Journal article
A thematic analysis of users’ experience of an AI-enabled mental health intervention for generalised anxiety symptoms
Behaviour and Information Technology, Vol.Advanced access
23-Jul-2026
Abstract
Anxiety disorders are highly prevalent, yet access to effective psychological treatments remains limited. Artificial intelligence (AI)-enabled mental health applications offer a scalable and accessible means to bridge treatment gaps. This study qualitatively explored the experiences of adults with anxiety symptoms using PATH, an AI-enabled mental health intervention. Participants (N = 100) with moderate-to-severe anxiety were recruited via Prolific and engaged with PATH before providing feedback. A total of 67 participants completed the qualitative questions at the 2-week timepoint, and 51 participants completed a further questionnaire at the 8-week timepoint. Participants had a mean age of 39.84 (SD = 11.19). Most were born in the UK (89.6%), and reported their ethnicity as White (92.5%), Asian (3.0%), mixed (3.0%) and Black (1.5%). Many worked full-time (53.7%) or part-time (20.9%), and a minority (14.9%) were students. Data were analysed using Qualitative Descriptive Analysis. Four overarching themes emerged: (1) Key Reasons for Use; (2) Usability and Functionality; (3) Preferred In-App Interventions; and (4) Facilitators and Barriers to Sustained Engagement. Findings underscore the value of empathetic, personalised and readily available AI-enabled interventions for anxiety management, while also highlighting design challenges requiring refinement.
Details
- Title
- A thematic analysis of users’ experience of an AI-enabled mental health intervention for generalised anxiety symptoms
- Authors
- Zalia Powell - University of the Sunshine CoastAndrew Allen (Corresponding Author) - University of the Sunshine CoastCindy Davis - University of the Sunshine CoastAni GisnarianFrancine JellesmaJuan Ramos-Cejudo - Camilo José Cela UniversityJosé M. Salguero - Universidad de MálagaLuke Balcombe - Griffith UniversityAnton Vorobev - Dr Jay SAS (France)Evgeniia Ivanova - Dr Jay SAS (France)Nikolay Babakov - Toray (United States)Geoff P. Lovell - University of WorcesterVasileios Stavropoulos - RMIT UniversityLee Kannis-Dymand - University of the Sunshine Coast
- Publication details
- Behaviour and Information Technology, Vol.Advanced access
- Publisher
- Taylor & Francis
- DOI
- 10.1080/0144929X.2026.2706675
- ISSN
- 1362-3001
- Copyright note
- © 2026 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent.
- Grant note
- Recruitment for this study was funded by Dr Jay SAS.
- Organisation Unit
- Thompson Institute; Cancer Research Cluster; School of Health - Psychology; School of Law and Society; Sexual Violence Research and Prevention Unit; Sustainability Research Cluster
- Language
- English
- Record Identifier
- 991249395702621
- Output Type
- Journal article
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