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

Web-based and Mobile Health Interventions (3345) Electronic Health Records (1067) Cardiac Self-Management (107) Focus Groups and Qualitative Research for Human Factors Research (871)

Published on in Vol 23, No 4 (2021): April

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/25333, first published .
An Internet-Based Intervention for Cardiovascular Disease Management Integrated With Primary Care Electronic Health Records: Mixed Methods Evaluation of Implementation Fidelity and User Engagement

An Internet-Based Intervention for Cardiovascular Disease Management Integrated With Primary Care Electronic Health Records: Mixed Methods Evaluation of Implementation Fidelity and User Engagement

An Internet-Based Intervention for Cardiovascular Disease Management Integrated With Primary Care Electronic Health Records: Mixed Methods Evaluation of Implementation Fidelity and User Engagement

Authors of this article:

Genevieve Coorey1, 2 Author Orcid Image ;   David Peiris1, 3 Author Orcid Image ;   Anish Scaria1 Author Orcid Image ;   John Mulley1 Author Orcid Image ;   Lis Neubeck4, 5 Author Orcid Image ;   Nashid Hafiz2 Author Orcid Image ;   Julie Redfern2 Author Orcid Image
Article Authors Cited by (8) Tweetations (6) Metrics

Journals

  1. Benton J, Cotterill S, Hawkes R, Miles L, French D. Changes in a Digital Type 2 Diabetes Self-management Intervention During National Rollout: Mixed Methods Study of Fidelity. Journal of Medical Internet Research 2022;24(12):e39483 View
  2. Seixas A, Richards S, Moore J, Izeogu C, Hollimon L, Jin P, Jean-Louis G. Precision Recruitment and Engagement of Individuals at Risk for Diabetes and Hypertension in Clinical Trials (PREDHICT): A Randomized Trial for an E-Persuasive Mobile Application to Inform Decision Making about Clinical Trials. International Journal of Environmental Research and Public Health 2023;20(23):7115 View
  3. Ma Y, Achiche S, Pomey M, Paquette J, Adjtoutah N, Vicente S, Engler K, Laymouna M, Lessard D, Lemire B, Asselah J, Therrien R, Osmanlliu E, Zawati M, Joly Y, Lebouché B. Adapting and Evaluating an AI-Based Chatbot Through Patient and Stakeholder Engagement to Provide Information for Different Health Conditions: Master Protocol for an Adaptive Platform Trial (the MARVIN Chatbots Study). JMIR Research Protocols 2024;13:e54668 View
  4. Firet L, Teunissen T, Kool R, Akkermans R, Lagro-Janssen A, van der Vaart H, Assendelft W. The relation between usage of an eHealth intervention for stress urinary incontinence and treatment outcomes: an observational study. BMC Primary Care 2024;25(1) View
  5. Peng P, Shen Y, Xiong H. Wearable monitoring device based on an internet management platform improves metabolic parameters in type 2 diabetes patients: a prospective pilot study. Postgraduate Medicine 2024;136(5):523 View
  6. Zhang P, Tao X, Ma Y, Zhang Y, Ma X, Song H, Liu Y, Patel A, Jan S, Peiris D. Improving the management of type 2 diabetes in China using a multifaceted digital health intervention in primary health care: the SMARTDiabetes cluster randomised controlled trial. The Lancet Regional Health - Western Pacific 2024;49:101130 View
  7. Eaton C, Vallejo N, McDonald X, Wu J, Rodríguez R, Muthusamy N, Mathioudakis N, Riekert K. User Engagement With mHealth Interventions to Promote Treatment Adherence and Self-Management in People With Chronic Health Conditions: Systematic Review. Journal of Medical Internet Research 2024;26:e50508 View
  8. Qi Y, Mohamad E, Azlan A, Zhang C, Ma Y, Wu A. Digital Health Solutions for Cardiovascular Disease Prevention: A Systematic Review (Preprint). Journal of Medical Internet Research 2024 View