A multiplicative effect of Education and Wealth associated with HIV-related knowledge and attitudes among Ghanaian women
Notice bibliographique
Résumé
BACKGROUND: Knowledge and attitudes regarding HIV play a crucial role in prevention and control efforts. Understanding the factors influencing HIV-related knowledge and attitudes is essential for formulating effective interventions and policies. This study aims to investigate the possibility of an interaction between education and wealth in influencing HIV-related knowledge and attitudes among women in Ghana. METHODS: Cross-sectional data from the Ghana Multiple Indicator Cluster Survey (MICS), a nationally representative sample, were analyzed. Statistical summaries were computed using place of residence, marital status, education level, wealth index quintile, use of insurance, functional difficulties, and exposure to modern media. Furthermore, a three-model Logistic regression analysis was conducted; Model 1 with main effects only, Model 2 with the interaction between education and wealth, and Model 3 with additional covariates. To account for the complexity of the survey data, the svyset command was executed in STATA. RESULTS: Although most interaction terms between wealth index quintiles and education levels did not show statistical significance, a few exceptions were observed. Notably, women with primary education in the second, middle, and fourth wealth quintiles, along with those with secondary education in the second wealth quintile, exhibited a negative significant association with HIV-related attitude level. However, no significant associations were found between other factors, including age, place of residence, marital status, and health insurance, and HIV-related attitude. The study also found significant associations between socioeconomic variables and HIV-related knowledge. There was a significant positive association between higher levels of education and HIV-related knowledge level. Women in wealthier quintiles had a significant positive association with HIV-related knowledge level. Factors such as place of residence and media exposure, including radio and television were also observed to be associated with HIV-related knowledge level. CONCLUSIONS: This study highlights the importance of socioeconomic status and media exposure in shaping HIV-related knowledge and attitudes among women in Ghana. Policy interventions should focus on reducing socioeconomic disparities, ensuring equitable access to education and healthcare services, and utilizing media platforms for effective HIV information dissemination.
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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 | 0,006 | 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 | 0,000 |
| 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 ».