Vance David E, Roenker Daniel L, Cissell Gayla M, Edwards Jerri D, Wadley Virginia G, Ball Karlene K
Department of Psychology, Center for Translational Research on Aging and Mobility, University of Alabama at Birmingham, 35294-2100, USA.
Accid Anal Prev. 2006 Jul;38(4):823-31. doi: 10.1016/j.aap.2006.02.008. Epub 2006 Mar 20.
Using structural equation modeling techniques, this study examines causal models of driving avoidance and exposure among older adults. Prior studies have revealed that past incidence of falls, Useful Field of View (UFOV) test performance, and Trails Making test performance are predictive of subsequent motor vehicle crash involvement [Owsley, C., Ball, K., McGwin Jr., G., Sloane, M.E., Roenker, D.L., White, M.F., Overley, E.T., 1998. Visual processing impairment and risk of motor vehicle crash among older adults. J. Am. Med. Assoc. 279 (14), 1083-1088; Sims, R.V., McGwin, G., Pulley, L., Roseman, J.M., 2001. Mobility impairments in crash-involved older drivers. J. Aging Health 13 (3), 430-438; Stutts, J.C., 1998. Do older drivers with visual nd cognitive impairments drive less? J. Am. Geriatr. Soc. 46, 854-861]. Data analyses used these indices, along with age, health, measures of physical functioning, and additional measures of cognitive functioning, to examine driving exposure and avoidance behaviors. A field sample of 4,234 drivers, 55 years of age and older, were recruited from the Maryland Motor Vehicles Administration after renewing their driver's licenses. A performance-based assessment, which included the Gross Impairment Screening battery and task 2 of the UFOV test, was completed by participants. A sub-sample of participants (n=815) were interviewed by telephone about their health and mobility 3-6 months following the initial assessment at a renewal center. In addition to age and gender, latent variables for health status, physical functioning, cognitive functioning, driving exposure, and driving avoidance were created. Direct and indirect causal paths were specified. Age, gender, health status, and cognitive functioning had direct effects on both driving exposure and driving avoidance; physical functioning did not have a direct effect on driving exposure or avoidance. The implications of these findings are discussed as they relate to designing interventions to promote mobility.
本研究运用结构方程建模技术，检验了老年人驾驶回避与驾驶暴露的因果模型。先前的研究表明，过去的跌倒发生率、有用视野（UFOV）测试表现以及连线测验表现可预测随后是否会卷入机动车碰撞事故[奥兹利，C.，鲍尔，K.，小麦克格温，G.，斯隆，M.E.，罗恩克，D.L.，怀特，M.F.，奥弗利，E.T.，1998年。老年人视觉处理障碍与机动车碰撞风险。《美国医学会杂志》279（14），1083 - 1088；西姆斯，R.V.，麦克格温，G.，普利，L.，罗斯曼，J.M.，2001年。卷入碰撞事故的老年驾驶员的行动能力障碍。《老龄健康杂志》13（3），430 - 438；斯塔茨，J.C.，1998年。有视觉和认知障碍的老年驾驶员开车更少吗？《美国老年医学会杂志》46，854 - 861]。数据分析使用了这些指标，以及年龄、健康状况、身体功能测量指标和认知功能的其他测量指标，以检验驾驶暴露和回避行为。从马里兰州机动车管理局更新驾照后的4234名55岁及以上的驾驶员中选取了一个实地样本。参与者完成了一项基于表现的评估，其中包括总体损伤筛查组套和UFOV测试的任务2。在更新中心进行初次评估后的3 - 6个月，通过电话对一部分参与者子样本（n = 815）进行了关于他们健康和行动能力的访谈。除了年龄和性别外，还创建了健康状况、身体功能、认知功能、驾驶暴露和驾驶回避的潜在变量。明确了直接和间接的因果路径。年龄、性别、健康状况和认知功能对驾驶暴露和驾驶回避都有直接影响；身体功能对驾驶暴露或回避没有直接影响。讨论了这些发现与设计促进行动能力的干预措施的相关性。
