This paper is in the following e-collection/theme issue:

mHealth for Symptom and Disease Monitoring, Chronic Disease Management (1561) mHealth for Data Collection and Research (1077) Evaluation and Research Methodology for mHealth (219) mHealth for Wellness, Behavior Change and Prevention (3089) Depression and Mood Disorders; Suicide Prevention (1510) Mobile Health in Psychiatry (476) Digital Mental Health Interventions, e-Mental Health and Cyberpsychology (1792)

Published on in Vol 10, No 1 (2022): January

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/28095, first published .
The Association Between Home Stay and Symptom Severity in Major Depressive Disorder: Preliminary Findings From a Multicenter Observational Study Using Geolocation Data From Smartphones

The Association Between Home Stay and Symptom Severity in Major Depressive Disorder: Preliminary Findings From a Multicenter Observational Study Using Geolocation Data From Smartphones

The Association Between Home Stay and Symptom Severity in Major Depressive Disorder: Preliminary Findings From a Multicenter Observational Study Using Geolocation Data From Smartphones

Authors of this article:

Petroula Laiou1 Author Orcid Image ;   Dzmitry A Kaliukhovich2 Author Orcid Image ;   Amos A Folarin1, 3, 4, 5, 6 Author Orcid Image ;   Yatharth Ranjan1 Author Orcid Image ;   Zulqarnain Rashid1 Author Orcid Image ;   Pauline Conde1 Author Orcid Image ;   Callum Stewart1 Author Orcid Image ;   Shaoxiong Sun1 Author Orcid Image ;   Yuezhou Zhang1 Author Orcid Image ;   Faith Matcham7 Author Orcid Image ;   Alina Ivan7 Author Orcid Image ;   Grace Lavelle7 Author Orcid Image ;   Sara Siddi8, 9, 10 Author Orcid Image ;   Femke Lamers11 Author Orcid Image ;   Brenda WJH Penninx11 Author Orcid Image ;   Josep Maria Haro8, 9, 10 Author Orcid Image ;   Peter Annas12 Author Orcid Image ;   Nicholas Cummins1 Author Orcid Image ;   Srinivasan Vairavan13 Author Orcid Image ;   Nikolay V Manyakov2 Author Orcid Image ;   Vaibhav A Narayan13 Author Orcid Image ;   Richard JB Dobson1, 3, 4, 5, 6 Author Orcid Image ;   Matthew Hotopf4, 7 Author Orcid Image ;   RADAR-CNS14
Article Authors Cited by (19) Tweetations (21) Metrics

Journals

  1. Matcham F, Carr E, White K, Leightley D, Lamers F, Siddi S, Annas P, de Girolamo G, Haro J, Horsfall M, Ivan A, Lavelle G, Li Q, Lombardini F, Mohr D, Narayan V, Penninx B, Oetzmann C, Coromina M, Simblett S, Weyer J, Wykes T, Zorbas S, Brasen J, Myin-Germeys I, Conde P, Dobson R, Folarin A, Ranjan Y, Rashid Z, Cummins N, Dineley J, Vairavan S, Hotopf M. Predictors of engagement with remote sensing technologies for symptom measurement in Major Depressive Disorder. Journal of Affective Disorders 2022;310:106 View
  2. Kulkarni P, Kirkham R, McNaney R. Opportunities for Smartphone Sensing in E-Health Research: A Narrative Review. Sensors 2022;22(10):3893 View
  3. Zhang Y, Pratap A, Folarin A, Sun S, Cummins N, Matcham F, Vairavan S, Dineley J, Ranjan Y, Rashid Z, Conde P, Stewart C, White K, Oetzmann C, Ivan A, Lamers F, Siddi S, Rambla C, Simblett S, Nica R, Mohr D, Myin-Germeys I, Wykes T, Haro J, Penninx B, Annas P, Narayan V, Hotopf M, Dobson R. Long-term participant retention and engagement patterns in an app and wearable-based multinational remote digital depression study. npj Digital Medicine 2023;6(1) View
  4. Zhang Y, Folarin A, Sun S, Cummins N, Vairavan S, Bendayan R, Ranjan Y, Rashid Z, Conde P, Stewart C, Laiou P, Sankesara H, Matcham F, White K, Oetzmann C, Ivan A, Lamers F, Siddi S, Vilella E, Simblett S, Rintala A, Bruce S, Mohr D, Myin-Germeys I, Wykes T, Haro J, Penninx B, Narayan V, Annas P, Hotopf M, Dobson R. Longitudinal Relationships Between Depressive Symptom Severity and Phone-Measured Mobility: Dynamic Structural Equation Modeling Study. JMIR Mental Health 2022;9(3):e34898 View
  5. Hassenstein M, Janzen I, Krause G, Harries M, Melhorn V, Kerrinnes T, Kemmling Y, Castell S. Seroepidemiology of Borrelia burgdorferi s.l. among German National Cohort (NAKO) Participants, Hanover. Microorganisms 2022;10(11):2286 View
  6. Lin B, Chang C, Astell-Burt T, Feng X, Gardner J, Andersson E. Nature experience from yards provide an important space for mental health during Covid-19. npj Urban Sustainability 2023;3(1) View
  7. Sun S, Folarin A, Zhang Y, Cummins N, Garcia-Dias R, Stewart C, Ranjan Y, Rashid Z, Conde P, Laiou P, Sankesara H, Matcham F, Leightley D, White K, Oetzmann C, Ivan A, Lamers F, Siddi S, Simblett S, Nica R, Rintala A, Mohr D, Myin-Germeys I, Wykes T, Haro J, Penninx B, Vairavan S, Narayan V, Annas P, Hotopf M, Dobson R. Challenges in Using mHealth Data From Smartphones and Wearable Devices to Predict Depression Symptom Severity: Retrospective Analysis. Journal of Medical Internet Research 2023;25:e45233 View
  8. Bufano P, Laurino M, Said S, Tognetti A, Menicucci D. Digital Phenotyping for Monitoring Mental Disorders: Systematic Review. Journal of Medical Internet Research 2023;25:e46778 View
  9. Shin J, Bae S. A Systematic Review of Location Data for Depression Prediction. International Journal of Environmental Research and Public Health 2023;20(11):5984 View
  10. Harari G, Gosling S. Understanding behaviours in context using mobile sensing. Nature Reviews Psychology 2023;2(12):767 View
  11. Leaning I, Ikani N, Savage H, Leow A, Beckmann C, Ruhé H, Marquand A. From smartphone data to clinically relevant predictions: A systematic review of digital phenotyping methods in depression. Neuroscience & Biobehavioral Reviews 2024;158:105541 View
  12. Bryan A, Heinz M, Salzhauer A, Price G, Tlachac M, Jacobson N. Behind the Screen: A Narrative Review on the Translational Capacity of Passive Sensing for Mental Health Assessment. Biomedical Materials & Devices 2024;2(2):778 View
  13. Flandreau E, Risbrough V. Reframing and refining model system validity for anxiety and depression research: A commentary on Gencturk & Unal (2024). Cognitive, Affective, & Behavioral Neuroscience 2024;24(2):225 View
  14. van Heerden A, Poudyal A, Hagaman A, Maharjan S, Byanjankar P, Bemme D, Thapa A, Kohrt B. Integration of passive sensing technology to enhance delivery of psychological interventions for mothers with depression: the StandStrong study. Scientific Reports 2024;14(1) View
  15. Kas M, Hyman S, Williams L, Hidalgo-Mazzei D, Huys Q, Hotopf M, Cuthbert B, Lewis C, De Picker L, Lalousis P, Etkin A, Modinos G, Marston H. Towards a consensus roadmap for a new diagnostic framework for mental disorders. European Neuropsychopharmacology 2025;90:16 View
  16. Lee T, Chen C, Chen I, Chen H, Liu C, Wu S, Hsiao C, Kuo P. Dynamic Bidirectional Associations Between Global Positioning System Mobility and Ecological Momentary Assessment of Mood Symptoms in Mood Disorders: Prospective Cohort Study. Journal of Medical Internet Research 2024;26:e55635 View
  17. Aledavood T, Luong N, Baryshnikov I, Darst R, Heikkilä R, Holmén J, Ikäheimonen A, Martikkala A, Riihimäki K, Saleva O, Triana A, Isometsä E. Multimodal Digital Phenotyping Study in Patients With Major Depressive Episodes and Healthy Controls (Mobile Monitoring of Mood): Observational Longitudinal Study. JMIR Mental Health 2025;12:e63622 View
  18. Adam D. Digital phenotyping using smartphones could help steer mental health treatment. Proceedings of the National Academy of Sciences 2025;122(14) View

Conference Proceedings

  1. Gupta A, Maurya C, Dhere K, Chaurasiya V. 2022 IEEE 6th Conference on Information and Communication Technology (CICT). Wellness Detection Using Clustered Federated Learning View