A systematic review on passive sensing for the prediction of suicidal thoughts and behaviors

Rebekka Büscher; Tanita Winkler; Jacopo Mocellin; Stephanie Homan; Natasha Josifovski; Marketa Ciharova; Ward van Breda; Sam Kwon; Mark E. Larsen; John Torous; Joseph Firth; Lasse B. Sander

doi:10.1038/s44184-024-00089-4

npj Mental Health Research (Sep 2024)

A systematic review on passive sensing for the prediction of suicidal thoughts and behaviors

Rebekka Büscher,
Tanita Winkler,
Jacopo Mocellin,
Stephanie Homan,
Natasha Josifovski,
Marketa Ciharova,
Ward van Breda,
Sam Kwon,
Mark E. Larsen,
John Torous,
Joseph Firth,
Lasse B. Sander

Affiliations

Rebekka Büscher: Medical Psychology and Medical Sociology, Faculty of Medicine, University of Freiburg
Tanita Winkler: Medical Psychology and Medical Sociology, Faculty of Medicine, University of Freiburg
Jacopo Mocellin: Experimental Psychopathology and Psychotherapy, Department of Psychology, University of Zurich
Stephanie Homan: Experimental Psychopathology and Psychotherapy, Department of Psychology, University of Zurich
Natasha Josifovski: Black Dog Institute, University of New South Wales
Marketa Ciharova: Department of Clinical, Neuro and Developmental Psychology, Vrije Universiteit Amsterdam
Ward van Breda: Department of Clinical, Neuro and Developmental Psychology, Vrije Universiteit Amsterdam
Sam Kwon: Beth Israel Deaconess Medical Center, Harvard Medical School
Mark E. Larsen: Black Dog Institute, University of New South Wales
John Torous: Beth Israel Deaconess Medical Center, Harvard Medical School
Joseph Firth: Division of Psychology and Mental Health, Manchester Academic Health Science Centre, University of Manchester
Lasse B. Sander: Medical Psychology and Medical Sociology, Faculty of Medicine, University of Freiburg

DOI: https://doi.org/10.1038/s44184-024-00089-4
Journal volume & issue: Vol. 3, no. 1
pp. 1 – 10

Abstract

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Abstract Passive sensing data from smartphones and wearables may help improve the prediction of suicidal thoughts and behaviors (STB). In this systematic review, we explored the feasibility and predictive validity of passive sensing for STB. On June 24, 2024, we systematically searched Medline, Embase, Web of Science, PubMed, and PsycINFO. Studies were eligible if they investigated the association between STB and passive sensing, or the feasibility of passive sensing in this context. From 2107 unique records, we identified eleven prediction studies, ten feasibility studies, and seven protocols. Studies indicated generally lower model performance for passive compared to active data, with three out of four studies finding no incremental value. PROBAST ratings revealed major shortcomings in methodology and reporting. Studies suggested that passive sensing is feasible in high-risk populations. In conclusion, there is limited evidence on the predictive value of passive sensing for STB. We highlight important quality characteristics for future research.

Published in npj Mental Health Research

ISSN: 2731-4251 (Online)
Publisher: Nature Portfolio
Country of publisher: United Kingdom
LCC subjects: Medicine: Internal medicine: Neurosciences. Biological psychiatry. Neuropsychiatry: Neurology. Diseases of the nervous system: Psychiatry: Therapeutics. Psychotherapy
Website: https://www.nature.com/npjmentalhealth/

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