Developing a digital heart failure symptom management intervention using the preparation phase of the Multiphase Optimization StraTegy

Abstract Background Persons with heart failure (HF) often experience bothersome symptoms in daily life, which can negatively affect their health-related quality of life (HRQOL). Self-care e.g. to monitor and manage symptoms, is essential in HF management. Self-care can stabilize the disease, reduce symptoms, and improve outcomes. However, patients often find it difficult to recognize and manage symptoms due to various factors. Consequently, many people delay acting until their symptoms become too severe to manage by themselves. This highlights the need for timely engagement in symptom monitoring and interpretation to enable early and appropriate responses. In the SympTom mAnagement and self-caRe (STAR) study, we prepare (phase 1), optimize (phase 2), and evaluate (phase 3) a digital intervention using the Multiphase Optimization StraTegy (MOST). The STAR intervention supports patients with HF in recognizing their symptoms and taking timely, appropriate actions. Objective The aim of this study is to describe the MOST preparation phase of the STAR intervention, including its development of the underlying conceptual model, identification of candidate components and optimization criterion, and assessment of intervention feasibility to inform the subsequent optimization phase. Methods We conducted four sequential activities from the preparation phase of MOST: (1) developing a conceptual model; (2) identifying candidate components; (3) identifying optimization criterion; and (4) conducting a feasibility study of the digital STAR intervention with patients with HF and HF nurses. Results The conceptual model includes four candidate components; a basic component, symptom awareness training, symptom management counselling, and symptom management experiments. We expect these components to influence behavioral outcomes such as reduced symptom burden and hospitalizations, and improved self-care and HRQOL. The set of candidate components were specified at two levels (low versus high) by varying intensity, frequency, or mode of delivery while maintaining consistent core content. Ten patients with HF and 5 HF nurses tested the STAR intervention in the feasibility study. The STAR intervention was perceived as feasible from both a patient and nurses’ perspective. Patients rated the intervention as clear, user-friendly and structured. Participants valued personal support from HF nurses and perceived it as important for continued use of the intervention. The feasibility findings provide concrete input to refine the intervention prior to the optimization trial. Conclusion The STAR intervention is feasible and acceptable to both patients with HF and HF nurses. Combined with the conceptual model, linking components to underlying mechanisms and outcomes, the findings provide us a solid foundation for optimizing the STAR intervention in a subsequent optimization trial.