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

mHealth for Data Collection and Research (1231) Evaluation and Research Methodology for mHealth (251) Digital Biomarkers and Digital Phenotyping (307) Digital Health Reviews (1794) Diagnostic Tools in Mental Health (335)

Published on in Vol 14 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/70840, first published .
Distinguishing Common Digital Phenotyping and Self-Report Parameters for Monitoring and Predicting Depression: Scoping Review

Distinguishing Common Digital Phenotyping and Self-Report Parameters for Monitoring and Predicting Depression: Scoping Review

Distinguishing Common Digital Phenotyping and Self-Report Parameters for Monitoring and Predicting Depression: Scoping Review

Authors of this article:

Lisa Busshart1 Author Orcid Image ;   Milica Petrovic1 Author Orcid Image ;   Rebeka Amin1 Author Orcid Image ;   Ulrich Hegerl1, 2 Author Orcid Image
Article Authors Cited by Tweetations Metrics

Lisa Busshart   1 * ;   Milica Petrovic   1 * , PhD ;   Rebeka Amin   1 , PhD ;   Ulrich Hegerl   1, 2 * , Prof Dr Med

1 Department of Psychiatry, Psychosomatics and Psychotherapy, University Hospital Frankfurt, Research Center of German Foundation for Depression and Suicide Prevention, Frankfurt am Main, Germany

2 Department for Psychiatry, Psychosomatics and Psychotherapy, Goethe University Frankfurt, Goethe Research Professorship, Frankfurt am Main, Germany

*these authors contributed equally

Corresponding Author:

  • Lisa Busshart
  • Department of Psychiatry, Psychosomatics and Psychotherapy
  • University Hospital Frankfurt, Research Center of German Foundation for Depression and Suicide Prevention
  • Heinrich-Hoffmann-Str. 10
  • Frankfurt am Main 60528
  • Germany
  • Phone: 49 162 9464667
  • Email: lisa.busshart@deutsche-depressionshilfe.de