Key factors of the functional ability of older people to self-manage medications

Daily medication use can be affected by the gradual loss of functional ability. Thus, elderly patients are at risk for nonadherence due to functional decline, namely, decreases in cognitive skills and visual and manual dexterity. The main objective was to assess the ability of older people to self-m...

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Bibliographic Details
Published in:Scientific reports Vol. 11; no. 1; p. 22196
Main Authors: Advinha, Ana Margarida, Nunes, Carla, de Barros, Carla Teixeira, Lopes, Manuel José, de Oliveira-Martins, Sofia
Format: Journal Article
Language:English
Published: London Nature Publishing Group UK 12-11-2021
Nature Publishing Group
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Summary:Daily medication use can be affected by the gradual loss of functional ability. Thus, elderly patients are at risk for nonadherence due to functional decline, namely, decreases in cognitive skills and visual and manual dexterity. The main objective was to assess the ability of older people to self-manage their medication and to identify the main predictors for unintentional nonadherence. A cross-sectional study was conducted (2014–2017) in community centers and pharmacies. Functional assessment was performed with the Portuguese versions of the Drug Regimen Unassisted Grading Scale (DRUGS-PT) and the Self-Medication Assessment Tool (SMAT-PT). A purposive sample including 207 elderly patients was obtained. To identify the main predictors, binary logistic regression was performed. The average DRUGS-PT score was slightly lower than that in other studies. On the SMAT-PT, the greatest challenge for patients was identifying medications by reading labels/prescriptions. The main difficulties identified were medication memorization and correct schedule identification. The scores were higher with the real regimen than with the simulated regimen, underlining the difficulties for patients in receiving new information. Regarding the predictors of an older individual’s ability to self-manage medications, two explanatory models were obtained, with very high areas under the curve (> 90%). The main predictors identified were cognitive ability, level of schooling and daily medication consumption.
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ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-021-01434-9