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A Participatory Design of Conversational Artificial Intelligence Agents for Mental Healthcare Application (Preprint)


 BACKGROUND
 Mobile applications for mental health are available on the market. While they seem to be promising for improving the accessibility of mental health care, little is known about their acceptance, design methodology, evaluation, and integration into protocolized psychotherapy. This makes it difficult for the healthcare professionals to judge whether these applications may help them and their patients.
 
 
 OBJECTIVE
 Describing and evaluating a protocol for the participatory design of mobile applications for mental health (m-health app). In this study, participants and psychotherapists are engaged in the early phases of the design and development of the application empowered by Conversational Artificial Intelligence (AI). The application supports interventions for Stress Management Training based on Cognitive Behavioral Theory.
 
 
 METHODS
 21 participants aged 33-61 with mild to moderate levels of stress, anxiety and depression (assessed by submitting them with the Italian version of SCL-90-R, OSI, and PSS scale) were assigned to two groups, A and B. Both groups received stress management training sessions along with cognitive behavioral treatment, but only participants assigned to Group A received support by a mobile personal healthcare agent, designed for mental care and empowered by AI techniques. Psychopathological outcomes were assessed by submitting those tests at baseline (T1), following eight weeks of treatment (T2), and after three months post-treatment (T3). A focus group with psychotherapists who administered the therapy was held post-treatment to collect their impressions and suggestions.
 
 
 RESULTS
 While the inter-group statistical analysis showed that Group B participants could rely on better coping strategies at T3, Group A subjects reported significant improvements in Obsessivity and Compulsivity assessment between T1 and T3. Psychotherapists’ acceptance of the protocol was good. In particular they were in favor of integrating an AI based m-health application in their practice because they could appreciate the increased engagement of patients in pursuing therapy goals.
 
 
 CONCLUSIONS
 The integration of an AI-based mobile application for m-health showed to be effective in improving participants’ strategies for coping with stress and anxiety. At the same time, the mental health professionals involved in the experiment reported interest and acceptance of the proposal of integrating AI-based conversational support in their daily practice.
 
 
 CLINICALTRIAL
 The protocol and the experimental plan were approved by the Ethical Committee of the University of Trento, Italy. The research described in this paper was the initial and exploratory phase of a larger intervention protocol that is currently registered in Clinical Trials, with reference NCT04809090.
