Examining the Effect of Polypharmacy on Quality of Life and Frailty in Older Adults from the Perspective of Community-Based Rehabilitation
Notice bibliographique
Résumé
Objective: Although the negative effects of polypharmacy on older adults are well-documented, studies exploring its relationship with frailty and quality of life within the framework of community-based rehabilitation (CBR) remain scarce. In this context, the aim of this study was to compare frailty and quality of life levels between older adults with and without polypharmacy and to examine the relationship between these parameters from a CBR perspective. The ultimate purpose of this study was to determine the usefulness of CBR. Method: A total of 120 community-dwelling older adults (60 with polypharmacy, 60 without polypharmacy), aged 65–75 years (mean age = 68.18 ± 3.50), were included in a community-based assessment carried out under the coordination of Lokman Hekim University in Ankara, Turkey. The use of five to nine medications was taken as a reference for those with polypharmacy, and the use of less than two medications was taken as a reference for those without polypharmacy. The quality of life of the older adults in the study was assessed with the Nottingham Health Profile (NHP), and frailty was assessed with the Edmonton Frailty Scale (EFS). In line with CBR principles, the findings were interpreted with a focus on promoting community-wide strategies to support older adults. Results: The study found a statistically significant difference in NHP and EFS results between older adults with and without polypharmacy (p < 0.05). In addition, a statistically significant relationship was found between NHP and all subdomains of NHP and EFS (p < 0.05). Conclusion: Older adults with polypharmacy had higher levels of frailty and lower quality of life, and an increase in frailty was significantly associated with a decrease in quality of life in both groups. These findings highlight the importance of community-level preventive interventions to support healthy aging. Within the framework of CBR, strategies such as creating accessible physical activity areas at the neighborhood level; organizing informative seminars on frailty, quality of life, medication use and health literacy in collaboration with volunteer health professionals and local authorities; and creating volunteer support networks to increase social interaction can contribute to the control of these symptoms in older adults.
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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 | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| 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 | 0,000 |
| 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 ».