This paper is in the following e-collection/theme issue:

Mobile Health (mhealth) (3132) Hypertension Prevention and Treatment (253) Engagement with and Adherence to Digital Health Interventions, Law of Attrition (534) Participatory Medicine & E-Patients (827) Evaluation and Research Methodology for mHealth (219) mHealth for Patient Education (260) mHealth for Symptom and Disease Monitoring, Chronic Disease Management (1554) Machine Learning (1695)

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
Article Authors Cited by (6) Tweetations (3) Metrics

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 2024 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

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