Health and eHealth Literacy of Patients With Diabetes in Low-Income Countries: Perspective From Guinea and Burkina Faso
Notice bibliographique
Résumé
Background: Diabetes is a significant health concern in sub-Saharan Africa, emphasizing the importance of assessing the health literacy and eHealth skills of hospitalized patients with diabetes. This study evaluated the health literacy and eHealth literacy of patients with diabetes at Donka Hospital in Guinea and Sanou Sourou Hospital in Burkina Faso, providing insights for targeted interventions and mobile health (mHealth) solutions to improve self-management and treatment outcomes. Objective: The aim of this study is to evaluate the levels of health literacy and eHealth literacy among patients at Sanou Sourou Hospital in Burkina Faso and Donka Hospital in Guinea. Methods: The study included 45 participants from Donka Hospital and 47 from Sanou Sourou Hospital. Data collection took place in May 2022, focusing on variables such as gender, age, education, income, and technology access. Health literacy and eHealth literacy were measured using the Brief Health Literacy Screen (BHLS) and the eHealth Literacy Scale (eHEALS), respectively. Statistical analysis was performed using SPSS 28. Results: The results indicated that 64% (64/99) of participants at Donka Hospital and 57% (57/99) at Sanou Sourou Hospital were female. The majority of participants (48/98, 49% in both hospitals) fell within the age range of 25-50 years. High rates of illiteracy were observed (62/100, 62% in Donka Hospital and 59/100, 59% in Sanou Sourou Hospital). Smartphone ownership was prevalent (62/99, 62% at Donka Hospital and 64/100, 64% at Sanou Sourou Hospital). Participants reported occasional use of technology for basic purposes and frequent internet usage for accessing health information. However, a significant proportion of participants demonstrated low health literacy (73/99, 73% at Donka Hospital; 79/101, 78% at Sanou Sourou Hospital) and inadequate eHealth literacy (57/100, 57% at Donka Hospital; 62/100, 62% at Sanou Sourou Hospital). Education was observed to positively correlate with health literacy, while age displayed a moderate negative correlation. Weak correlations were observed between gender, income, and health literacy, but these were not statistically significant. No significant correlation was found between the scores of the BHLS and the eHEALS in either hospital. Conclusions: This study highlights the importance of targeted educational interventions and mHealth solutions aimed at enhancing health and eHealth literacy among hospitalized patients with diabetes. Addressing both health literacy and eHealth literacy is paramount for improving diabetes management and treatment outcomes in Guinea and Burkina Faso. Targeted interventions and mHealth solutions have the potential to empower patients, enabling their active involvement in health care decisions and ultimately improving overall health outcomes.
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 | 0,001 | 0,000 |
| 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 | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| 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 ».