Background and Rationale:
Heart failure is a chronic, progressive, and life-limiting syndrome characterized by frequent hospitalizations, reduced quality of life, and high mortality. Despite advances in pharmacological and device-based treatments, effective disease management continues to rely heavily on the patient's and caregiver's ability to perform adequate self-care behaviors. These include medication adherence, symptom monitoring, dietary control, physical activity, and timely medical contact in case of deterioration.
Numerous studies demonstrate that self-care in HF remains suboptimal. Poor adherence is often related to low health literacy, cognitive decline, depression, or limited support from family and healthcare providers. Informal caregivers play a central role in assisting patients, yet they experience significant burden, anxiety, and uncertainty regarding effective disease management. Interventions aimed at improving both patient and caregiver engagement are critical for better health outcomes.
Motivational interviewing is a structured, patient-centered counseling technique designed to enhance intrinsic motivation for behavior change by exploring ambivalence and strengthening commitment. MI has been successfully applied in chronic disease management and has shown promise in improving self-care and adherence in cardiovascular populations. Remote delivery of MI using telecommunication tools can increase accessibility, continuity, and cost-effectiveness of support for patients with heart failure.
The REMIND HF study has been developed to evaluate the efficacy of remote nurse-delivered motivational interviewing in improving self-care behaviors among patients with heart failure and their informal caregivers. The project is conducted at the Wroclaw Medical University (Poland) and funded by the National Science Centre (NCN, OPUS 27 grant).
Objectives and Hypotheses:
The primary objective is to determine whether remote motivational interviewing enhances self-care behaviors in patients with chronic heart failure compared with standard care.
Secondary objectives are to examine the effects of the intervention on:
* Quality of life in patients and caregivers.
* Anxiety and depression in patients and caregivers.
* Caregiver contribution to patient self-care and perceived burden.
* Healthcare utilization (hospitalizations and emergency visits).
* Cost-effectiveness of the intervention.
Hypothesis: Participants receiving the remote MI intervention will demonstrate improved self-care (based on Self-Care of Heart Failure Index - SCHFI), greater caregiver contribution (based on Caregiver Contribution to Self-Care of Heart Failure Index - CCSCHFI), and better quality of life than those receiving standard care.
Study Design:
The REMIND HF study is a randomized, controlled, two-arm interventional trial using a parallel assignment model. Participants will be allocated in a 1:1 ratio to either the intervention (remote MI) or control (standard care) group.
Study Type: Interventional (Behavioral)
Allocation: Randomized
Intervention Model: Parallel Assignment
Masking: None (Open Label)
Primary Purpose: Supportive / Behavioral Intervention
Sample Size: 600 participants (300 HF patients and 300 caregivers)
Duration: 12 months per dyad (baseline, 3-month, 6-month, 9- month and 12-months after the end of the study)
Recruitment will take place at the Clinical University Hospital in Wroclaw. The study is coordinated by the Department of Clinical Nursing at the Wroclaw Medical University in collaboration with the University of Rome Tor Vergata.
Intervention Description:
Intervention Arm (Remote Motivational Interviewing):
Participants receive a structured program of seven remote motivational interviewing sessions delivered by trained nurses over 12 months using a secure video platform. Each session lasts 45-60 minutes and follows a standardized manual. Core session topics include:
Baseline assessment and motivation building.
Goal setting and overcoming ambivalence.
Medication adherence and symptom monitoring.
Diet and physical activity optimization.
Stress management and coping strategies.
Strengthening communication within the patient-caregiver dyad.
Maintenance of behavior change and self-efficacy.
Control Arm (Standard Care):
Participants receive routine medical care and standard HF education consistent with European Society of Cardiology (ESC) guidelines, without motivational interviewing.
Data Collection and Instruments:
Data are collected at baseline, 3 months, 6 months, 9 months and 12 months after the end of the study .
* Self-Care of Heart Failure Index (SCHFI) - primary outcome, assessing self-care maintenance, management, and confidence.
* Caregiver Contribution to Self-Care of Heart Failure Index (CCSCHFI) - assessment of caregiver engagement and support in patient self-care.
* Kansas City Cardiomyopathy Questionnaire (KCCQ) and Short Form 12 (SF-12) - patient and caregiver quality of life.
* Hospital Anxiety and Depression Scale (HADS) - emotional well-being of patients and caregivers.
* Clinical data - NYHA class, comorbidities, hospital admissions, and mortality.
All data are entered into a secure electronic case report form (eCRF) hosted on password-protected university servers. Data integrity and completeness are verified via built-in validation checks.
Quality Assurance and Data Management:
A detailed quality assurance (QA) plan governs all study operations. It includes:
Validation checks within the eCRF to ensure internal data consistency.
Cross-verification of clinical and self-reported data at each follow-up.
Periodic on-site audits by the study coordinator to verify consent forms and data accuracy.
Maintenance of a data dictionary describing each variable, coding scheme, and reference range.
Standard Operating Procedures (SOPs) covering recruitment, data entry, data monitoring, and corrective actions.
Annual data review by an independent statistician to confirm representativeness and data quality.
Source Data Verification:
Data will be periodically compared with hospital medical records and participant source documents to ensure completeness and accuracy.
Missing Data Management:
Missing or inconsistent data will be tracked automatically in the database. For analyses, multiple imputation will be used when appropriate.
Statistical Analysis Plan:
Statistical analysis will be carried out with the use of R, Python, and their packages. Inference will be frequentist, based on α = 0.05. Depending on the distribution and scale of the variables (assessed using graphical methods and tests of normality), descriptive statistics will include means with standard deviations or medians with interquartile ranges. Group comparisons will be performed using standard parametric or non-parametric tests, as appropriate, and ANOVA (with post-hoc procedures) for multi-group comparisons. Primary analyses will use mixed-effects models for repeated measures with fixed effects for treatment group, time, and their interaction, adjusting for key covariates. Random effects will account for within-participant correlation; additional clustering (e.g., by interventionist or within patient-caregiver dyads) will be accommodated if present. Time will be modelled as a categorical or continuous variable depending on the distribution of the data and the clinical relevance of the chosen parametrization. Although beta distribution fits these scores based on the presence of floor and ceiling scores (0 and 100%), the choice of distribution will be assessed using information criteria (Akaike Information Criterion- AIC/ Bayesian Information Criterion - BIC), residual diagnostics, and graphical inspection. Upon presence of zeroes in scoring, the use of zero-inflated GLMMs will be considered. Interaction analysis will be carried out so as to further explore the data. If multiple multivariate models are developed, they will be compared in terms of their goodness of fit. Model selection strategies (e.g., penalization or stepwise procedures) will be considered for exploratory multivariate analyses. All necessary statistical assumptions will be thoroughly tested, with appropriate statistical tests. All analyses will be conducted under the intention-to-treat principle, and secondary analyses will be considered exploratory without adjustment for multiplicity unless otherwise specified.
If a minimal clinically important difference (MCID) for the primary/secondary questionnaire scores can be defined based on existing literature, a secondary logistic regression analysis will be performed to model the probability of exceeding this threshold. Model performance will be evaluated with sensitivity, specificity, Brier score (via 10-fold cross-validation), and clinical utility will be assessed using decision curve analysis (DCA).
Ethical and Regulatory Oversight:
The protocol has been submitted to the Bioethics Committee of Wroclaw Medical University for review. Written informed consent will be obtained from all participants (patients and caregivers).
The study involves minimal risk because it is a non-invasive behavioral intervention. No drugs or devices are tested.
Data protection and confidentiality will comply with General Data Protection Regulation (GDPR) and institutional standards. Participant data will be pseudonymized, and access will be restricted to authorized personnel.
Because the study is low risk, a formal Data Safety Monitoring Board (DSMB) will not be appointed; instead, monitoring will be performed by the study steering committee under the principal investigator's supervision.
Sample Size Assessment:
Based on previous MI studies, a sample of 240 patients per group provides 80% power (α = 0.05) to detect a 10-point difference in SCHFI total score (SD = 25). Allowing for 20% attrition, 300 dyads (600 total participants) will be enrolled.
Timeline:
Study Start: February 2026 (anticipated)
Primary Completion: December 2027 (anticipated)
Study Completion: June 2028 (anticipated)
Expected Results and Significance:
The REMIND HF study is expected to demonstrate that remote motivational interviewing significantly improves self-care behaviors in HF patients and enhances caregiver contribution to disease management. Improved self-care is anticipated to reduce hospitalization rates, improve health-related quality of life, and lower healthcare costs.
Findings from this study will provide evidence supporting the integration of behavioral and telehealth interventions into standard HF management and will contribute to international research on patient-caregiver collaboration in chronic disease care
