Junyan Tian, Jacqueline Mogle, Kaarin J Anstey, Lesley A Ross
{"title":"老年人驾驶安全多因素模型的评价与修正。","authors":"Junyan Tian, Jacqueline Mogle, Kaarin J Anstey, Lesley A Ross","doi":"10.1093/geroni/igae113","DOIUrl":null,"url":null,"abstract":"<p><strong>Background and objectives: </strong>Cognitive, visual, and physical performance are associated with driving safety. However, there are few comprehensive models that empirically evaluate how such factors together affect driving safety in older adults. The present study used structural equation modeling (SEM) to evaluate Anstey's original Multifactorial Model of Driving Safety (MMDS) (2005) as well as a modified MMDS that incorporates recent research.</p><p><strong>Research design and methods: </strong>We used the baseline data from the Advanced Cognitive Training for Independent and Vital Elderly study. Participants (<i>n</i> = 2,391) were drivers with a reported mean age of 73.28 (<i>SD</i> = 5.70; range 65-91), 75.7% White, and 73.3% women.</p><p><strong>Results: </strong>Using SEM, Anstey's original MMDS did not achieve adequate fit (CFI = 0.850, TLI = 0.777, RMSEA = 0.074). However, the modified MMDS had a good fit (CFI = 0.961, TLI = 0.934, RMSEA = 0.040). We found that better physical function was correlated with less driving avoidance (β = 0.28, <i>p</i> < .01) and a lower crash risk (β = -0.14, <i>p</i> < .01). Better cognitive abilities were associated with less driving avoidance (β = 0.08, <i>p</i> <.01) and better self-reported driving quality (β = 0.19, <i>p</i> < .01). Driving avoidance partially mediated the relationship between physical function and crash.</p><p><strong>Discussion and implications: </strong>This study highlights the importance of cognition and physical function in older adults safe driving. Implications for future directions and public policy considerations are discussed. Future research should examine possible dynamic changes between these predictors and driving in a longitudinal model.</p>","PeriodicalId":13596,"journal":{"name":"Innovation in Aging","volume":"9 2","pages":"igae113"},"PeriodicalIF":4.9000,"publicationDate":"2025-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11831225/pdf/","citationCount":"0","resultStr":"{\"title\":\"Evaluation and Modification of the Multifactorial Model of Driving Safety Among Older Adults.\",\"authors\":\"Junyan Tian, Jacqueline Mogle, Kaarin J Anstey, Lesley A Ross\",\"doi\":\"10.1093/geroni/igae113\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background and objectives: </strong>Cognitive, visual, and physical performance are associated with driving safety. However, there are few comprehensive models that empirically evaluate how such factors together affect driving safety in older adults. The present study used structural equation modeling (SEM) to evaluate Anstey's original Multifactorial Model of Driving Safety (MMDS) (2005) as well as a modified MMDS that incorporates recent research.</p><p><strong>Research design and methods: </strong>We used the baseline data from the Advanced Cognitive Training for Independent and Vital Elderly study. Participants (<i>n</i> = 2,391) were drivers with a reported mean age of 73.28 (<i>SD</i> = 5.70; range 65-91), 75.7% White, and 73.3% women.</p><p><strong>Results: </strong>Using SEM, Anstey's original MMDS did not achieve adequate fit (CFI = 0.850, TLI = 0.777, RMSEA = 0.074). However, the modified MMDS had a good fit (CFI = 0.961, TLI = 0.934, RMSEA = 0.040). We found that better physical function was correlated with less driving avoidance (β = 0.28, <i>p</i> < .01) and a lower crash risk (β = -0.14, <i>p</i> < .01). Better cognitive abilities were associated with less driving avoidance (β = 0.08, <i>p</i> <.01) and better self-reported driving quality (β = 0.19, <i>p</i> < .01). Driving avoidance partially mediated the relationship between physical function and crash.</p><p><strong>Discussion and implications: </strong>This study highlights the importance of cognition and physical function in older adults safe driving. Implications for future directions and public policy considerations are discussed. Future research should examine possible dynamic changes between these predictors and driving in a longitudinal model.</p>\",\"PeriodicalId\":13596,\"journal\":{\"name\":\"Innovation in Aging\",\"volume\":\"9 2\",\"pages\":\"igae113\"},\"PeriodicalIF\":4.9000,\"publicationDate\":\"2025-01-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11831225/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Innovation in Aging\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1093/geroni/igae113\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q1\",\"JCRName\":\"GERIATRICS & GERONTOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Innovation in Aging","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1093/geroni/igae113","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q1","JCRName":"GERIATRICS & GERONTOLOGY","Score":null,"Total":0}
Evaluation and Modification of the Multifactorial Model of Driving Safety Among Older Adults.
Background and objectives: Cognitive, visual, and physical performance are associated with driving safety. However, there are few comprehensive models that empirically evaluate how such factors together affect driving safety in older adults. The present study used structural equation modeling (SEM) to evaluate Anstey's original Multifactorial Model of Driving Safety (MMDS) (2005) as well as a modified MMDS that incorporates recent research.
Research design and methods: We used the baseline data from the Advanced Cognitive Training for Independent and Vital Elderly study. Participants (n = 2,391) were drivers with a reported mean age of 73.28 (SD = 5.70; range 65-91), 75.7% White, and 73.3% women.
Results: Using SEM, Anstey's original MMDS did not achieve adequate fit (CFI = 0.850, TLI = 0.777, RMSEA = 0.074). However, the modified MMDS had a good fit (CFI = 0.961, TLI = 0.934, RMSEA = 0.040). We found that better physical function was correlated with less driving avoidance (β = 0.28, p < .01) and a lower crash risk (β = -0.14, p < .01). Better cognitive abilities were associated with less driving avoidance (β = 0.08, p <.01) and better self-reported driving quality (β = 0.19, p < .01). Driving avoidance partially mediated the relationship between physical function and crash.
Discussion and implications: This study highlights the importance of cognition and physical function in older adults safe driving. Implications for future directions and public policy considerations are discussed. Future research should examine possible dynamic changes between these predictors and driving in a longitudinal model.
期刊介绍：
Innovation in Aging, an interdisciplinary Open Access journal of the Gerontological Society of America (GSA), is dedicated to publishing innovative, conceptually robust, and methodologically rigorous research focused on aging and the life course. The journal aims to present studies with the potential to significantly enhance the health, functionality, and overall well-being of older adults by translating scientific insights into practical applications. Research published in the journal spans a variety of settings, including community, clinical, and laboratory contexts, with a clear emphasis on issues that are directly pertinent to aging and the dynamics of life over time. The content of the journal mirrors the diverse research interests of GSA members and encompasses a range of study types. These include the validation of new conceptual or theoretical models, assessments of factors impacting the health and well-being of older adults, evaluations of interventions and policies, the implementation of groundbreaking research methodologies, interdisciplinary research that adapts concepts and methods from other fields to aging studies, and the use of modeling and simulations to understand factors and processes influencing aging outcomes. The journal welcomes contributions from scholars across various disciplines, such as technology, engineering, architecture, economics, business, law, political science, public policy, education, public health, social and psychological sciences, biomedical and health sciences, and the humanities and arts, reflecting a holistic approach to advancing knowledge in gerontology.
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