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

Wearable Devices and Sensors (825) Mobile Health (mhealth) (2777) Evaluation and Research Methodology for mHealth (195) mHealth for Symptom and Disease Monitoring, Chronic Disease Management (1317) mHealth for Data Collection and Research (917) Depression and Mood Disorders; Suicide Prevention (1290) Insomnia and Sleep Hygiene (153) Sleep Monitoring, Sleep Quality, Sleep Disorders (170)

Published on in Vol 9, No 4 (2021): April

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/24604, first published .
Relationship Between Major Depression Symptom Severity and Sleep Collected Using a Wristband Wearable Device: Multicenter Longitudinal Observational Study

Relationship Between Major Depression Symptom Severity and Sleep Collected Using a Wristband Wearable Device: Multicenter Longitudinal Observational Study

Relationship Between Major Depression Symptom Severity and Sleep Collected Using a Wristband Wearable Device: Multicenter Longitudinal Observational Study

Authors of this article:

Yuezhou Zhang1 Author Orcid Image ;   Amos A Folarin1, 2, 3 Author Orcid Image ;   Shaoxiong Sun1 Author Orcid Image ;   Nicholas Cummins1 Author Orcid Image ;   Rebecca Bendayan1, 3 Author Orcid Image ;   Yatharth Ranjan1 Author Orcid Image ;   Zulqarnain Rashid1 Author Orcid Image ;   Pauline Conde1 Author Orcid Image ;   Callum Stewart1 Author Orcid Image ;   Petroula Laiou1 Author Orcid Image ;   Faith Matcham4 Author Orcid Image ;   Katie M White4 Author Orcid Image ;   Femke Lamers5 Author Orcid Image ;   Sara Siddi6, 7, 8 Author Orcid Image ;   Sara Simblett9 Author Orcid Image ;   Inez Myin-Germeys10 Author Orcid Image ;   Aki Rintala10, 11 Author Orcid Image ;   Til Wykes3, 9 Author Orcid Image ;   Josep Maria Haro6, 7, 8 Author Orcid Image ;   Brenda WJH Penninx5 Author Orcid Image ;   Vaibhav A Narayan12 Author Orcid Image ;   Matthew Hotopf3, 4 Author Orcid Image ;   Richard JB Dobson1, 2, 3 Author Orcid Image ;   RADAR-CNS Consortium13
Article Authors Cited by (30) Tweetations (46) Metrics

Journals

  1. Zhang Y, Folarin A, Sun S, Cummins N, Ranjan Y, Rashid Z, Conde P, Stewart C, Laiou P, Matcham F, Oetzmann C, Lamers F, Siddi S, Simblett S, Rintala A, Mohr D, Myin-Germeys I, Wykes T, Haro J, Penninx B, Narayan V, Annas P, Hotopf M, Dobson R. Predicting Depressive Symptom Severity Through Individuals’ Nearby Bluetooth Device Count Data Collected by Mobile Phones: Preliminary Longitudinal Study. JMIR mHealth and uHealth 2021;9(7):e29840 View
  2. 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
  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. White K, Williamson C, Bergou N, Oetzmann C, de Angel V, Matcham F, Henderson C, Hotopf M. A systematic review of engagement reporting in remote measurement studies for health symptom tracking. npj Digital Medicine 2022;5(1) View
  5. White K, Dawe-Lane E, Siddi S, Lamers F, Simblett S, Riquelme Alacid G, Ivan A, Myin-Germeys I, Haro J, Oetzmann C, Popat P, Rintala A, Rubio-Abadal E, Wykes T, Henderson C, Hotopf M, Matcham F. Understanding the Subjective Experience of Long-term Remote Measurement Technology Use for Symptom Tracking in People With Depression: Multisite Longitudinal Qualitative Analysis. JMIR Human Factors 2023;10:e39479 View
  6. Anmella G, Corponi F, Li B, Mas A, Sanabra M, Pacchiarotti I, Valentí M, Grande I, Benabarre A, Giménez-Palomo A, Garriga M, Agasi I, Bastidas A, Cavero M, Fernández-Plaza T, Arbelo N, Bioque M, García-Rizo C, Verdolini N, Madero S, Murru A, Amoretti S, Martínez-Aran A, Ruiz V, Fico G, De Prisco M, Oliva V, Solanes A, Radua J, Samalin L, Young A, Vieta E, Vergari A, Hidalgo-Mazzei D. Exploring Digital Biomarkers of Illness Activity in Mood Episodes: Hypotheses Generating and Model Development Study. JMIR mHealth and uHealth 2023;11:e45405 View
  7. Sun S, Folarin A, Zhang Y, Cummins N, Liu S, Stewart C, Ranjan Y, Rashid Z, Conde P, Laiou P, Sankesara H, Dalla Costa G, Leocani L, Sørensen P, Magyari M, Guerrero A, Zabalza A, Vairavan S, Bailon R, Simblett S, Myin-Germeys I, Rintala A, Wykes T, Narayan V, Hotopf M, Comi G, Dobson R. The utility of wearable devices in assessing ambulatory impairments of people with multiple sclerosis in free-living conditions. Computer Methods and Programs in Biomedicine 2022;227:107204 View
  8. Ahmed A, Aziz S, Alzubaidi M, Schneider J, Irshaidat S, Abu Serhan H, Abd-alrazaq A, Solaiman B, Househ M. Wearable devices for anxiety & depression: A scoping review. Computer Methods and Programs in Biomedicine Update 2023;3:100095 View
  9. Makhmutova M, Kainkaryam R, Ferreira M, Min J, Jaggi M, Clay I. Predicting Changes in Depression Severity Using the PSYCHE-D (Prediction of Severity Change-Depression) Model Involving Person-Generated Health Data: Longitudinal Case-Control Observational Study. JMIR mHealth and uHealth 2022;10(3):e34148 View
  10. de Angel V, Lewis S, Munir S, Matcham F, Dobson R, Hotopf M. Using digital health tools for the Remote Assessment of Treatment Prognosis in Depression (RAPID): a study protocol for a feasibility study. BMJ Open 2022;12(5):e059258 View
  11. Dlima S, Shevade S, Menezes S, Ganju A. Digital Phenotyping in Health Using Machine Learning Approaches: Scoping Review. JMIR Bioinformatics and Biotechnology 2022;3(1):e39618 View
  12. Dai R, Kannampallil T, Zhang J, Lv N, Ma J, Lu C. Multi-Task Learning for Randomized Controlled Trials. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2022;6(2):1 View
  13. Vairavan S, Rashidisabet H, Li Q, Ness S, Morrison R, Soares C, Uher R, Frey B, Lam R, Kennedy S, Trivedi M, Drevets W, Narayan V. Personalized relapse prediction in patients with major depressive disorder using digital biomarkers. Scientific Reports 2023;13(1) View
  14. Singh D, Nagaraj S, Daniel R, Flood C, Kulik D, Flook R, Goldenberg A, Brudno M, Stedman I. The promises and challenges of clinical AI in community paediatric medicine. Paediatrics & Child Health 2023;28(4):212 View
  15. Peerenboom N, Aryal S, Blankenship J, Swibas T, Zhai Y, Clay I, Lyden K. The Case for the Patient-Centric Development of Novel Digital Sleep Assessment Tools in Major Depressive Disorder. Digital Biomarkers 2023;7(1):124 View
  16. Clay I, De Luca V, Sano A. Editorial: Multimodal digital approaches to personalized medicine. Frontiers in Big Data 2023;6 View
  17. 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
  18. Pickles A, Edwards D, Horvath L, Emsley R. Research Reviews: Advances in methods for evaluating child and adolescent mental health interventions. Journal of Child Psychology and Psychiatry 2023;64(12):1765 View
  19. Sun S, Denyer H, Sankesara H, Deng Q, Ranjan Y, Conde P, Rashid Z, Bendayan R, Asherson P, Bilbow A, Groom M, Hollis C, Folarin A, Dobson R, Kuntsi J. Remote Administration of ADHD-Sensitive Cognitive Tasks: A Pilot Study. Journal of Attention Disorders 2023;27(9):1040 View
  20. Shende C, Sahoo S, Sam S, Patel P, Morillo R, Wang X, Ware S, Bi J, Kamath J, Russell A, Song D, Wang B. Predicting Symptom Improvement During Depression Treatment Using Sleep Sensory Data. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2023;7(3):1 View
  21. McDuff D, Barakat A, Winbush A, Jiang A, Cordeiro F, Crowley R, Kahn L, Hernandez J, Allen N. The Google Health Digital Well-Being Study: Protocol for a Digital Device Use and Well-Being Study. JMIR Research Protocols 2024;13:e49189 View
  22. 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
  23. Zhang Y, Folarin A, Sun S, Cummins N, Ranjan Y, Rashid Z, Stewart C, Conde P, Sankesara H, Laiou P, Matcham F, White K, Oetzmann C, Lamers F, Siddi S, Simblett S, Vairavan S, Myin-Germeys I, Mohr D, Wykes T, Haro J, Annas P, Penninx B, Narayan V, Hotopf M, Dobson R. Longitudinal Assessment of Seasonal Impacts and Depression Associations on Circadian Rhythm Using Multimodal Wearable Sensing: Retrospective Analysis. Journal of Medical Internet Research 2024;26:e55302 View
  24. Zhang Y, Folarin A, Dineley J, Conde P, de Angel V, Sun S, Ranjan Y, Rashid Z, Stewart C, Laiou P, Sankesara H, Qian L, Matcham F, White K, Oetzmann C, Lamers F, Siddi S, Simblett S, Schuller B, Vairavan S, Wykes T, Haro J, Penninx B, Narayan V, Hotopf M, Dobson R, Cummins N. Identifying depression-related topics in smartphone-collected free-response speech recordings using an automatic speech recognition system and a deep learning topic model. Journal of Affective Disorders 2024;355:40 View
  25. Song Y, Jeong J, de los Reyes A, Lim D, Cho C, Yeom J, Lee T, Lee J, Lee H, Kim J. Causal dynamics of sleep, circadian rhythm, and mood symptoms in patients with major depression and bipolar disorder: insights from longitudinal wearable device data. eBioMedicine 2024;103:105094 View
  26. Qiao M, Yu H, Li T. Non-invasive neurostimulation to improve sleep quality and depressive symptoms in patients with major depressive disorder: A meta-analysis of randomized controlled trials. Journal of Psychiatric Research 2024;176:282 View
  27. Janssen Daalen J, van den Bergh R, Prins E, Moghadam M, van den Heuvel R, Veen J, Mathur S, Meijerink H, Mirelman A, Darweesh S, Evers L, Bloem B. Digital biomarkers for non-motor symptoms in Parkinson’s disease: the state of the art. npj Digital Medicine 2024;7(1) View
  28. Matcham F, Carr E, Meyer N, White K, Oetzmann C, Leightley D, Lamers F, Siddi S, Cummins N, Annas P, de Girolamo G, Haro J, Lavelle G, Li Q, Lombardini F, Mohr D, Narayan V, Penninx B, Coromina M, Riquelme Alacid G, Simblett S, Nica R, Wykes T, Brasen J, Myin-Germeys I, Dobson R, Folarin A, Ranjan Y, Rashid Z, Dineley J, Vairavan S, Hotopf M. The relationship between wearable-derived sleep features and relapse in Major Depressive Disorder. Journal of Affective Disorders 2024;363:90 View

Books/Policy Documents

  1. Poli A, Cosoli G, Verdenelli L, Scardulla F, D’Acquisto L, Spinsante S, Scalise L. IoT Technologies for Health Care. View