ArticleDigital health
User perceptions and preferences for GeoHealth tools: A qualitative focus group study of non-expert and expert users.
Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Authors and funding
6 authors.
Funding
Abstract
Background: GeoHealth tools differ from other health-IT platforms, requiring analytical transformation tools, location-based discovery, and responsive design frameworks. While knowledge exists surrounding related platforms, there is a literature gap specific to GeoHealth tool end-user needs. Methods: This qualitative focus group study identified design needs for GeoHealth tools. Seven focus groups included non-experts (three sessions, n = 15) and experts (healthcare professionals, four sessions, n = 16) from October 2024 to February 2025. Researchers conducted inductive thematic analysis, identifying emerging themes. Results: Thirty-one participants completed seven sessions: 20 [65%] female, 16 [52%] White, and 16 [52%] with graduate degrees. Both groups identified similar facilitators and barriers: simple interfaces, contrasting colors, cross-device functionality. Both valued filtering, customizing regions, downloading data, and chatbot integration. Non-experts reported frustrations with mobile use and content density, while experts emphasized integrating GeoHealth tools into clinical workflows for decision-making. Discussion and Conclusion: End-user preferences are critical as GeoHealth tools expand. Key recommendations include: customizable features (filters, personalized regions, data layering, and export options), accessible design with high-contrast color schemes and intuitive navigation, and mobile optimization (tap-triggered overlays, optimized touch targets). Chatbots were valued with transparent data sourcing. Healthcare professionals highlighted integrating tools into Health-IT systems for clinical decision-making. These findings can improve usability and acceptance, making health information more accessible and potentially improving health outcomes. Future work should validate findings through iterative usability testing with diverse samples and investigate technical pathways for Health-IT integrations and trustworthy chatbot development.
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