Developing an AI-Powered UX Research Point of View for Digital Health in A Regulatory Context: An Exemplar Case from MSM and Transgender HIV Care in Nigeria

2026-05-29

AI Summary

This study addresses the limited effectiveness of digital health platforms serving marginalized populations in Nigeria—particularly men who have sex with men (MSM) and transgender individuals living with HIV—due to a lack of theoretically grounded user experience (UX) research that integrates legal, psychosocial, and privacy considerations. To bridge this gap, the work proposes an innovative UX research framework incorporating generative AI through a four-stage process: AI-assisted hypothesis generation, foundational planning, Building Blocks–based insight extraction, and stakeholder-tailored point-of-view (PoV) storytelling. This approach yields a set of anti-stigmatizing, privacy-first, and replicable UX Play Cards, each synthesizing psychological mechanisms, empirical insights, AI-enhanced strategies, and ethical safeguards. The resulting toolkit offers low cognitive load, psychologically safe design guidance for digital health interventions targeting sensitive populations, thereby advancing the responsible application of generative AI in UX research for marginalized communities.

Abstract

User Experience Research (UXR) in a legal and regulatory contexts presents unique challenges that require specialised approaches to protect vulnerable populations whilst generating actionable insights. Digital consultation, appointment booking, and medication delivery platforms show promise for extending care access; however, their real-world effectiveness is curtailed by an absence of theoretically grounded user experience research (UXR) methodologies that adequately account for the psychosocial conditions of these populations. This paper introduces a Generative AI-augmented UXR methodology, grounded in the UXR Point of View (PoV) Playbook, to guide the design of psychologically safe, low-cognitive-load digital health interventions for MSM and transgender individuals living with HIV/AIDS in Nigeria. Drawing from empirical research involving co-design workshops, thematic analysis, and requirements engineering, the methodology is operationalised through a four-stage UXR process encompassing AI-supported hypothesis generation, foundational planning, insight generation via Building Blocks, and the construction of stakeholder-specific PoV narratives. This process results in ten theory-informed UXR Play Cards that translate psychological mechanisms and empirical findings into actionable design guidance. Each play contains actionable tasks, AI-augmented approaches, and ethical guardrails tailored for research with marginalised populations. The output is a set of ten theory-informed UXR Play Cards translating psychological insight and empirical evidence into actionable design guidance. The core contribution is a replicable, stigma-aware, and privacy-centred framework for responsible GenAI use in UXR practice, advancing human-centred digital health design for marginalised communities.

Problem

• UX Research
• Digital Health
• Regulatory Context
• Vulnerable Populations
• HIV Care

Innovation

• Generative AI
• UX Research
• Digital Health
• Marginalized Populations
• Ethical Design