I Have a Dream…Altering New Zealand Medical Students’ Interpretation Bias of Māori in Healthcare Using Cognitive Bias Modification (CBM)

Abstract

Abstract Health inequity is commonly experienced by marginalized populations and is a risk factor for developing health problems. One major contributor to health inequity is implicit (unconscious) bias. Many existing bias trainings aim to shift individuals' stereotype beliefs and evaluations of marginalized groups (the ‘what’ training), which can be challenging as these beliefs and evaluations are intrinsic. Here, we developed and tested a novel digital bias training tool called cognitive bias modification for stereotype (CBM-S), a tool designed to address more malleable context-dependent thinking patterns (the ‘how’ training). CBM-S uses an implicit learning task designed to force a less biased interpretation of situations involving Māori patients, an indigenous population of Aotearoa New Zealand. Using a pre-post training design, we tested the effectiveness of a single session 59-item CBM-S training session delivered via a web application against an active-reading control group. We adopted three implicit bias measures at pre- and post-test: two interpretation bias tests and one beliefs/evaluation assessment. Additionally, explicit bias measures were administered at post-test. Following CBM-S training, we found a reduction over time in stereotype interpretation bias scores with moderate practical significance (n2p= .11). Further analysis revealed a similar reduction in post-training stereotype bias scores after adjusting for baseline bias scores (n2p= .07). We found no significant differences in the beliefs/evaluation test scores or the explicit bias measures between the intervention and control groups but observed positive correlations between interpretation bias and explicit bias scores. Implications and potential applications are discussed.