Accepted for/Published in: Journal of Medical Internet Research
Date Submitted: Mar 6, 2025
Open Peer Review Period: Mar 7, 2025 - May 2, 2025
Date Accepted: Oct 20, 2025
(closed for review but you can still tweet)
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Exploring Generative AI in Digital Mental Health: Adolescent Perspectives from Rural South Africa on Culturally Relevant Content Creation
ABSTRACT
Background:
The Kuamsha app was originally developed for a two-arm randomised controlled pilot trial (the DoBAt study), which assessed the feasibility, acceptability, and initial efficacy of a digital choose-your-own-adventure style serious game that delivered behavioural activation (BA) therapy to adolescents with depression in rural South Africa.
Objective:
This qualitative study explored the role of generative artificial intelligence (AI) as a novel method of developing engaging, relatable, and relevant digital mental health content for adolescents in rural South Africa.
Methods:
Through interactive, exploratory workshops and focus group discussions, adolescents compared stories, images, and songs created by generative AI to those in the Kuamsha app, a digital mental health intervention developed without AI.
Results:
Inductive thematic analysis revealed three themes: ‘Use of generative AI tools in a workshop’, ‘Reflections on the creations and comparison’ and ‘Thinking towards the future’. Adolescents generally showed a preference for AI-generated media compared to the Kuamsha app media, and the creative process was an important aspect of the process for adolescents.
Conclusions:
This study highlighted current biases of existing generative AI tools while also demonstrating the significant potential of generative AI to enhance ‘real-time’ co-design of digital mental health interventions by incorporating more culturally relevant and personalised content.
Citation
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Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.