Published on 15.04.14 in Vol 16, No 4 (2014): April
Works citing "Factors Related to Sustained Use of a Free Mobile App for Dietary Self-Monitoring With Photography and Peer Feedback: Retrospective Cohort Study"
According to Crossref, the following articles are citing this article (DOI 10.2196/jmir.3084):
(note that this is only a small subset of citations)
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Direito A, Jiang Y, Whittaker R, Maddison R. Apps for IMproving FITness and Increasing Physical Activity Among Young People: The AIMFIT Pragmatic Randomized Controlled Trial. Journal of Medical Internet Research 2015;17(8):e210
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Kuang J, Argo L, Stoddard G, Bray BE, Zeng-Treitler Q. Assessing Pictograph Recognition: A Comparison of Crowdsourcing and Traditional Survey Approaches. Journal of Medical Internet Research 2015;17(12):e281
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Hilliard ME, Hahn A, Ridge AK, Eakin MN, Riekert KA. User Preferences and Design Recommendations for an mHealth App to Promote Cystic Fibrosis Self-Management. JMIR mHealth and uHealth 2014;2(4):e44
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Ben Neriah D, Geliebter A. Weight Loss Following Use of a Smartphone Food Photo Feature: Retrospective Cohort Study. JMIR mHealth and uHealth 2019;7(6):e11917
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Steinhubl SR, Muse ED, Topol EJ. The emerging field of mobile health. Science Translational Medicine 2015;7(283)
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Rubanovich CK, Mohr DC, Schueller SM. Health App Use Among Individuals With Symptoms of Depression and Anxiety: A Survey Study With Thematic Coding. JMIR Mental Health 2017;4(2):e22
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Leung L, Chen C. E-health/m-health adoption and lifestyle improvements: Exploring the roles of technology readiness, the expectation-confirmation model, and health-related information activities. Telecommunications Policy 2019;43(6):563
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Lee HE, Cho J. What Motivates Users to Continue Using Diet and Fitness Apps? Application of the Uses and Gratifications Approach. Health Communication 2017;32(12):1445
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Perski O, Blandford A, West R, Michie S. Conceptualising engagement with digital behaviour change interventions: a systematic review using principles from critical interpretive synthesis. Translational Behavioral Medicine 2017;7(2):254
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Oser M, Wallace ML, Solano F, Szigethy EM. Guided Digital Cognitive Behavioral Program for Anxiety in Primary Care: Propensity-Matched Controlled Trial. JMIR Mental Health 2019;6(4):e11981
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Kankanhalli A, Shin J, Oh H. Mobile-Based Interventions for Dietary Behavior Change and Health Outcomes: Scoping Review. JMIR mHealth and uHealth 2019;7(1):e11312
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Sanders JP, Loveday A, Pearson N, Edwardson C, Yates T, Biddle SJ, Esliger DW. Devices for Self-Monitoring Sedentary Time or Physical Activity: A Scoping Review. Journal of Medical Internet Research 2016;18(5):e90
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Elaheebocus SMRA, Weal M, Morrison L, Yardley L. Peer-Based Social Media Features in Behavior Change Interventions: Systematic Review. Journal of Medical Internet Research 2018;20(2):e20
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Mummah S, Robinson TN, Mathur M, Farzinkhou S, Sutton S, Gardner CD. Effect of a mobile app intervention on vegetable consumption in overweight adults: a randomized controlled trial. International Journal of Behavioral Nutrition and Physical Activity 2017;14(1)
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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
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Khamzina M, Parab KV, An R, Bullard T, Grigsby-Toussaint DS. Impact of Pokémon Go on Physical Activity: A Systematic Review and Meta-Analysis. American Journal of Preventive Medicine 2020;58(2):270
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Xiaofei Z, Guo X, Ho SY, Lai K, Vogel D. Effects of emotional attachment on mobile health-monitoring service usage: An affect transfer perspective. Information & Management 2021;58(2):103312
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Lattie EG, Schueller SM, Sargent E, Stiles-Shields C, Tomasino KN, Corden ME, Begale M, Karr CJ, Mohr DC. Uptake and usage of IntelliCare: A publicly available suite of mental health and well-being apps. Internet Interventions 2016;4:152
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Naslund JA, Aschbrenner KA, Barre LK, Bartels SJ. Feasibility of Popular m-Health Technologies for Activity Tracking Among Individuals with Serious Mental Illness. Telemedicine and e-Health 2015;21(3):213
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Kim JY, Wineinger NE, Taitel M, Radin JM, Akinbosoye O, Jiang J, Nikzad N, Orr G, Topol E, Steinhubl S. Self-Monitoring Utilization Patterns Among Individuals in an Incentivized Program for Healthy Behaviors. Journal of Medical Internet Research 2016;18(11):e292
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König LM, Sproesser G, Schupp HT, Renner B. Describing the Process of Adopting Nutrition and Fitness Apps: Behavior Stage Model Approach. JMIR mHealth and uHealth 2018;6(3):e55
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Wessels NJ, Hulshof L, Loohuis AMM, van Gemert-Pijnen L, Jellema P, van der Worp H, Blanker MH. User Experiences and Preferences Regarding an App for the Treatment of Urinary Incontinence in Adult Women: Qualitative Study. JMIR mHealth and uHealth 2020;8(6):e17114
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Direito A, Tooley M, Hinbarji M, Albatal R, Jiang Y, Whittaker R, Maddison R. Tailored Daily Activity: An Adaptive Physical Activity Smartphone Intervention. Telemedicine and e-Health 2020;26(4):426
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Turner-McGrievy GM, Wilcox S, Kaczynski AT, Spruijt-Metz D, Hutto BE, Muth ER, Hoover A. Crowdsourcing for self-monitoring: Using the Traffic Light Diet and crowdsourcing to provide dietary feedback. DIGITAL HEALTH 2016;2:205520761665721
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Chib A, Lin SH. Theoretical Advancements in mHealth: A Systematic Review of Mobile Apps. Journal of Health Communication 2018;23(10-11):909
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Yu Z, Sealey-Potts C, Rodriguez J. Dietary Self-Monitoring in Weight Management: Current Evidence on Efficacy and Adherence. Journal of the Academy of Nutrition and Dietetics 2015;115(12):1931
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D’Ambrosio A, Agricola E, Russo L, Gesualdo F, Pandolfi E, Bortolus R, Castellani C, Lalatta F, Mastroiacovo P, Tozzi AE, Cai T. Web-Based Surveillance of Public Information Needs for Informing Preconception Interventions. PLOS ONE 2015;10(4):e0122551
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Patrick K, Hekler EB, Estrin D, Mohr DC, Riper H, Crane D, Godino J, Riley WT. The Pace of Technologic Change. American Journal of Preventive Medicine 2016;51(5):816
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Turner-McGrievy GM, Dunn CG, Wilcox S, Boutté AK, Hutto B, Hoover A, Muth E. Defining Adherence to Mobile Dietary Self-Monitoring and Assessing Tracking Over Time: Tracking at Least Two Eating Occasions per Day Is Best Marker of Adherence within Two Different Mobile Health Randomized Weight Loss Interventions. Journal of the Academy of Nutrition and Dietetics 2019;119(9):1516
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Fritz MM, Armenta CN, Walsh LC, Lyubomirsky S. Gratitude facilitates healthy eating behavior in adolescents and young adults. Journal of Experimental Social Psychology 2019;81:4
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Crane D, Garnett C, Brown J, West R, Michie S. Factors Influencing Usability of a Smartphone App to Reduce Excessive Alcohol Consumption: Think Aloud and Interview Studies. Frontiers in Public Health 2017;5
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Tonkin E, Jeffs L, Wycherley TP, Maher C, Smith R, Hart J, Cubillo B, Brimblecombe J. A Smartphone App to Reduce Sugar-Sweetened Beverage Consumption Among Young Adults in Australian Remote Indigenous Communities: Design, Formative Evaluation and User-Testing. JMIR mHealth and uHealth 2017;5(12):e192
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Sawesi S, Rashrash M, Phalakornkule K, Carpenter JS, Jones JF. The Impact of Information Technology on Patient Engagement and Health Behavior Change: A Systematic Review of the Literature. JMIR Medical Informatics 2016;4(1):e1
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Rasche P, Schlomann A, Mertens A. Who Is Still Playing Pokémon Go? A Web-Based Survey. JMIR Serious Games 2017;5(2):e7
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Mummah SA, Mathur M, King AC, Gardner CD, Sutton S. Mobile Technology for Vegetable Consumption: A Randomized Controlled Pilot Study in Overweight Adults. JMIR mHealth and uHealth 2016;4(2):e51
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Mohr DC, Tomasino KN, Lattie EG, Palac HL, Kwasny MJ, Weingardt K, Karr CJ, Kaiser SM, Rossom RC, Bardsley LR, Caccamo L, Stiles-Shields C, Schueller SM. IntelliCare: An Eclectic, Skills-Based App Suite for the Treatment of Depression and Anxiety. Journal of Medical Internet Research 2017;19(1):e10
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. Review of researches on smartphone applications for physical activity promotion in healthy adults. Journal of Exercise Rehabilitation 2017;13(1):3
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Cheung K, Ling W, Karr CJ, Weingardt K, Schueller SM, Mohr DC. Evaluation of a recommender app for apps for the treatment of depression and anxiety: an analysis of longitudinal user engagement. Journal of the American Medical Informatics Association 2018;25(8):955
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Maringer M, van’t Veer P, Klepacz N, Verain MCD, Normann A, Ekman S, Timotijevic L, Raats MM, Geelen A. User-documented food consumption data from publicly available apps: an analysis of opportunities and challenges for nutrition research. Nutrition Journal 2018;17(1)
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Hu X, Qian M, Cheng B, Cheung YK. Personalized Policy Learning Using Longitudinal Mobile Health Data. Journal of the American Statistical Association 2021;116(533):410
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Vinnikova A, Lu L, Wei J, Fang G, Yan J. The Use of Smartphone Fitness Applications: The Role of Self-Efficacy and Self-Regulation. International Journal of Environmental Research and Public Health 2020;17(20):7639
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Yan M, Filieri R, Gorton M. Continuance intention of online technologies: A systematic literature review. International Journal of Information Management 2021;58:102315
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Berglind D, Yacaman-Mendez D, Lavebratt C, Forsell Y. The Effect of Smartphone Apps Versus Supervised Exercise on Physical Activity, Cardiorespiratory Fitness, and Body Composition Among Individuals With Mild-to-Moderate Mobility Disability: Randomized Controlled Trial. JMIR mHealth and uHealth 2020;8(2):e14615
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Jung J, Wellard-Cole L, Cai C, Koprinska I, Yacef K, Allman-Farinelli M, Kay J. Foundations for Systematic Evaluation and Benchmarking of a Mobile Food Logger in a Large-scale Nutrition Study. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2020;4(2):1
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Minen MT, Jaran J, Boyers T, Corner S. Understanding What People With Migraine Consider to be Important Features of Migraine Tracking: An Analysis of the Utilization of Smartphone‐Based Migraine Tracking With a Free‐Text Feature. Headache: The Journal of Head and Face Pain 2020;60(7):1402
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Harjumaa M, Absetz P, Ermes M, Mattila E, Männikkö R, Tilles-Tirkkonen T, Lintu N, Schwab U, Umer A, Leppänen J, Pihlajamäki J. Internet-Based Lifestyle Intervention to Prevent Type 2 Diabetes Through Healthy Habits: Design and 6-Month Usage Results of Randomized Controlled Trial. JMIR Diabetes 2020;5(3):e15219
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Meyerowitz-Katz G, Ravi S, Arnolda L, Feng X, Maberly G, Astell-Burt T. Rates of Attrition and Dropout in App-Based Interventions for Chronic Disease: Systematic Review and Meta-Analysis. Journal of Medical Internet Research 2020;22(9):e20283
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Yan M, Filieri R, Raguseo E, Gorton M. Mobile apps for healthy living: Factors influencing continuance intention for health apps. Technological Forecasting and Social Change 2021;166:120644
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Zhang P, Burns RD, Fu Y, Godin S, Li Z, Zhang X. Efficacy of a 4-Week Smartphone Application Intervention on College Students’ BMI, Physical Activity, and Motivation. International Journal of Kinesiology in Higher Education 2022;6(1):15
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Flaherty SJ, McCarthy M, Collins AM, McCafferty C, McAuliffe FM. Exploring engagement with health apps: the emerging importance of situational involvement and individual characteristics. European Journal of Marketing 2021;55(13):122
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Garnett C, Perski O, Michie S, West R, Field M, Kaner E, Munafò MR, Greaves F, Hickman M, Burton R, Brown J. Refining the content and design of an alcohol reduction app, Drink Less, to improve its usability and effectiveness: a mixed methods approach. F1000Research 2021;10:511
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Das SK, Bukhari AS, Taetzsch AG, Ernst AK, Rogers GT, Gilhooly CH, Hatch-McChesney A, Blanchard CM, Livingston KA, Silver RE, Martin E, McGraw SM, Chin MK, Vail TA, Lutz LJ, Montain SJ, Pittas AG, Lichtenstein AH, Allison DB, Dickinson S, Chen X, Saltzman E, Young AJ, Roberts SB. Randomized trial of a novel lifestyle intervention compared with the Diabetes Prevention Program for weight loss in adult dependents of military service members. The American Journal of Clinical Nutrition 2021;114(4):1546
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Fowers R, Berardi V, Huberty J, Stecher C. Using mobile meditation app data to predict future app engagement: an observational study. Journal of the American Medical Informatics Association 2022;29(12):2057
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Silva VC, Gorgulho B, Marchioni DM, Alvim SM, Giatti L, de Araujo TA, Alonso AC, Santos IDS, Lotufo PA, Benseñor IM. Recommender System Based on Collaborative Filtering for Personalized Dietary Advice: A Cross-Sectional Analysis of the ELSA-Brasil Study. International Journal of Environmental Research and Public Health 2022;19(22):14934
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Ploderer B, Rezaei Aghdam A, Burns K. Patient-Generated Health Photos and Videos Across Health and Well-being Contexts: Scoping Review. Journal of Medical Internet Research 2022;24(4):e28867
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Jacob C, Lindeque J, Klein A, Ivory C, Heuss S, Peter MK. Assessing the Quality and Impact of eHealth Tools: Systematic Literature Review and Narrative Synthesis. JMIR Human Factors 2023;10:e45143
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Lu X, Chen Y, Epstein DA. A Model of Socially Sustained Self-Tracking for Food and Diet. Proceedings of the ACM on Human-Computer Interaction 2021;5(CSCW2):1
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Jakob R, Harperink S, Rudolf AM, Fleisch E, Haug S, Mair JL, Salamanca-Sanabria A, Kowatsch T. Factors Influencing Adherence to mHealth Apps for Prevention or Management of Noncommunicable Diseases: Systematic Review. Journal of Medical Internet Research 2022;24(5):e35371
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Stewart C, Piernas C, Frie K, Cook B, Jebb SA. Evaluation of OPTIMISE (Online Programme to Tackle Individual’s Meat Intake Through Self-regulation): Cohort Study. Journal of Medical Internet Research 2022;24(12):e37389
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Nwolise CH, Carey N, Shawe J. Preconception and Diabetes Information (PADI) App for Women with Pregestational Diabetes: a Feasibility and Acceptability Study. Journal of Healthcare Informatics Research 2021;5(4):446
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Stecher C, Sullivan M, Huberty J. Using Personalized Anchors to Establish Routine Meditation Practice With a Mobile App: Randomized Controlled Trial. JMIR mHealth and uHealth 2021;9(12):e32794
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Ulfa M, Setyonugroho W, Lestari T, Widiasih E, Nguyen Quoc A, Schiavo L. Nutrition-Related Mobile Application for Daily Dietary Self-Monitoring. Journal of Nutrition and Metabolism 2022;2022:1
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Stark AL, Geukes C, Dockweiler C. Digital Health Promotion and Prevention in Settings: Scoping Review. Journal of Medical Internet Research 2022;24(1):e21063
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Jacob C, Sezgin E, Sanchez-Vazquez A, Ivory C. Sociotechnical Factors Affecting Patients’ Adoption of Mobile Health Tools: Systematic Literature Review and Narrative Synthesis. JMIR mHealth and uHealth 2022;10(5):e36284
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Garnett C, Perski O, Michie S, West R, Field M, Kaner E, Munafò MR, Greaves F, Hickman M, Burton R, Brown J. Refining the content and design of an alcohol reduction app, Drink Less, to improve its usability and effectiveness: a mixed methods approach. F1000Research 2021;10:511
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Sharma S, Hoover A. Top-Down Detection of Eating Episodes by Analyzing Large Windows of Wrist Motion Using a Convolutional Neural Network. Bioengineering 2022;9(2):70
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Tonkin E, Brimblecombe J, Wycherley TP. Characteristics of Smartphone Applications for Nutrition Improvement in Community Settings: A Scoping Review. Advances in Nutrition 2017;8(2):308
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Valcarce-Torrente M, Javaloyes V, Gallardo L, García-Fernández J, Planas-Anzano A. Influence of Fitness Apps on Sports Habits, Satisfaction, and Intentions to Stay in Fitness Center Users: An Experimental Study. International Journal of Environmental Research and Public Health 2021;18(19):10393
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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)
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van der Haar S, Raaijmakers I, Verain MCD, Meijboom S. Incorporating Consumers’ Needs in Nutrition Apps to Promote and Maintain Use: Mixed Methods Study. JMIR mHealth and uHealth 2023;11:e39515
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Stecher C, Cloonan S, Linnemayr S, Huberty J. Combining Behavioral Economics–Based Incentives With the Anchoring Strategy: Protocol for a Randomized Controlled Trial. JMIR Research Protocols 2023;12:e39930
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Chen E, Prakash S, Janapa Reddi V, Kim D, Rajpurkar P. A framework for integrating artificial intelligence for clinical care with continuous therapeutic monitoring. Nature Biomedical Engineering 2023;
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Borst F, Reuss-Borst M, Boschmann J, Schwarz P, König LM. Can mobile-health applications contribute to long-term increase in physical activity after medical rehabilitation?–A pilot-study. PLOS Digital Health 2023;2(10):e0000359
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Zhou X, Wei X, Cheng A, Liu Z, Su Z, Li J, Qin R, Zhao L, Xie Y, Huang Z, Xia X, Liu Y, Song Q, Xiao D, Wang C. Mobile Phone–Based Interventions for Smoking Cessation Among Young People: Systematic Review and Meta-Analysis. JMIR mHealth and uHealth 2023;11:e48253
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Theodore Armand TP, Kim H, Kim J. Digital Anti-Aging Healthcare: An Overview of the Applications of Digital Technologies in Diet Management. Journal of Personalized Medicine 2024;14(3):254
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Kim M, Lee H, Park G, Khang AR. Participation experience in self-care program for type 2 diabetes: A mixed-methods study. Journal of Korean Gerontological Nursing 2024;26(1):31
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Mensinger JL, Weissinger GM, Cantrell MA, Baskin R, George C. A Pilot Feasibility Evaluation of a Heart Rate Variability Biofeedback App to Improve Self-Care in COVID-19 Healthcare Workers. Applied Psychophysiology and Biofeedback 2024;
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According to Crossref, the following books are citing this article (DOI 10.2196/jmir.3084):
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. M‐Health: Fundamentals and Applications. 2016. :67
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. Reference Module in Biomedical Sciences. 2018.
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Ramirez V, Starobin B, Monti J. Encyclopedia of Cardiovascular Research and Medicine. 2018. :257
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Wang L, He D, Ni X, Zou R, Yuan X, Shang Y, Hu X, Geng X, Jiang K, Dong J, Wu H. Smart Health. 2018. Chapter 29:292
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Nagarajan B, Khatun R, Bolaños M, Aguilar E, Angelini L, El Kamali M, Mugellini E, Khaled OA, Boqué N, Tarro L, Radeva P. Digital Health Technology for Better Aging. 2021. Chapter 5:77
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. Design, User Experience, and Usability: UX Research and Design. 2021. Chapter 14:204
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Valcarce M, Angosto S. Innovation in Physical Activity and Sport. 2022. Chapter 10:88
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Folta SC, Brown AGM, Blumberg JB. Preventive Nutrition. 2015. Chapter 1:3
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Lurz M, Fischer S, Böhm M, Krcmar H. Human-Computer Interaction. Theoretical Approaches and Design Methods. 2022. Chapter 32:462
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