From Evidence to Design: Developing an AI-Augmented UX Research Point of View for Digital Wellbeing in Emergency and Public Safety Contexts

2026-05-29

AI Summary

This study addresses the challenges emergency and public safety personnel face in adopting conventional digital health tools due to high-pressure shift work and unpredictable schedules. To overcome these barriers, the research proposes an AI-augmented user experience research (UXR) perspective framework that integrates behavior change techniques (BCTs) with persuasive design principles. By synergizing AI-assisted literature analysis with human design judgment, the study distills tailored health intervention strategies for this population. The project yields a UXR Perspective Pyramid, nine action cards, and contextualized narratives, collectively demonstrating that effective digital health systems for high-stress occupations must exhibit low cognitive load, contextual adaptability, and psychological safety. These outputs establish a scalable design paradigm for health interventions targeting individuals in demanding professional environments.

Abstract

This paper investigates how User Experience Research (UXR) methods can be combined with AI-supported analysis to develop clearer design direction for digital wellbeing interventions targeting Emergency and Public Safety Personnel (EPSP). EPSP work in high-stress, shift-based environments where cognitive fatigue and unpredictable schedules reduce engagement with conventional wellbeing tools. Using the UXR Point-of-View (PoV) framework, this study applied an AI-supported literature analysis process to identify recurring psychological, behavioural, and design patterns. Behaviour Change Techniques and Persuasive Technology principles were integrated throughout interpretation to connect evidence with practical design reasoning. The process resulted in a UXR PoV Pyramid, nine UXR Play Cards, and stakeholder focused PoV narratives. Findings show that effective wellbeing systems for EPSP must minimise cognitive effort, adapt to operational context, and prioritise psychological safety. The work demonstrates how AI can assist large-scale evidence interpretation while human researchers maintain responsibility for contextual judgement and design direction.

Problem

• Digital Wellbeing
• Emergency Personnel
• Public Safety
• User Experience Research
• Cognitive Fatigue

Innovation

• AI-augmented UX research
• digital wellbeing
• Emergency and Public Safety Personnel
• Point-of-View framework
• behaviour change techniques