Motivational Interviewing for Enhancing Self-care in Patients With Heart Failure: Protocol for a Randomized Controlled Trial
Notice bibliographique
Résumé
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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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,033 | 0,027 |
| Méta-épidémiologie (sens strict) | 0,006 | 0,003 |
| Méta-épidémiologie (sens large) | 0,014 | 0,006 |
| Bibliométrie | 0,003 | 0,004 |
| Études des sciences et des technologies | 0,004 | 0,004 |
| Communication savante | 0,005 | 0,003 |
| Science ouverte | 0,004 | 0,002 |
| Intégrité de la recherche | 0,007 | 0,009 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,070 | 0,010 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».