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

Posttraumatic Stress Disorder (PTSD) (116) Usability of Apps and User Perceptions of mHealth (974) Anxiety and Stress Disorders (1053) Fitness Trackers and Smart Pedometers/Accelerometers (561) Special Issue on Computing and Mental Health (2018) (33)

Published on in Vol 5, No 2 (2018): Apr-Jun

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/10415, first published .
Veterans’ Perspectives on Fitbit Use in Treatment for Post-Traumatic Stress Disorder: An Interview Study

Veterans’ Perspectives on Fitbit Use in Treatment for Post-Traumatic Stress Disorder: An Interview Study

Veterans’ Perspectives on Fitbit Use in Treatment for Post-Traumatic Stress Disorder: An Interview Study

Authors of this article:

Ada Ng1 Author Orcid Image ;   Madhu Reddy2 Author Orcid Image ;   Alyson K Zalta3 Author Orcid Image ;   Stephen M Schueller4 Author Orcid Image
Article Authors Cited by (24) Tweetations (33) Metrics

Journals

  1. Wu D, Xin C, Bindhu S, Xu C, Sachdeva J, Brown J, Jung H. Clinician Perspectives and Design Implications in Using Patient-Generated Health Data to Improve Mental Health Practices: Mixed Methods Study. JMIR Formative Research 2020;4(8):e18123 View
  2. Bruen A, Wall A, Haines-Delmont A, Perkins E. Exploring Suicidal Ideation Using an Innovative Mobile App-Strength Within Me: The Usability and Acceptability of Setting up a Trial Involving Mobile Technology and Mental Health Service Users. JMIR Mental Health 2020;7(9):e18407 View
  3. Nicholas J, Shilton K, Schueller S, Gray E, Kwasny M, Mohr D. The Role of Data Type and Recipient in Individuals’ Perspectives on Sharing Passively Collected Smartphone Data for Mental Health: Cross-Sectional Questionnaire Study. JMIR mHealth and uHealth 2019;7(4):e12578 View
  4. Ng A, Kornfield R, Schueller S, Zalta A, Brennan M, Reddy M. Provider Perspectives on Integrating Sensor-Captured Patient-Generated Data in Mental Health Care. Proceedings of the ACM on Human-Computer Interaction 2019;3(CSCW):1 View
  5. Saleem J, Moon B, Bross E, Anders S, Conway B, Wilck N, Frisbee K, Herout J. Understanding Veteran Attitudes, Interests, and Needs around Virtual Care Applications. Proceedings of the Human Factors and Ergonomics Society Annual Meeting 2020;64(1):731 View
  6. Borghouts J, Eikey E, Mark G, De Leon C, Schueller S, Schneider M, Stadnick N, Zheng K, Mukamel D, Sorkin D. Barriers to and Facilitators of User Engagement With Digital Mental Health Interventions: Systematic Review. Journal of Medical Internet Research 2021;23(3):e24387 View
  7. Zidaru T, Morrow E, Stockley R. Ensuring patient and public involvement in the transition to AI‐assisted mental health care: A systematic scoping review and agenda for design justice. Health Expectations 2021;24(4):1072 View
  8. 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
  9. Stawarz K, Katz D, Ayobi A, Marshall P, Yamagata T, Santos-Rodriguez R, Flach P, O’Kane A. Co-designing opportunities for Human-Centred Machine Learning in supporting Type 1 diabetes decision-making. International Journal of Human-Computer Studies 2023;173:103003 View
  10. Rantala E, Järvelä-Reijonen E, Pettersson K, Laine J, Vartiainen P, Närväinen J, Pihlajamäki J, Poutanen K, Absetz P, Karhunen L. Sensory Appeal and Routines Beat Health Messages and Visibility Enhancements: Mixed-Methods Analysis of a Choice-Architecture Intervention in a Workplace Cafeteria. Nutrients 2022;14(18):3731 View
  11. Bessenyei K, Suruliraj B, Bagnell A, McGrath P, Wozney L, Huguet A, Elger B, Meier S, Orji R. Comfortability with the passive collection of smartphone data for monitoring of mental health: An online survey. Computers in Human Behavior Reports 2021;4:100134 View
  12. Saleem J, Wilck N, Murphy J, Herout J. Veteran and Staff Experience from a Pilot Program of Health Care System–Distributed Wearable Devices and Data Sharing. Applied Clinical Informatics 2022;13(03):532 View
  13. Rantala E, Vanhatalo S, Tilles-Tirkkonen T, Kanerva M, Hansen P, Kolehmainen M, Männikkö R, Lindström J, Pihlajamäki J, Poutanen K, Karhunen L, Absetz P. Choice Architecture Cueing to Healthier Dietary Choices and Physical Activity at the Workplace: Implementation and Feasibility Evaluation. Nutrients 2021;13(10):3592 View
  14. Bhattacharjee A, Chen P, Mandal A, Hsu A, O'Leary K, Mariakakis A, Williams J. Exploring User Perspectives on Brief Reflective Questioning Activities for Stress Management: Mixed Methods Study. JMIR Formative Research 2024;8:e47360 View
  15. Rantala E, Vanhatalo S, Perez-Cueto F, Pihlajamäki J, Poutanen K, Karhunen L, Absetz P. Acceptability of workplace choice architecture modification for healthy behaviours. BMC Public Health 2023;23(1) View
  16. Evans H, Ryu M, Hsieh T, Zhou J, Xu K, Akers K, Sherrill A, Arriaga R. Using Sensor-Captured Patient-Generated Data to Support Clinical Decision-making in PTSD Therapy. Proceedings of the ACM on Human-Computer Interaction 2024;8(CSCW1):1 View
  17. Bovens D, van Baarle E, Ziesemer K, Molewijk B. The ethical dimension of personal health monitoring in the armed forces: a scoping review. BMC Medical Ethics 2024;25(1) View
  18. Hogan T, Etingen B, Zocchi M, Bixler F, McMahon N, Patrianakos J, Robinson S, Newton T, Shah N, Frisbee K, Shimada S, Lipschitz J, Smith B. Veteran Preferences and Willingness to Share Patient-Generated Health Data. Journal of General Internal Medicine 2024 View

Books/Policy Documents

  1. Bischoff R, Springer P, Taylor N. The Handbook of Systemic Family Therapy. View
  2. Bischoff R, Springer P, Taylor N. The Handbook of Systemic Family Therapy. View
  3. Gonzalez A, Bufe J, Tran H. Encyclopedia of Sleep and Circadian Rhythms. View
  4. Cipriano M, Costagliola G, De Rosa M, Fuccella V, Shevchenko S. Innovation in Medicine and Healthcare. View