski

C. J.

Bottoms

B. L.

Goff

P. A.

Najdowski

C. J.

Bottoms

B. L.

Goff

P. A.

(2015). Stereotype threat and racial differences in citizens’ experiences of police encounters stereotype threat and racial differences in citizens’ experiences of police encounters. Law and Human Behavior, 39, 463-477. doi:10.1037/lhb0000140

50.

Petitclerc

Gatti

Vitaro

Tremblay

R. E.

(2013). Effects of juvenile court exposure on crime in young adulthood. Journal of Child Psychology and Psychiatry and Allied Disciplines, 54, 291-297. doi:10.1111/j.1469-7610.2012.02616.x

51.

Phinney

(1992). The Multigroup Ethnic Identity Measure: A new scale for use with adolescents and young adults from diverse groups. Journal of Adolescent Research, 7, 156-176.

52.

Punyanunt-Carter

N. M.

(2008). The perceived realism of African American portrayals on television. Howard Journal of Communications, 19, 241-257. doi:10.1080/10646170802218263

53.

Schmader

Johns

Barquissau

(2004). The costs of accepting gender differences: The role of stereotype endorsement in women’s experience in the math domain. Sex Roles, 50, 835-850. doi:10.1023/B:SERS.0000029101.74557.a0

54.

Schwab-Stone

Fisher

Piacentini

Shaffer

Davies

Briggs

(1993). The Diagnostic Interview Schedule for Children–Revised Version (DISC-R): II. Test-retest reliability. Journal of the American Academy of Child and Adolescent Psychiatry, 32, 651-657. doi:10.1097/00004583-199305000-00024

55.

Schwarz

(1999). Self-reports: How the questions shape the answers. American Psychologist, 54, 93-105. doi:10.1037/0003-066X.54.2.93

56.

Shapiro

J. R.

Neuberg

S. L.

(2007). From stereotype threat to stereotype threats: Implications of a multi-threat framework for causes, moderators, mediators, consequences, and interventions. Personality and Social Psychology Review, 11, 107-130. doi:10.1177/1088868306294790

57.

Shapiro

J. R.

Williams

A. M.

Hambarchyan

(2013). Are all interventions created equal? A multi-threat approach to tailoring stereotype threat interventions. Journal of Personality and Social Psychology, 104, 277-288. doi:10.1037/a0030461

58.

Sidanius

Van Laar

Levin

(2004). Ethnic enclaves and the dynamics of social identity on the college campus: The good, the bad, and the ugly. Journal of Personality and Social Psychology, 87, 96-110. doi:10.1037/0022-3514.87.1.96

59.

Sigelman

Tuch

S. A.

(1997). Metastereotypes: Blacks’ perceptions of Whites’ stereotypes of Blacks. Public Opinion Quarterly, 61, 87-101.

60.

Sniderman

P. M.

Piazza

(1993). The scar of race. Cambridge, MA: Harvard University Press.

61.

StataCorp. (2015). Stata Statistical Software: Release 14. College Station, TX: Author.

62.

Steele

C. M.

Aronson

(1995). Stereotype threat and the intellectual test performance of African Americans. Journal of Personality and Social Psychology, 69, 797-811. doi:10.1037/0022-3514.69.5.797

63.

Stone

Harrison

K. C.

Mottley

(2012). “Don’t call me a student-athlete”: The effect of identity priming on stereotype threat for academically engaged African American college athletes. Basic and Applied Social Psychology, 34, 99-106. doi:10.1080/01973533.2012.655624

64.

Sussman

Beaujean

A. A.

Worrell

F. C.

Watson

(2012). An analysis of Cross Racial Identity Scale scores using classical test theory and Rasch item response models. Measurement and Evaluation in Counseling and Development, 46, 136-153. doi:10.1177/0748175612468594

65.

Tellhed

Björklund

(2011). Stereotype threat in salary negotiations is mediated by reservation salary. Scandinavian Journal of Psychology, 52, 185-195. doi:10.1111/j.1467-9450.2010.00855.x

66.

Thompson

V. L. S.

Bazile

Akbar

(2004). African Americans’ perceptions of psychotherapy and psychotherapists. Professional Psychology: Research and Practice, 35, 19-26. doi:10.1037/0735-7028.35.1.19

67.

Tyree

(2011). African American stereotypes in reality television. Howard Journal of Communications, 22, 394-413.

68.

Vandiver

B. J.

Cross

W. E.

Jr. Fhagen-Smith

P. E.

Worrell

F. C.

Swim

J. K.

Caldwell

L. D.

(2000). The Cross Racial Identity Scale. State College, PA: Author.

69.

Vandiver

B. J.

Cross

W E.

Jr. Worrell

F. C.

Fhagen-Smith

P. E.

(2002). Validating the Cross Racial Identity Scale. Journal of Counseling Psychology, 49, 71-85. doi:10.1037//0022-0167.49.1.71

70.

Vandiver

B. J.

Fhagen-Smith

P. E.

Cokley

K. O.

Cross

W. E.

Jr. Worrell

F. C.

(2001). Cross’ nigrescence model: From theory to scale to theory. Journal of Multicultural Counseling and Development, 29, 174-200. doi:10.1002/j.2161-1912.2001.tb00516.x

71.

Wang

(2012). Structural equation modeling: Applications in Mplus. Chichester, England: Wiley.

72.

Worrell

F. C.

Andretta

J. R.

Woodland

M. H.

(2014). Cross Racial Identity Scale (CRIS) scores and profiles in African American adolescents involved in the juvenile justice system. Journal of Counseling Psychology, 61, 570-580. doi:10.1037/cou0000041

73.

Worrell

Vandiver

Schaefer

Cross

Fhagen-Smith

(2006). Generalizing nigrescence profiles: Cluster analyses of cross racial identity scale (CRIS) scores in three independent samples. The Counseling Psychologist, 34, 519-547. doi:10.1177/0011000005278281

74.

Worrell

F. C.

Watson

(2008). A confirmatory factor analysis of Cross Racial Identity Scale (CRIS) scores: Testing the expanded nigrescence model. Educational and Psychological Measurement, 68, 1041-1058. doi:10.1177/0013164408318771

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

0.30 MB