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
.
Journals
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- 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
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- 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
- 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
- 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
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- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- Zhang Y, Zhao C. The role of sustainable urban employee basic medical insurance in health risk appraisal of urban residents. Work 2021:1 View
- 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
- 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
- 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
- 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
- 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
- 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
- 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 2024;63(1):49 View
- 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
- 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
- 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
- Calvignac C. Des médecins du sommeil aux prises avec les technologies d’automesure. Médecine du Sommeil 2023;20(4):213 View
- 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 2023;25(9):2300 View
- 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
- 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 View
- 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;9(17):15 View
- Körner R, Schütz A. Examining the links between self-tracking and perfectionism dimensions. Current Issues in Personality Psychology 2023 View
- Lu J, Sijm M, Janssens G, Goh J, Maier A. Remote monitoring technologies for measuring cardiovascular functions in community-dwelling adults: a systematic review. GeroScience 2023;45(5):2939 View
- Gauthier-Beaupré A, Grosjean S. Understanding acceptability of digital health technologies among francophone-speaking communities across the world: a meta-ethnographic study. Frontiers in Communication 2023;8 View
- Henson C, Rambaldini B, Freedman B, Carlson B, Parter C, Christie V, Skinner J, Meharg D, Kirwan M, Ward K, Speier S, Gwynne K. Wearables for early detection of atrial fibrillation and timely referral for Indigenous people ≥55 years: mixed-methods protocol. BMJ Open 2024;14(1):e077820 View
- Karsan S, Kuhn T, Ogrodnik M, Middleton L, Heisz J. Exploring the interactive effect of dysfunctional sleep beliefs and mental health on sleep in university students. Frontiers in Sleep 2024;3 View
- Karim J, Wan R, Tabet R, Chiu D, Talhouk A. Person-Generated Health Data in Women’s Health: Scoping Review. Journal of Medical Internet Research 2024;26:e53327 View
- Gagnon M, Brilz A, Alberts N, Gordon J, Risling T, Stinson J. Understanding Adolescents’ Experiences With Menstrual Pain to Inform the User-Centered Design of a Mindfulness-Based App: Mixed Methods Investigation Study. JMIR Pediatrics and Parenting 2024;7:e54658 View
- Tóth K, Takács P, Balatoni I. Users’ Expectations of Smart Devices during Physical Activity—A Literature Review. Applied Sciences 2024;14(8):3518 View
- Goodings A, Fadahunsi K, Tarn D, Henn P, Shiely F, O'Donoghue J. Factors influencing smartwatch use and comfort with health data sharing: a sequential mixed-method study protocol. BMJ Open 2024;14(5):e081228 View
- Min H, Li J, Di M, Huang S, Sun X, Li T, Wu Y. Factors influencing the continuance intention of the women’s health WeChat public account: an integrated model of UTAUT2 and HBM. Frontiers in Public Health 2024;12 View
- Song L, Li B, Wu H, Wu C, Zhang X, Yu Z. Understanding the factors of wearable devices among the patients with thyroid cancer: A modified UTAUT2 model. PLOS ONE 2024;19(7):e0305944 View
- Wong A, Bayuo J, Su J, Chow K, Wong S, Wong B, Lee A, Wong F. Exploring the Experiences of Community-Dwelling Older Adults on Using Wearable Monitoring Devices With Regular Support From Community Health Workers, Nurses, and Social Workers: Qualitative Descriptive Study. Journal of Medical Internet Research 2024;26:e49403 View
- Henson C, Freedman B, Rambaldini B, Carlson B, Parter C, Nalliah C, Chapman F, Shepherd G, Orchard J, Skinner J, Gwynn J, Macniven R, Ramsden R, Speier S, Nahdi S, Christie V, Huang Y, Ward K, Gwynne K. Wearables are a viable digital health tool for older Indigenous adults living remotely in Australia (research). DIGITAL HEALTH 2024;10 View
- Wang B, Zhang L, Asan O. The Impact of Wearable Devices on Health Management: Insights from Consumers Data. Proceedings of the International Symposium on Human Factors and Ergonomics in Health Care 2024;13(1):175 View
- Orsso C, Gormaz T, Valentine S, Trottier C, Matias de Sousa I, Ferguson-Pell M, Johnson S, Kirkham A, Klein D, Maeda N, Mota J, Neil-Sztramko S, Quintanilha M, Salami B, Prado C. Digital Intervention for behaviouR changE and Chronic disease prevenTION (DIRECTION): Study protocol for a randomized controlled trial of a web-based platform integrating nutrition, physical activity, and mindfulness for individuals with obesity. Methods 2024;231:45 View
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- Ozaki I, Nishijima M, Shibata E, Zako Y, Chiang C. Factors Related to mHealth App Use Among Japanese Workers: Cross-Sectional Survey. JMIR Human Factors 2024;11:e54673 View
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Books/Policy Documents
- Pomey M. Patient Engagement. View
- Vaid S, Harari G. Digital Phenotyping and Mobile Sensing. View
- Maloney S, Hagens S. Introduction to Nursing Informatics. View
- Ologeanu-Taddei R. Crises de confiance ?. View
- Vaid S, Harari G. Digital Phenotyping and Mobile Sensing. View
- Kadena K, Lazarou E. Handbook of Computational Neurodegeneration. View
- Kadena K, Lazarou E. Handbook of Computational Neurodegeneration. View