Motivational Interviewing for Enhancing Self-care in Patients With Heart Failure: Protocol for a Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Heart failure (HF) is characterized by an increasing prevalence, representing a public health problem and a significant cause of morbidity and mortality. Self-care is a cornerstone approach for optimizing therapy for patients with HF. Patients play a crucial role in managing their condition, given that several adverse health outcomes might be avoided with adequate self-care. In this regard, the literature describes motivational interviewing (MI) as highly favorable for treating chronic diseases, with promising results supporting its efficacy in enhancing self-care. Moreover, caregivers' availability constitutes a fundamental supporting factor among the strategies to improve self-care behaviors in people with HF. OBJECTIVE: The primary study aim is to test the efficacy of a structured program, including scheduled MI interventions, in improving self-care maintenance in the 3-month follow-up from the enrollment. Secondary aims comprehend the assessment of the effectiveness of the above intervention on secondary outcomes (eg, self-care monitoring, quality of life, sleep disturbance) and the corroboration of the superiority of caregivers' participation to the intervention over the program administrated only to individual patients in enhancing self-care behaviors and other outcomes at 3, 6, 9, and 12 months from the enrollment. METHODS: This study protocol designed a prospective, parallel-arm, open-label, 3-arm, controlled trial. The MI intervention will be administered by nurses trained in HF self-care and MI; the education program will be provided to nurses by an expert psychologist. Analyses will be performed within the framework of intention-to-treat analysis. Comparisons between groups will be based on an alpha of 5% and 2-tailed null hypotheses. In the case of missingness, analyzing the extent of the missingness and identifying underlying mechanisms and patterns will guide imputation methods. RESULTS: The data collection was started in May 2017. We completed the data collection with the last follow-up in May 2021. We plan to perform data analysis by December 2022. We plan to publish the study results within March 2023. CONCLUSIONS: MI enhances potential self-care practices in patients with HF and their caregivers. Although MI is effectively largely employed either alone or combined with other treatments and is administered in different settings and ways, face-to-face interventions seem to be more effective. Dyads with higher shared HF knowledge are more efficient in promoting self-care adherence behaviors. Moreover, patients and caregivers may perceive proximity with health care professionals, resulting in a better ability to follow the received health professionals' directions. The scheduled in-person meetings with patients and caregivers will be exploited to administer MI, respecting all the safety regulations for infection containment. The conduction of this study may support changes in clinical practice to include MI to improve self-care for patients with HF. TRIAL REGISTRATION: ClinicalTrials.gov NCT05595655; https://clinicaltrials.gov/ct2/show/NCT05595655. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/44629.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.033 | 0.027 |
| Meta-epidemiology (narrow) | 0.006 | 0.003 |
| Meta-epidemiology (broad) | 0.014 | 0.006 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.070 | 0.010 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".