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Evaluating the Impact AI Avatar-led Mental Health Interventions for Keeping Employees in Work
Sponsor: University of Roehampton
Summary
This study will examine whether an artificial intelligence (AI) avatar-led mental health programme can help employees experiencing symptoms of depression. The programme delivers structured, self-guided psychological support over several short sessions that participants complete online over a period of several weeks. Approximately 50-80 adults will take part. Participants will be randomly assigned either to start the AI programme immediately or to continue with their usual support and access the programme later. All participants will complete questionnaires before and after the study period to assess changes in mood, anxiety, and work functioning. Some participants will also be invited to take part in brief interviews to share their experiences of using the programme. The aim of the study is to evaluate whether this AI-based intervention can improve mental health and workplace functioning, and to assess how acceptable and safe it is for use in a working population.
Key Details
Gender
All
Age Range
18 Years - Any
Study Type
INTERVENTIONAL
Enrollment
50
Start Date
2025-10-07
Completion Date
2026-06-30
Last Updated
2026-02-27
Healthy Volunteers
No
Conditions
Interventions
Remi, AI avatar-led cognitive behavioural therapy intervention
The InsideOut AI programme for low mood is based on principles of Cognitive Behavioral Therapy (CBT), adapted into a self-paced, avatar-led format. Participants in the intervention group will complete six sessions over a four to six-week period, each lasting 10-15 minutes. The sessions will cover the following key components: 1. Session 1-2: Psychoeducation on depression and the role of CBT. 2. Session 3-4: Cognitive restructuring techniques to challenge negative thought patterns. 3. Session 5-6: Coping behavioural strategies for managing low mood and preventing relapse. The programme is designed to be fully automated, with personalised feedback provided by the AI avatar based on participants' responses and progress. Throughout the programme, participants will also complete self-check-ins to track their mood and identify progress. Engagement and adherence to the programme will be monitored through the platform's data analytics, allowing us to track session completion rates and user int
Locations (1)
University of Roehampton
London, United Kingdom