This paper is in the following e-collection/theme issue:

mHealth for Data Collection and Research (675) Depression and Mood Disorders; Suicide Prevention (1029) Evaluation and Research Methodology for mHealth (160) mHealth for Symptom and Disease Monitoring, Chronic Disease Management (1030) mHealth for Wellness, Behavior Change and Prevention (2268)

Published on in Vol 10 , No 3 (2022) :March

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/34148, first published .
Predicting Changes in Depression Severity Using the PSYCHE-D (Prediction of Severity Change-Depression) Model Involving Person-Generated Health Data: Longitudinal Case-Control Observational Study

Predicting Changes in Depression Severity Using the PSYCHE-D (Prediction of Severity Change-Depression) Model Involving Person-Generated Health Data: Longitudinal Case-Control Observational Study

Predicting Changes in Depression Severity Using the PSYCHE-D (Prediction of Severity Change-Depression) Model Involving Person-Generated Health Data: Longitudinal Case-Control Observational Study

Authors of this article:

Mariko Makhmutova 1 Author Orcid Image ;   Raghu Kainkaryam 2 Author Orcid Image ;   Marta Ferreira 2 Author Orcid Image ;   Jae Min 2 Author Orcid Image ;   Martin Jaggi 1 Author Orcid Image ;   Ieuan Clay 2, 3 Author Orcid Image
Article Authors Cited by (2) Tweetations (7) Metrics

Journals

  1. Makhmutova M, Kainkaryam R, Ferreira M, Min J, Jaggi M, Clay I. Predicting Changes in Depression Severity Using the PSYCHE-D (Prediction of Severity Change-Depression) Model Involving Person-Generated Health Data: Longitudinal Case-Control Observational Study. JMIR mHealth and uHealth 2022;10(3):e34148 View
  2. Abd-alrazaq A, AlSaad R, Aziz S, Ahmed A, Denecke K, Househ M, Farooq F, Sheikh J. Wearable Artificial Intelligence for Anxiety and Depression: Scoping Review. Journal of Medical Internet Research 2023;25:e42672 View