Managing Editor
@ShahidNShah
@ShahidNShah
A Proposed Participatory Framework for Explainable AI in mHealth: Mixed Methods Study Integrating User and Stakeholder Requirements
Artificial intelligence (AI) integration in mobile health (mHealth) apps offers health care access opportunities in low-resource settings, yet opaque AI recommendations undermine trust and adoption. Existing explainable AI (XAI) frameworks, designed in Western contexts, fail to address the linguistic, cultural, and infrastructural realities of South Asian populations, creating barriers where users cannot understand AI recommendations, clinicians cannot validate outputs, and developers lack implementation guidance.
Medigy Insights
Trust in AI-powered health apps depends less on algorithmic accuracy alone and more on whether users can understand how recommendations are made. Researchers found that patients, clinicians, and developers consistently favored AI systems that provide transparent explanations, human oversight, and culturally relevant guidance.
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