Do digital technologies reduce racially biased reporting? Evidence from NYPD administrative data.

Recent work has emphasized the disproportionate bias faced by minorities when interacting with law enforcement. However, research on the topic has been hampered by biased sampling in administrative data, namely that records of police interactions with citizens only reflect information on the civilians that police elect to investigate, and not civilians that police observe but do not investigate. In this work, we address a related bias in administrative police data which has received less empirical attention, namely reporting biases around investigations that have taken place. Further, we investigate whether digital monitoring tools help mitigate this reporting bias. To do so, we examine changes in reports of interactions between law enforcement and citizens in the wake of the New York City Police Department's replacement of analog memo books with mobile smartphones. Results from a staggered difference in differences estimation indicate a significant increase in reports of citizen stops once the new smartphones are deployed. Importantly, we observe that the rise is driven by increased reports of "unproductive" stops, stops involving non-White citizens, and stops occurring in areas characterized by a greater concentration of crime and non-White residents. These results reinforce the recent observation that prior work has likely underestimated the extent of racial bias in policing. Further, they highlight that the implementation of digital monitoring tools can mitigate the issue to some extent.

The Black Lives Matter movement mitigates bias against racial minority actors.

Watching movies is among the most popular entertainment and cultural activities. How do viewers react when a movie sequel increases racial minority actors in the main cast ("minority increase")? On the one hand, such sequels may receive better evaluations if viewers appreciate racially inclusive casting for its novel elements (the value-in-diversity perspective) and moral appeal (the fairness perspective on diversity). On the other hand, discrimination research suggests that if viewers harbor biases against racial minorities, sequels with minority increase may receive worse evaluations. To examine these competing possibilities, we analyze a unique panel dataset of movie series released from 1998 to 2021 and conduct text analysis of 312,457 reviews of these movies. Consistent with discrimination research, we find that movies with minority increase receive lower ratings and more toxic reviews. Importantly, these effects weaken after the advent of the Black Lives Matter (BLM) movement, especially when the movement's intensity is high. These results are reliable across various robustness checks (e.g., propensity score matching, random implementation test). We conceptually replicate the bias mitigation effect of BLM in a preregistered experiment: Heightening the salience of BLM increases White individuals' acceptance of racial minority increase in a movie sequel. This research demonstrates the power of social movements in fostering diversity, equality, and inclusion.

The racial composition of road users, traffic citations, and police stops.

This paper exploits the potential of Global Positioning System datasets sourced from mobile phones to estimate the racial composition of road users, leveraging data from their respective Census block group. The racial composition data encompasses approximately 46 million trips in the Chicago metropolitan region. The research focuses on the relationship between camera tickets and racial composition of drivers vs. police stops for traffic citations and the racial composition in these locations. Black drivers exhibit a higher likelihood of being ticketed by automated speed cameras and of being stopped for moving violations on roads, irrespective of the proportion of White drivers present. The research observes that this correlation attenuates as the proportion of White drivers on the road increases. The citation rate measured by cameras better matches the racial composition of road users on the links with cameras than do stops by police officers. This study therefore presents an important contribution to understanding racial disparities in moving violation stops, with implications for policy interventions and social justice reforms.

Developmental origins of anti-Black bias in White children in the United States: Exposure to and beliefs about racial inequality.

Anti-Black racism remains a pervasive crisis in the United States. Racist social systems reinforce racial inequalities and perpetuate prejudicial beliefs. These beliefs emerge in childhood, are difficult to change once entrenched in adolescence and adulthood, and lead people to support policies that further reinforce racist systems. Therefore, it is important to identify what leads children to form prejudicial beliefs and biases and what steps can be taken to preempt their development. This study examined how children's exposure to and beliefs about racial inequalities predicted anti-Black biases in a sample of 646 White children (4 to 8 years) living across the United States. We found that for children with more exposure to racial inequality in their daily lives, those who believed that racial inequalities were caused by intrinsic differences between people were more likely to hold racial biases, whereas those who recognized the extrinsic factors underlying racial inequalities held more egalitarian attitudes. Grounded in constructivist theories in developmental science, these results are consistent with the possibility that racial biases emerge in part from the explanatory beliefs that children construct to understand the racial inequalities they see in the world around them.

White patients' physical responses to healthcare treatments are influenced by provider race and gender.

The healthcare workforce in the United States is becoming increasingly diverse, gradually shifting society away from the historical overrepresentation of White men among physicians. However, given the long-standing underrepresentation of people of color and women in the medical field, patients may still associate the concept of doctors with White men and may be physiologically less responsive to treatment administered by providers from other backgrounds. To investigate this, we varied the race and gender of the provider from which White patients received identical treatment for allergic reactions and measured patients' improvement in response to this treatment, thus isolating how a provider's demographic characteristics shape physical responses to healthcare. A total of 187 White patients experiencing a laboratory-induced allergic reaction interacted with a healthcare provider who applied a treatment cream and told them it would relieve their allergic reaction. Unbeknownst to the patients, the cream was inert (an unscented lotion) and interactions were completely standardized except for the provider's race and gender. Patients were randomly assigned to interact with a provider who was a man or a woman and Asian, Black, or White. A fully blinded research assistant measured the change in the size of patients' allergic reaction after cream administration. Results indicated that White patients showed a weaker response to the standardized treatment over time when it was administered by women or Black providers. We explore several potential explanations for these varied physiological treatment responses and discuss the implications of problematic race and gender dynamics that can endure "under the skin," even for those who aim to be bias free.

Racial disparities across multiple stages of the deceased organ donation process.

Pervasive structural violence causes higher organ failure rates among Black Americans and excess Black potential deceased organ donors. Underuse of Black donors would exacerbate organ shortages that disproportionately harm Black transplant candidates. This study investigates racial differences in transit between distinct donation steps among 132 968 potential donors across 557 hospitals and 6 Organ Procurement Organizations (OPOs) from 2015 through 2021. Multilevel multistate modeling with patient covariates and OPO random effects shows adjusted likelihoods (95% confidence interval [CI]) of non-Black versus Black patients transitioning from OPO referral to approach: odds ratio (OR) 1.23 (95% CI 1.18, 1.27), approach to authorization: OR 1.64 (95% CI 1.56, 1.72), authorization to procurement: OR 1.08 (95% CI 1.02, 1.14), and procurement to transplant: OR 0.99 (95% CI 0.93, 1.04). Overall organ utilization rates for Black, Latino, White, and other OPO referrals were 5.88%, 8.17%, 6.78%, and 5.24%, respectively. Adjusting for patient covariates and hospital and OPO random effects, multilevel logistic models estimated that compared with Black patients, Latino, White, and other patients had ORs of organ utilization of 1.82 (95% CI 1.61, 2.04), 3.19 (95% CI 2.91, 3.50), and 1.25 (95% CI 1.06, 1.47), respectively. Nationwide in 2022, donor conversion disparities likely lost more than 1800 donors-70% of whom would have been Black. Achieving racial equity for transplant candidates will require reducing racial disparities in organ donation.

Comparing barriers to early stage diagnosis of hepatocellular carcinoma between safety net hospitals and academic medical centers: An analysis from the United States Safety-Net Collaborative.

BACKGROUND AND OBJECTIVES: Early detection of hepatocellular carcinoma (HCC) is associated with improved survival. However, a greater proportion of patients treated at safety net hospitals (SNHs) present with late-stage disease compared to those at academic medical centers (AMCs). This study aims to identify barriers to diagnosis of HCC, highlighting differences between SNHs and AMCs. METHODS: The US Safety Net Collaborative-HCC database was queried. Patients were stratified by facility of diagnosis (SNH or AMC). Patient demographics and HCC screening rates were examined. The primary outcome was stage at diagnosis (AJCC I/II-"early"; AJCC III/IV-"late"). RESULTS: 1290 patients were included; 50.2% diagnosed at SNHs and 49.8% at AMCs. At SNHs, 44.4% of patients were diagnosed late, compared to 27.6% at AMCs. On multivariable regression, Black race was associated with late diagnosis in both facilities (SNH: odds ratio 1.96, p = 0.03; AMC: 2.27, <0.01). Screening was associated with decreased odds of late diagnosis (SNH: 0.46, p = 0.04; AMC: 0.37, p < 0.01). CONCLUSIONS: Black race was associated with late diagnosis of HCC, while screening was associated with early diagnosis across institutional types. These results suggest socially constructed racial bias in screening and diagnosis of HCC. Screening efforts targeting SNH patients and Black patients at all facilities are essential to reduce disparities.

Effect of skin tone on the accuracy of the estimation of arterial oxygen saturation by pulse oximetry: a systematic review.

BACKGROUND: Pulse oximetry-derived oxygen saturation (SpO2) is an estimate of true arterial oxygen saturation (SaO2). The aim of this review was to evaluate available evidence determining the effect of skin tone on the ability of pulse oximeters to accurately estimate SaO2. METHODS: Published literature was screened to identify clinical and non-clinical studies enrolling adults and children when SpO2 was compared with a paired co-oximetry SaO2 value. We searched literature databases from their inception to March 20, 2023. Risk of bias (RoB) was assessed using the QUADAS-2 tool. Certainty of assessment was evaluated using the GRADE tool. RESULTS: Forty-four studies were selected reporting on at least 222 644 participants (6121 of whom were children) and 733 722 paired SpO2-SaO2 measurements. Methodologies included laboratory studies, prospective clinical, and retrospective clinical studies. A high RoB was detected in 64% of studies and there was considerable heterogeneity in study design, data analysis, and reporting metrics. Only 11 (25%) studies measured skin tone in 2353 (1.1%) participants; the remainder reported participant ethnicity: 68 930 (31.0%) participants were of non-White ethnicity or had non-light skin tones. The majority of studies reported overestimation of SaO2 by pulse oximetry in participants with darker skin tones or from ethnicities assumed to have darker skin tones. Several studies reported no inaccuracy related to skin tone. Meta-analysis of the data was not possible. CONCLUSIONS: Pulse oximetry can overestimate true SaO2 in people with darker skin tones. The clinical relevance of this bias remains unclear, but its magnitude is likely to be greater when SaO2 is lower. SYSTEMATIC REVIEW PROTOCOL: International Prospective Register of Systematic Reviews (PROSPERO): CRD42023390723.

Are Americans less likely to reply to emails from Black people relative to White people?

In this article, we present the results from a large-scale field experiment designed to measure racial discrimination among the American public. We conducted an audit study on the general public-sending correspondence to 250,000 citizens randomly drawn from public voter registration lists. Our within-subjects experimental design tested the public's responsiveness to electronically delivered requests to volunteer their time to help with completing a simple task-taking a survey. We randomized whether the request came from either an ostensibly Black or an ostensibly White sender. We provide evidence that in electronic interactions, on average, the public is less likely to respond to emails from people they believe to be Black (rather than White). Our results give us a snapshot of a subtle form of racial bias that is systemic in the United States. What we term everyday or "paper cut" discrimination is exhibited by all racial/ethnic subgroups-outside of Black people themselves-and is present in all geographic regions in the United States. We benchmark paper cut discrimination among the public to estimates of discrimination among various groups of social elites. We show that discrimination among the public occurs more frequently than discrimination observed among elected officials and discrimination in higher education and the medical sector but simultaneously, less frequently than discrimination in housing and employment contexts. Our results provide a window into the discrimination that Black people in the United States face in day-to-day interactions with their fellow citizens.

Assessment of skin pigmentation-related bias in pulse oximetry readings among adults.

PURPOSE: Recent reports that pulse oximeters may overestimate oxygen saturation in individuals with darker skin pigmentation have prompted concerns from regulatory authorities regarding racial bias. We investigated the performance of TruSignal SpO2 sensors (GE Healthcare, Helsinki, Finland) in adults with varying skin pigmentation. METHODS: A retrospective study was conducted using a set of pooled assessments of SpO2/SaO2 measurements from nine studies to assess bias, accuracy (Arms), and precision of TruSignal sensors in healthy adults under induced hypoxia. Subgroup analyses were performed based on oxygen saturation levels (band 1, ≥ 70 and ≤ 80%; band 2, > 80 and ≤ 90%; band 3, > 90 and ≤ 100%). RESULTS: Of the 10,800 data points from 131 individuals, 8,202 (75.9%) and 2,598 (24.1%) were assigned to the light and dark pigment groups, respectively. Bias was 0.14% overall and less than 1% across oxygenation bands. The difference in bias between dark and light pigment groups was statistically significant at the low oxygenation band with SpO2 ≥ 70 and ≤ 80% (+ 0.58% and + 0.30% respectively; p = 0.0035). Throughout the saturation range, Arms was 1.64% in the light and 1.71% in the dark pigment group, within device specifications and regulatory requirements. Oxygenation was the dominating factor in stepwise ANOVA modeling. The mixed model also showed that bias was strongly affected by the oxygenation range. CONCLUSION: TruSignal sensors demonstrated higher bias at lower oxygen saturation, with less than 0.5% difference between pigment groups. These findings raise new questions, such as ways to improve pulse oximetry measurements during challenging clinical conditions, including low perfusion.

Performance of pulse oximeters as a function of race compared to skin pigmentation: a single center retrospective study.

Pulse oximetry (SpO2) is a critical monitor for assessing oxygenation status and guiding therapy in critically ill patients. Race has been identified as a potential source of SpO2 error, with consequent bias and inequities in healthcare. This study was designed to evaluate the incidence of occult hypoxemia and accuracy of pulse oximetry associated with the Massey-Martin scale and characterize the relationship between Massey scores and self-identified race. This retrospective single institute study utilized the Massey-Martin scale as a quantitative assessment of skin pigmentation. These values were recorded peri-operatively in patients enrolled in unrelated clinical trials. The electronic medical record was utilized to obtain demographics, arterial blood gas values, and time matched SpO2 values for each PaO2 ≤ 125 mmHg recorded throughout their hospitalizations. Differences between SaO2 and SpO2 were compared as a function of both Massey score and self-reported race. 4030 paired SaO2-SpO2 values were available from 579 patients. The average error (SaO2-SpO2) ± SD was 0.23 ± 2.6%. Statistically significant differences were observed within Massey scores and among races, with average errors that ranged from - 0.39 ± 2.3 to 0.53 ± 2.5 and - 0.55 ± 2.1 to 0.37 ± 2.7, respectively. Skin color varied widely within each self-identified race category. There was no clinically significant association between error rates and Massey-Martin scale grades and no clinically significant difference in accuracy observed between self-reported Black and White patients. In addition, self-reported race is not an appropriate surrogate for skin color.

Reading the mind in the eyes of Black and White people: Interracial contact and perceived race affects brain activity when inferring mental states.

Inferring others' mental states, or mentalizing, is a critical social cognitive ability that underlies humans' remarkable capacity for complex social interactions. Recent work suggests that interracial contact shapes the recruitment of brain regions involved in mentalizing during impression formation. However, it remains unclear how a target's perceived racial group and a perceiver's previous contact with that racial group shapes mental state inferences. In this study, we examined brain activity in regions of interest associated with mentalizing and race perception among self-identified White perceivers who varied in lifetime contact while they inferred secondary emotions from perceived White eyes and perceived Black eyes (i.e., the Reading the Mind in the Eyes test). The interaction between lifetime contact and perceived target race predicted activity in the superior temporal sulcus (STS), a region consistently implicated in mental state inferences from perceptual cues, tracking eye gaze, and biological motion. Low and average contact White perceivers showed more left STS activity when inferring mental states from perceived White eyes than perceived Black eyes, whereas high contact White perceivers showed similar left STS activity regardless of perceived target race. These results indicate that interracial contact decreases racial biases in the recruitment of regions involved in mentalizing when inferring mental states from perceptual cues.

Invited Commentary: Undiagnosed and Undertreated-the Suffocating Consequences of the Use of Racially Biased Medical Devices During the COVID-19 Pandemic.

While medical technology is typically considered neutral, many devices rely upon racially biased algorithms that prioritize care for White patients over Black patients, who may require more urgent medical attention. In their accompanying article, Sudat et al. (Am J Epidemiol. 2023;XXX(XX):XXX-XXX) document striking inaccuracies in pulse oximeter readings among Black patients, with significant clinical implications. Their findings suggest that this resulted in racial differences in delivery of evidence-based care during the coronavirus disease 2019 (COVID-19) pandemic, affecting admissions and treatment protocols. Despite the medical community's growing awareness of the pulse oximeter's significant design flaw, the device is still in use. In this article, I contextualize Sudat et al.'s study results within the larger history of racial bias in medical devices by highlighting the consequences of the continued underrepresentation of diverse populations in clinical trials. I probe the implications of racially biased assessments within clinical practice and research and illustrate the disproportionate impact on patients of color by examining 2 medical tools, the pulse oximeter and pulmonary function tests. Both cases result in the undertreatment and underdiagnosis of Black patients. I also demonstrate how the social underpinnings of racial bias in medical technology contribute to poor health outcomes and reproduce health disparities, and propose several recommendations for the field to rectify the harms of racial bias in medical technology.

Particles and Prejudice: Nanomedicine Approaches to Reducing Health Disparities in Endometrial Cancer.

Endometrial cancer is the most common gynecological malignancy worldwide and unfortunately has a much higher mortality rate in Black women compared with White women. Many potential factors contribute to these mortality rates, including the underlying effects of systemic and interpersonal racism. Furthermore, other trends in medicine have potential links to these rates including participation in clinical trials, hormone therapy, and pre-existing health conditions. Addressing the high incidence and disparate mortality rates in endometrial cancer requires novel methods, such as nanoparticle-based therapeutics. These therapeutics have been growing in increasing prevalence in pre-clinical development and have far-reaching implications in cancer therapy. The rigor of pre-clinical studies is enhanced by the likeness of the model to the human body. In systems for 3D cell culture, for example, the extracellular matrix mimics the tumor more closely. The increasing emphasis on precision medicine can be applied to cancer using nanoparticle-based methods and applied to pre-clinical models by using patient-derived model data. This review highlights the intersections of nanomedicine, precision medicine, and racial disparities within endometrial cancer and provides insights into reducing health disparities using recent scientific advances on the nanoscale.

Associations between provider-assigned Apgar score and neonatal race.

BACKGROUND: For decades, the Apgar scoring system has been used to evaluate neonatal status and determine need for resuscitation or escalation in care, such as admission to a neonatal intensive care unit. However, the variation and accuracy of provider-assigned Apgar scores across neonatal racial groups have yet to be evaluated. OBJECTIVE: This study aimed to investigate how provider-assigned Apgar scores vary by neonatal race independently of clinical factors and umbilical cord gas values. STUDY DESIGN: We conducted a retrospective cohort study at an urban academic medical center. All live births at ≥23 weeks and 0 days of gestation from January 1, 2019 through December 31, 2019 with complete data available were included. Data were queried from the electronic medical record and included race, ethnicity, gestational age of neonate, umbilical cord gas values (umbilical artery pH and base deficit), admission to the neonatal intensive care unit, and presence of maternal-fetal complications. Primary outcome measures were neonates' Apgar scores at 1 and 5 minutes. Color Apgar score and admission to the neonatal intensive care unit served as secondary outcome measures. We performed 3 partially proportional ordinal regression models controlling for an increasing number of covariates, with Model 1, the baseline model, adjusted for gestational age, Model 2 additionally adjusted for umbilical cord gases, and Model 3 additionally adjusted for maternal medical conditions and pregnancy complications. RESULTS: A total of 977 neonates met selection criteria; 553 (56.6%) were Black. Providers assigned Black neonates significantly lower Apgar scores at 1 minute (odds ratio, 0.63; 95% confidence interval, 0.49-0.80) and 5 minutes (odds ratio, 0.64; 95% confidence interval, 0.47-0.87), when controlling for umbilical artery gases, gestational age, and maternal-fetal complications. This difference seemed related to significantly lower assigned color Apgar scores at 1 minute when controlling for all the above factors (odds ratio, 0.52; 95% confidence interval, 0.39-0.68). Providers admitted full-term Black neonates to the neonatal intensive care unit at higher rates than non-Black neonates when controlling for all factors (odds ratio, 1.29; 95% confidence interval, 0.94-1.77). Black neonates did not have more abnormal cord gas values (mean umbilical artery pH of 7.259 for Black vs 7.256 for non-Black neonates), which would have supported their admission to the neonatal intensive care unit. CONCLUSION: Providers applied inaccurate Apgar scores to Black neonates given that the umbilical cord gases were not in agreement with lower Apgar scores. These inaccuracies may be a factor in unnecessary admissions to neonatal intensive care units, and suggest that colorism and racial biases exist among healthcare providers.

Racial bias in recruitment to clinical trials on paediatric asthma.

Asthma is now the commonest chronic disease of childhood, but not all children with asthma receive equivalent standards of medical care which influences their clinical outcomes. In this paper we sought to determine the proportion of participants in registered clinical trials relating to paediatric or adolescent asthma over the last decade that were from white and non-white backgrounds. We searched the ClinicalTrials.gov database for all completed interventional studies between the dates 1st January 2011 and 1st January 2021 that were on the topic of 'asthma', and included participants below 18 years of age. Of the 500 studies returned, 208 had results available on the ClinicalTrials.gov website. In total, of the 112,327 patients studied, almost 69 % (77,333) of the patients were described as White or Caucasian, and fewer than 13 % (14,189) were described as Black, African, or African-American. Overall, approximately 30 % of study participants - some 34,207 children - were from non-white backgrounds. To redress this imbalance, researchers designing clinical trials must ensure that their study populations are as representative of the target population for the intervention as possible.

The impact of patient skin colour on diagnostic ability and confidence of medical students.

Previous literature has explored unconscious racial biases in clinical education and medicine, finding that people with darker skin tones can be underrepresented in learning resources and managed differently in a clinical setting. This study aimed to examine whether patient skin colour can affect the diagnostic ability and confidence of medical students, and their cognitive reasoning processes. We presented students with 12 different clinical presentations on both white skin (WS) and non-white skin (NWS). A think aloud (TA) study was conducted to explore students' cognitive reasoning processes (n = 8). An online quiz was also conducted where students submitted a diagnosis and confidence level for each clinical presentation (n = 185). In the TA interviews, students used similar levels of information gathering and analytical reasoning for each skin type but appeared to display increased uncertainty and reduced non-analytical reasoning methods for the NWS images compared to the WS images. In the online quiz, students were significantly more likely to accurately diagnose five of the 12 clinical presentations (shingles, cellulitis, Lyme disease, eczema and meningococcal disease) on WS compared to NWS (p < 0.01). With regards to students' confidence, they were significantly more confident diagnosing eight of the 12 clinical presentations (shingles, cellulitis, Lyme disease, eczema, meningococcal disease, urticaria, chickenpox and Kawasaki disease) on WS when compared to NWS (p < 0.01). These findings highlight the need to improve teaching resources to include a greater diversity of skin colours exhibiting clinical signs, to improve students' knowledge and confidence, and ultimately, to avoid patients being misdiagnosed due to the colour of their skin.

Does extended experience with other-race nannies predict racial bias in the preschool years?

Most existing studies on racial bias reduction have used short-term interracial interaction interventions with fleeting effects. The current natural experiment examined whether daily interactions with other-race nannies relate to reduced racial bias in the preschool years. We capitalized on a unique child-rearing situation in Singapore whereby children are often cared for by other-race nannies since infancy. Singaporean Chinese 3- to 6-year-olds (N = 100) completed explicit and implicit racial bias measures assessing their preferential bias favoring own-race adults over adults of their nannies' race. Differential findings were obtained for children's explicit and implicit racial bias. Extensiveness, but not mere presence, of other-race nanny experience was associated with lower levels of explicit racial bias in children. In contrast, neither presence nor extensiveness of other-race nanny experience was associated with children's implicit racial bias. Together, these findings suggest that long-term and extensive contact with an other-race caregiver could have subtle mitigating effects on children's explicit, but not implicit, racial bias.

Racial-ethnic disparities in psychological distress during the COVID-19 pandemic in the United States: the role of experienced discrimination and perceived racial bias.

BACKGROUND: Research on mental health disparities by race-ethnicity in the United States (US) during COVID-19 is limited and has generated mixed results. Few studies have included Asian Americans as a whole or by subgroups in the analysis. METHODS: Data came from the 2020 Health, Ethnicity, and Pandemic Study, based on a nationally representative sample of 2,709 community-dwelling adults in the US with minorities oversampled. The outcome was psychological distress. The exposure variable was race-ethnicity, including four major racial-ethnic groups and several Asian ethnic subgroups in the US. The mediators included experienced discrimination and perceived racial bias toward one's racial-ethnic group. Weighted linear regressions and mediation analyses were performed. RESULTS: Among the four major racial-ethnic groups, Hispanics (22%) had the highest prevalence of severe distress, followed by Asians (18%) and Blacks (16%), with Whites (14%) having the lowest prevalence. Hispanics' poorer mental health was largely due to their socioeconomic disadvantages. Within Asians, Southeast Asians (29%), Koreans (27%), and South Asians (22%) exhibited the highest prevalence of severe distress. Their worse mental health was mainly mediated by experienced discrimination and perceived racial bias. CONCLUSIONS: Purposefully tackling racial prejudice and discrimination is necessary to alleviate the disproportionate psychological distress burden in racial-ethnic minority groups.

Call for algorithmic fairness to mitigate amplification of racial biases in artificial intelligence models used in orthodontics and craniofacial health.

Machine Learning (ML), a subfield of Artificial Intelligence (AI), is being increasingly used in Orthodontics and craniofacial health for predicting clinical outcomes. Current ML/AI models are prone to accentuate racial disparities. The objective of this narrative review is to provide an overview of how AI/ML models perpetuate racial biases and how we can mitigate this situation. A narrative review of articles published in the medical literature on racial biases and the use of AI/ML models was undertaken. Current AI/ML models are built on homogenous clinical datasets that have a gross underrepresentation of historically disadvantages demographic groups, especially the ethno-racial minorities. The consequence of such AI/ML models is that they perform poorly when deployed on ethno-racial minorities thus further amplifying racial biases. Healthcare providers, policymakers, AI developers and all stakeholders should pay close attention to various steps in the pipeline of building AI/ML models and every effort must be made to establish algorithmic fairness to redress inequities.