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 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
  23. Perrot S, Louis P, Milon J, Bismut H. Automédication de la douleur : état des lieux, enjeux et rôle attendu du pharmacien dans le parcours de soins. Douleur et Analgésie 2021;34(2):104 View
  24. Li J, Yu K, Bao X, Liu X, Yao J. Patterns of eHealth Website User Engagement Based on Cross-site Clickstream Data: Correlational Study. Journal of Medical Internet Research 2021;23(8):e29299 View
  25. Xu T, Xia M, Jiang H. Advances in Medicine-Engineering Crossover in Automated Anesthesia. Journal of Shanghai Jiaotong University (Science) 2022;27(2):137 View
  26. Wu D, An J, Yu P, Lin H, Ma L, Duan H, Deng N. Patterns for Patient Engagement with the Hypertension Management and Effects of Electronic Health Care Provider Follow-up on These Patterns: Cluster Analysis. Journal of Medical Internet Research 2021;23(9):e25630 View
  27. Giordano F, Welzel G, Siefert V, Jahnke L, Ganslandt T, Wenz F, Grosu A, Heinemann F, Nicolay N. Digital Follow-Up and the Perspective of Patient-Centered Care in Oncology: What’s the PROblem?. Oncology 2020;98(6):379 View
  28. Van Schalkwyk A, Grobbelaar S, Vermeulen E, Herselman M. A Scoping Review of the Use of Log Data for Evaluating Mobile Apps: Exploring Implications for mHealth Apps. IEEE Access 2022;10:124805 View
  29. Bricker J, Mull K, Santiago-Torres M, Miao Z, Perski O, Di C. Smoking Cessation Smartphone App Use Over Time: Predicting 12-Month Cessation Outcomes in a 2-Arm Randomized Trial. Journal of Medical Internet Research 2022;24(8):e39208 View
  30. Baumel A. Therapeutic Activities as a Link between Program Usage and Clinical Outcomes in Digital Mental Health Interventions: a Proposed Research Framework. Journal of Technology in Behavioral Science 2022;7(2):234 View
  31. Wu D, Huyan X, She Y, Hu J, Duan H, Deng N. Exploring and Characterizing Patient Multibehavior Engagement Trails and Patient Behavior Preference Patterns in Pathway-Based mHealth Hypertension Self-Management: Analysis of Use Data. JMIR mHealth and uHealth 2022;10(2):e33189 View
  32. Ader L, Schick A, Löffler M, Löffler A, Beiner E, Eich W, Vock S, Sirazitdinov A, Malone C, Hesser J, Hopp M, Ruckes C, Flor H, Tesarz J, Reininghaus U. Refocusing of Attention on Positive Events Using Monitoring-Based Feedback and Microinterventions for Patients With Chronic Musculoskeletal Pain in the PerPAIN Randomized Controlled Trial: Protocol for a Microrandomized Trial. JMIR Research Protocols 2023;12:e43376 View
  33. Sheng Y, Bond R, Jaiswal R, Dinsmore J, Doyle J. Augmenting K-Means Clustering With Qualitative Data to Discover the Engagement Patterns of Older Adults With Multimorbidity When Using Digital Health Technologies: Proof-of-Concept Trial. Journal of Medical Internet Research 2024;26:e46287 View
  34. Xing Y, Yang K, Lu A, Mackie K, Guo F. Sensors and Devices Guided by Artificial Intelligence for Personalized Pain Medicine. Cyborg and Bionic Systems 2024;5 View
  35. Trò R, Orecchia A, Disma N, Uva P, Cavanna R, Zanardi N, Torre M, Fato M. Comparison of Analgesia Methods Through a Web Platform in Patients Undergoing Thoracic Surgery: Pilot Design, Implementation, and Validation Study. JMIR Formative Research 2024;8:e56674 View