Within-person dynamics of attention to race and expression of race bias: a real-time test of the self-regulation of prejudice model

Prior research has supported some aspects of a theorized prejudice self-regulation model. We provide the first test of the full model-based process of bias regulation as it unfolds in real time. Event-related potentials (ERPs) were recorded from White undergraduates at two large American universities (N = 130; 40% female) during a racial stereotype priming task. Attention to Black male face primes, indexed by the P2 ERP, increased following self-regulation failures. In turn, within-person, trial-to-trial variability in attention to Black male faces predicted variability in bias expression. The latter effect was moderated by individual differences in internal motivation to respond without prejudice (IMS). Specifically, among lower-IMS individuals, trials in which Black faces elicited relatively larger P2 amplitudes (relative to an individual's own average P2 amplitude) were associated with increased behavioral race bias. In contrast, and consistent with theory, among higher-IMS individuals trials in which Black faces elicited larger relative P2 amplitudes were associated with decreased bias. Findings provide direct evidence supporting the temporal sequencing of race-bias regulation and identify within-person variability in attention to race as a potential mechanism for determining when and in whom bias will be regulated.

Implicit bias assessment by career stage in medical education training: a narrative review

Implicit biases involve associations outside conscious awareness that lead to a negative evaluation of a person based on individual characteristics. Early evaluation of implicit bias in medical training can prevent long-term adverse health outcomes related to racial bias. However, to our knowledge, no present studies examine the sequential assessment of implicit bias through the different stages of medical training. The objective of this narrative review is to examine the breadth of existing publications that assess implicit bias at the current levels of medical training, pre-medical, graduate, and postgraduate. Protocol for this study was drafted using the Scale for the Assessment of Narrative Reviews (SANRA). Keyword literature search on peer-reviewed databases Google Scholar, PubMed, Ebsco, ScienceDirect, and MedEd Portal from January 1, 2017, to March 1, 2022, was used to identify applicable research articles. The online database search identified 1,512 articles. Full screening resulted in 75 papers meeting the inclusion criteria. Over 50% of extracted papers (74%) were published between 2019 and 2021 and investigated implicit bias at the post-graduate level (43%), followed by the graduate level (34%), and pre-medical level (9.4%). Fourteen percent were classified as mixed. Studies at the medical and medical graduate level identified an implicit preference towards white, male, non-LGBTQIA+, thin, patients. Study findings highlight notable gaps within the sequential assessment of implicit bias, specifically at the pre-medical training level. Longitudinal epidemiological research is needed to examine the long-term effect of implicit biases on existing healthcare disparities.

Establishing and evaluating trustworthy AI: overview and research challenges

Artificial intelligence (AI) technologies (re-)shape modern life, driving innovation in a wide range of sectors. However, some AI systems have yielded unexpected or undesirable outcomes or have been used in questionable manners. As a result, there has been a surge in public and academic discussions about aspects that AI systems must fulfill to be considered trustworthy. In this paper, we synthesize existing conceptualizations of trustworthy AI along six requirements: (1) human agency and oversight, (2) fairness and non-discrimination, (3) transparency and explainability, (4) robustness and accuracy, (5) privacy and security, and (6) accountability. For each one, we provide a definition, describe how it can be established and evaluated, and discuss requirement-specific research challenges. Finally, we conclude this analysis by identifying overarching research challenges across the requirements with respect to (1) interdisciplinary research, (2) conceptual clarity, (3) context-dependency, (4) dynamics in evolving systems, and (5) investigations in real-world contexts. Thus, this paper synthesizes and consolidates a wide-ranging and active discussion currently taking place in various academic sub-communities and public forums. It aims to serve as a reference for a broad audience and as a basis for future research directions.

A Systematic Review of Empirical Studies Measuring Training Effects on Biases Evidenced by Professionals toward Intimate Partner Violence

A professional's response to a client's disclosure of intimate partner violence (IPV) is shown to significantly impact client outcomes. The quality of a professional's response is largely influenced by that professional's beliefs or biases surrounding IPV. This systematic review examined empirical studies conducted in North America and published between 2000 and 2020 evaluating training effects on biases held by professional groups toward victim-survivors of IPV. Search and extraction were conducted in accordance with preferred reporting items for systematic reviews and meta-analyses standards across seven electronic databases. A total of 17 studies met inclusion criteria. Participant groups included professionals from medical, academic, and social/community service disciplines. All included studies reported significant gains on at least one measure of bias. Upon visual inspection, we found no correlations between characteristics of training interventions and reported outcomes on measures of bias. We discuss results in terms of challenges to measuring bias and functional relationships between training interventions, measures of bias, and professional behavior. Variation presented across studies within and between disciplines in regards to training methodology and measurement of bias. Experts in the field of IPV call for a more cohesive approach. We propose the behavior analytic conceptualization of bias as a framework through which interdisciplinary efforts might be unified toward addressing IPV-related biases. Through this lens, we discuss environmental cues within professional settings that might be influencing problematic IPV-related bias. We offer preliminary recommendations for curricular enhancements. We advocate for revision of terms commonly used in IPV-related research and intervention to better reflect and honor diversity across persons experiencing IPV.

Implicit racial biases are lower in more populous more diverse and less segregated US cities

Implicit biases - differential attitudes towards members of distinct groups - are pervasive in human societies and create inequities across many aspects of life. Recent research has revealed that implicit biases are generally driven by social contexts, but not whether they are systematically influenced by the ways that humans self-organize in cities. We leverage complex system modeling in the framework of urban scaling theory to predict differences in these biases between cities. Our model links spatial scales from city-wide infrastructure to individual psychology to predict that cities that are more populous, more diverse, and less segregated are less biased. We find empirical support for these predictions in U.S. cities with Implicit Association Test data spanning a decade from 2.7 million individuals and U.S. Census demographic data. Additionally, we find that changes in cities' social environments precede changes in implicit biases at short time-scales, but this relationship is bi-directional at longer time-scales. We conclude that the social organization of cities may influence the strength of these biases.

Defensiveness Toward IAT Feedback Predicts Willingness to Engage in Anti-Bias Behaviors

People who are more defensive about their feedback on the Race-Attitudes Implicit Association Test (IAT) are less willing to engage in anti-bias behaviors. Extending on this work, we statistically clarified defensiveness constructs to predict willingness to engage in anti-bias behaviors among people who received pro-White versus no-bias IAT feedback. We replicated the finding that U.S. Americans are generally defensive toward pro-White IAT feedback, and that more defensiveness predicts less willingness to engage in anti-bias behaviors. However, people who believed their pro-White IAT feedback was an inaccurate reflection of their "true attitudes" were more willing to engage in anti-bias behaviors compared with people who received no-bias IAT feedback. These results better illuminate the defensiveness construct suggesting that receiving self-threatening feedback about bias may motivate people's willingness to engage in anti-bias behaviors in different ways depending on how people respond to that feedback.

Stuck on Intergroup Attitudes: The Need to Shift Gears to Change Intergroup Behaviors

Decades of research on how to improve intergroup relations have primarily examined ways to change prejudiced attitudes. However, this focus on negative intergroup attitudes has yielded few effective solutions. Because intergroup relations are shaped by behavior during intergroup interactions, it is necessary to identify constructs that have a strong causal impact on intergroup behavior change. In this article, I will discuss evidence showing that intergroup attitude change is neither a sufficient nor necessary cause for intergroup behavior change. Empirical research suggests that intergroup attitudes are difficult to change and have a limited effect on intergroup behavior. I also distinguish between constructs that primarily affect intergroup attitude change (e.g., counterstereotypical exemplars, evaluative conditioning) and constructs that primarily affect intergroup behavior change (e.g., social norms, self-efficacy). Further, suggestions for future research will also be provided to advance understanding of the various psychological constructs that influence intergroup behavior change, which will help us develop effective methods of improving intergroup relations.

Predicting suicidal ideation in psychiatrically hospitalized veterans using the death/suicide Implicit Association Test: A prospective cohort study

INTRODUCTION

We investigated whether the Death/Suicide Implicit Association Test (D/S-IAT) predicted suicidal ideation (SI) in psychiatric inpatients.

METHODS

One hundred eighty veterans admitted for either SI or suicidal behavior (SB) (the primary sample) (N = 90) or alcohol detoxification (N = 90) completed the D/S-IAT and scales measuring SI. Correlation and regression coefficients were measured between the D/S-IAT (as a full-scale or dichotomized score [D > 0]) and self-reported current or imminent SI (over the next 1-3 days).

RESULTS

In the primary sample, the full-scale D/S-IAT was significantly correlated with the intensity of current SI (r = 0.22, p = 0.04) and especially with wishes to be dead (r = 0.35, p < 0.001). The intensity of imminent SI was significantly predicted by the full-scale (p = 0.02) and dichotomized D/S-IAT score (p = 0.05) in a multiple regression model. However, no significant associations were observed when both the D/S-IAT score and current (present/absent) or imminent SI (occurred/did not occur) were dichotomous measures. In participants receiving alcohol detoxification, the D/S-IAT significantly predicted only wishes to be dead (r = 0.33, p < 0.001).

CONCLUSION

The full-scale D/S-IAT score predicted the current intensity of wishes to be dead in both inpatient samples, and current and imminent SI in participants admitted for SI/SB. The dichotomized D/S-IAT score did not predict the simple occurrence of SI.

How to Build and How not to Build an Implicit Measure in Behavior Analysis: A case Study Using the Function Acquisition Speed Test

This article provides a comprehensive overview of the development of a behavior-analytic alternative to the popular implicit association test (IAT), namely, the function acquisition speed test (FAST). The IAT appears, prima facia, to indirectly assess participants' learning histories with regard to the categorization of stimuli. However, its origin within cognitive psychology has rendered it replete with mentalism, conceptual ambiguity, statistical arbitrariness, and confounding procedural artifacts. The most popular behavioral alternative to the IAT, the widely used implicit relational assessment procedure (IRAP), has inherited many of these concerning artifacts. In this article, we present a behavior-analytic critique of both the IAT and IRAP, and argue that a behavior-analytic approach to implicit measures must have stimulus control front and center in its analysis. We then outline a series of early research studies that provided the basis for a potentially superior procedure within our field. We go on to outline how this early research was harnessed in stepwise research, guided by a strict adherence to traditional behavior-analytic methods for the analysis of stimulus relations, to increasingly modify a test format fit for the behavior analyst interested in assessing stimulus relatedness.

A Call to Action on Assessing and Mitigating Bias in Artificial Intelligence Applications for Mental Health

Advances in computer science and data-analytic methods are driving a new era in mental health research and application. Artificial intelligence (AI) technologies hold the potential to enhance the assessment, diagnosis, and treatment of people experiencing mental health problems and to increase the reach and impact of mental health care. However, AI applications will not mitigate mental health disparities if they are built from historical data that reflect underlying social biases and inequities. AI models biased against sensitive classes could reinforce and even perpetuate existing inequities if these models create legacies that differentially impact who is diagnosed and treated, and how effectively. The current article reviews the health-equity implications of applying AI to mental health problems, outlines state-of-the-art methods for assessing and mitigating algorithmic bias, and presents a call to action to guide the development of fair-aware AI in psychological science.

Automatic pro-thin/anti-fat biases can develop without previous visual exposure to body shapes

Endorsement of the thin beauty ideal increases risk for future body dissatisfaction and eating disorders among women. Visual-based media is theorized to be a central pathway through which the thin ideal is internalized. This internalization process results in formation of automatic pro-thin and anti-fat attitudes. However, it is often difficult to separate the contribution of visual-based media and other forms of communication in the creation of such attitudes. Using a novel auditory implicit association test, we show that women with congenital blindness with no previous exposure to body shapes develop automatic pro-thin and anti-fat attitudes to the same extent as sighted women. This result was replicated in studies conducted in two countries involving a combined total of 62 women with blindness and 80 sighted women. Results suggest that internalization of the thin ideal can occur without visual exposure to images of the thin beauty ideal or visual exposure to one's own body.

Individual Differences in Implicit Bias Can Be Measured Reliably by Administering the Same Implicit Association Test Multiple Times

The use of the Implicit Association Test (IAT) as a measure of individual differences is stymied by insufficient test-retest reliability for assessing trait-level constructs. We assess the degree to which the IAT measures individual differences and test a method to improve its validity as a "trait" measure: aggregating across IATs. Across three studies, participants (total n = 960) completed multiple IATs in the same session or across multiple sessions. Using latent-variable models, we found that half of the variance in IAT scores reflects individual differences. Aggregating across multiple IATs approximately doubled the variance explained with explicit measures compared with a single IAT D-score. These findings show that IAT scores contain considerable noise and that a single IAT is inadequate to estimate trait bias. However, aggregation across multiple administrations can correct this and better estimate individual differences in implicit attitudes.

Integrating Diversity, Equity, and Inclusion Readings within Coursework: Suggestions for Instructors Teaching Behavior Analysis

Behavior analysis graduate programs must train their students to be culturally responsive so that they are prepared to effectively serve a diverse clientele. One important strategy for helping students gain a culturally responsive repertoire is embedding diversity, equity, and inclusion materials into behavior analysis graduate course sequences. However, little guidance exists for selecting content related to diversity, equity, and inclusion within behavior analysis to include in behavior analytic coursework. This article provides suggested readings for diversity, equity, and inclusion within behavior analysis that can be embedded into typical course structures in behavior analysis graduate programs. Each course requirement in the Association for Behavior Analysis International's Verified Course Sequence is given specific recommendations.

Testing the effectiveness of a mobile approach avoidance intervention and measuring approach biases in an ecological momentary assessment context: study protocol for a randomised-controlled trial

INTRODUCTION

Unhealthy eating behaviour is a major contributor to obesity and related diseases and is associated with a behavioural bias to approach rather than avoid desired foods, as measured with reaction time tasks. Approach-avoidance interventions (AAIs) have been proposed as a way to modify food evaluations and help people to eat in accordance with their dietary goals. Mobile implementations of AAI might be easily accessible, low threshold interventions, but their effectiveness has not been established yet.

METHODS AND ANALYSIS

Participants who aim to change their eating behaviour are randomised to intervention or control groups. They complete six sessions of a smartphone-based AAI, in which they push (ie, avoid) or pull (ie, approach) personalised food images. Intervention group participants always avoid foods that they personally want to eat less often and approach foods that they personally want to eat more often. In the control group, images are paired equally often with both response directions. To evaluate contextual and dynamic intervention effects, ecological momentary assessment (EMA) is measured throughout, with questions about food intake, hunger, stress, emotions, eating intentions, food craving and impulsivity twice a day. Additional EMA preintervention and postintervention measures are administered before and after the intervention phase (4 days each) with a 1-day follow-up EMA 4 weeks after the intervention. Multilevel models will examine the temporal covariance between approach bias and self-reported variables as well as short-term and long-term intervention effects on approach bias, food intake and craving.

ETHICS AND DISSEMINATION

The study was approved by the Ethics Committee of the University of Salzburg. Results will be published in peer-reviewed scientific journals and presented at scientific conferences.

TRIAL REGISTRATION NUMBER

German Clinical Trials Register DRKS, registration number DRKS00030780.

Fighting bias with bias: How same-race endorsements reduce racial discrimination on Airbnb

Recent studies have documented racial discrimination in online interactions, mirroring the historic bias observed offline. The sharing economy is especially vulnerable due to greater dependence on mutual trust in sharing a ride, residence, or date with a stranger. These services rely on user recommendations to build trust, but the effects of these peer evaluations on racial bias are only beginning to be explored. Using data from Airbnb, we examine in-group preference for same-race hosts as well as same-race recommendations. The unexpected result is that these two manifestations of racial bias are offsetting, not reinforcing. White guests largely overcame their racial bias in host selection when hosts were endorsed by previous white guests. Moreover, we found no evidence of racial bias in the affective enthusiasm of endorsements, which suggests that the preference for same-race endorsements is motivated by the race of the recommender, not the content of the recommendation.

Visual biases in evaluation of speakers' and singers' voice type by cis and trans listeners

Introduction

A singer's or speaker's Fach (voice type) should be appraised based on acoustic cues characterizing their voice. Instead, in practice, it is often influenced by the individual's physical appearance. This is especially distressful for transgender people who may be excluded from formal singing because of perceived mismatch between their voice and appearance. To eventually break down these visual biases, we need a better understanding of the conditions under which they occur. Specifically, we hypothesized that trans listeners (not actors) would be better able to resist such biases, relative to cis listeners, precisely because they would be more aware of appearance-voice dissociations.

Methods

In an online study, 85 cisgender and 81 transgender participants were presented with 18 different actors singing or speaking short sentences. These actors covered six voice categories from high/bright (traditionally feminine) to low/dark (traditionally masculine) voices: namely soprano, mezzo-soprano (referred to henceforth as mezzo), contralto (referred to henceforth as alto), tenor, baritone, and bass. Every participant provided voice type ratings for (1) Audio-only (A) stimuli to get an unbiased estimate of a given actor's voice type, (2) Video-only (V) stimuli to get an estimate of the strength of the bias itself, and (3) combined Audio-Visual (AV) stimuli to see how much visual cues would affect the evaluation of the audio.

Results

Results demonstrated that visual biases are not subtle and hold across the entire scale, shifting voice appraisal by about a third of the distance between adjacent voice types (for example, a third of the bass-to-baritone distance). This shift was 30% smaller for trans than for cis listeners, confirming our main hypothesis. This pattern was largely similar whether actors sung or spoke, though singing overall led to more feminine/high/bright ratings.

Conclusion

This study is one of the first demonstrations that transgender listeners are in fact better judges of a singer's or speaker's voice type because they are better able to separate the actors' voice from their appearance, a finding that opens exciting avenues to fight more generally against implicit (or sometimes explicit) biases in voice appraisal.

Actively Addressing Systemic Racism Using a Behavioral Community Approach

Recent police brutality and related violence against Black people, coupled with the COVID-19 pandemic, has further evidenced the disproportionate impact of systemic racism in our institutions and across society. In the United States, the alarming mortality rates for Black people due to police violence and COVID-19 related deaths are clear demonstrations of inequities within a long history of disparate outcomes. In understanding systemic racism, it is essential to consider how it is embedded within society and across socio-ecological levels. The Social-Ecological Model (SEM) is used to examine conditions within the environment that maintain systemic racism, including within our field and discipline. A behavioral-community approach for examining racism aids in determining points of intervention across multiple ecological levels that may contribute to behavior change, including with behaviorists. The science of behavior is well-suited to help examine the contingencies governing behaviors within and across systems, which is pivotal for addressing operant behaviors to influence long-term behavior change. This paper calls on the behavioral community to address systemic racism within our environments and systems of influence to contribute to a more equitable community. Systemic racism, including within the context of anti-Blackness, is examined by considering behavior change strategies that can be supported by behaviorists across socio-ecological levels. Tools for collaborative action are provided to support behaviorists in demonstrating the skills needed across a continuum of behaviors from allyship to anti-racism to actively address systemic racism.

Whose metaphor? Rethinking conceptual metaphor in Lacanian terms

Recent research on the psychology of metaphor is based primarily on the cognitivist framework provided by conceptual metaphor theory (Lakoff & Johnson, 1980). This approach has been generative and does much to explain the pervasive role that metaphoric language plays in everyday life. However, interest in metaphor is not limited to this cognitive approach; Lacan accorded metaphor a central role in his psychoanalytic understanding of the process of signification that structures language and, thereby, the unconscious. Although the two frameworks have different assumptions and aims, they are largely compatible ways of thinking about the role of metaphor in psychology. The goal of this article is to briefly introduce both approaches and ultimately to suggest several key insights about metaphor that could be gained through a greater attention to Lacanian psychoanalysis.

Why Antibias Interventions (Need Not) Fail

There is a critical disconnect between scientific knowledge about the nature of bias and how this knowledge gets translated into organizational debiasing efforts. Conceptual confusion around what implicit bias is contributes to misunderstanding. Bridging these gaps is the key to understanding when and why antibias interventions will succeed or fail. Notably, there are multiple distinct pathways to biased behavior, each of which requires different types of interventions. To bridge the gap between public understanding and psychological research, we introduce a visual typology of bias that summarizes the process by which group-relevant cognitions are expressed as biased behavior. Our typology spotlights cognitive, motivational, and situational variables that affect the expression and inhibition of biases while aiming to reduce the ambiguity of what constitutes implicit bias. We also address how norms modulate how biases unfold and are perceived by targets. Using this typology as a framework, we identify theoretically distinct entry points for antibias interventions. A key insight is that changing associations, increasing motivation, raising awareness, and changing norms are distinct goals that require different types of interventions targeting individual, interpersonal, and institutional structures. We close with recommendations for antibias training grounded in the science of prejudice and stereotyping.

Integrating mindfulness and connection practices into preservice teacher education results in durable automatic race bias reductions

Automatic race bias, which is the tendency to associate positive attributes more quickly with White as compared to Black faces, reflects enculturation processes linked to inequitable teaching behaviors. In sample of undergraduate preservice teachers (N = 88), we examined whether a novel mindfulness and connection practice intervention without anti-bias content incorporated into undergraduate teacher education would result in reduced automatic race bias favoring White faces. Random assignment to the intervention predicted significantly reduced race preference for White child faces immediately after the intervention. These significant reductions persisted at the 6-month follow-up, which are the most durable reductions in automatic race bias reported to date in adults. Data from semi-structured interviews indicated that the intervention enhanced self-awareness and self-regulation while reducing automatic responding among preservice teachers. These qualities are instrumental to adaptive teaching and putative mechanisms for reducing automatic race bias. The potential value of integrating mindfulness and connection practices into undergraduate preservice teacher education is discussed.

Developing Cultural Awareness Curricular Competencies for Humanitarian Non-Governmental Organization Staff

BACKGROUND

Cultural awareness is an important part of organizational success when interacting with multiple cultures. Research has shown a dearth of standardized cultural awareness training programs for non-governmental humanitarian organization staff.

PURPOSE

This study aims to develop an expert-consensus set of cultural awareness competencies as the basis for development of humanitarian staff cultural awareness trainings.

METHODS

A modified Delphi process was selected. The first round of surveys collected a list of cultural awareness competencies from experts in the fields of non-governmental organization (NGO) operations and cultural awareness education and research. This collated list of competencies was then used as the basis of a survey obtaining ratings by the group on a five-point Likert scale. Competencies which achieved an average rating of 4.0 or higher were considered to be "important" for inclusion in future training programs.

RESULTS

A total of 67.9% of contacted experts agreed to participate, with 84.2% of those completing all rounds of the survey. This group developed a list of ten competencies, including: Cultural Awareness/Sensitivity and Intercultural Communication; Cultural Intelligence; Unconscious Bias/Diversity Awareness; a Universal Declaration of Ethical Principles; Gender and Lesbian, Gay, Bisexual, Transgender, Queer, and Other Sexual Identities (LGBTQ+) Issues and Safety; Analytical and Critical Thinking Skills; Negotiation; Program Mission; Power Dynamics; and Empathy.

CONCLUSIONS

This study defined a set of ten expert-consensus cultural awareness competencies which can be a basis for future NGO staff training. Future work can both use these competencies to create educational programs and further define and expand the set of competencies based on analyses of their implementation.

Specificity and incremental predictive validity of implicit attitudes: studies of a race-based phenotype

Four studies involving 2552 White American participants were conducted to investigate bias based on the race-based phenotype of hair texture. Specifically, we probed the existence and magnitude of bias in favor of Eurocentric (straight) over Afrocentric (curly) hair and its specificity in predicting responses to a legal decision involving the phenotype. Study 1 revealed an implicit preference, measured by an Implicit Association Test (IAT), favoring Eurocentric over Afrocentric hair texture among White Americans. This effect was not reducible to a Black/White implicit race attitude nor to mere perceptual preference favoring straight over curly hair. In Study 2, the phenotype (hair) IAT significantly and uniquely predicted expressions of support in response to an actual legal case that involved discrimination on the basis of Afrocentric hair texture. Beyond replicating this result, Studies 3 and 4 (the latter preregistered) provided further, and even more stringent, evidence for incremental predictive validity: in both studies, the phenotype IAT was associated with support for a Black plaintiff above and beyond the effects of two parallel explicit scales and, additionally, a race attitude IAT. Overall, these studies support the idea that race bias may be uniquely detected by examining implicit attitudes elicited by group-based phenotypicality, such as hair texture. Moreover, the present results inform theoretical investigations of the correspondence principle in the context of implicit social cognition: they suggest that tailoring IATs to index specific aspects of an attitude object (e.g., by decomposition of phenotypes) can improve prediction of intergroup behavior.

A faculty and staff workshop on microaggression and implicit bias: Knowledge and awareness of student, faculty, and staff experiences

BACKGROUND AND PURPOSE

This paper describes the context and experiences of a workshop to raise knowledge and awareness of a college of pharmacy's faculty and staff about microaggressive behaviors and implicit biases. The workshop was intended to provide a non-threatening, interactive, and informative professional development program to demonstrate the cumulative marginalizing effects on students, faculty, and staff who may perceive themselves as targets.

EDUCATIONAL ACTIVITY AND SETTING

A half-day workshop was conducted during July 2018. Participants were initially provided with definitions and categories of microaggression and implicit bias. To bring the subject matter "alive" and foster receptivity, interactive videos were shown with scenarios depicting situations reflective of microaggressions and implicit biases. College faculty, staff, and students made these relatable. To foster objectivity, an outside consultant was hired to facilitate the ensuing roundtable and plenary discussions.

FINDINGS

Sixty-eight participants responded to a pre-survey designed by the workshop team, and 78% indicated never having attended a training/seminar on microaggression and/or implicit bias. Sixty-two individuals responded to the post-survey with 92% indicating increased knowledge gained from workshop. Anecdotal reports suggested that the workshop had an ongoing impact, as faculty and staff continued the discussions in subsequent months and requested additional training sessions.

SUMMARY

The workshop heightened awareness and increased faculty and staff knowledge on microaggressive behaviors, implicit biases, and the potential consequences thereof. It also demonstrated the importance of addressing conversations that are perceived as difficult, in order to create a diverse and inclusive workplace and learning environment for all.

Guidance for Behavior Analysts in Addressing Racial Implicit Bias

In the practice of applied behavior analysis (ABA) treatment, implicit bias, which can be defined in behavioral terms, needs to be addressed because it may inadvertently lead to overt forms of discrimination on the basis of race. Although little research has been conducted within the field of ABA on racial implicit bias, information gathered from related fields can provide insight as to how behavior analysts can promote positive change in this area. Drawing from existing literature, recommendations are provided regarding assessment and administration of interventions to reduce racial implicit bias for clinicians. The purpose of this article is to provide strategies that behavior analysts can implement to assess and reduce behaviors related to implicit bias exhibited by practitioners, thereby reducing racial discrimination with clients and staff.

Attitudes as propositional representations

Attitudes are mental representations that help to explain why stimuli evoke positive or negative responses. Until recently, attitudes were often thought of as associations in memory. This idea inspired extensive research on evaluative conditioning (EC) and implicit evaluation. However, attitudes can also be seen as propositional representations, which, unlike associations, specify relational information and have a truth value. We review research on EC and implicit evaluation that tested the basic tenets of the propositional perspective on attitudes. In line with this perspective, studies show that both phenomena are moderated by relational and truth information. We discuss implications for the prediction and influencing of seemingly irrational behavior such as excessive alcohol intake and implicit racial bias.

Examining Automatic Stereotyping From a Propositional Perspective: Is Automatic Stereotyping Sensitive to Relational and Validity Information?

Research on automatic stereotyping is dominated by the idea that automatic stereotyping reflects the activation of (group-trait) associations. In two preregistered experiments (total N = 391), we tested predictions derived from an alternative perspective that suggests that automatic stereotyping is the result of the activation of propositional representations that, unlike associations, can encode relational information and have truth values. Experiment 1 found that automatic stereotyping is sensitive to the validity of information about pairs of traits and groups. Experiment 2 showed that automatic stereotyping is sensitive to the specific relations (e.g., whether a particular group is more or less friendly than a reference person) between pairs of traits and groups. Interestingly, both experiments found a weaker influence of validity/relational information on automatic stereotyping than on non-automatic stereotyping. We discuss the implications of these findings for research on automatic stereotyping.

On the Uncanny Similarities Between Police Brutality and Client Mistreatment

Direct-care staff are responsible for carrying out behavior-analytic services in a culture that perpetuates systemic racism and other problematic systems that can lead to the mistreatment of clients. Limited data exist on factors that influence the mistreatment of clients, so behavior analysts must look to better studied comparison contexts as a way to identify risk factors. Police brutality is one context where problematic systems are apparent. Therefore, examining variables known to affect police brutality offers one way to identify aspects of direct-care staff's implementation of behavior-analytic treatment that may harbor similar systems. The purpose of this article is to examine variables associated with police brutality as risk factors for the mistreatment of clients in direct-care settings. The primary risk factors discussed include racial bias, the warrior mentality, a lack of transparency and accountability, and ineffective intervention. This article concludes that the field of behavior analysis needs sensitive data collection methods and systematic evaluation of risk factors to better protect clients from mistreatment.

Reasons to remember: A functionalist view on the relation between memory and psychopathology

Memory is under investigation as one of the core mechanisms of psychopathology. The traditional cognitive view of memory as a stable structure with a range of set characteristics can be complemented with a perspective that considers remembering as a behaviour that varies fluidly across contexts. Remembering may serve adaptation to the environment by fulfilling a directive function, a self-function and a social function. A failure to fulfil these functions may be a risk factor for psychopathology. Implications of the discussed functionalist perspective include the importance of reinforcing adaptive ways of remembering during early development, the possibility of treating maladaptive ways of remembering through contextual interventions and the added ecological validity of using ambulatory assessment methods.

Validity evidence for a novel instrument assessing medical student attitudes toward instruction in implicit bias recognition and management

BACKGROUND

Implicit bias instruction is becoming more prevalent in health professions education, with calls for skills-based curricula moving from awareness and recognition to management of implicit bias. Evidence suggests that health professionals and students learning about implicit bias ("learners") have varying attitudes about instruction in implicit bias, including the concept of implicit bias itself. Assessing learner attitudes could inform curriculum development and enable instructional designs that optimize learner engagement. To date, there are no instruments with evidence for construct validity that assess learner attitudes about implicit bias instruction and its relevance to clinical care.

METHODS

The authors developed a novel instrument, the Attitude Towards Implicit Bias Instrument (ATIBI) and gathered evidence for three types of construct validity- content, internal consistency, and relationship to other variables.

RESULTS

Authors utilized a modified Delphi technique with an interprofessional team of experts, as well as cognitive interviews with medical students leading to item refinement to improve content validity. Seven cohorts of medical students, N = 1072 completed the ATIBI. Psychometric analysis demonstrated high internal consistency (α = 0.90). Exploratory factor analysis resulted in five factors. Analysis of a subset of 100 medical students demonstrated a moderate correlation with similar instruments, the Integrative Medicine Attitude Questionnaire (r = 0.63, 95% CI: [0.59, 0.66]) and the Internal Motivation to Respond Without Prejudice Scale (r = 0.36, 95% CI: [0.32, 0.40]), providing evidence for convergent validity. Scores on our instrument had low correlation to the External Motivation to Respond Without Prejudice Scale (r = 0.15, 95% CI: [0.09, 0.19]) and the Groningen Reflection Ability Scale (r = 0.12, 95% CI: [0.06, 0.17]) providing evidence for discriminant validity. Analysis resulted in eighteen items in the final instrument; it is easy to administer, both on paper form and online.

CONCLUSION

The Attitudes Toward Implicit Bias Instrument is a novel instrument that produces reliable and valid scores and may be used to measure medical student attitudes related to implicit bias recognition and management, including attitudes toward acceptance of bias in oneself, implicit bias instruction, and its relevance to clinical care.

Physician gender as a source of implicit bias affecting clinical decision-making processes: a scoping review

BACKGROUND

The demographic profile of practicing physicians is changing as more female medical students are graduating and practicing in the field. While the education received may not differ by gender, studies have shown that physician practice outcomes vary by provider gender. Various factors could contribute to these differences, including culture and explicit biases which may lead to implicit bias. This study aims to identify the available evidence of gender-based implicit bias throughout the delivery process of medicine.

METHODS

This scoping review evaluated published literature within the PubMed, Ovid MEDLINE, PsychINFO, Web of Science, and BioMed Central databases pertaining to physician's gender as a factor in the delivery of medicine. Arksey and O'Malley's six-stage methodology was used as a framework and reported using the updated Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR). Searches occurred between May 2020 and June 2020, and the timeframe was not limited. Included articles had gender as a factor in the delivery of medicine and implicit bias. Articles were excluded if they did not include the gender of the physician. After screening by reviewers and a medical librarian, study characteristics were charted and analyzed.

RESULTS

The initial search resulted in 2420 records. After screening, 162 of the records were selected based on title and keyword relevance. After additional screening, 15 records were ultimately included in the review based on full-text evaluation. Records were organized into sub-topics post hoc focused on clinical qualities, diagnostics, treatment, and outcomes.

CONCLUSION

This scoping review found that gender-based implicit bias may be inadvertently acquired from culture and education. Although implicit bias is highly researched, much of the current literature focuses on the gender of the patient. This study found important gaps in the available literature regarding race and gender of the physician. Further studies could explore outcome differences between recent graduates and career physicians, for both female and male physicians.

A Behavioral Analysis of Two Strategies to Eliminate Racial Bias in Police Use of Force

Structural racism is rooted in American social systems that were supposedly designed to promote citizens' right to life, liberty, and the pursuit of happiness. Social systems like policing, for example, are built on a foundation of discriminatory practices designed to disenfranchise Black, Indigenous, and people of color (BIPOC). One of the most recent visible examples of racially biased policing is the excessive use of force by officers toward BIPOC. In response, advocates, policy makers, and researchers have sought solutions. Police use-of-force reforms such as body-worn cameras (BWCs) and implicit bias training (IBT) have become popular and are currently being applied in many police departments across the country. However, evidence supporting the effectiveness of these reform strategies to reduce the use of force is mixed, and further evaluations are needed to understand why these strategies are purported to be an effective solution. The purpose of the current review is to ignite future empirical evaluations of use-of-force reform. Following a summary of the research conducted to date on BWCs and IBT, we will conclude with a brief discussion of how behavior analysts might improve and foster strategies that are efficacious. Our ultimate goal is to leave the reader with an understanding of where the data have taken us thus far and how behavior analysts and others can contribute to the reduction and eradication of the discriminatory practices present in policing and other social systems.

Accurate by Being Noisy: A Formal Network Model of Implicit Measures of Attitudes

In this article, we model implicit attitude measures using our network theory of attitudes. The model rests on the assumption that implicit measures limit attitudinal entropy reduction, because implicit measures represent a measurement outcome that is the result of evaluating the attitude object in a quick and effortless manner. Implicit measures therefore assess attitudes in high entropy states (i.e., inconsistent and unstable states). In a simulation, we illustrate the implications of our network theory for implicit measures. The results of this simulation show a paradoxical result: Implicit measures can provide a more accurate assessment of conflicting evaluative reactions to an attitude object (e.g., evaluative reactions not in line with the dominant evaluative reactions) than explicit measures, because they assess these properties in a noisier and less reliable manner. We conclude that our network theory of attitudes increases the connection between substantive theorizing on attitudes and psychometric properties of implicit measures.

Research With Implicit Measures: Suggestions for a New Agenda of Sub-Personal Psychology

Research with implicit measures has been criticized for an unclear meaning of the term implicit and inadequate psychometric properties, as well as problems regarding internal validity and low predictive validity of implicit measures. To these criticisms, we add an overly restrictive theoretical focus and research agenda that is limited to the narrow dichotomy between associations versus propositional beliefs. In this article, we address the last problem by introducing a new perspective of a sub-personal psychology. This broad approach expands the conceptual horizon in order to make use of the full potential that experimental paradigms can offer for assessing, explaining, predicting, and modifying human functioning and behavior. Going beyond the analysis of associations and beliefs, we highlight the use of experimental paradigms to examine and modify motivational, environmental, and episodic memory factors that influence human action.

Moving Beyond the Relative Assessment of Implicit Biases: Navigating the Complexities of Absolute Measurement

A relative assessment of implicit biases is limited because it produces a combined summary evaluation of two attitudinal beliefs while concealing the biases driving this evaluation. Similar limitations occur for relative explicit measures. Here, we will discuss the benefits and weaknesses of using relative versus absolute (individual/separate) assessments of implicit and explicit attitudes. The Implicit Association Test (IAT) will be the focal implicit measure discussed, and we will present a new perspective challenging the evidence that the IAT can only be utilized to measure relative, not absolute, implicit attitudes. Modeling techniques (i.e., Quad models) that can determine the separate biases behind the relative summary evaluation will also be considered. Accurately utilizing absolute implicit bias scores will enable academia and industry to answer more complex research questions. For implicit social cognition to maintain and expand its usefulness, we encourage researchers to further test and refine the measurement of absolute implicit biases.

Reflecting on 25 Years of Research Using Implicit Measures: Recommendations for Their Future Use

For more than 25 years, implicit measures have shaped research, theorizing, and intervention in psychological science. During this period, the development and deployment of implicit measures have been predicated on a number of theoretical, methodological, and applied assumptions. Yet these assumptions are frequently violated and rarely met. As a result, the merit of research using implicit measures has increasingly been cast into doubt. In this article, we argue that future implicit measures research could benefit from adherence to four guidelines based on a functional approach wherein performance on implicit measures is described and analyzed as behavior emitted under specific conditions and captured in a specific measurement context. We unpack this approach and highlight recent work illustrating both its theoretical and practical value.

Women's Representation Among Members and Leaders of National Medical Specialty Societies

PURPOSE

National medical specialty societies speak for their respective fields in policy debates, influence research, affect trainees' specialization decisions, provide career development opportunities, and confer awards and recognitions. This study provides a comprehensive overview of the gender demographics of society members and leaders.

METHOD

In 2016, the Group on Women in Medicine and Science (of the Association of American Medical Colleges) sought to characterize the gender of members and leaders of specialty societies from 2000 to 2015. This report provides descriptive data, including how many of the responding societies (representing each of 30 major medical specialties) had substantial (> 10%) increases in women's representation among leadership between the first and second halves of the study period.

RESULTS

The average proportion of full members who were female in responding societies was 25.4% in 2005 and 29.3% in 2015. The proportion of women among those serving as the highest-ranking elected leader between 2000 and 2015 in each specialty ranged from 0% to 37.5% (mean, 15.8%). The mean proportion of women on governing boards ranged from 0% to 37.3% (mean of means, 18.8%) in 2000-2007 and from 0% to 47.6% (mean of means, 25.2%) in 2008-2015. In 9 specialties, the mean percentage of women serving on governing boards increased by over 10% from the first to the second half of the study period.

CONCLUSIONS

Although many women are full members of specialty societies, women still constitute a minority of leaders. This report establishes a baseline from which to evaluate the effect of societies' efforts to improve diversity, equity, and inclusion.

Can Behavior Analysis Help Us Understand and Reduce Racism? A review of the Current Literature

Despite ongoing efforts to eradicate racism, it persists globally, negatively affecting education, mental health, community relations, and economic development. Every behavior analyst can, and should, contribute to the reduction of racism in some way. Unfortunately, little behavior-analytic research exists to guide us. This article proposes ways that members of our scientific community can learn about racism from a behavioral perspective, extend experimental analyses of prejudice, and intervene to reduce racism in varied settings. It describes both traditional behavior-analytic and functional-contextualist accounts of racism and summarizes the small amount of related empirical and applied research. The review suggests that combining traditional behavior-analytic methods with acceptance and commitment training techniques may attenuate racism more effectively. The article ends with a call to collaborate around this globally important issue-and to do more to reduce racism.

Dissociating Automatic Associations: Comparing Two Implicit Measurements of Race Bias

Weak correspondence across different implicit bias tasks may arise from the contribution of unique forms of automatic and controlled processes to response behavior. Here, we examined the correspondence between estimates of automatic and controlled processing derived from two sequential priming tasks with identical structure and timing designed to separately measure stereotypic (Weapons Identification Task; WIT) and evaluative (Affective Priming Task; APT) associations. Across two studies using predominantly White samples, three consistent patterns emerged in the data: (1) stereotypic bias was stronger for Black targets, whereas evaluative bias was stronger for White targets; (2) overall response accuracy bias correlated modestly across the two tasks; and (3) multinomial processing tree estimates of controlled processing corresponded much more strongly than estimates of automatic processing. These findings support models positing distinct learning and memory systems for different forms of race bias, and suggest that these differing forms contribute to estimates of automatic associations.

Can the Implicit Association Test Serve as a Valid Measure of Automatic Cognition? A Response to Schimmack (2021)

Much of human thought, feeling, and behavior unfolds automatically. Indirect measures of cognition capture such processes by observing responding under corresponding conditions (e.g., lack of intention or control). The Implicit Association Test (IAT) is one such measure. The IAT indexes the strength of association between categories such as “planes” and “trains” and attributes such as “fast” and “slow” by comparing response latencies across two sorting tasks (planes–fast/trains–slow vs. trains–fast/planes–slow). Relying on a reanalysis of multitrait–multimethod (MTMM) studies, Schimmack (this issue, p. 396) argues that the IAT and direct measures of cognition, for example, Likert scales, can serve as indicators of the same latent construct, thereby purportedly undermining the validity of the IAT as a measure of individual differences in automatic cognition. Here we note the compatibility of Schimmack’s empirical findings with a range of existing theoretical perspectives and the importance of considering evidence beyond MTMM approaches to establishing construct validity. Depending on the nature of the study, different standards of validity may apply to each use of the IAT; however, the evidence presented by Schimmack is easily reconcilable with the potential of the IAT to serve as a valid measure of automatic processes in human cognition, including in individual-difference contexts.