The Relation Between Passively Collected GPS Mobility Metrics and Depressive Symptoms: Systematic Review and Meta-Analysis.

J Med Internet Res

Department of Clinical Psychology and Psychotherapy, Institute of Psychology and Education, University Ulm, Ulm, Germany.

Published: November 2024

AI Article Synopsis

  • The study explores the potential use of GPS data collected from devices like smartphones to assess depression, as current methods may benefit from this type of unobtrusive data.
  • Researchers reviewed 19 studies with nearly 3,000 participants to analyze the relationship between GPS features (like distance traveled) and depressive symptoms.
  • Significant correlations were found, indicating that less distance traveled (and other GPS metrics) is associated with higher levels of depression symptoms, suggesting GPS data could be a valuable tool in understanding mental health.

Article Abstract

Background: The objective, unobtrusively collected GPS features (eg, homestay and distance) from everyday devices like smartphones may offer a promising augmentation to current assessment tools for depression. However, to date, there is no systematic and meta-analytical evidence on the associations between GPS features and depression.

Objective: This study aimed to investigate the between-person and within-person correlations between GPS mobility and activity features and depressive symptoms, and to critically review the quality and potential publication bias in the field.

Methods: We searched MEDLINE, PsycINFO, Embase, CENTRAL, ACM, IEEE Xplore, PubMed, and Web of Science to identify eligible articles focusing on the correlations between GPS features and depression from December 6, 2022, to March 24, 2023. Inclusion and exclusion criteria were applied in a 2-stage inclusion process conducted by 2 independent reviewers (YT and JK). To be eligible, studies needed to report correlations between wearable-based GPS variables (eg, total distance) and depression symptoms measured with a validated questionnaire. Studies with underage persons and other mental health disorders were excluded. Between- and within-person correlations were analyzed using random effects models. Study quality was determined by comparing studies against the STROBE (Strengthening the Reporting of Observational studies in Epidemiology) guidelines. Publication bias was investigated using Egger test and funnel plots.

Results: A total of k=19 studies involving N=2930 participants were included in the analysis. The mean age was 38.42 (SD 18.96) years with 59.64% (SD 22.99%) of participants being female. Significant between-person correlations between GPS features and depression were identified: distance (r=-0.25, 95% CI -0.29 to -0.21), normalized entropy (r-0.17, 95% CI -0.29 to -0.04), location variance (r-0.17, 95% CI -0.26 to -0.04), entropy (r=-0.13, 95% CI -0.23 to -0.04), number of clusters (r=-0.11, 95% CI -0.18 to -0.03), and homestay (r=0.10, 95% CI 0.00 to 0.19). Studies reporting within-correlations (k=3) were too heterogeneous to conduct meta-analysis. A deficiency in study quality and research standards was identified: all studies followed exploratory observational designs, but no study referenced or fully adhered to the international guidelines for reporting observational studies (STROBE). A total of 79% (k=15) of the studies were underpowered to detect a small correlation (r=.20). Results showed evidence for potential publication bias.

Conclusions: Our results provide meta-analytical evidence for between-person correlations of GPS mobility and activity features and depression. Hence, depression diagnostics may benefit from adding GPS mobility and activity features as an integral part of future assessment and expert tools. However, confirmatory studies for between-person correlations and further research on within-person correlations are needed. In addition, the methodological quality of the evidence needs to improve.

Trial Registration: OSF Registeries cwder; https://osf.io/cwder.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11568401PMC
http://dx.doi.org/10.2196/51875DOI Listing

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