This study explored whether vibe coding, building software by describing it in natural language to a generative AI tool, enables health professionals without programming skills to develop digital health applications. In a three-hour workshop, medical students built working mHealth prototypes for dementia care challenges. Every group succeeded, but none of the prototypes protected users’ health data, showing that this democratisation must be paired with training.
What was the context of our study?
Vibe coding tools generate software from natural language prompts using generative AI, dramatically lowering the technical barrier to building applications. This could empower health professionals without programming backgrounds to create digital health tools, yet the approach remains largely unexplored in the literature.
What did we do?
Using a design science approach, we ran a three-hour, in-person workshop in which medical students used a vibe coding platform to build mHealth prototypes for dementia care challenges. The process covered problem identification, ideation, prototyping, presentation and reflection. Data came from participant observation, review of the prototypes and a post-workshop satisfaction survey.
What did we find?
All three groups built functional prototypes within the allotted time.
- Enablers: Conversational accessibility, immediately visible results and direct relevance to clinical practice.
- Barriers: Unfamiliarity with health data privacy regulations and a tendency to define problems too broadly.
- Risks: None of the prototypes included security measures such as user authentication or data encryption.
Why is this important?
Vibe coding can bring health professionals much closer to developing their own digital health applications. But this democratisation is not enough on its own: it must be accompanied by training in data security, health informatics and AI fundamentals.
Reference
Quispe CK, Berhongaray Kenny E, Gamez I, Couce A, Brusco LI, Giunti G. Vibe Coding to Democratize Dementia mHealth Development: Preliminary Findings. Studies in Health Technology and Informatics. 2026;338:601–605. https://doi.org/10.3233/SHTI260915