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. 2022 Jan 7;10(1):e30557. doi: 10.2196/30557

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©Aditya Vaidyam, John Halamka, John Torous. Originally published in JMIR mHealth and uHealth (https://mhealth.jmir.org), 07.01.2022.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR mHealth and uHealth, is properly cited. The complete bibliographic information, a link to the original publication on https://mhealth.jmir.org/, as well as this copyright and license information must be included.

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Flow of the data collection process from native app to backend: (1) an activity specification describes the types of interactive elements available in the mindLAMP app, along with their possible configuration parameters; (2) when participants interact with a configured and scheduled activity (such as a mood survey based on the survey specification), all metadata and data from the interaction session is integrated into a single unit of patient-generated health data called events; (3) events are then submitted to the backend in real time as part of a continuously generated stream of patient-generated health data; and (4) clinicians and researchers are able to perform continuously updating queries on the data with their desired parameters.