Published on in Vol 23, No 9 (2021): September

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/25630, first published .
Patterns for Patient Engagement with the Hypertension Management and Effects of Electronic Health Care Provider Follow-up on These Patterns: Cluster Analysis

Patterns for Patient Engagement with the Hypertension Management and Effects of Electronic Health Care Provider Follow-up on These Patterns: Cluster Analysis

Patterns for Patient Engagement with the Hypertension Management and Effects of Electronic Health Care Provider Follow-up on These Patterns: Cluster Analysis

Authors of this article:

Dan Wu1 Author Orcid Image ;   Jiye An1 Author Orcid Image ;   Ping Yu2 Author Orcid Image ;   Hui Lin1 Author Orcid Image ;   Li Ma3 Author Orcid Image ;   Huilong Duan1 Author Orcid Image ;   Ning Deng1 Author Orcid Image

Journals

  1. Peng M, Shi X, Zhu L, Wang Z. Follow-up management service and health outcomes of hypertensive patients in China: A cross-sectional analysis from the national health service survey in Jiangsu province. Frontiers in Public Health 2022;10 View
  2. 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 View
  3. Manasyan A, Lasky S, Stanton E, Cannata B, Moshal T, Roohani I, Koesters E, Daar D. Resources on lymphedema surgery: How effective are they for patients?. Journal of Surgical Oncology 2024;130(3):360 View
  4. Manasyan A, Lasky S, Jolibois M, Moshal T, Roohani I, Munabi N, Urata M, Hammoudeh J. Expanding Accessibility in Cleft Care: The Role of Artificial Intelligence in Improving Literacy of Alveolar Bone Grafting Information. The Cleft Palate Craniofacial Journal 2025;62(11):1873 View
  5. Eze C, Dorsch M, Coe A, Lester C, Buis L, Farris K. Behavioral Factors Related to Participation in Remote Blood Pressure Monitoring Among Adults With Hypertension: Cross-Sectional Study. JMIR Formative Research 2024;8:e56954 View
  6. Kang B, Park M, Kim J, Yoon S, Heo S, Kang C, Lee S, Choi Y, Hong D. Exploring Factors Related to Social Isolation Among Older Adults in the Predementia Stage Using Ecological Momentary Assessments and Actigraphy: Machine Learning Approach. Journal of Medical Internet Research 2025;27:e69379 View
  7. Zhang N, Lin H, Wu X, Zheng Y, Yin J, Ding C, Pan Q, Yang S, Luo H, Zou X, Ge Y, Zhang J. Impact of Patient Engagement on Blood Pressure Control Among Older Individuals With Hypertension in a Mobile Health Intervention: Longitudinal Analysis Using Latent Growth Curve Modeling. Journal of Medical Internet Research 2025;27:e71668 View
  8. Peuters C, DeSmet A, Maenhout L, Cardon G, Debeer D, Crombez G. Adolescent Engagement With a Multicomponent mHealth Tool: Identifying Usage Patterns, Determinants, and Health Behavior Change in an Intervention Trial. JMIR mHealth and uHealth 2025;13:e59041 View
  9. Matsumoto A, Mineharu Y, Kohjitani H, Koshimizu H, Okuno Y. Predicting measurement continuity in home blood pressure monitoring using machine learning. Hypertension Research 2025 View
  10. Ni X, Xue H, Fan L, Li M, Yang J, Du W. Network meta analysis of contributions by different healthcare practitioners in digital self care for hypertension. npj Digital Medicine 2025;8(1) View

Conference Proceedings

  1. Li S, Chen J, An J, Deng N, Hu J. 2022 12th International Conference on Information Technology in Medicine and Education (ITME)v. Research on factors related to management effect based on chronic disease management platform View