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
.
Journals
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- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- Clay I, De Luca V, Sano A. Editorial: Multimodal digital approaches to personalized medicine. Frontiers in Big Data 2023;6 View
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- Rashid Z, Folarin A, Zhang Y, Ranjan Y, Conde P, Sankesara H, Sun S, Stewart C, Laiou P, Dobson R. Digital Phenotyping of Mental and Physical Conditions: Remote Monitoring of Patients Through RADAR-Base Platform. JMIR Mental Health 2024;11:e51259 View
- Pick S, Millman L, Davies J, Hodsoll J, Stanton B, David A, Edwards M, Goldstein L, Mehta M, Nicholson T, Reinders A, Winston J, Chalder T, Hotopf M. Real-time biopsychosocial antecedents and correlates of functional neurological symptoms in daily life: A pilot remote monitoring technology study. Psychiatry Research 2024;342:116247 View
- Sankesara H, Denyer H, Sun S, Deng Q, Ranjan Y, Conde P, Rashid Z, Asherson P, Bilbow A, Groom M, Hollis C, Dobson R, Folarin A, Kuntsi J. Identifying Digital Markers of ADHD in a Remote Monitoring Setting: Prospective Observational Study (Preprint). JMIR Formative Research 2023 View
Books/Policy Documents
- Poli A, Cosoli G, Verdenelli L, Scardulla F, D’Acquisto L, Spinsante S, Scalise L. IoT Technologies for Health Care. View