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

Methods and Feasibility Studies (764) Mobile Health (mhealth) (5232) mHealth for Data Collection and Research (1751) Depression and Mood Disorders; Suicide Prevention (2494) Diagnostic Tools in Mental Health (447) Formative Evaluation of Digital Health Interventions (5249) Development and Evaluation of Research Methods, Instruments and Tools (1366)

Published on in Vol 13 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/51540, first published .
Young Indian businessman in blue shirt using smartphone in office hallway

Investigating Rhythmicity in App Usage to Predict Depressive Symptoms: Protocol for Personalized Framework Development and Validation Through a Countrywide Study

Investigating Rhythmicity in App Usage to Predict Depressive Symptoms: Protocol for Personalized Framework Development and Validation Through a Countrywide Study

Authors of this article:

Md Sabbir Ahmed1 Author Orcid Image ;   Tanvir Hasan1 Author Orcid Image ;   Salekul Islam2 Author Orcid Image ;   Nova Ahmed1 Author Orcid Image
Article Authors Cited by (2) Tweetations (6) Metrics

Journals

  1. Castillo Zorro C, Fonzo G, Moscoso-Barrera W. Use of physiological signals, behavioral data, and processing algorithms in electronic devices and mobile applications for diagnosing depression, anxiety, and stress. DIGITAL HEALTH 2026;12 View
  2. Ismail M, Yusoff M, Zulkifli Z, Saad A, Abidin M, Rahim A. Implementation Determinants for AI-Enabled Digital Mental Health Interventions Across Asian Mental Health Systems: A Scoping Review Using the Donabedian Model. Administration and Policy in Mental Health and Mental Health Services Research 2026 View