%0 Journal Article
%@ 2368-7959
%I JMIR Publications
%V 9
%N 3
%P e34898
%T Longitudinal Relationships Between Depressive Symptom Severity and Phone-Measured Mobility: Dynamic Structural Equation Modeling Study
%A Zhang,Yuezhou
%A Folarin,Amos A
%A Sun,Shaoxiong
%A Cummins,Nicholas
%A Vairavan,Srinivasan
%A Bendayan,Rebecca
%A Ranjan,Yatharth
%A Rashid,Zulqarnain
%A Conde,Pauline
%A Stewart,Callum
%A Laiou,Petroula
%A Sankesara,Heet
%A Matcham,Faith
%A White,Katie M
%A Oetzmann,Carolin
%A Ivan,Alina
%A Lamers,Femke
%A Siddi,Sara
%A Vilella,Elisabet
%A Simblett,Sara
%A Rintala,Aki
%A Bruce,Stuart
%A Mohr,David C
%A Myin-Germeys,Inez
%A Wykes,Til
%A Haro,Josep Maria
%A Penninx,Brenda WJH
%A Narayan,Vaibhav A
%A Annas,Peter
%A Hotopf,Matthew
%A Dobson,Richard JB
%A ,
%+ Department of Biostatistics & Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, De Crespigny Park, Denmark Hill, London, SE5 8AF, United Kingdom, 44 20 7848 0473, richard.j.dobson@kcl.ac.uk
%K depression
%K mobile health
%K location data
%K mobility
%K dynamic structural equation modeling
%K mHealth
%K mental health
%K medical informatics
%K modeling
%D 2022
%7 11.3.2022
%9 Original Paper
%J JMIR Ment Health
%G English
%X Background: The mobility of an individual measured by phone-collected location data has been found to be associated with depression; however, the longitudinal relationships (the temporal direction of relationships) between depressive symptom severity and phone-measured mobility have yet to be fully explored. Objective: We aimed to explore the relationships and the direction of the relationships between depressive symptom severity and phone-measured mobility over time. Methods: Data used in this paper came from a major EU program, called the Remote Assessment of Disease and Relapse–Major Depressive Disorder, which was conducted in 3 European countries. Depressive symptom severity was measured with the 8-item Patient Health Questionnaire (PHQ-8) through mobile phones every 2 weeks. Participants’ location data were recorded by GPS and network sensors in mobile phones every 10 minutes, and 11 mobility features were extracted from location data for the 2 weeks prior to the PHQ-8 assessment. Dynamic structural equation modeling was used to explore the longitudinal relationships between depressive symptom severity and phone-measured mobility. Results: This study included 2341 PHQ-8 records and corresponding phone-collected location data from 290 participants (age: median 50.0 IQR 34.0, 59.0) years; of whom 215 (74.1%) were female, and 149 (51.4%) were employed. Significant negative correlations were found between depressive symptom severity and phone-measured mobility, and these correlations were more significant at the within-individual level than the between-individual level. For the direction of relationships over time, Homestay (time at home) (φ=0.09, P=.01), Location Entropy (time distribution on different locations) (φ=−0.04, P=.02), and Residential Location Count (reflecting traveling) (φ=0.05, P=.02) were significantly correlated with the subsequent changes in the PHQ-8 score, while changes in the PHQ-8 score significantly affected (φ=−0.07, P<.001) the subsequent periodicity of mobility. Conclusions: Several phone-derived mobility features have the potential to predict future depression, which may provide support for future clinical applications, relapse prevention, and remote mental health monitoring practices in real-world settings. 
%M 35275087
%R 10.2196/34898
%U https://mental.jmir.org/2022/3/e34898
%U https://doi.org/10.2196/34898
%U http://www.ncbi.nlm.nih.gov/pubmed/35275087