Digital heart failure symptom intervention judged feasible in MOST preparation phase

Researchers have completed the preparation phase of a digital intervention designed to help people with heart failure recognize their symptoms and respond to them earlier, reporting in BMC Nursing that the tool was perceived as feasible and acceptable by both patients and heart failure nurses. The work is part of the SympTom mAnagement and self-caRe study, known as STAR, which is using the Multiphase Optimization StraTegy, or MOST, to build and refine the intervention across three phases: preparation, optimization, and evaluation. The newly published paper describes only the first of those phases, laying the groundwork for a subsequent optimization trial rather than demonstrating treatment effects.

The rationale for the intervention rests on a persistent clinical problem. People living with heart failure frequently experience bothersome symptoms in daily life, which can negatively affect their health-related quality of life. Self-care, meaning the monitoring and management of those symptoms, is considered essential in heart failure management and can stabilize the disease, reduce symptoms, and improve outcomes. In practice, however, patients often find it difficult to recognize and manage their symptoms, and many delay acting until symptoms become too severe to manage by themselves. The STAR team argues that timely engagement in symptom monitoring and interpretation is therefore needed to enable early and appropriate responses, and that a structured digital support system could supply that engagement.

The preparation phase followed four sequential activities drawn from the MOST framework. The researchers first developed a conceptual model linking candidate intervention components to the mechanisms and outcomes they are expected to influence. They then identified the candidate components themselves, specified an optimization criterion to guide later decisions about which components to retain, and finally conducted a feasibility study of the digital STAR intervention with patients and heart failure nurses. This staged approach is characteristic of MOST, which treats intervention development as an engineering-like process in which components are specified and refined before the full package is evaluated.

The resulting conceptual model contains four candidate components: a basic component, symptom awareness training, symptom management counselling, and symptom management experiments. According to the researchers, these components are expected to influence behavioral outcomes such as reduced symptom burden and hospitalizations, alongside improved self-care and health-related quality of life. Importantly, the set of candidate components was specified at two levels, low versus high, by varying their intensity, frequency, or mode of delivery while keeping the core content consistent. That design choice sets up the optimization phase, in which the team can compare component levels empirically rather than assuming in advance which configuration works best.

The feasibility study involved ten patients with heart failure and five heart failure nurses who tested the digital STAR intervention. From both perspectives, the intervention was perceived as feasible. Patients rated it as clear, user-friendly, and structured. Participants also valued the personal support provided by heart failure nurses and perceived that support as important for continued use of the intervention, a finding the researchers say offers concrete input for refining the intervention before the optimization trial begins.

The authors are careful about what these results do and do not establish. Feasibility and acceptability are necessary conditions for moving forward, but they are not evidence of efficacy; whether the STAR intervention actually reduces symptom burden or hospitalizations remains a question for the later phases of the MOST framework. What the preparation phase does provide, the team writes, is a solid foundation for optimization: a conceptual model that ties each candidate component to underlying mechanisms and outcomes, a defined optimization criterion, and feasibility data confirming that patients and nurses can and will engage with the digital tool. The next step for the STAR team is the optimization trial itself, in which the component levels specified during preparation will be put to empirical test.

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

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

Article References: van Rijn, M., Jaarsma, T., Andersson, G., Aryal, S., Freedland, K., Lee, C., Page, S., Pettersson, S., Riegel, B., Strömberg, A., Vellone, E., & Westland, H. (2026). Developing a digital heart failure symptom management intervention using the preparation phase of the Multiphase Optimization StraTegy. BMC Nursing, 25(1), Article 1012. https://doi.org/10.1186/s12912-026-05571-2

Image Credits: AI Generated

DOI: 10.1186/s12912-026-05571-2

Keywords: Developing, digital, heart, failure, symptom, management, intervention, preparation, phase, Multiphase, Optimization, StraTegy