Exploring the racial diagnostic bias of schizophrenia using behavioral and clinical-based measures.

Abstract

There is evidence that African Americans are 2.4 times more likely to be diagnosed with a schizophrenia-spectrum diagnosis compared with White individuals, who are more likely to receive an affective diagnosis. The reason for these diagnostic discrepancies is unclear, however, 2 explanations have garnered attention: epigenetic differences and systematic error or bias in the diagnostic process. The latter is the focus of the present study and it is hypothesized that the bias involves cultural insensitivity on the part of the clinician. The present study has investigated bias-driven diagnostic disparities between African Americans and White individuals, by using traditional symptom rating scales, clinical diagnoses, and objective, behaviorally based measures. Data was aggregated from 3 separate studies conducted on outpatients (N = 251) with schizophrenia-spectrum or affective disorders. The present study used computationally derived acoustic markers of speech to tap hallmark negative symptoms (e.g., blunted affect or alogia) and behavioral-based markers of language failures to tap disorganization. Clinician symptom ratings were made using the Brief Psychiatric Rating Scale. Our findings confirmed the diagnostic bias between African Americans and White individuals though there were no differences on clinician symptom ratings. On the other hand, the computerized and behavioral measures revealed more speech disorder and less blunted affect in African Americans versus White individuals. Moderation analysis suggests that behaviorally based measures impact the relationship between race and diagnosis; however, this was largely unsupported for race and clinical symptom ratings. Further research is needed to disentangle normative variations from psychopathology.

Is There a Bias in the Diagnosis of Borderline Personality Disorder Among Lesbian, Gay, and Bisexual Patients?

“…C. Schwartz & Blankenship, 2014). Furthermore, it is possible that such group-based discrepancies reflect potential misinterpretation of culturally normative behavior as pathological (E. K. Schwartz et al, 2019).…”

Implicit bias of encoded variables: frameworks for addressing structured bias in EHR–GWAS data

“…White patients, on the other hand, are more likely to be diagnosed with an affective disorder ( 39 ). This divergence has been attributed to epigenetic differences ( 40 ), with little to no empirical support, and differences in socioeconomic status ( 41 ), but the diagnostic discrepancy remains present even after controlling for age, sex, income, site and education ( 42 ), suggesting that physician bias or systemic bias presenting across various levels of healthcare and legislative processes ( Fig. 1 ) may present the most notable factor.…”

Shared decision‐making in mental and behavioural health interventions

“…Even in cases where patients are fully capable of participating in SDM, clinicians' biases regarding certain types of patients may present another barrier to using this model. Clinicians' biases relating to a variety of patient characteristics (eg, race, gender, and age) are well documented in the literature and often affect their decisions . Biases relating to patient characteristics may also influence clinicians' use of SDM, as evidenced by recent studies indicating that some minority groups, such as African‐Americans and Latino/as, are less likely than White patients to report being involved in SDM with their health care providers .…”

“…Clinicians' biases relating to a variety of patient characteristics (eg, race, gender, and age) are well documented in the literature and often affect their decisions. [60][61][62] Biases relating to patient characteristics may also influence clinicians' use of SDM, as evidenced by recent studies indicating that some minority groups, such as African-Americans and Latino/as, are less likely than White patients to report being involved in SDM with their health care providers. 63,64 This differential use of SDM may be due to negative stereotypes about individuals being less capable of participating in health care decisions based on their demographics (ie, beliefs that they lack the knowledge, willingness, or trust to be able to collaborate).…”