Published on in Vol 23, No 7 (2021): July

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/26670, first published .
Measuring Success of Patients’ Continuous Use of Mobile Health Services for Self-management of Chronic Conditions: Model Development and Validation

Measuring Success of Patients’ Continuous Use of Mobile Health Services for Self-management of Chronic Conditions: Model Development and Validation

Measuring Success of Patients’ Continuous Use of Mobile Health Services for Self-management of Chronic Conditions: Model Development and Validation

Journals

  1. Kim D, Lee Y, Oh J, Seo D, Lee K, Kim Y, Kim W, Lee J. Effects of Patient-Generated Health Data: Comparison of Two Versions of Long-Term Mobile Personal Health Record Usage Logs. Healthcare 2021;10(1):53 View
  2. Werner N, Brown J, Loganathar P, Holden R. Quality of Mobile Apps for Care Partners of People With Alzheimer Disease and Related Dementias: Mobile App Rating Scale Evaluation. JMIR mHealth and uHealth 2022;10(3):e33863 View
  3. Gao C, Shen Y, Xu W, Zhang Y, Tu Q, Zhu X, Lu Z, Yang Y. A fuzzy-set qualitative comparative analysis exploration of multiple paths to users’ continuous use behavior of diabetes self-management apps. International Journal of Medical Informatics 2023;172:105000 View
  4. 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
  5. Lee Y, Huang L, Chen S, Shao J, Lai C, Yang N. Effects of Mobile Application Program (App)-Assisted Health Education on Preventive Behaviors and Cancer Literacy among Women with Cervical Intraepithelial Neoplasia. International Journal of Environmental Research and Public Health 2021;18(21):11603 View
  6. Jiang Y, Lau A. Understanding Post-Adoption Behavioral Intentions of Mobile Health Service Users: An Empirical Study during COVID-19. International Journal of Environmental Research and Public Health 2023;20(5):3907 View
  7. Abasi S, Yazdani A, Kiani S, Mahmoudzadeh‐Sagheb Z. Effectiveness of mobile health‐based self‐management application for posttransplant cares: A systematic review. Health Science Reports 2021;4(4) View
  8. Lu F, Wang X, Huang X. Counseling for Health: How Psychological Distance Influences Continuance Intention towards Mobile Medical Consultation. International Journal of Environmental Research and Public Health 2023;20(3):1718 View
  9. Liu Y, Hu B, Yan W, Lin Z. Can chatbots satisfy me? A mixed-method comparative study of satisfaction with task-oriented chatbots in mainland China and Hong Kong. Computers in Human Behavior 2023;143:107716 View
  10. Pathiraja Rathnayaka Hitige N, Song T, Houston L, Smith N, Probst Y, Bliokas V, Yu P. A 6P Framework for Engaging Consumers in Focus Group Discussions to Identify Needs, Experiences, and Expectations with Digital Health Solutions. SSRN Electronic Journal 2022 View
  11. Nie L, Oldenburg B, Cao Y, Ren W. Continuous usage intention of mobile health services: model construction and validation. BMC Health Services Research 2023;23(1) View
  12. Yu H, Tan L, Zhu T, Deng X. A WeChat applet-based national remote emergency system for malignant hyperthermia in China: a usability study. BMC Medical Informatics and Decision Making 2023;23(1) View
  13. Zhang M, Zhang H, Zhu R, Yang H, Chen M, Wang X, Li Z, Xiong Z. Factors affecting the willingness of patients with type 2 diabetes to use digital disease management applications: a cross-sectional study. Frontiers in Public Health 2023;11 View
  14. Liu F, Song T, Yu P, Deng N, Guan Y, Yang Y, Ma Y. Efficacy of an mHealth App to Support Patients’ Self-Management of Hypertension: Randomized Controlled Trial. Journal of Medical Internet Research 2023;25:e43809 View
  15. Cho J, Yoo S, Lee E, Lee H. Impact of a Nationwide Medication History Sharing Program on the Care Process and End-User Experience in a Tertiary Teaching Hospital: Cohort Study and Cross-Sectional Study. JMIR Medical Informatics 2024;12:e53079 View
  16. Cheah K, Abdul Manaf Z, Fitri Mat Ludin A, Razalli N, Mohd Mokhtar N, Md Ali S. Mobile Apps for Common Noncommunicable Disease Management: Systematic Search in App Stores and Evaluation Using the Mobile App Rating Scale. JMIR mHealth and uHealth 2024;12:e49055 View
  17. Thabet Z, Albashtawi S, Ansari H, Al-Emran M, Al-Sharafi M, AlQudah A. Exploring the Factors Affecting Telemedicine Adoption by Integrating UTAUT2 and IS Success Model: A Hybrid SEM–ANN Approach. IEEE Transactions on Engineering Management 2024;71:8938 View
  18. Rana R, Ibrahim B, Huri H, Wahab I, Govindaraju K, Shukeri M, Ng C, Ong S. Development and validation of the mobile adherence satisfaction scale (MASS) for medication adherence apps. Research in Social and Administrative Pharmacy 2024;20(10):959 View
  19. Merdekawati U, Nugraheni D, Nurhayati O. Analisis Penerimaan dan Kesuksesan Aplikasi M-health pada Lansia menggunakan Model UTAUT dan Delone & McLean. Jurnal Sistem Informasi Bisnis 2024;14(3):267 View
  20. Li F, Tolessa Negera D, Adnan Zahid Chudhery M, Zhao Q, Gao L. IoT and Motion Recognition-Based Healthcare Rehabilitation Systems (IMRHRS): An Empirical Examination From Physicians’ Perspective Using Stimulus-Organism-Response Theory. IEEE Access 2024;12:142863 View
  21. Li L. What are the Key Drivers to Promote Continuance Intention of Undergraduates in Mobile Learning? A Multi-perspective Framework. Sage Open 2024;14(4) View
  22. Song F, Gong X, Yang Y, Guo R. Comparing the Quality of Direct-to-Consumer Telemedicine Dominated and Delivered by Public and Private Sector Platforms in China: Standardized Patient Study. Journal of Medical Internet Research 2024;26:e55400 View