Mobile-phone-readable 2.45GHz passive digital sensor tag

Background: Objective unobtrusively collected GPS features (e.g., homestay, 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 metaanalytical evidence on the associations between GPS features and depression.Objective: The present systematic review with meta-analysis investigated the between-person and within-person correlations between GPS features and depressive symptoms. Furthermore, it critically reviews 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. In-and exclusion criteria were applied in a two-stage inclusion process conducted by two independent reviewers. Between and within-person correlations were analyzed using random effects models. Study quality was determined by comparing studies against the STROBE guidelines. Publication bias was investigated using Egger's test and funnel plots.Results: A total of k=19 studies involving N=2,930 participants were included in the analysis. Mean age was M=28.42 (SD=18.96) with 59.64% participants being female. Significant between-person correlations between GPS features and depression were identified: Distance (r=-0.25, 95%-

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

Terhorst,

Knauer,

Philippi

et al. 2023

Preprint

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BACKGROUND Objective unobtrusively collected GPS features (e.g., homestay, 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 The present systematic review with meta-analysis investigated the between-person and within-person correlations between GPS features and depressive symptoms. Furthermore, it critically reviews 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. In- and exclusion criteria were applied in a two-stage inclusion process conducted by two independent reviewers. Between and within-person correlations were analyzed using random effects models. Study quality was determined by comparing studies against the STROBE guidelines. Publication bias was investigated using Egger’s test and funnel plots. RESULTS A total of k=19 studies involving N=2,930 participants were included in the analysis. Mean age was M=28.42 (SD=18.96) with 59.64% 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 heterogenous 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). 79% 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 features and depression. Hence, depression diagnostics may benefit from adding GPS features as an integral part in 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. CLINICALTRIAL https://osf.io/cwder

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Mobile-phone-readable 2.45GHz passive digital sensor tag

Cited by 3 publications

References 8 publications

Battery-free wireless sensors for industrial applications based on UHF RFID technology

Battery-free wireless sensors for industrial applications based on UHF RFID technology

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

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

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