Published on in Vol 9, No 7 (2021): July

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/29840, first published .
Predicting Depressive Symptom Severity Through Individuals’ Nearby Bluetooth Device Count Data Collected by Mobile Phones: Preliminary Longitudinal Study

Predicting Depressive Symptom Severity Through Individuals’ Nearby Bluetooth Device Count Data Collected by Mobile Phones: Preliminary Longitudinal Study

Predicting Depressive Symptom Severity Through Individuals’ Nearby Bluetooth Device Count Data Collected by Mobile Phones: Preliminary Longitudinal Study

Journals

  1. Sato S, Bunney B, Mendoza-Viveros L, Bunney W, Borrelli E, Sassone-Corsi P, Orozco-Solis R. Rapid-acting antidepressants and the circadian clock. Neuropsychopharmacology 2022;47(4):805 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. White K, Matcham F, Leightley D, Carr E, Conde P, Dawe-Lane E, Ranjan Y, Simblett S, Henderson C, Hotopf M. Exploring the Effects of In-App Components on Engagement With a Symptom-Tracking Platform Among Participants With Major Depressive Disorder (RADAR-Engage): Protocol for a 2-Armed Randomized Controlled Trial. JMIR Research Protocols 2021;10(12):e32653 View
  4. Polignano M, Lops P, de Gemmis M, Semeraro G. HELENA: An intelligent digital assistant based on a Lifelong Health User Model. Information Processing & Management 2023;60(1):103124 View
  5. 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
  6. Zhang Y, Folarin A, Sun S, Cummins N, Vairavan S, Qian L, Ranjan Y, Rashid Z, Conde P, Stewart C, Laiou P, Sankesara H, Matcham F, White K, Oetzmann C, Ivan A, 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. Associations Between Depression Symptom Severity and Daily-Life Gait Characteristics Derived From Long-Term Acceleration Signals in Real-World Settings: Retrospective Analysis. JMIR mHealth and uHealth 2022;10(10):e40667 View
  7. Maatoug R, Oudin A, Adrien V, Saudreau B, Bonnot O, Millet B, Ferreri F, Mouchabac S, Bourla A. Digital phenotype of mood disorders: A conceptual and critical review. Frontiers in Psychiatry 2022;13 View
  8. Guo Y, Liu X, Wang X, Zhu T, Zhan W. Automatic Decision-Making Style Recognition Method Using Kinect Technology. Frontiers in Psychology 2022;13 View
  9. 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
  10. Adler D, Wang F, Mohr D, Choudhury T, Chen C. Machine learning for passive mental health symptom prediction: Generalization across different longitudinal mobile sensing studies. PLOS ONE 2022;17(4):e0266516 View
  11. 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
  12. Andrews J, Craven M, Guo B, Weyer J, Lees S, Zormpas S, Thorpe S, Devonshire J, San Antonio-Arce V, Whitehouse W, Julie J, Malins S, Hammers A, Reif A, Ruhe H, Durbano F, Barlati S, Sen A, Frederiksen J, Martinelli A, Callen A, Torras-Borrell J, Berrocal-Izquierdo N, Zabalza A, Morriss R, Hollis C. Clinical Perspectives on Using Remote Measurement Technology in Assessing Epilepsy, Multiple Sclerosis, and Depression: Delphi Study. JMIR Neurotechnology 2023;2:e41439 View
  13. 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
  14. 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
  15. Vignapiano A, Monaco F, Pagano C, Piacente M, Farina F, Petrillo G, Sica R, Marenna A, Shin J, Solmi M, Corrivetti G. A narrative review of digital biomarkers in the management of major depressive disorder and treatment-resistant forms. Frontiers in Psychiatry 2023;14 View
  16. 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
  17. Rykov Y, Patterson M, Gangwar B, Jabar S, Leonardo J, Ng K, Kandiah N. Predicting cognitive scores from wearable-based digital physiological features using machine learning: data from a clinical trial in mild cognitive impairment. BMC Medicine 2024;22(1) View
  18. 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
  19. 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
  20. Yılmaz Bingöl T, Özmaya E, Uzun S, Gürhan N, Geniş B, Altun E, Karakaş İnce D, Coşar B. Bipolar Affektif Bozukluk Tanılı Bireylerin B12 Düzeyi Yönünden Değerlendirilmesi: 10 Yıllık Retrospektif Çalışma. Adnan Menderes Üniversitesi Sağlık Bilimleri Fakültesi Dergisi 2024;8(2):133 View
  21. Park Y, Park S, Lee M. Effectiveness of artificial intelligence in detecting and managing depressive disorders: Systematic review. Journal of Affective Disorders 2024;361:445 View
  22. dos Santos M, Heckler W, Bavaresco R, Barbosa J. Machine learning applied to digital phenotyping: A systematic literature review and taxonomy. Computers in Human Behavior 2024;161:108422 View
  23. 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
  24. 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
  25. 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
  26. Bosma C, Wojcik C, Haigh E. Evaluating Individual Differences in Emotion Regulation in Response to Sadness Using Digital Phenotyping. Journal of Technology in Behavioral Science 2024 View
  27. Adler D, Yang Y, Viranda T, Xu X, Mohr D, Van Meter A, Tartaglia J, Jacobson N, Wang F, Estrin D, Choudhury T. Beyond Detection: Towards Actionable Sensing Research in Clinical Mental Healthcare. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2024;8(4):1 View