Towards good health and wellbeing: understanding health conditions and healthcare needs among informal caregivers of older adults in Ghana
Notice bibliographique
Résumé
BACKGROUND: Informal caregivers provide care for a substantial number of older adults in Ghana, underscoring their significant contribution within the health and social care systems. However, policymakers and researchers often prioritise the health and wellbeing of care recipients over those providing the care, which could undermine the health outcomes of informal caregivers. Therefore, research on health conditions and healthcare needs among informal caregivers of older adults remains limited in Ghana. To promote good health, wellbeing and equity, this study explores health conditions and healthcare needs among informal caregivers of older adults in Ghana. METHODS: This study, conducted in 14 communities within the Ashanti Region, Ghana, employed a descriptive phenomenological research design. Forty-five informal caregivers (aged 18 and above) of older adults (aged 50 and over) were recruited using purposive sampling techniques. Data were collected from July 2022 to September 2022 using interviews and analysed following Braun and Clarke's six-phase thematic analysis method. RESULTS: Two main themes were identified: health conditions and healthcare needs. The first theme revealed that the participants' health conditions included chronic non-communicable diseases (NCDs) (e.g., high blood pressure, diabetes, and stroke), infectious and tropical diseases (e.g., malaria and typhoid), waist and bodily pains (e.g., ulcers) and post-surgery complications. The burden of chronic NCDs was linked to factors like overthinking, lack of physical activity, noise from care recipients, and reduced sleep, all due to demanding caregiving duties. Infectious and tropical diseases were associated with caring for infected care recipients and working in poor environmental conditions, including not sleeping under insecticide-treated mosquito nets, which significantly increases their exposure to mosquito bites and contributes to diseases such as malaria. Waist and bodily pains were caused by caregiving tasks, such as lifting heavy items and assisting recipients with bed transfers. Stomach ulcers were linked to food insecurity, as participants often sacrificed their own food for their care recipients. The second theme revealed that the participants' healthcare needs encompassed medical treatment/regular healthcare, financial assistance, and medication needs. CONCLUSION: This study argues that meeting the healthcare needs of informal caregivers of older adults could greatly enhance their health-related quality of life. To improve the health conditions of informal caregivers, health stakeholders should enhance routine health promotion and disease prevention initiatives that emphasise adopting a healthy lifestyle (e.g., regular physical activity and adequate sleep), maintaining a healthy environment, and regular use of formal healthcare services. The government should also provide financial support to informal caregivers of older adults from low-income backgrounds by enrolling them in the Livelihood Empowerment Against Poverty programme. This support would enhance their financial ability to access necessary healthcare services and treatment, including medication, thereby addressing their healthcare needs.
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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 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,003 | 0,002 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,000 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».