Published on in Vol 5, No 7 (2017): July

Patterns of User Engagement With the Mobile App, Manage My Pain: Results of a Data Mining Investigation

Patterns of User Engagement With the Mobile App, Manage My Pain: Results of a Data Mining Investigation

Patterns of User Engagement With the Mobile App, Manage My Pain: Results of a Data Mining Investigation

Journals

  1. Seng E, Prieto P, Boucher G, Vives-Mestres M. Anxiety, Incentives, and Adherence to Self-Monitoring on a Mobile Health Platform: A Naturalistic Longitudinal Cohort Study in People With Headache. Headache: The Journal of Head and Face Pain 2018;58(10):1541 View
  2. Bidargaddi N, Pituch T, Maaieh H, Short C, Strecher V. Predicting which type of push notification content motivates users to engage in a self-monitoring app. Preventive Medicine Reports 2018;11:267 View
  3. Black N, Loomes M, Juraskova I, Johnston I. Engagement in a Novel Internet Intervention for Alcohol Reduction: A Qualitative Study of User Motivations and Experiences. Cyberpsychology, Behavior, and Social Networking 2020;23(4):225 View
  4. Schobel J, Probst T, Reichert M, Schlee W, Schickler M, Kestler H, Pryss R. Measuring Mental Effort for Creating Mobile Data Collection Applications. International Journal of Environmental Research and Public Health 2020;17(5):1649 View
  5. Clarke H, Azargive S, Montbriand J, Nicholls J, Sutherland A, Valeeva L, Boulis S, McMillan K, Ladak S, Ladha K, Katznelson R, McRae K, Tamir D, Lyn S, Huang A, Weinrib A, Katz J. Opioid weaning and pain management in postsurgical patients at the Toronto General Hospital Transitional Pain Service. Canadian Journal of Pain 2018;2(1):236 View
  6. Böhm A, Jensen M, Sørensen M, Stargardt T. Real-World Evidence of User Engagement With Mobile Health for Diabetes Management: Longitudinal Observational Study. JMIR mHealth and uHealth 2020;8(11):e22212 View
  7. Mohan D, Bashingwa J, Dane P, Chamberlain S, Tiffin N, Lefevre A. Use of Big Data and Machine Learning Methods in the Monitoring and Evaluation of Digital Health Programs in India: An Exploratory Protocol. JMIR Research Protocols 2019;8(5):e11456 View
  8. Rahman Q, Janmohamed T, Clarke H, Ritvo P, Heffernan J, Katz J. Interpretability and Class Imbalance in Prediction Models for Pain Volatility in Manage My Pain App Users: Analysis Using Feature Selection and Majority Voting Methods. JMIR Medical Informatics 2019;7(4):e15601 View
  9. Alshurafa N, Jain J, Alharbi R, Iakovlev G, Spring B, Pfammatter A. Is More Always Better?. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2018;2(4):1 View
  10. Schobel J, Pryss R, Probst T, Schlee W, Schickler M, Reichert M. Learnability of a Configurator Empowering End Users to Create Mobile Data Collection Instruments: Usability Study. JMIR mHealth and uHealth 2018;6(6):e148 View
  11. Azam M, Latman V, Katz J. Effects of a 12-Minute Smartphone-Based Mindful Breathing Task on Heart Rate Variability for Students With Clinically Relevant Chronic Pain, Depression, and Anxiety: Protocol for a Randomized Controlled Trial. JMIR Research Protocols 2019;8(12):e14119 View
  12. Wildemeersch D, D'Hondt M, Bernaerts L, Mertens P, Saldien V, Hendriks J, Walcarius A, Sterkens L, Hans G. Implementation of an Enhanced Recovery Pathway for Minimally Invasive Pectus Surgery: A Population-Based Cohort Study Evaluating Short- and Long-Term Outcomes Using eHealth Technology. JMIR Perioperative Medicine 2018;1(2):e10996 View
  13. Bidargaddi N, Almirall D, Murphy S, Nahum-Shani I, Kovalcik M, Pituch T, Maaieh H, Strecher V. To Prompt or Not to Prompt? A Microrandomized Trial of Time-Varying Push Notifications to Increase Proximal Engagement With a Mobile Health App. JMIR mHealth and uHealth 2018;6(11):e10123 View
  14. Biviji R, Vest J, Dixon B, Cullen T, Harle C. Factors Related to User Ratings and User Downloads of Mobile Apps for Maternal and Infant Health: A Cross-Sectional Study. JMIR mHealth and uHealth 2020;8(1):e15663 View
  15. Chen A, Wu S, Tomasino K, Lattie E, Mohr D. A multi-faceted approach to characterizing user behavior and experience in a digital mental health intervention. Journal of Biomedical Informatics 2019;94:103187 View
  16. Hendrikoff L, Kambeitz-Ilankovic L, Pryss R, Senner F, Falkai P, Pogarell O, Hasan A, Peters H. Prospective acceptance of distinct mobile mental health features in psychiatric patients and mental health professionals. Journal of Psychiatric Research 2019;109:126 View
  17. Perrot S, Cittée J, Louis P, Quentin B, Robert C, Milon J, Bismut H, Baumelou A. Self‐medication in pain management: The state of the art of pharmacists’ role for optimal Over‐The‐Counter analgesic use. European Journal of Pain 2019;23(10):1747 View
  18. Rahman Q, Janmohamed T, Pirbaglou M, Clarke H, Ritvo P, Heffernan J, Katz J. Defining and Predicting Pain Volatility in Users of the Manage My Pain App: Analysis Using Data Mining and Machine Learning Methods. Journal of Medical Internet Research 2018;20(11):e12001 View
  19. Miller S, Ainsworth B, Yardley L, Milton A, Weal M, Smith P, Morrison L. A Framework for Analyzing and Measuring Usage and Engagement Data (AMUsED) in Digital Interventions: Viewpoint. Journal of Medical Internet Research 2019;21(2):e10966 View
  20. Holdener M, Gut A, Angerer A. Applicability of the User Engagement Scale to Mobile Health: A Survey-Based Quantitative Study. JMIR mHealth and uHealth 2020;8(1):e13244 View
  21. Slepian P, Peng M, Janmohamed T, Kotteeswaran Y, Manoo V, Blades A, Fiorellino J, Katznelson R, Tamir D, McRae K, Kahn M, Huang A, Kona S, Thaker S, Weinrib A, Katz J, Clarke H. Engagement with Manage My Pain mobile health application among patients at the Transitional Pain Service. DIGITAL HEALTH 2020;6:205520762096229 View
  22. Bhatia A, Kara J, Janmohamed T, Prabhu A, Lebovic G, Katz J, Clarke H. User Engagement and Clinical Impact of the Manage My Pain App in Patients With Chronic Pain: A Real-World, Multi-site Trial. JMIR mHealth and uHealth 2021;9(3):e26528 View