Integrating Lived Experience Perspectives in AI-based Mental Health Research: A Practice-based Reflective Account.

Abstract

The embedding of lived experience experts (LEEs) is increasingly recognized as important in research, but evidence from low- and middle-income countries (LMIC) remains sparse. This viewpoint aims to present and critically reflect on a model for integrating LEEs into the design of an artificial intelligence (AI)-based mental health (MH) study to develop an automated depression screening system in India. We report on the process of forming a diverse Lived Experience Advisory Panel (LEAP) and show how LEAP influenced methodology, system design, ethics, and language through a three-day workshop and co-design sessions. We also highlight the ethical, structural, and power-dynamic challenges encountered, demonstrating that meaningful LEE partnership is both feasible and essential for developing culturally grounded, safe, and clinically acceptable AI applications in LMIC settings.