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

Wearable Devices and Sensors (703) Mobile Health (mhealth) (2234) Evaluation and Research Methodology for mHealth (168) mHealth for Symptom and Disease Monitoring, Chronic Disease Management (1121) mHealth for Data Collection and Research (745) Depression and Mood Disorders; Suicide Prevention (1138) Insomnia and Sleep Hygiene (122) Sleep Monitoring, Sleep Quality, Sleep Disorders (133)

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 Zhang 1 Author Orcid Image ;   Amos A Folarin 1, 2, 3 Author Orcid Image ;   Shaoxiong Sun 1 Author Orcid Image ;   Nicholas Cummins 1 Author Orcid Image ;   Rebecca Bendayan 1, 3 Author Orcid Image ;   Yatharth Ranjan 1 Author Orcid Image ;   Zulqarnain Rashid 1 Author Orcid Image ;   Pauline Conde 1 Author Orcid Image ;   Callum Stewart 1 Author Orcid Image ;   Petroula Laiou 1 Author Orcid Image ;   Faith Matcham 4 Author Orcid Image ;   Katie M White 4 Author Orcid Image ;   Femke Lamers 5 Author Orcid Image ;   Sara Siddi 6, 7, 8 Author Orcid Image ;   Sara Simblett 9 Author Orcid Image ;   Inez Myin-Germeys 10 Author Orcid Image ;   Aki Rintala 10, 11 Author Orcid Image ;   Til Wykes 3, 9 Author Orcid Image ;   Josep Maria Haro 6, 7, 8 Author Orcid Image ;   Brenda WJH Penninx 5 Author Orcid Image ;   Vaibhav A Narayan 12 Author Orcid Image ;   Matthew Hotopf 3, 4 Author Orcid Image ;   Richard JB Dobson 1, 2, 3 Author Orcid Image ;   RADAR-CNS Consortium 13
Article Authors Cited by (14) Tweetations (30) 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

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