Published on in Vol 3, No 2 (2015): Apr-Jun

Patient Engagement With a Mobile Web-Based Telemonitoring System for Heart Failure Self-Management: A Pilot Study

Patient Engagement With a Mobile Web-Based Telemonitoring System for Heart Failure Self-Management: A Pilot Study

Patient Engagement With a Mobile Web-Based Telemonitoring System for Heart Failure Self-Management: A Pilot Study

Journals

  1. Ghosh A, Misra A. Pokémon Go, Obesity and Diabetes: A Perspective from India. Diabetes Technology & Therapeutics 2016;18(11):725 View
  2. Chib A, Lin S. Theoretical Advancements in mHealth: A Systematic Review of Mobile Apps. Journal of Health Communication 2018;23(10-11):909 View
  3. Liu X, Wang R, Zhou D, Hong Z. Smartphone applications for seizure care and management in children and adolescents with epilepsy: Feasibility and acceptability assessment among caregivers in China. Epilepsy Research 2016;127:1 View
  4. Payne J, Turk M, Kalarchian M, Pellegrini C. Defining Adherence to Dietary Self-Monitoring Using a Mobile App: A Narrative Review. Journal of the Academy of Nutrition and Dietetics 2018;118(11):2094 View
  5. Pham Q, Graham G, Carrion C, Morita P, Seto E, Stinson J, Cafazzo J. 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 View
  6. Finkenflügel R, Hoornenborg E, Achterbergh R, Marra E, Davidovich U, de Vries H, Prins M, Schim van der Loeff M. A Mobile Application to Collect Daily Data on Preexposure Prophylaxis Adherence and Sexual Behavior Among Men Who Have Sex With Men: Use Over Time and Comparability With Conventional Data Collection. Sexually Transmitted Diseases 2019;46(6):400 View
  7. Nie L, Xie B, Yang Y, Shan Y. Characteristics of Chinese m-Health Applications for Diabetes Self-Management. Telemedicine and e-Health 2016;22(7):614 View
  8. Milward J, Deluca P, Drummond C, Kimergård A. Developing Typologies of User Engagement With the BRANCH Alcohol-Harm Reduction Smartphone App: Qualitative Study. JMIR mHealth and uHealth 2018;6(12):e11692 View
  9. Hu J, Yuan D, Zhao Q, Wang X, Zhang X, Jiang Q, Luo H, Li J, Ran J, Li J. Acceptability and practicability of self-management for patients with Parkinson’s disease based on smartphone applications in China. BMC Medical Informatics and Decision Making 2020;20(1) View
  10. Anderson K, Emmerton L. Contribution of mobile health applications to self-management by consumers: review of published evidence. Australian Health Review 2016;40(5):591 View
  11. Liu X, Wang R, Zhou D, Hong Z. Feasibility and acceptability of smartphone applications for seizure self-management in China: Questionnaire study among people with epilepsy. Epilepsy & Behavior 2016;55:57 View
  12. Bricker J, Sridharan V, Zhu Y, Mull K, Heffner J, Watson N, McClure J, Di C. Trajectories of 12-Month Usage Patterns for Two Smoking Cessation Websites: Exploring How Users Engage Over Time. Journal of Medical Internet Research 2018;20(4):e10143 View
  13. Si Y, Xiao X, Xia C, Guo J, Hao Q, Mo Q, Niu Y, Sun H. Optimising epilepsy management with a smartphone application: a randomised controlled trial. Medical Journal of Australia 2020;212(6):258 View
  14. Martos-Cabrera M, Velando-Soriano A, Pradas-Hernández L, Suleiman-Martos N, Cañadas-De la Fuente G, Albendín-García L, Gómez-Urquiza J. Smartphones and Apps to Control Glycosylated Hemoglobin (HbA1c) Level in Diabetes: A Systematic Review and Meta-Analysis. Journal of Clinical Medicine 2020;9(3):693 View
  15. Kruse C, Mileski M, Moreno J. Mobile health solutions for the aging population: A systematic narrative analysis. Journal of Telemedicine and Telecare 2017;23(4):439 View
  16. Ye T, Zhang P, Ouyang Z, Yang J, Xu C, Pan Z, Wu Z, Zhang L, Li B. Multi-trajectory modeling of home blood pressure telemonitoring utilization among hypertensive patients in China: A latent class growth analysis. International Journal of Medical Informatics 2018;119:70 View
  17. 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 View
  18. Bt Wan Mohamed Radzi C, Salarzadeh Jenatabadi H, Samsudin N. mHealth Apps Assessment among Postpartum Women with Obesity and Depression. Healthcare 2020;8(2):72 View
  19. Zapata K, Wang-Price S, Fletcher T, Johnston C. Factors influencing adherence to an app-based exercise program in adolescents with painful hyperkyphosis. Scoliosis and Spinal Disorders 2018;13(1) View
  20. Bonner A, Gillespie K, Campbell K, Corones-Watkins K, Hayes B, Harvie B, Kelly J, Havas K. Evaluating the prevalence and opportunity for technology use in chronic kidney disease patients: a cross-sectional study. BMC Nephrology 2018;19(1) View
  21. Cho J, Lee S, Shin J, Kim J, Lee H. The Impact of Patient Education with a Smartphone Application on the Quality of Bowel Preparation for Screening Colonoscopy. Clinical Endoscopy 2017;50(5):479 View
  22. 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 View
  23. 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 View
  24. Yang Q, Hatch D, Crowley M, Lewinski A, Vaughn J, Steinberg D, Vorderstrasse A, Jiang M, Shaw R. Digital Phenotyping Self-Monitoring Behaviors for Individuals With Type 2 Diabetes Mellitus: Observational Study Using Latent Class Growth Analysis. JMIR mHealth and uHealth 2020;8(6):e17730 View
  25. Park K, Lee H, Lee Y, Cho J, Kim B, Song Y. Reliability and Validity of Korean version of Diabetes Empowerment Scale Short Form. Journal of Korean Academy of Fundamentals of Nursing 2017;24(4):296 View
  26. Bradway M, Gabarron E, Johansen M, Zanaboni P, Jardim P, Joakimsen R, Pape-Haugaard L, Årsand E. Methods and Measures Used to Evaluate Patient-Operated Mobile Health Interventions: Scoping Literature Review. JMIR mHealth and uHealth 2020;8(4):e16814 View
  27. Buck H, Shadmi E, Topaz M, Sockolow P. An integrative review and theoretical examination of chronic illness mHealth studies using the Middle‐Range Theory of Self‐care of Chronic Illness. Research in Nursing & Health 2021;44(1):47 View
  28. Maassen O, Fritsch S, Gantner J, Deffge S, Kunze J, Marx G, Bickenbach J. Future Mobile Device Usage, Requirements, and Expectations of Physicians in German University Hospitals: Web-Based Survey. Journal of Medical Internet Research 2020;22(12):e23955 View

Books/Policy Documents

  1. Chen Y, Yang L, Hu H, Chen J, Shen B. Healthcare and Big Data Management. View
  2. Klimova B. Mobile Web and Intelligent Information Systems. View