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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.
Afiliação
  • Zhang Y; Department of Biostatistics & Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.
  • Folarin AA; Department of Biostatistics & Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.
  • Sun S; Institute of Health Informatics, University College London, London, United Kingdom.
  • Cummins N; NIHR Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London, London, United Kingdom.
  • Vairavan S; Health Data Research UK London, University College London, London, United Kingdom.
  • Bendayan R; NIHR Biomedical Research Centre at University College London Hospitals NHS Foundation Trust, London, United Kingdom.
  • Ranjan Y; Department of Biostatistics & Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.
  • Rashid Z; Department of Biostatistics & Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.
  • Conde P; Janssen Research and Development LLC, Titusville, NJ, United States.
  • Stewart C; Department of Biostatistics & Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.
  • Laiou P; NIHR Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London, London, United Kingdom.
  • Sankesara H; Department of Biostatistics & Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.
  • Matcham F; Department of Biostatistics & Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.
  • White KM; Department of Biostatistics & Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.
  • Oetzmann C; Department of Biostatistics & Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.
  • Ivan A; Department of Biostatistics & Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.
  • Lamers F; Department of Biostatistics & Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.
  • Siddi S; Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.
  • Vilella E; Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.
  • Simblett S; Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.
  • Rintala A; Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.
  • Bruce S; Department of Psychiatry, Amsterdam Public Health Research Institute and Amsterdam Neuroscience, Amsterdam University Medical Centre, Vrije Universiteit and GGZ inGeest, Amsterdam, Netherlands.
  • Mohr DC; Teaching Research and Innovation Unit, Parc Sanitari Sant Joan de Déu, Fundació Sant Joan de Déu, Barcelona, Spain.
  • Myin-Germeys I; Centro de Investigación Biomédica en Red de Salud Mental, Madrid, Spain.
  • Wykes T; Faculty of Medicine and Health Sciences, Universitat de Barcelona, Barcelona, Spain.
  • Haro JM; Centro de Investigación Biomédica en Red de Salud Mental, Madrid, Spain.
  • Penninx BW; Hospital Universitari Institut Pere Mata, Institute of Health Research Pere Virgili, Universitat Rovira i Virgili, Reus, Spain.
  • Narayan VA; Department of Psychology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.
  • Annas P; Center for Contextual Psychiatry, Department of Neurosciences, Katholieke Universiteit Leuven, Leuven, Belgium.
  • Hotopf M; Faculty of Social Services and Health Care, LAB University of Applied Sciences, Lahti, Finland.
  • Dobson RJ; RADAR-CNS Patient Advisory Board, King's College London, London, United Kingdom.
JMIR Ment Health ; 9(3): e34898, 2022 Mar 11.
Article em En | MEDLINE | ID: mdl-35275087
ABSTRACT

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.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: JMIR Ment Health Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Reino Unido

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: JMIR Ment Health Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Reino Unido