Published on 24.03.16 in Vol 4, No 1 (2016): Jan-Mar
Works citing "Uptake of a Consumer-Focused mHealth Application for the Assessment and Prevention of Heart Disease: The <30 Days Study"
According to Crossref, the following articles are citing this article (DOI 10.2196/mhealth.4730):
(note that this is only a small subset of citations)
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Pham Q, Cafazzo JA, Feifer A. Adoption, Acceptability, and Effectiveness of a Mobile Health App for Personalized Prostate Cancer Survivorship Care: Protocol for a Realist Case Study of the Ned App. JMIR Research Protocols 2017;6(10):e197
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Matthews P, Topham P, Caleb-Solly P. Interaction and Engagement with an Anxiety Management App: Analysis Using Large-Scale Behavioral Data. JMIR Mental Health 2018;5(4):e58
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Reading MJ, Merrill JA. Converging and diverging needs between patients and providers who are collecting and using patient-generated health data: an integrative review. Journal of the American Medical Informatics Association 2018;25(6):759
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Pham Q, Graham G, Carrion C, Morita PP, Seto E, Stinson JN, Cafazzo JA. A Library of Analytic Indicators to Evaluate Effective Engagement with Consumer mHealth Apps for Chronic Conditions: Scoping Review. JMIR mHealth and uHealth 2019;7(1):e11941
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Mitchell M, White L, Oh P, Alter D, Leahey T, Kwan M, Faulkner G. Uptake of an Incentive-Based mHealth App: Process Evaluation of the Carrot Rewards App. JMIR mHealth and uHealth 2017;5(5):e70
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Pham Q, Wiljer D, Cafazzo JA. Beyond the Randomized Controlled Trial: A Review of Alternatives in mHealth Clinical Trial Methods. JMIR mHealth and uHealth 2016;4(3):e107
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Liao G, Chien Y, Chen Y, Hsiung H, Chen H, Hsieh M, Wu W. What to Build for Middle-Agers to Come? Attractive and Necessary Functions of Exercise-Promotion Mobile Phone Apps: A Cross-Sectional Study. JMIR mHealth and uHealth 2017;5(5):e65
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Mitchell M, White L, Lau E, Leahey T, Adams MA, Faulkner G. Evaluating the Carrot Rewards App, a Population-Level Incentive-Based Intervention Promoting Step Counts Across Two Canadian Provinces: Quasi-Experimental Study. JMIR mHealth and uHealth 2018;6(9):e178
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Morita PP, Yeung MS, Ferrone M, Taite AK, Madeley C, Stevens Lavigne A, To T, Lougheed MD, Gupta S, Day AG, Cafazzo JA, Licskai C. A Patient-Centered Mobile Health System That Supports Asthma Self-Management (breathe): Design, Development, and Utilization. JMIR mHealth and uHealth 2019;7(1):e10956
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Reiners F, Sturm J, Bouw LJ, Wouters EJ. Sociodemographic Factors Influencing the Use of eHealth in People with Chronic Diseases. International Journal of Environmental Research and Public Health 2019;16(4):645
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Brower J, LaBarge MC, White L, Mitchell MS. Examining Responsiveness to an Incentive-Based Mobile Health App: Longitudinal Observational Study. Journal of Medical Internet Research 2020;22(8):e16797
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Shah LM, Yang WE, Demo RC, Lee MA, Weng D, Shan R, Wongvibulsin S, Spaulding EM, Marvel FA, Martin SS. Technical Guidance for Clinicians Interested in Partnering With Engineers in Mobile Health Development and Evaluation. JMIR mHealth and uHealth 2019;7(5):e14124
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Kabeza CB, Harst L, Schwarz PE, Timpel P. A qualitative study of users’ experiences after 3 months: the first Rwandan diabetes self-management Smartphone application “Kir’App”. Therapeutic Advances in Endocrinology and Metabolism 2020;11:204201882091451
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Chin WSY, Kurowski A, Gore R, Chen G, Punnett L. Use of a Mobile App for the Process Evaluation of an Intervention in Health Care: Development and Usability Study. JMIR Formative Research 2021;5(10):e20739
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Shah LM, Ding J, Spaulding EM, Yang WE, Lee MA, Demo R, Marvel FA, Martin SS. Sociodemographic Characteristics Predicting Digital Health Intervention Use After Acute Myocardial Infarction. Journal of Cardiovascular Translational Research 2021;14(5):951
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Bevens W, Gray K, Neate S, Nag N, Weiland T, Jelinek G, Simpson-Yap S. Characteristics of mHealth app use in an international sample of people with multiple sclerosis. Multiple Sclerosis and Related Disorders 2021;54:103092
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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
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Mbotwa C, Kazaura M, Moen K, Leshabari M, Metta E, Leyna G, Mmbaga EJ. Predictors of mHealth use in promoting adherence to pre-exposure prophylaxis among female sex workers: an evaluation of the Jichunge intervention in Dar es Salaam, Tanzania. BMC Health Services Research 2022;22(1)
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Elnaggar A, von Oppenfeld J, Whooley MA, Merek S, Park LG. Applying Mobile Technology to Sustain Physical Activity After Completion of Cardiac Rehabilitation: Acceptability Study. JMIR Human Factors 2021;8(3):e25356
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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
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Kay MC, Miller HN, Askew S, Spaulding EM, Chisholm M, Christy J, Yang Q, Steinberg DM. Patterns of Engagement With an Application-Based Dietary Self-Monitoring Tool Within a Randomized Controlled Feasibility Trial. AJPM Focus 2022;1(2):100037
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Rodríguez-Fernández JM, Danies E, Hoertel N, Galanter W, Saner H, Franco OH. Telemedicine Readiness Across Medical Conditions in a US National Representative Sample of Older Adults. Journal of Applied Gerontology 2022;41(4):982
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According to Crossref, the following books are citing this article (DOI 10.2196/mhealth.4730):