Accepted for/Published in: JMIR Serious Games
Date Submitted: Jul 29, 2023
Date Accepted: Dec 12, 2023
Development of Smartphone-based Virtual and Augmented Reality Implicit Association Training (VARIAT) for Reducing Implicit Biases Toward Patients among Healthcare Providers: A Pilot Study
ABSTRACT
Background:
Implicit bias is as prevalent among healthcare professionals as among the wider population and is significantly associated with lower healthcare quality.
Objective:
The study goal was to develop and evaluate the preliminary efficacy of an innovative mobile application, Virtual and Augmented Reality-based Implicit Association Training (VARIAT), to reduce implicit biases among Medicaid providers.
Methods:
An interdisciplinary team developed two interactive case-based training modules for Medicaid providers focused on implicit bias towards lower socioeconomic status (SES) and Sexual Orientation & Gender Identity (SOGI), respectively. The simulations combine experiential learning, facilitated debriefing, and game-based educational strategies. A total of 18 Medicaid providers participated in this pilot study. Outcomes were measured on three domains: training reactions, affective knowledge, and skill-based knowledge related to implicit biases in SES/SOGI.
Results:
Participants reported high relevance of training to their job for both the SES module (M= 4.75, SD = 0.45) and SOGI module (M = 4.67, SD = 0.50). Significant improvement in skill-based knowledge for minimizing health disparities for LGBTQ+ patients was found post-training (d= 0.72). Participants reported that they expected the training to help improve their relationship and avoid undesirable events with patients.
Conclusions:
This study developed an innovative smartphone-based implicit bias training program for Medicaid providers and conducted a pilot evaluation on the user experience and preliminary efficacy. Preliminary evidence showed positive satisfaction and preliminary efficacy of the intervention.
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