• Patient Prefer Adher · Jan 2023

    A Conceptual Model of Home-Based Cardiac Rehabilitation Exercise Adherence in Patients with Chronic Heart Failure: A Constructivist Grounded Theory Study.

    • Zhen Yang, Longfeng Sun, Yuanhui Sun, Yu Dong, and Aiping Wang.
    • Department of Public Service, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning Province, People's Republic of China.
    • Patient Prefer Adher. 2023 Jan 1; 17: 851860851-860.

    PurposeThis study aimed to explore a conceptual model of home-based cardiac rehabilitation exercise adherence and reveal its internal behavioral logic.Patients And MethodsA constructivist grounded theory design was adopted to explore the conceptual model of home-based cardiac rehabilitation exercise adherence. Semi-structured interviews were completed to collect qualitative data for constructing the conceptual model. The theoretical saturation and validation strategies were adopted to demonstrate the adequacy of qualitative data. A three-level coding procedure with constant comparisons was completed to analyze this qualitative data.ResultsA total of 21 patients with chronic heart failure were recruited in this study. As a result of this study, 32 initial codes, 12 category codes, and four core categories were extracted, namely, seeking supports, rehabilitation exercise, exercise monitoring and information feedback. According to the internal behavioral logic, the conceptual model of home cardiac rehabilitation exercise adherence was finally formed. In this closed-chain model, seeking supports is the initial adherence behavior, and rehabilitation exercise is the core adherence behavior, and exercise monitoring is the key adherence behavior, and information feedback is the driving adherence behavior.ConclusionThe conceptual model of home-based cardiac rehabilitation exercise adherence in patients with chronic heart failure was developed, revealing its internal behavioral logic and providing theoretical references for developing relevant clinical research tools with comprehensive coverage and identifying weak links.© 2023 Yang et al.

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