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

Digital Mental Health Interventions, e-Mental Health and Cyberpsychology (2111) mHealth for Data Collection and Research (1196) Depression and Mood Disorders; Suicide Prevention (1691) Wearable Devices and Sensors (1133) Digital Biomarkers and Digital Phenotyping (284) Diagnostic Tools in Mental Health (326) Ecological Momentary Assessment (EMA) (405)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/55308, first published .
Investigating Smartphone-Based Sensing Features for Depression Severity Prediction: Observation Study

Investigating Smartphone-Based Sensing Features for Depression Severity Prediction: Observation Study

Investigating Smartphone-Based Sensing Features for Depression Severity Prediction: Observation Study

Authors of this article:

Yannik Terhorst1, 2, 3 Author Orcid Image ;   Eva-Maria Messner1 Author Orcid Image ;   Kennedy Opoku Asare4 Author Orcid Image ;   Christian Montag5 Author Orcid Image ;   Christopher Kannen5 Author Orcid Image ;   Harald Baumeister1 Author Orcid Image
Article Authors Cited by (2) Tweetations (2) Metrics

Journals

  1. Zhu N, Sarawgi A, Bühner M, Baumeister H, Garatva P, Ehring T, Terhorst Y. The relation between passively collected data and PTSD: a systematic review and meta-analysis. npj Digital Medicine 2025;8(1) View
  2. Moreira L, Sá M, de Mendonça L, Raddaoui L, Elabd N, Rahman Z, Silva Júnior J, Campos L, Baltatu O. Predictive modeling of depression and anxiety after myocardial infarction: a study on influential factors and heart rate variability. Health Information Science and Systems 2025;13(1) View