Published on in Vol 20 , No 5 (2018) :May

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/9388, first published .
Diffusion of the Digital Health Self-Tracking Movement in Canada: Results of a National Survey

Diffusion of the Digital Health Self-Tracking Movement in Canada: Results of a National Survey

Diffusion of the Digital Health Self-Tracking Movement in Canada: Results of a National Survey

Authors of this article:

Guy Paré 1 Author Orcid Image ;   Chad Leaver 2 Author Orcid Image ;   Claire Bourget 3 Author Orcid Image

Journals

  1. Ake A, Arcand M. The impact of mobile health monitoring on the evolution of patient-pharmacist relationships. International Journal of Pharmaceutical and Healthcare Marketing 2020;14(1):1 View
  2. Brietzke E, Vazquez G, Kang M, Soares C. Pharmacological treatment for insomnia in patients with major depressive disorder. Expert Opinion on Pharmacotherapy 2019;20(11):1341 View
  3. Strain T, Wijndaele K, Brage S. Physical Activity Surveillance Through Smartphone Apps and Wearable Trackers: Examining the UK Potential for Nationally Representative Sampling. JMIR mHealth and uHealth 2019;7(1):e11898 View
  4. Huh U, Tak Y, Song S, Chung S, Sung S, Lee C, Bae M, Ahn H. Feedback on Physical Activity Through a Wearable Device Connected to a Mobile Phone App in Patients With Metabolic Syndrome: Pilot Study. JMIR mHealth and uHealth 2019;7(6):e13381 View
  5. Dolezel M. Prevention-oriented ECG Teleconsulting That Involves Consumer Wearables: Exploration of Service Adoption Patterns and Institutional Impact. Procedia Computer Science 2019;160:417 View
  6. Mayer G, Alvarez S, Gronewold N, Schultz J. Expressions of Individualization on the Internet and Social Media: Multigenerational Focus Group Study. Journal of Medical Internet Research 2020;22(11):e20528 View
  7. Bove L. Increasing Patient Engagement Through the Use of Wearable Technology. The Journal for Nurse Practitioners 2019;15(8):535 View
  8. Siaw A, Jiang Y, Twumasi M, Agbenyo W. The Impact of Internet Use on Income: The Case of Rural Ghana. Sustainability 2020;12(8):3255 View
  9. Appireddy R, Khan S, Leaver C, Martin C, Jin A, Durafourt B, Archer S. Home Virtual Visits for Outpatient Follow-Up Stroke Care: Cross-Sectional Study. Journal of Medical Internet Research 2019;21(10):e13734 View
  10. Rising C, Jensen R, Moser R, Oh A. Characterizing the US Population by Patterns of Mobile Health Use for Health and Behavioral Tracking: Analysis of the National Cancer Institute's Health Information National Trends Survey Data. Journal of Medical Internet Research 2020;22(5):e16299 View
  11. Holtz B, Vasold K, Cotten S, Mackert M, Zhang M. Health Care Provider Perceptions of Consumer-Grade Devices and Apps for Tracking Health: A Pilot Study. JMIR mHealth and uHealth 2019;7(1):e9929 View
  12. McKinney P, Cox A, Sbaffi L. Information Literacy in Food and Activity Tracking Among Parkrunners, People With Type 2 Diabetes, and People With Irritable Bowel Syndrome: Exploratory Study. Journal of Medical Internet Research 2019;21(8):e13652 View
  13. Heidel A, Hagist C. Potential Benefits and Risks Resulting From the Introduction of Health Apps and Wearables Into the German Statutory Health Care System: Scoping Review. JMIR mHealth and uHealth 2020;8(9):e16444 View
  14. Ringeval M, Wagner G, Denford J, Paré G, Kitsiou S. Fitbit-Based Interventions for Healthy Lifestyle Outcomes: Systematic Review and Meta-Analysis. Journal of Medical Internet Research 2020;22(10):e23954 View
  15. Lin A, Baik S, Aaby D, Tello L, Linville T, Alshurafa N, Spring B. eHealth Practices in Cancer Survivors With BMI in Overweight or Obese Categories: Latent Class Analysis Study. JMIR Cancer 2020;6(2):e24137 View
  16. Wong A, Bhyat R, Srivastava S, Boissé Lomax L, Appireddy R. Patient Care During the COVID-19 Pandemic: Use of Virtual Care. Journal of Medical Internet Research 2021;23(1):e20621 View
  17. Jaana M, Paré G. Comparison of Mobile Health Technology Use for Self-Tracking Between Older Adults and the General Adult Population in Canada: Cross-Sectional Survey. JMIR mHealth and uHealth 2020;8(11):e24718 View
  18. Grenier Ouimet A, Wagner G, Raymond L, Pare G. Investigating Patients’ Intention to Continue Using Teleconsultation to Anticipate Postcrisis Momentum: Survey Study. Journal of Medical Internet Research 2020;22(11):e22081 View
  19. Lokker C, Jezrawi R, Gabizon I, Varughese J, Brown M, Trottier D, Alvarez E, Schwalm J, McGillion M, Ma J, Bhagirath V. Feasibility of a Web-Based Platform (Trial My App) to Efficiently Conduct Randomized Controlled Trials of mHealth Apps For Patients With Cardiovascular Risk Factors: Protocol For Evaluating an mHealth App for Hypertension. JMIR Research Protocols 2021;10(2):e26155 View
  20. Kitsiou S, Gerber B, Kansal M, Buchholz S, Chen J, Ruppar T, Arrington J, Owoyemi A, Leigh J, Pressler S. Patient-centered mobile health technology intervention to improve self-care in patients with chronic heart failure: Protocol for a feasibility randomized controlled trial. Contemporary Clinical Trials 2021;106:106433 View
  21. Palos-Sanchez P, Saura J, Rios Martin M, Aguayo-Camacho M. Toward a Better Understanding of the Intention to Use mHealth Apps: Exploratory Study. JMIR mHealth and uHealth 2021;9(9):e27021 View
  22. Dolezel M, Smutny Z. Usage of eHealth/mHealth Services among Young Czech Adults and the Impact of COVID-19: An Explorative Survey. International Journal of Environmental Research and Public Health 2021;18(13):7147 View
  23. Feng S, Mäntymäki M, Dhir A, Salmela H. How Self-tracking and the Quantified Self Promote Health and Well-being: A Systematic Literature Review (Preprint). Journal of Medical Internet Research 2020 View
  24. Zhang Y, Zhao C. The role of sustainable urban employee basic medical insurance in health risk appraisal of urban residents. Work 2021:1 View
  25. Kingsnorth A, Patience M, Moltchanova E, Esliger D, Paine N, Hobbs M. Changes in Device-Measured Physical Activity Patterns in U.K. Adults Related to the First COVID-19 Lockdown. Journal for the Measurement of Physical Behaviour 2021;4(3):247 View
  26. Buss V, Varnfield M, Harris M, Barr M. Mobile Health Use by Older Individuals at Risk of Cardiovascular Disease and Type 2 Diabetes Mellitus in an Australian Cohort: Cross-sectional Survey Study. JMIR mHealth and uHealth 2022;10(9):e37343 View
  27. Wang T, Wang W, Liang J, Nuo M, Wen Q, Wei W, Han H, Lei J. Identifying major impact factors affecting the continuance intention of mHealth: a systematic review and multi-subgroup meta-analysis. npj Digital Medicine 2022;5(1) View
  28. Kim B, Ghasemi P, Stolee P, Lee J. Clinicians and Older Adults’ Perceptions of the Utility of Patient-Generated Health Data in Caring for Older Adults: Exploratory Mixed Methods Study. JMIR Aging 2021;4(4):e29788 View
  29. Buss V, Varnfield M, Harris M, Barr M. Remotely Conducted App-Based Intervention for Cardiovascular Disease and Diabetes Risk Awareness and Prevention: Single-Group Feasibility Trial. JMIR Human Factors 2022;9(3):e38469 View
  30. Walle A, Jemere A, Tilahun B, Endehabtu B, Wubante S, Melaku M, Tegegne M, Gashu K. Intention to use wearable health devices and its predictors among diabetes mellitus patients in Amhara region referral hospitals, Ethiopia: Using modified UTAUT-2 model. Informatics in Medicine Unlocked 2023;36:101157 View
  31. Van Wier M, Urry E, Lissenberg-Witte B, Kramer S. User characteristics associated with use of wrist-worn wearables and physical activity apps by adults with and without impaired speech-in-noise recognition: a cross-sectional analysis. International Journal of Audiology 2022:1 View
  32. Lau E, Mitchell M, Faulkner G. Long-term usage of a commercial mHealth app: A “multiple-lives” perspective. Frontiers in Public Health 2022;10 View
  33. Peng C, Zhao H, Zhang S. Determinants and Cross-National Moderators of Wearable Health Tracker Adoption: A Meta-Analysis. Sustainability 2021;13(23):13328 View
  34. Henson C, Chapman F, Shepherd G, Carlson B, Chau J, Gwynn J, McCowen D, Rambaldini B, Ward K, Gwynne K. Mature aged Aboriginal and Torres Strait Islander adults are using digital health technologies (original research). DIGITAL HEALTH 2022;8:205520762211458 View
  35. Calvignac C. Des médecins du sommeil aux prises avec les technologies d’automesure. Médecine du Sommeil 2023 View
  36. Findeis C, Salfeld B, Voigt S, Gerisch B, King V, Ostern A, Rosa H. Quantifying self-quantification: A statistical study on individual characteristics and motivations for digital self-tracking in young- and middle-aged adults in Germany. New Media & Society 2021:146144482110390 View
  37. Pilgrim K, Bohnet-Joschko S. Donating Health Data to Research: Influential Characteristics of Individuals Engaging in Self-Tracking. International Journal of Environmental Research and Public Health 2022;19(15):9454 View
  38. Baumann M, Weinberger N, Maia M, Schmid K. User types, psycho-social effects and societal trends related to the use of consumer health technologies. DIGITAL HEALTH 2023;9:205520762311639 View
  39. SEKERCİOGLU F, HAMİD S. Ontario's Digital Health Vision in the post-COVID-19 Pandemic Era: A Canadian Perspective. Journal of International Health Sciences and Management 2023 View
  40. Körner R, Schütz A. Examining the links between self-tracking and perfectionism dimensions. Current Issues in Personality Psychology 2023 View

Books/Policy Documents

  1. Pomey M. Patient Engagement. View
  2. Vaid S, Harari G. Digital Phenotyping and Mobile Sensing. View
  3. Maloney S, Hagens S. Introduction to Nursing Informatics. View
  4. Ologeanu-Taddei R. Crises de confiance ?. View
  5. Vaid S, Harari G. Digital Phenotyping and Mobile Sensing. View
  6. Kadena K, Lazarou E. Handbook of Computational Neurodegeneration. View