Attention-deficit/hyperactivity disorder (ADHD) is a psychiatric disorder which presents itself in individuals through patterns of developmentally inappropriate levels of inattentiveness, hyperactivity, and impulsivity, with difficulties in decision making and emotional regulation (ER). Although digital and AI-based interventions have expanded access to ER support, many existing systems remain limited by weak theoretical integration, insufficient accommodation of neurodiversity, and a lack of structured user experience research (UXR) methodologies, that bridge psychological insight with design practice. This paper introduces a Generative AI-augmented UXR methodology, grounded in the UXR Point of View (PoV) Playbook, to support the design of emotionally intelligent and Neuroinclusive digital ER interventions for adults with ADHD. The approach integrates empirical evidence with established psychological frameworks Dialectical Behaviour Therapy (DBT), Self-Determination Theory (SDT), and the COM-B behavioural model and leverages Generative AI as a co-analytic tool to support synthesis, hypothesis formation, and design articulation. The methodology is operationalized 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 a set of ten theory informed UXR Play Cards that translate psychological mechanisms and empirical findings into actionable design guidance. The primary contribution of this work is a replicable, bias-aware framework for integrating Generative AI into UXR practice, advancing human-centred and Neuroinclusive approaches to digital mental health design.

翻译：注意力缺陷/多动症（ADHD）是一种精神障碍，表现为个体存在与发育水平不相称的注意力不集中、多动和冲动行为，并伴有决策困难和情绪调节障碍。尽管基于数字和人工智能的干预措施已扩展了情绪调节支持的可及性，但许多现有系统仍受限于理论整合薄弱、对神经多样性的适应性不足，以及缺乏衔接心理学洞见与设计实践的结构化用户体验研究方法论。本文提出了一种生成式人工智能增强的UXR方法论，其以UXR视角剧本为基础，旨在支持面向ADHD成人的情感智能且神经包容性数字情绪调节干预设计。该方法将经验证据与既定心理学框架（辩证行为疗法、自我决定理论和COM-B行为模型）相结合，并利用生成式人工智能作为协同分析工具，以支持综合分析、假设形成和设计阐述。该方法论通过四阶段UXR流程实现具体操作，涵盖人工智能支持的假设生成、基础规划、通过构建模块形成洞见，以及构建利益相关者特定视角叙事。该流程最终产出一套十张基于理论的UXR设计卡，将心理学机制和经验发现转化为可操作的设计指导。本研究的主要贡献在于提出了一种可复现、具有偏差意识的框架，用于将生成式人工智能整合到UXR实践中，从而推进以人为中心和神经包容性的数字心理健康设计方法。