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
Researchers developed a generative AI-augmented user experience research methodology designed to improve digital health platforms for marginalized populations, specifically MSM and transgender individuals with HIV/AIDS in Nigeria. The framework combines AI-supported hypothesis generation with ethical guardrails to create psychologically safe, low-cognitive-load health interventions while protecting vulnerable users in restrictive regulatory environments.
This research addresses a critical gap in digital health design by centering the experiences of populations facing intersecting stigma, legal risk, and psychological vulnerability. Digital health platforms have demonstrated potential to expand care access, yet their real-world effectiveness remains limited by generic UX methodologies that fail to account for the specific psychosocial contexts of marginalized users. The authors developed a theoretically grounded approach that leverages generative AI not to replace human insight, but to augment and systematize the research process while maintaining ethical safeguards.
The methodology emerges from a broader recognition that responsible technology design requires moving beyond one-size-fits-all approaches. By grounding their framework in the UXR Point of View Playbook and conducting empirical research through co-design workshops, the team generated ten theory-informed Play Cards that translate psychological mechanisms into actionable design guidance. This represents a maturation of AI applications beyond consumer-facing optimization toward healthcare equity.
For digital health innovators and technology practitioners, this framework offers replicable pathways for designing systems that respect user dignity while operating within complex regulatory contexts where users face criminalization or discrimination. The emphasis on privacy-centered, stigma-aware design is particularly significant for global health initiatives operating in regions with restrictive laws. The research demonstrates that AI can serve equity-focused goals when deliberately constrained by ethical principles and community co-design processes. Future implementations will reveal whether this methodology scales across different populations and healthcare contexts while maintaining its commitment to marginalized communities.
- →AI-augmented UX research can improve digital health design for stigmatized populations without compromising privacy or ethical standards
- →Ten theory-informed Play Cards translate psychological insights into actionable design guidance for marginalized communities
- →The framework prioritizes psychological safety and low-cognitive-load interfaces for users facing legal and social risks
- →Community co-design and empirical research grounded the methodology in real user needs rather than assumptions
- →The approach offers replicable patterns for responsible generative AI use in healthcare technology development