Healthcare utilization among informal caregivers of older adults in the Ashanti region of Ghana: a study based on the health belief model
Notice bibliographique
Résumé
BACKGROUND: Existing global evidence suggests that informal caregivers prioritize the health (care) of their care recipients (older adults) over their own health (care) resulting in sub-optimal health outcomes among this population group. However, data on what factors are associated with healthcare utilization among informal caregivers of older adults are not known in a sub-Saharan African context. Guided by the Health Belief Model (HBM), the principal objective of this study was to examine the association between the dimensions of the HBM and healthcare utilization among informal caregivers of older adults in the Ashanti Region of Ghana. METHODS: Data were extracted from a large cross-sectional study of informal caregiving, health, and healthcare survey among caregivers of older adults aged 50 years or above (N = 1,853; mean age of caregivers = 39.15 years; and mean age of care recipients = 75.08 years) in the Ashanti Region of Ghana. Poisson regression models were used to estimate the association between the dimensions of the HBM and healthcare utilization among informal caregivers of older adults. Statistical significance of the test was set at a probability level of 0.05 or less. RESULTS: The results showed that 72.9% (n = 1351) of the participants were females, 56.7% (n = 1051) were urban informal caregivers and 28.6% (n = 530) had no formal education. The results further showed that 49.4% (n = 916) of the participants utilized healthcare for their health problems at least once in the past year before the survey. The final analysis showed a positive and statistically significant association between perceived susceptibility to a health problem (β = 0.054, IRR = 1.056, 95% CI = [1.041-1.071]), cues to action (β = 0.076, IRR = 1.079, 95% CI = [1.044-1.114]), self-efficacy (β = 0.042, IRR = 1.043, 95% CI = [1.013-1.074]) and healthcare utilization among informal caregivers of older adults. The study further revealed a negative and statistically significant association between perceived severity of a health problem and healthcare utilization (β= - 0.040, IRR = 0.961, 95% CI= [0.947-0.975]) among informal caregivers of older adults. The results again showed that non-enrollment in a health insurance scheme (β= - 0.174, IRR = 0.841, 95% CI= [0.774-0.913]) and being unemployed (β= - 0.088, IRR = 0.916, 95% CI= [0.850-0.986]) were statistically significantly associated with a lower log count of healthcare utilization among informal caregivers of older adults. CONCLUSION: The findings of this study to a large extent support the dimensions of the HBM in explaining healthcare utilization among informal caregivers of older adults in the Ashanti Region of Ghana. Although all the dimensions of the HBM were significantly associated with healthcare utilization in Model 1, perceived barriers to care-seeking and perceived benefits of care-seeking were no longer statistically significant after controlling for demographic, socio-economic and health-related variables in the final model. The findings further suggest that the dimensions of the HBM as well as demographic, socio-economic and health-related factors contribute to unequal healthcare utilization among informal caregivers of older adults in the Ashanti Region of Ghana.
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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 | 0,002 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 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 ».