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

Wearable Devices and Sensors (888) Mobile Health (mhealth) (2939) mHealth for Data Collection and Research (955) mHealth for Wellness, Behavior Change and Prevention (2871) Depression and Mood Disorders; Suicide Prevention (1363) Fitness Trackers and Smart Pedometers/Accelerometers (561)

Published on in Vol 6, No 8 (2018): August

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/9691, first published .
Correlations Between Objective Behavioral Features Collected From Mobile and Wearable Devices and Depressive Mood Symptoms in Patients With Affective Disorders: Systematic Review

Correlations Between Objective Behavioral Features Collected From Mobile and Wearable Devices and Depressive Mood Symptoms in Patients With Affective Disorders: Systematic Review

Correlations Between Objective Behavioral Features Collected From Mobile and Wearable Devices and Depressive Mood Symptoms in Patients With Affective Disorders: Systematic Review

Authors of this article:

Darius A Rohani1, 2 Author Orcid Image ;   Maria Faurholt-Jepsen3 Author Orcid Image ;   Lars Vedel Kessing3, 4 Author Orcid Image ;   Jakob E Bardram1, 2 Author Orcid Image
Article Authors Cited by (127) Tweetations (17) Metrics

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  103. Knauer J, Baumeister H, Schmitt A, Terhorst Y. Acceptance of smart sensing, its determinants, and the efficacy of an acceptance-facilitating intervention in people with diabetes: results from a randomized controlled trial. Frontiers in Digital Health 2024;6 View
  104. Wang W, Chen J, Hu Y, Liu H, Chen J, Gadekallu T, Garg L, Guizani M, Hu X. Integration of Artificial Intelligence and Wearable Internet of Things for Mental Health Detection. International Journal of Cognitive Computing in Engineering 2024;5:307 View
  105. Terhorst Y, Knauer J, Philippi P, Baumeister H. The Relation Between Passively Collected GPS Mobility Metrics and Depressive Symptoms: Systematic Review and Meta-Analysis. Journal of Medical Internet Research 2024;26:e51875 View
  106. Beames J, Han J, Shvetcov A, Zheng W, Slade A, Dabash O, Rosenberg J, O'Dea B, Kasturi S, Hoon L, Whitton A, Christensen H, Newby J. Use of smartphone sensor data in detecting and predicting depression and anxiety in young people (12–25 years): A scoping review. Heliyon 2024;10(15):e35472 View
  107. Lamichhane B, Moukaddam N, Sabharwal A. Mobile sensing-based depression severity assessment in participants with heterogeneous mental health conditions. Scientific Reports 2024;14(1) View
  108. Jilka S, Giacco D. Digital phenotyping: how it could change mental health care and why we should all keep up. Journal of Mental Health 2024;33(4):439 View
  109. Edler J, Winter M, Steinmetz H, Cohrdes C, Baumeister H, Pryss R. Predicting depressive symptoms using GPS-based regional data: A study with the CORONA HEALTH app during the COVID-19 pandemic in Germany (Preprint). Interactive Journal of Medical Research 2023 View
  110. Terhorst Y, Messner E, Asare K, Montag C, Kannen C, Baumeister H. Which Smartphone-Based Sensing Features Matter in Depression Severity Prediction? Results from an Observation Study. (Preprint). Journal of Medical Internet Research 2023 View
  111. Lee T, Chen C, Chen I, Chen H, Wu S, Liu C, Hsiao C, Kuo P. Dynamic bidirectional associations between GPS mobility and ecological momentary assessment of mood symptoms in mood disorders (Preprint). Journal of Medical Internet Research 2023 View
  112. Lim D, Jeong J, Song Y, Cho C, Yeom J, Lee T, Lee J, Lee H, Kim J. Accurately predicting mood episodes in mood disorder patients using wearable sleep and circadian rhythm features. npj Digital Medicine 2024;7(1) View

Books/Policy Documents

  1. Välimäki M, Hipp K. Advanced Practice in Mental Health Nursing. View
  2. Opoku Asare K, Visuri A, Vega J, Ferreira D. Wireless Mobile Communication and Healthcare. View
  3. Hilty D, Armstrong C, Edwards-Stewart A, Luxton D. Digital Therapeutics for Mental Health and Addiction. View
  4. Terhorst Y, Knauer J, Baumeister H. Digital Phenotyping and Mobile Sensing. View
  5. Harrer M, Terhorst Y, Baumeister H, Ebert D. Digitale Gesundheitsinterventionen. View