Stephen Giff

Melike Akca, Mona Giff, Deniz Cetinkaya et al.

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.

Mona Giff, Stephen Giff, Huseyin Dogan

User Experience Research (UXR) is currently undergoing a transition from traditional usability testing towards design-led and data-driven approaches, yet it faces an identity crisis due to a lack of methodological grounding in UXR and time-intensive methodologies which often lag behind product decision cycles. To address this, the UXR Point of View (PoV) framework formalises the UXR process by transitioning from raw data collection to forming an evidence-based PoV which drives strategic product impact. Furthermore, the use of GenAI in UXR has been investigated, but researchers often face increased work intensity when using GenAI, attributed to time spent on prompt engineering, data cleaning, and verification of AI outputs. This paper proposes and evaluates a formalised methodology for leveraging GenAI, specifically Google's NotebookLM, to augment the UXR PoV process. The methodology consists of five prompts across four stages: (1) leveraging the framework, (2) establishing roadmaps, (3) applying best-practices, and (4) crafting PoV narratives; and was tested on eleven UXR papers. Results showed that by using the proposed methodology, NotebookLM successfully leveraged the UXR PoV framework across all stages of PoV creation. These findings demonstrate that NotebookLM can serve as an effective collaborative partner in UXR, so long as it is provided with sufficient context and specific prompting.