Abstract
Health inequity is commonly experienced by marginalized populations and is a risk factor for developing health problems, in part due to unconscious bias. Many existing bias trainings aim to shift stereotype beliefs, which are often less malleable than higher level thought processes. Here, we developed and tested a novel digital bias intervention called cognitive bias modification for stereotype (CBM-S), a tool designed to address interpretation bias in medical students. CBM-S uses an implicit learning task designed to force a less biased interpretation of Maori patients in common health care scenarios. Using a pre-post training design, we tested the effectiveness of a single session 59-item CBM-S training against control. We adopted three implicit bias measures at pre- and posttest: two interpretation bias tests and one beliefs assessment. Additional explicit bias measures were administered at posttest. Following CBM-S training, we found a reduction over time in stereotype interpretation bias scores (eta(2)(p) = .11) and in posttraining stereotype bias scores after adjusting for baseline bias scores (eta(2)(p) = .07). We found no significant difference on the beliefs test and explicit bias scores across training groups but observed positive correlations between interpretation bias and explicit bias scores. Results provided a "proof of principle" of CBM-S.