Developing a digital heart failure symptom management intervention using the preparation phase of the Multiphase Optimization StraTegy
10 affiliations
- 1Julius Center for Health Sciences and Primary Care, Department of General Practice and Nursing Science, University Medical Centre Utrecht
- 2Department of Health, Medicine and Caring Sciences, Linköping University
- 3Department of Behavioural Sciences and Learning, Linköping University
- 4Johns Hopkins University (School of Nursing)
- 5Washington University School of Medicine
- 6Boston College William F. Connell School of Nursing
- 7Hunter-Bellevue School of Nursing, Hunter College of The City University of New York
- 8Division of Nursing, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet
- 9Center for Home Care Policy & Research at VNS Health
- 10Tor Vergata University of Rome
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.
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BibTeX
@article{rijn2026developing,
title = {{Developing a digital heart failure symptom management intervention using the preparation phase of the Multiphase Optimization StraTegy}},
author = {Michelle van Rijn and Tiny Jaarsma and Gerhard Andersson and Subhash Aryal and Kenneth Freedland and Christopher Lee and Shayleigh Page and Sara Pettersson and Barbara Riegel and Anna Strömberg and Ercole Vellone and Heleen Westland},
journal = {BMC Nursing},
year = {2026},
month = oct,
doi = {10.1186/s12912-026-05571-2},
url = {https://doi.org/10.1186/s12912-026-05571-2},
note = {CC BY},
}
RIS
TY - JOUR
TI - Developing a digital heart failure symptom management intervention using the preparation phase of the Multiphase Optimization StraTegy
AU - Michelle van Rijn
AU - Tiny Jaarsma
AU - Gerhard Andersson
AU - Subhash Aryal
AU - Kenneth Freedland
AU - Christopher Lee
AU - Shayleigh Page
AU - Sara Pettersson
AU - Barbara Riegel
AU - Anna Strömberg
AU - Ercole Vellone
AU - Heleen Westland
PY - 2026
DA - 2026/10/25
JO - BMC Nursing
DO - 10.1186/s12912-026-05571-2
UR - https://doi.org/10.1186/s12912-026-05571-2
AB - 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.
SN - 1472-6955
ER -