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

Focus Groups and Qualitative Research for Human Factors Research (1088) Usability of Apps and User Perceptions of mHealth (1104) Telehealth and Telemonitoring (1926) Digital Mental Health Interventions, e-Mental Health and Cyberpsychology (1880) mHealth for Telemedicine and Homecare (493)

Published on in Vol 10 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/39479, first published .
Understanding the Subjective Experience of Long-term Remote Measurement Technology Use for Symptom Tracking in People With Depression: Multisite Longitudinal Qualitative Analysis

Understanding the Subjective Experience of Long-term Remote Measurement Technology Use for Symptom Tracking in People With Depression: Multisite Longitudinal Qualitative Analysis

Understanding the Subjective Experience of Long-term Remote Measurement Technology Use for Symptom Tracking in People With Depression: Multisite Longitudinal Qualitative Analysis

Authors of this article:

Katie M White1 Author Orcid Image ;   Erin Dawe-Lane2 Author Orcid Image ;   Sara Siddi3 Author Orcid Image ;   Femke Lamers4 Author Orcid Image ;   Sara Simblett2 Author Orcid Image ;   Gemma Riquelme Alacid3 Author Orcid Image ;   Alina Ivan1 Author Orcid Image ;   Inez Myin-Germeys5 Author Orcid Image ;   Josep Maria Haro3 Author Orcid Image ;   Carolin Oetzmann1 Author Orcid Image ;   Priya Popat1 Author Orcid Image ;   Aki Rintala5 Author Orcid Image ;   Elena Rubio-Abadal3 Author Orcid Image ;   Til Wykes2 Author Orcid Image ;   Claire Henderson6 Author Orcid Image ;   Matthew Hotopf1 Author Orcid Image ;   Faith Matcham1, 7 Author Orcid Image
Article Authors Cited by (7) Tweetations (6) Metrics

Journals

  1. Denyer H, Deng Q, Adanijo A, Asherson P, Bilbow A, Folarin A, Groom M, Hollis C, Wykes T, Dobson R, Kuntsi J, Simblett S. Barriers to and Facilitators of Using Remote Measurement Technology in the Long-Term Monitoring of Individuals With ADHD: Interview Study. JMIR Formative Research 2023;7:e44126 View
  2. White K, Carr E, Leightley D, Matcham F, Conde P, Ranjan Y, Simblett S, Dawe-Lane E, Williams L, Henderson C, Hotopf M. Engagement With a Remote Symptom-Tracking Platform Among Participants With Major Depressive Disorder: Randomized Controlled Trial. JMIR mHealth and uHealth 2024;12:e44214 View
  3. Bye A, Wilson-Lemoine E, Trevillion K, Carter B, Dutta R. Factors that affect clinical youth engagement in digital mental health research: a qualitative sub-study nested within a prospective cohort study. BMC Medical Research Methodology 2025;25(1) View
  4. Lo B, Durocher K, Charow R, Kimball S, Pham Q, Sockalingam S, Wiljer D, Strudwick G. Application of a Sociotechnical Framework to Uncover Factors That Influence Effective User Engagement With Digital Mental Health Tools in Clinical Care Contexts: Scoping Review. Journal of Medical Internet Research 2025;27:e67820 View
  5. Reich H, Schreynemackers S, Amin R, Ludwig S, Zippelius J, Leimhofer J, Dunker T, Schriewer E, Carell A, Weber Y, Hegerl U. Links between self-monitoring data collected through smartphones and smartwatches and the individual disease trajectories of adult patients with depressive disorders: Study protocol of a one-year observational trial. Contemporary Clinical Trials Communications 2025;45:101492 View
  6. Manrai R, Swiffen D, Wyse C, Gray D, Ferguson A, M. Lopez L, Campbell I, Murray A, Caddick L, Gale E, Scorza L, Marwick K, Tsanas A, Coogan A, Spitschan M, Millar A, Riha R, Grigorjeva M, Thedie D, Gardani M, Zienliński T, Whalley H, Smith D. Ambient and passive collection of sleep and circadian data in bipolar disorder to understand symptom trajectories and clinical outcomes (AMBIENT-BD): Study protocol. Wellcome Open Research 2025;10:254 View
  7. Haley F, Andrews J, Moghaddam N. Acceptability of Remote Monitoring Technologies for Early Warning of Major Depression. Journal of Technology in Behavioral Science 2025 View