Comprehensive perceptions at the interface between health and environment: Applications models with a citizen science tool
BackgroundLived experience - how individuals perceive and interact with their environment - plays a central role in understanding mental health. Yet, insights into this first-person perspective, including subjective thoughts, emotions, and socio-contextual influences, remain limited in current resea...
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| Hauptverfasser: | , , , , , , , , , |
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| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
20 November 2025
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| In: |
European psychiatry
Year: 2025, Jahrgang: 68, Heft: 1, Pages: 1-15 |
| ISSN: | 1778-3585 |
| DOI: | 10.1192/j.eurpsy.2025.10107 |
| Online-Zugang: | Verlag, kostenfrei, Volltext: https://doi.org/10.1192/j.eurpsy.2025.10107 Verlag, kostenfrei, Volltext: https://www.cambridge.org/core/journals/european-psychiatry/article/comprehensive-perceptions-at-the-interface-between-health-and-environment-applications-models-with-a-citizen-science-tool/D596AE75B11E48E36D26320B6C79DC95 
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| Verfasserangaben: | Frauke Nees, Karina Janson, Stephan Lehmler, Sarah Böttger, Mira Tschorn, Philipp Hummer, Gunter Schumann, Michael Rapp, Sebastian Siehl, Nathalie Holz and for the environMENTAL Consortium |
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| 520 | |a BackgroundLived experience - how individuals perceive and interact with their environment - plays a central role in understanding mental health. Yet, insights into this first-person perspective, including subjective thoughts, emotions, and socio-contextual influences, remain limited in current research approaches.MethodsTo address this gap, we developed StreetMind, a scalable, secure, and user-friendly digital citizen science platform grounded in a psycho-sociogeographic framework. The platform collects self-reported data on individuals’ activity spaces through a mobile app and web interface, capturing location visits, travel routes, and daily experiences. These subjective reports are combined with objective real-time health, environmental, and sociocultural data to generate integrated community “footprints.”ResultsInitial usage data (N = 1,010 for location and route entries; N = 509 for daily experiential data) demonstrate the platform’s structural robustness and functional feasibility. StreetMind enables classification of daily experiences by linking personal perceptions with contextual environmental data. This integration facilitates the identification and quantification of key environmental and psychosocial factors associated with mental well-being.ConclusionStreetMind offers a novel, data-rich mapping of health-environment interactions by merging individual lived experience with environmental metrics. This approach supports the creation of dynamic “health-environment spaces” and holds promise for informing public health strategies and advancing precision mental health care. | ||
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