Smartphone-Based Virtual and Augmented Reality Implicit Association Training (VARIAT) for Reducing Implicit Biases Toward Patients Among Health Care Providers: App Development and Pilot Testing

• Published in: JMIR serious games Vol. 12; p. e51310
• Main Authors: Shen, Jiabin, Clinton, Alex J, Penka, Jeffrey, Gregory, Megan E, Sova, Lindsey, Pfeil, Sheryl, Patterson, Jeremy, Maa, Tensing
• Format: Journal Article
• Language: English
• Published: Canada JMIR Publications 07.03.2024; JMIR Serious Games
• Subjects: Augmented reality; Bias; Clinical Integration of XR and Spatial Computing; Design; e-Learning and Medical Education; Educational objectives; Extended Reality, Virtual Reality and Virtual Worlds; Games and Gamification for Health; Games for Medical Education and Training; Gender identity; Immersive learning; Medical personnel; Minority & ethnic groups; Original Paper; Patients; Sexual orientation; Smartphones; Socioeconomic factors; Systemic Racism and Racial Bias in Health Care and Society; Training; Usability of Apps and User Perceptions of mHealth; Virtual reality; virtual reality; gender identity; smartphone; sexual orientation; health care provider; mobile application; mHealth; augmented reality; socioeconomic; sexual orientations; training; implicit bias training program; efficacy; extended reality; innovative; gender preference; implicit bias; XR; gender identities; gender preferences; Medicaid; health care providers; health care; mobile app
• ISSN: 2291-9279; 2291-9279
• DOI: 10.2196/51310

Implicit bias is as prevalent among health care professionals as among the wider population and is significantly associated with lower health care quality. The study goal was to develop and evaluate the preliminary efficacy of an innovative mobile app, VARIAT (Virtual and Augmented Reality Implicit Association Training), to reduce implicit biases among Medicaid providers. An interdisciplinary team developed 2 interactive case-based training modules for Medicaid providers focused on implicit bias related to race and socioeconomic status (SES) and sexual orientation and gender identity (SOGI), respectively. The simulations combine experiential learning, facilitated debriefing, and game-based educational strategies. Medicaid providers (n=18) participated in this pilot study. Outcomes were measured on 3 domains: training reactions, affective knowledge, and skill-based knowledge related to implicit biases in race/SES or SOGI. Participants reported high relevance of training to their job for both the race/SES module (mean score 4.75, SD 0.45) and SOGI module (mean score 4.67, SD 0.50). Significant improvement in skill-based knowledge for minimizing health disparities for lesbian, gay, bisexual, transgender, and queer patients was found after training (Cohen d=0.72; 95% CI -1.38 to -0.04). 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.