Rationale and design of a multi-component intervention study to address implicit racial bias amongst healthcare professionals
1
Ecole de Santé Publique, Université Libre Bruxelles, Brussels, Belgium
Popul. Med. 2026;8(Supplement Supplement 1):A2731
ABSTRACT
BACKGROUND:
A growing body of empirical research highlights the importance of implicit bias among medical trainees and healthcare professionals in explaining racial and other disparities in healthcare services. Implicit-bias measures, such as the Implicit Association Test (IAT), correlate with a lower quality of patient–provider interactions and with discriminatory clinical decision making towards racialized patients, but also with worse patient adherence to treatment and health outcomes (1-3). Some public health scholars propose control-based interventions to remedy implicit bias, amongst others relying on disparity finding methods and preventive measures to disable the path from implicit biases to discriminatory behaviors (4). Yet, most intervention studies aim at reducing implicit racial bias by training programs focused on individual healthcare professionals. These interventions showed limited efficacy. Our study hypothesizes that implicit bias can be addressed by implementing change-based interventions at an institutional level. Specifically, it aims to assess an intervention for durably reducing the implicit racial bias of healthcare professionals in large healthcare institutions.
METHODS:
The paper describes the study protocol of this intervention study. The intervention is a multi-component intervention, involving counter-stereotype exposure and organizational diversity messaging. Its effect is measured through sequential IAT-tests amongst a sample of healthcare professionals across three large healthcare institutions in Brussels, differing in baseline average IAT-scores and team ethnic diversity. It uses a stepped-wedge cluster randomization design. This is complemented with multi-site, focused ethnographic observation.
RESULTS:
This paper reports baseline characteristics and mean IAT scores of participating healthcare institutions and presents preliminary results on IAT participation rates and factors influencing participation.
CONCLUSIONS:
Different strategies exist to reduce discriminatory consequences of implicit racial bias. The results of this study will contribute to actionable, evidence-based recommendations to tackle structural discrimination in health care systems.
A growing body of empirical research highlights the importance of implicit bias among medical trainees and healthcare professionals in explaining racial and other disparities in healthcare services. Implicit-bias measures, such as the Implicit Association Test (IAT), correlate with a lower quality of patient–provider interactions and with discriminatory clinical decision making towards racialized patients, but also with worse patient adherence to treatment and health outcomes (1-3). Some public health scholars propose control-based interventions to remedy implicit bias, amongst others relying on disparity finding methods and preventive measures to disable the path from implicit biases to discriminatory behaviors (4). Yet, most intervention studies aim at reducing implicit racial bias by training programs focused on individual healthcare professionals. These interventions showed limited efficacy. Our study hypothesizes that implicit bias can be addressed by implementing change-based interventions at an institutional level. Specifically, it aims to assess an intervention for durably reducing the implicit racial bias of healthcare professionals in large healthcare institutions.
METHODS:
The paper describes the study protocol of this intervention study. The intervention is a multi-component intervention, involving counter-stereotype exposure and organizational diversity messaging. Its effect is measured through sequential IAT-tests amongst a sample of healthcare professionals across three large healthcare institutions in Brussels, differing in baseline average IAT-scores and team ethnic diversity. It uses a stepped-wedge cluster randomization design. This is complemented with multi-site, focused ethnographic observation.
RESULTS:
This paper reports baseline characteristics and mean IAT scores of participating healthcare institutions and presents preliminary results on IAT participation rates and factors influencing participation.
CONCLUSIONS:
Different strategies exist to reduce discriminatory consequences of implicit racial bias. The results of this study will contribute to actionable, evidence-based recommendations to tackle structural discrimination in health care systems.
| eISSN: | 2654-1459 |
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