The Intergroup Time Bias and Its Implications for Medical Healthcare

Abstract

The Intergroup Time Bias (ITB) is an unobtrusive yet impactful form of discrimination, characterized by the unequal allocation of time, favoring White individuals compared to Black individuals. This biased time allocation has significant implications for racial inequities in critical social domains, including healthcare. Across three studies, we demonstrate the ITB as a pervasive factor contributing to racial healthcare disparities. Study 1 (N = 166 patients, N = 9 physicians) examined real-world clinical interactions in Brazil, revealing that White physicians consistently spent more time with White patients than Black patients across multiple medical specialties. Study 2 (N = 210) extended these findings to Portugal through a vignette study, where White medical trainees spent significantly more time to clinical tasks involving a White (vs. Black) patient, leading to enhanced diagnostic accuracy and more comprehensive clinical recommendations for the White patient. Study 3 (N = 99) explored additional ITB consequences, specifically medical trainees’ written email communication to patients in Portugal, using the same clinical scenario as Study 2. Consistent with Study 2, trainees spent significantly more time on clinical tasks involving a White (vs. Black) patient, which translated into higher quality written communication for the White patient. Notably, trainees who scored high on implicit racial bias but low on explicit racial bias (i.e., aversive racists) showed stronger ITB than those with high implicit and explicit racial bias (i.e., prejudiced) or low implicit and explicit racial bias (i.e., non-prejudiced). This research represents work in T1, with a goal to establish proof of concept, through observational and experimental studies, on the critical role that ITB plays in contributing to racial healthcare disparities. Future T2–T4 research is needed to understand how the ITB manifests in multiple aspects of patient care in the actual clinical settings, test interventions to reduce it, and refine these interventions for broader effectiveness.