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

Digital Mental Health Interventions, e-Mental Health and Cyberpsychology (1701) mHealth for Data Collection and Research (1035) Depression and Mood Disorders; Suicide Prevention (1466) Wearable Devices and Sensors (947) Digital Biomarkers and Digital Phenotyping (215) Diagnostic Tools in Mental Health (272) Ecological Momentary Assessment (EMA) (336)

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 Tweetations (2) Metrics
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KONDO Masahiro KONDO Masahiro @mkondo1042

スマートフォンで取得された客観的なデータ（GPSに基づく在宅時間など）とうつ病の重症度の関連に対する観察研究。 "Investigating Smartphone-Based Sensing Features for Depression Severity Prediction: Observation Study" https://t.co/HUPzJysmOc

5:04 AM · Feb 04, 2025

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レンタル博士 レンタル博士 @ToM_Psy_s

RT @mkondo1042: スマートフォンで取得された客観的なデータ（GPSに基づく在宅時間など）とうつ病の重症度の関連に対する観察研究。 "Investigating Smartphone-Based Sensing Features for Depression Se…

1:02 AM · Feb 15, 2025

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