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Acceptability of a Conversational Agent-Led Digital Program for Anxiety: Mixed Methods Study of User Perspectives
Pearla Papiernik1, Sylwia Dzula1, Marta Zimanyi1
1ieso Digital Health, Cambridge, United Kingdom.
JMIR Human Factors
|August 18, 2025
Summary
Digital Mental Health Interventions (DMHIs) with AI chatbots are acceptable and engaging for generalized anxiety. However, personalization needs further development for optimal patient experience.
Area of Science:
- Digital Health
- Artificial Intelligence in Mental Health
- Human-Computer Interaction
Background:
- Rising global rates of anxiety and depression strain traditional mental health services.
- Digital Mental Health Interventions (DMHIs) offer scalable solutions but face engagement challenges.
- AI-powered conversational agents show promise for enhancing DMHIs, yet their acceptability is under investigation.
Purpose of the Study:
- To assess the acceptability, engagement, and usability of a conversational agent-led DMHI with human support for generalized anxiety.
- To explore patient expectations and experiences with this digital mental health program using mixed methods.
Main Methods:
- A mixed-methods approach was employed with 299 participants engaging in a DMHI for up to 9 weeks.
- Quantitative data collected post-intervention included validated measures for engagement (UES), usability (SUS), and acceptability (SUTAQ).
- Qualitative data from pre- and post-intervention interviews (N=21 and N=16, respectively) were analyzed thematically to understand user experiences.
Main Results:
- Participants reported high engagement (mean UES=3.7) and ease of use (SUS=78.6), finding the program rewarding and accessible.
- The DMHI enhanced care access and satisfaction (mean SUTAQ=4.3-4.9), meeting most user needs.
- Key acceptability themes included accessible care, effective solutions, personalization, guided control, and human support, though participants desired greater personalization.
Conclusions:
- DMHIs incorporating patient-centered design factors are crucial for global mental healthcare impact.
- This study validates the acceptability of a structured, AI-driven DMHI with human support for generalized anxiety.
- Optimizing personalization and leveraging stratified human support with safe AI integration can significantly enhance patient experience and the real-world effectiveness of DMHIs.
Keywords:
acceptabilityanxietyartificial intelligenceconversational agentdigital interventionengagementmental healththematic analysisuser experienceMore Related Videos
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