Utilize este identificador para referenciar este registo: https://hdl.handle.net/1822/86974

TítuloOlder people living alone: a predictive model of fall risk
Autor(es)Lage, Isabel
Braga, Fátima
Almendra, Manuela
Meneses, Filipe
Teixeira, Laetitia
Araújo, Odete
Palavras-chaveOlder people
Living alone
Falls prediction
Risk of falling
Nursing
Data3-Jul-2023
EditoraMultidisciplinary Digital Publishing Institute (MDPI)
RevistaInternational Journal of Environmental Research and Public Health
CitaçãoLage, I.; Braga, F.; Almendra, M.; Meneses, F.; Teixeira, L.; Araújo, O. Older People Living Alone: A Predictive Model of Fall Risk. Int. J. Environ. Res. Public Health 2023, 20, 6284. https://doi.org/10.3390/ijerph20136284
Resumo(s)Falls in older people are a result of a combination of multiple risk factors. There are few studies involving predictive models in a community context. The aim of this study was to determine the validation of a new model for predicting fall risk in older adults (65+) living alone in community dwellings (n = 186; n = 117) with a test–retest reliability study. We consider in the predictive model the significant factors emerged from the bivariate analysis: age, zone, social community resources, physical exercise, self-perception of health, difficulty to keep standing, difficulty to sit and get up from a chair, strain to see, use of technical devices, hypertension and number of medications. The final model explained 28.5% of the risk of falling in older adults living alone in community dwellings. The AUC = 0.660 (se = 0.065, IC 95% 0.533–0.787, p = 0.017). The predictive model developed revealed a satisfactory discriminatory performance of the model and can contribute to clinical practice, with respect to the evaluation of risk of falling in this frailty group and preventing falls.
TipoArtigo
URIhttps://hdl.handle.net/1822/86974
DOI10.3390/ijerph20136284
ISSN1661-7827
e-ISSN1660-4601
Versão da editorahttps://www.mdpi.com/1660-4601/20/13/6284
Arbitragem científicayes
AcessoAcesso aberto
Aparece nas coleções:BUM - MDPI

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Este trabalho está licenciado sob uma Licença Creative Commons Creative Commons

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