Characterizing health literacy in cardiac rehabilitation patients: a decade of multinational data (2014–2024)
Notice bibliographique
Résumé
Background Cardiovascular disease (CVD) is a leading global health issue, with a high prevalence and significant economic impact. Cardiac rehabilitation (CR) can help mitigate this burden through its comprehensive approach, which includes, among other components, patient education. Health literacy, the ability to access and understand health information, is crucial for effective CR and better health outcomes. However, data on health literacy levels among CR patients across different countries is limited.Aims This study aimed to assess health literacy levels among CR patients from multiple countries and examine how these levels relate to various demographic and clinical characteristics. The goal was to provide insights that could help clinicians tailor their CR programs to better meet patient needs.Methods We conducted a cross-sectional analysis using baseline data from CR programs in Brazil, Canada, Colombia, Costa Rica, Peru, Spain, and the Philippines, collected between 2014 and 2024. Health literacy was measured using the Medical Term Recognition Test and the BRIEF Health Literacy Screening Tool. Descriptive statistics, chi-square tests, and logistic regression models were used to analyze the data and explore associations between health literacy and various conditions.Results Data from 1,491 patients revealed that approximately two-thirds had marginal (48.6%) or inadequate (13.5%) health literacy. Younger patients and those with lower educational attainment and income levels had higher rates of limited/marginal health literacy, while older individuals and those with higher educational levels or incomes showed better health literacy. Significant ethnic disparities were observed, with people from Southeast and South Asian exhibiting lower health literacy levels compared to White/European respondents. Marginal and inadequate health literacy were linked to higher rates of obesity and type 2 diabetes.Discussion This study is the first to provide a comprehensive assessment of health literacy among CR patients across multiple countries. The findings highlight the need for CR programs to incorporate broader educational strategies that address varying health literacy levels. The observed ethnic, age, and socioeconomic disparities suggest that CR programs should consider these factors when designing interventions. Future research should focus on longitudinal studies to further explore the relationship between CR participation and health literacy.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,013 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,008 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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 tête enseignante, 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 ».