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.

翻译：用户体验研究在法规监管情境下面临独特挑战，需要专门方法来保护弱势群体同时生成可操作见解。数字咨询、预约挂号及药物配送平台在扩大医疗服务可及性方面展现出潜力，但其现实有效性因缺乏充分考量这些群体心理社会状况的理论化用户体验研究方法论而受限。本文提出基于生成式AI增强的用户体验研究方法论，以用户体验研究视角手册为理论框架，指导为尼日利亚HIV/AIDS感染者中的男男性行为者及跨性别者设计心理安全、低认知负荷的数字健康干预措施。基于包含协同设计工作坊、主题分析与需求工程的实证研究，该方法论通过四阶段用户体验研究流程实现：涵盖AI支持的假设生成、基础规划、基于构建模块的洞察生成，以及构建利益相关者特定视角叙事。该流程最终产出十张理论驱动的用户体验研究游戏卡，将心理机制与实证发现转化为可操作的设计指南。每张游戏卡包含适合边缘群体研究的可执行任务、AI增强方法及伦理保护措施。核心贡献在于构建了可复制、具有污名意识且以隐私为中心的负责任生成式AI在用户体验研究实践中的应用框架，推动面向边缘群体的人本数字健康设计发展。