Remote Digital Psychiatry for Mobile Mental Health Assessment and Therapy: MindLogger Platform Development Study

Universal access to assessment and treatment of mental health and learning disorders remains a significant and unmet need. There are many people without access to care because of economic, geographic, and cultural barriers, as well as the limited availability of clinical experts who could help advan...

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Veröffentlicht in:Journal of medical Internet research 2021-11, Vol.23 (11), p.e22369-e22369
Hauptverfasser: Klein, Arno, Clucas, Jon, Krishnakumar, Anirudh, Ghosh, Satrajit S, Van Auken, Wilhelm, Thonet, Benjamin, Sabram, Ihor, Acuna, Nino, Keshavan, Anisha, Rossiter, Henry, Xiao, Yao, Semenuta, Sergey, Badioli, Alessandra, Konishcheva, Kseniia, Abraham, Sanu Ann, Alexander, Lindsay M, Merikangas, Kathleen R, Swendsen, Joel, Lindner, Ariel B, Milham, Michael P
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Sprache:eng
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Zusammenfassung:Universal access to assessment and treatment of mental health and learning disorders remains a significant and unmet need. There are many people without access to care because of economic, geographic, and cultural barriers, as well as the limited availability of clinical experts who could help advance our understanding and treatment of mental health. This study aims to create an open, configurable software platform to build clinical measures, mobile assessments, tasks, and interventions without programming expertise. Specifically, our primary requirements include an administrator interface for creating and scheduling recurring and customized questionnaires where end users receive and respond to scheduled notifications via an iOS or Android app on a mobile device. Such a platform would help relieve overwhelmed health systems and empower remote and disadvantaged subgroups in need of accurate and effective information, assessment, and care. This platform has the potential to advance scientific research by supporting the collection of data with instruments tailored to specific scientific questions from large, distributed, and diverse populations. We searched for products that satisfy these requirements. We designed and developed a new software platform called MindLogger, which exceeds the requirements. To demonstrate the platform's configurability, we built multiple applets (collections of activities) within the MindLogger mobile app and deployed several of them, including a comprehensive set of assessments underway in a large-scale, longitudinal mental health study. Of the hundreds of products we researched, we found 10 that met our primary requirements with 4 that support end-to-end encryption, 2 that enable restricted access to individual users' data, 1 that provides open-source software, and none that satisfy all three. We compared features related to information presentation and data capture capabilities; privacy and security; and access to the product, code, and data. We successfully built MindLogger mobile and web applications, as well as web browser-based tools for building and editing new applets and for administering them to end users. MindLogger has end-to-end encryption, enables restricted access, is open source, and supports a variety of data collection features. One applet is currently collecting data from children and adolescents in our mental health study, and other applets are in different stages of testing and deployment for use in clinical a
ISSN:1438-8871
1439-4456
1438-8871
DOI:10.2196/22369