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Longitudinal Relationships Between Depressive Symptom Severity and Phone-Measured Mobility: Dynamic Structural Equation Modeling Study
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...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8957008/ https://www.ncbi.nlm.nih.gov/pubmed/35275087 http://dx.doi.org/10.2196/34898 |
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author | Zhang, Yuezhou Folarin, Amos A Sun, Shaoxiong Cummins, Nicholas Vairavan, Srinivasan Bendayan, Rebecca Ranjan, Yatharth Rashid, Zulqarnain Conde, Pauline Stewart, Callum Laiou, Petroula Sankesara, Heet Matcham, Faith White, Katie M Oetzmann, Carolin Ivan, Alina Lamers, Femke Siddi, Sara Vilella, Elisabet Simblett, Sara Rintala, Aki Bruce, Stuart Mohr, David C Myin-Germeys, Inez Wykes, Til Haro, Josep Maria Penninx, Brenda WJH Narayan, Vaibhav A Annas, Peter Hotopf, Matthew Dobson, Richard JB |
author_facet | Zhang, Yuezhou Folarin, Amos A Sun, Shaoxiong Cummins, Nicholas Vairavan, Srinivasan Bendayan, Rebecca Ranjan, Yatharth Rashid, Zulqarnain Conde, Pauline Stewart, Callum Laiou, Petroula Sankesara, Heet Matcham, Faith White, Katie M Oetzmann, Carolin Ivan, Alina Lamers, Femke Siddi, Sara Vilella, Elisabet Simblett, Sara Rintala, Aki Bruce, Stuart Mohr, David C Myin-Germeys, Inez Wykes, Til Haro, Josep Maria Penninx, Brenda WJH Narayan, Vaibhav A Annas, Peter Hotopf, Matthew Dobson, Richard JB |
author_sort | Zhang, Yuezhou |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-8957008 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | JMIR Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-89570082022-03-27 Longitudinal Relationships Between Depressive Symptom Severity and Phone-Measured Mobility: Dynamic Structural Equation Modeling Study Zhang, Yuezhou Folarin, Amos A Sun, Shaoxiong Cummins, Nicholas Vairavan, Srinivasan Bendayan, Rebecca Ranjan, Yatharth Rashid, Zulqarnain Conde, Pauline Stewart, Callum Laiou, Petroula Sankesara, Heet Matcham, Faith White, Katie M Oetzmann, Carolin Ivan, Alina Lamers, Femke Siddi, Sara Vilella, Elisabet Simblett, Sara Rintala, Aki Bruce, Stuart Mohr, David C Myin-Germeys, Inez Wykes, Til Haro, Josep Maria Penninx, Brenda WJH Narayan, Vaibhav A Annas, Peter Hotopf, Matthew Dobson, Richard JB JMIR Ment Health Original Paper 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. JMIR Publications 2022-03-11 /pmc/articles/PMC8957008/ /pubmed/35275087 http://dx.doi.org/10.2196/34898 Text en ©Yuezhou Zhang, Amos A Folarin, Shaoxiong Sun, Nicholas Cummins, Srinivasan Vairavan, Rebecca Bendayan, Yatharth Ranjan, Zulqarnain Rashid, Pauline Conde, Callum Stewart, Petroula Laiou, Heet Sankesara, Faith Matcham, Katie M White, Carolin Oetzmann, Alina Ivan, Femke Lamers, Sara Siddi, Elisabet Vilella, Sara Simblett, Aki Rintala, Stuart Bruce, David C Mohr, Inez Myin-Germeys, Til Wykes, Josep Maria Haro, Brenda WJH Penninx, Vaibhav A Narayan, Peter Annas, Matthew Hotopf, Richard JB Dobson, RADAR-CNS consortium. Originally published in JMIR Mental Health (https://mental.jmir.org), 11.03.2022. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Mental Health, is properly cited. The complete bibliographic information, a link to the original publication on https://mental.jmir.org/, as well as this copyright and license information must be included. |
spellingShingle | Original Paper Zhang, Yuezhou Folarin, Amos A Sun, Shaoxiong Cummins, Nicholas Vairavan, Srinivasan Bendayan, Rebecca Ranjan, Yatharth Rashid, Zulqarnain Conde, Pauline Stewart, Callum Laiou, Petroula Sankesara, Heet Matcham, Faith White, Katie M Oetzmann, Carolin Ivan, Alina Lamers, Femke Siddi, Sara Vilella, Elisabet Simblett, Sara Rintala, Aki Bruce, Stuart Mohr, David C Myin-Germeys, Inez Wykes, Til Haro, Josep Maria Penninx, Brenda WJH Narayan, Vaibhav A Annas, Peter Hotopf, Matthew Dobson, Richard JB Longitudinal Relationships Between Depressive Symptom Severity and Phone-Measured Mobility: Dynamic Structural Equation Modeling Study |
title | Longitudinal Relationships Between Depressive Symptom Severity and Phone-Measured Mobility: Dynamic Structural Equation Modeling Study |
title_full | Longitudinal Relationships Between Depressive Symptom Severity and Phone-Measured Mobility: Dynamic Structural Equation Modeling Study |
title_fullStr | Longitudinal Relationships Between Depressive Symptom Severity and Phone-Measured Mobility: Dynamic Structural Equation Modeling Study |
title_full_unstemmed | Longitudinal Relationships Between Depressive Symptom Severity and Phone-Measured Mobility: Dynamic Structural Equation Modeling Study |
title_short | Longitudinal Relationships Between Depressive Symptom Severity and Phone-Measured Mobility: Dynamic Structural Equation Modeling Study |
title_sort | longitudinal relationships between depressive symptom severity and phone-measured mobility: dynamic structural equation modeling study |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8957008/ https://www.ncbi.nlm.nih.gov/pubmed/35275087 http://dx.doi.org/10.2196/34898 |
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