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

Mobile Health (mhealth) (3234) Depression and Mood Disorders; Suicide Prevention (1557) Machine Learning (1819) Artificial Intelligence (1833) Electronic/Mobile Data Capture, Internet-based Survey & Research Methodology (931) mHealth for Data Collection and Research (1109) Diagnostic Tools in Mental Health (287) Digital Biomarkers and Digital Phenotyping (238) Digital Mental Health Interventions, e-Mental Health and Cyberpsychology (1886)

Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/56874, first published .
Predicting and Monitoring Symptoms in Patients Diagnosed With Depression Using Smartphone Data: Observational Study

Predicting and Monitoring Symptoms in Patients Diagnosed With Depression Using Smartphone Data: Observational Study

Predicting and Monitoring Symptoms in Patients Diagnosed With Depression Using Smartphone Data: Observational Study

Authors of this article:

Arsi Ikäheimonen1 Author Orcid Image ;   Nguyen Luong1 Author Orcid Image ;   Ilya Baryshnikov2, 3 Author Orcid Image ;   Richard Darst4 Author Orcid Image ;   Roope Heikkilä5 Author Orcid Image ;   Joel Holmen6, 7 Author Orcid Image ;   Annasofia Martikkala2, 3 Author Orcid Image ;   Kirsi Riihimäki3, 8 Author Orcid Image ;   Outi Saleva3 Author Orcid Image ;   Erkki Isometsä2, 3 Author Orcid Image ;   Talayeh Aledavood1 Author Orcid Image
Article Authors Cited by (5) Tweetations (1) Metrics

Journals

  1. Aledavood T, Luong N, Baryshnikov I, Darst R, Heikkilä R, Holmén J, Ikäheimonen A, Martikkala A, Riihimäki K, Saleva O, Triana A, Isometsä E. Multimodal Digital Phenotyping Study in Patients With Major Depressive Episodes and Healthy Controls (Mobile Monitoring of Mood): Observational Longitudinal Study. JMIR Mental Health 2025;12:e63622 View
  2. Adam D. Digital phenotyping using smartphones could help steer mental health treatment. Proceedings of the National Academy of Sciences 2025;122(14) View
  3. Zha B, Cai A, Yu H, Wang Z. Development and validation of a predictive model for depression in patients with advanced stage of cardiovascular-kidney-metabolic syndrome. Journal of Affective Disorders 2025;383:32 View
  4. Shin Y, Kim A, Kim S, Shin M, Choi J, Lee K, Lee J, Byun S, Kim S, Lee H, Cho C. Development of prediction models for screening depression and anxiety using smartphone and wearable-based digital phenotyping: protocol for the Smartphone and Wearable Assessment for Real-Time Screening of Depression and Anxiety (SWARTS-DA) observational study in Korea. BMJ Open 2025;15(6):e096773 View
  5. Ringwald W, King G, Vize C, Wright A. Passive Smartphone Sensors for Detecting Psychopathology. JAMA Network Open 2025;8(7):e2519047 View