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DOI: 10.1590/0004-282X-ANP-2021-0054
Verbal Learning as a predictor of risks of accidents in elderly drivers
Aprendizado verbal como preditor de risco de acidentes em idosos
ABSTRACT
Background: Age-related cognitive decline impacts cognitive abilities essential for driving. Objective: We aimed to measure main cognitive functions associated with a high number of traffic violations in different driving settings. Methods: Thirty-four elderly individuals, aged between 65 and 90 years, were evaluated with a driving simulator in four different settings (Intersection, Overtaking, Rain, and Malfunction tasks) and underwent a battery of cognitive tests, including memory, attention, visuospatial, and cognitive screening tests. Individuals were divided into two groups: High-risk driving (HR, top 20% of penalty points) and normal-risk driving (NR). Non-parametric group comparison and regression analysis were performed. Results: The HR group showed higher total driving penalty score compared to the NR group (median=29, range= 9-44 vs. median=61, range= 47-97, p<0.001). The HR group showed higher penalty scores in the Intersection task (p<0.001) and the Overtaking and Rain tasks (p<0.05 both). The verbal learning score was significantly lower in the HR group (median=33, range=12-57) compared with the NR group (median=38, range=23-57, p<0.05), and it was observed that this score had the best predictive value for worse driving performance in the regression model. General cognitive screening tests (Mini-Mental State Examination and Addenbrooke's Cognitive Evaluation) were similar between the groups (p>0.05), with a small effect size (Cohen’s d=0.3 both). Conclusion: The verbal learning score may be a better predictor of driving risk than cognitive screening tests. High-risk drivers also showed significantly higher traffic driving penalty scores in the Intersection, Overtaking, and Rain tests.
RESUMO
Antecedentes: O declínio cognitivo relacionado à idade impacta as habilidades cognitivas essenciais para direção.
Objetivos: Nosso objetivo foi medir as funções cognitivas associadas ao alto número de violações de trânsito em diferentes contextos de direção. Métodos: Trinta e quatro idosos entre 65 e 90 anos foram avaliados em simulador de direção em quatro diferentes contextos (Travessia, Ultrapassagem, Chuva e Mal-funcionamento) e realizaram uma série de testes cognitivos, incluindo memória, atenção, visuoespacial e rastreamento. Indivíduos foram então divididos em dois grupos: Alto Risco de condução (HR, top 20% de pontos de penalidades de condução), e Risco Normal (NR). Comparações não-paramétricas e análise de regressão foram realizadas. Resultados: O grupo HR mostrou aumento no escore total de penalidades de condução quando comparado com o grupo NR (mediana=29, limites=9-44 vs. mediana=61, limites=47-97, p<0.001). O grupo HR mostrou maiores escores de penalidade na tarefa de Travessia (p<0.001), Ultrapassagem e Chuva (p<0.05 ambos). O escore de aprendizado verbal foi significativamente menor no grupo HR (mediana=33, limite=12-57) comparado com o grupo NR (mediana=38, limite=23-57, p<0.05), e foi observado que este escore foi o melhor preditor de pior performance de condução no modelo de regressão. Testes de rastreio cognitivo (Mini-exame do estado mental e Avaliação Cognitiva de Addenbroke) foram similar entre os grupos (p>0.05), com pequena magnitude de efeito (Cohen’s d=0.3). Conclusões: O escore de aprendizado verbal pode ser o melhor preditor de risco de condução do que os testes de rastreio cognitivos. Motoristas de alto risco também mostraram maior escores de penalidade de trânsito nos testes de Travessia, Ultrapassagem e Chuva.
Authors’ contributions:
AMV: collected the data, wrote the manuscript and designed this study; WVB: analyzed the results, wrote the manuscript and reviewed its final version; MSP: designed the study, coordinated it and reviewed the final version; MWP: coordinated the study and reviewed its final version.
Publication History
Received: 04 February 2021
Accepted: 18 May 2021
Article published online:
30 January 2023
© 2021. Academia Brasileira de Neurologia. This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commecial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/)
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