School Mental Health Professionals’ Stereotype Knowledge and Implicit Bias toward Black and Latinx Youth

Abstract

Clinician bias has been identified as a contributor to healthcare disparities. However, research on racial/ethnic bias among mental health professionals, especially toward minoritized youths, is limited. This report describes two studies with mental health clinicians in schools, where most youths access mental health services. Study-1 used a mixed-methods approach to identify stereotypes of Black and Latinx Youth (BLY) salient to clinicians (e.g., academic failure, anger/aggression). Study-2 developed 4 new Implicit Association Tests to assess clinicians’ implicit prejudice and stereotyping of BLY and found that clinicians hold levels of pro-White/anti-racial minority bias similar to other healthcare providers and the general population.

Despite similar rates of disorder, Black/African American and Latinx/Hispanic youth receive lower quantity and quality of mental health services and have critically higher rates of unmet need compared to their Non-Hispanic White (NHW) counterparts.¹ Research shows persistent disparities in diagnosis, service access, treatment quantity and quality that lead Black and Latinx youth to have worse outcomes in many life domains beyond mental health.¹

The broader health services literature points to healthcare providers’ bias as a major contributor to persistent disparities.² Clinician bias includes prejudice (positive/negative evaluations) and stereotyping (traits associated with a given social group). Prejudice and stereotyping can manifest as implicit biases that are relatively less conscious or controllable than explicit or overt biases.² Implicit bias has been shown to negatively impact clinical decision-making and patient-provider relationships, both of which can lead to downstream disparate outcomes for minoritized versus mainstream NHW populations.² As implicit biases may influence behavior outside of one’s awareness or conscious control, their impacts may be present in almost any interaction between healthcare providers and patients belonging to minoritized groups.³ Thus, understanding clinicians’ knowledge of the specific stereotypes of minoritized patient groups can inform the development of interventions designed to reduce discrimination.

While there is an established literature on healthcare providers’ implicit racial bias,⁴ only a few of those studies included mental health professionals—a group that has been shown to be more empathic⁵ and by extension potentially less biased than other healthcare professionals (as empathy has been shown to reduce bias⁶). However, mental health clinicians’ bias may also have greater influence on disparate outcomes given the field’s limited adoption of treatment algorithms or standardized guidelines of care that could mitigate the impact of clinician bias.⁷ The healthcare provider literature also primarily focuses on bias toward Black/African American adult patients, with only a few studies examining bias toward youth or other minoritized populations.⁴ Previous research with non-healthcare populations (e.g., teachers, undergraduates) has found that adults have implicit racial bias toward youths as young as preschool age.⁸

School is the most common setting for youth mental health service delivery and one that has been shown to ameliorate some service disparities (e.g., access), while others persist (e.g., treatment engagement).⁹ No studies have examined school-based mental health clinicians’ racial bias toward youth. Improving understanding of bias among school-based clinicians is an important step in addressing pediatric mental health service disparity in a setting where youths are most likely to access mental healthcare. This report describes two novel studies of school-based clinicians’ stereotype knowledge and implicit bias toward Black and Latinx youth (BLY).

Study-1

As part of a series of studies contributing to the development of an online implicit bias intervention for school-based mental health clinicians, this study aimed to identify stereotypes of Black and Latinx youth known to school clinicians.

Methods

A geographically diverse U.S. sample of school-based clinicians (N = 42) was recruited via relevant professional listservs. The sample was demographically representative of school-based clinicians nationally, being predominately white (81%) and female (95%), with 10% identifying as Black/African American and 7% as Hispanic. Following the approach of Bean and colleagues,³ participants completed a brief online survey that asked them to “think about conversations [they’ve] overheard or had with [their] colleagues” and identify “behaviors or characteristics [they] think school mental health professionals mostly commonly associate with “Black/African American youth” and then separately for “Latinx/Hispanic youth”. For each minoritized group, participants were first asked to generate free responses, then select the top 3 characteristics from a list of 14 characteristics, 8 of which were previously documented in the literature (i.e., aggressive, angry, delinquent, gang-involved, low IQ, poor academics, and unmotivated) and 6 were positive or neutral counter attributes included for balance (i.e., conscientious, easy-going, hard-working, high-achieving, natural leader, passive). The same list of characteristics was used for Black and Latinx youth.

Following established methodology for thematic coding of qualitative data, participants’ free-responses were systematically reviewed and coded by three independent coders blinded to the identified minoritized group. This process (delineated in the Online Supplement) reduced each free-response to nominal data that indicated whether high frequency stereotypes (i.e., aggression/anger, academic failure, delinquency, lack of motivation) were identified by each participant. Then cross-category coding (following Bean et al.³) was completed such that if a participant indicated a stereotype either in their free-response or in their top 3 multiple-choice selections, they were coded as having identified that stereotype for the relevant minoritized group.

Results

for both Black and Latinx youth, 81% of participants identified “academic failure” as a characteristic most frequently associated with each group. While 76% identified “anger/aggression” as a stereotype for Black youth, only 29% identified this characteristic as a stereotype for Latinx youth, χ² (42, 1) = 18.38, p < .01. The second and third most frequently identified stereotypes for Latinx youth were “unmotivated” (62%) and “delinquency/rule-breaking” (48%). Both stereotypes were also the next most frequently identified for Black youth (45%, 55%, respectively) at lower though not significantly different rate from Latinx youth. See Online Supplement for graph and table of Chi-square analysis results.

Study-2

Based on findings of Study-1, four distinct Implicit Association Tests (IATs) were developed to assess school-based mental health clinicians’ implicit prejudice and stereotyping of BLY relative to NHW youth. The IAT, the most well-established measure of implicit biases,¹⁰ is a computerized categorization task that measures the relative strengths of associations by examining the speed with which people assign images/words to categories. For example, people who have stronger pro-White/anti-Black biases would be faster at pairing White people with good things and Black people with bad things than the reverse (i.e., Black+good / White+bad). This difference in reaction times can be computed as an IAT D-score, where a positive score (in this example) indicates a pro-White/anti-Black bias, a negative score indicates a pro-Black/anti-White bias, and a zero or near-zero score indicates no bias.

Methods

Using the same procedures as Study-1, a new sample of school-based mental health clinicians (N = 58) was recruited for Study-2. The sample was again predominately White (74%) and female (90%), with 19% identifying as Black/African American and 9% identifying as Latinx/Hispanic. Participants completed all study procedures online via a secure data collection platform (Qualtrics) including the 4 IATs, a demographic questionnaire and the Bias Awareness Scale—a 4-item questionnaire that measures awareness of and concern for one’s own implicit bias.¹¹ Participants were asked about their awareness of bias toward Black and Latinx youth separately, yielding 2 distinct bias awareness scores.

The original Black/White race IAT and more recently developed Latinx IATs all use sets of adult faces. To the best of our knowledge, there are no previously published IATs with Black or Latinx youth faces representing the full developmental range of school age youths (Kindergarten – 12^th grade). Thus, we developed 2 IATs to assess implicit prejudice (e.g., Black-White/good-bad, Latinx-White/good-bad) and 2 IATs to assess implicit stereotyping (i.e., Black-White/defiant-obedient; Latinx-White/academic failure-academic success; based on the two most frequently identified stereotypes found in Study-1). This was done following established best practices for IAT development¹² (see Online Supplement for more details, including complete citations and the list of photo stimuli and attributes used).

Results

All 4 IATs performed as expected, with adequate internal consistency (α = .71 to .91) and low rates of dropped trials (5–6%) and dropped participants (1 per IAT) due to invalid responding (e.g., too slow, too fast, or making too many errors). All 4 IATs generated average D-scores (i.e., IAT difference scores) between .30 and .42, which are indicative of implicit prejudice or stereotypes favoring White over BLY. These results (Cohen’s d = .81) are similar to those previously reported among healthcare providers⁴ and the general population toward other racial minoritize groups.¹³ All 4 IATs were positively correlated with each other (suggesting that they are capturing clinician bias in similar ways) and negatively correlated with participants’ self-reported awareness of their own implicit bias as expected (i.e., those who demonstrated greater implicit bias reported less personal awareness and concern for implicit bias). See Online Supplement for psychometrics and correlation tables.

Discussion

These 2 studies on school mental health clinicians’ stereotype knowledge and implicit bias contribute foundational knowledge toward developing interventions to address implicit racial bias among mental health professionals working in schools—the setting where youths are most likely to access mental health services.⁹

Knowledge of stereotypes is a critical antecedent to biased care because stereotype knowledge can cause biased behavior even when clinicians do not endorse those stereotypes. Findings from Study-1 suggest that most school mental health clinicians are aware of stereotypes of Latinx and Black youth. Several stereotypes were roughly equally attributed to both Black and Latinx youth, including “academic failure,” “delinquency/rule-breaking,” and being “unmotivated,” but “anger/aggression” was clearly more often identified for Black than Latinx youth. The content of these stereotypes sheds light on putative mechanisms through which clinician bias can lead to care disparities. For example, implicit associations of Black youth with anger and aggression may lead to over-identification of oppositional defiant and conduct disorder and under-identification of other diagnostic explanations of non-compliant behavior such as Attention Deficit / Hyperactivity Disorder. Similarly, if Latinx and Black youths’ school disengagement was interpreted as just part of the stereotypical academic failure attributable to lack of motivation or delinquency associated with BLY, learning disabilities or internalizing disorders such as depression or anxiety could go under-identified and unsupported.¹⁴

Results of Study-2 not only substantiate the presence of implicit bias among mental health professionals, similar to other healthcare providers, but also demonstrate that those biases apply to youth consistent with previous findings with other youth-oriented professionals.⁸ Study-2 also provides 4 new IATs to support the study of implicit racial biases toward youth (available from corresponding author upon request), with the Latinx/NHW IATs being especially novel given that previous studies of implicit racial bias has focused predominantly on Black/White comparisons. Given the possible negative downstream impacts of implicit bias on minoritized youth, the availability of these research tools allows the field to not only better detect implicit bias but more effectively measure the impact of interventions to reduce implicit bias.

The small sample sizes of both studies limit the generalizability of findings, such that replication is needed before firm conclusions can be drawn. Commonly cited limitations of the IAT are also relevant, particularly those related to the IAT being a measure of relative bias (e.g., pro-White/anti-Black) as opposed to assessing bias about a single construct. In other words, although we know that Study-2 finds that school-based clinicians held stronger implicit associations of BLY with negativity, defiance, and academic failure relative to White youth, we cannot make inferences about the strength of these associations in absolute terms.

Conclusion

Together, these studies are a first examination of school mental health clinicians’ stereotype knowledge and implicit racial bias about youth. They provide important foundational knowledge and research tools (new IATs) to better understand how clinician bias contributes to biased care and inequitable outcomes in youth mental health.

Highlights.

• Clinician bias has long been identified as a key contributing factor to healthcare disparities, but previous research rarely studied bias among mental health professionals.

• School-based mental health clinicians identified distinct stereotypes associated with Black and Latinx youth including academic failure for both groups and anger/aggression more frequently for Black youth.

• School-based mental health professionals evidenced pro-White/anti-Black, and anti-Latinx biases toward school-age youth at levels similar to those of other healthcare professionals and the general population toward marginalized groups.