Institute for Aging Research, Hebrew SeniorLife; Alfred A and Gilda Slifka Chair in Social Gerontological Research, United States.
Northeastern University, Bouve College of Health Sciences, School of Nursing, United States.
Accid Anal Prev. 2014 Feb;63:104-10. doi: 10.1016/j.aap.2013.10.030. Epub 2013 Nov 2.
This project used the interRAI based, community health assessment (CHA) to develop a model for identifying current elder drivers whose driving behavior should be reviewed. The assessments were completed by independent housing sites in COLLAGE, a non-profit, national senior housing consortium. Secondary analysis of data drawn from older adults in COLLAGE sites in the United States was conducted using a baseline assessment with 8042 subjects and an annual follow-up assessment with 3840 subjects. Logistic regression was used to develop a Driving Review Index (DRI) based on the most useful items from among the many measures available in the CHA assessment. Thirteen items were identified by the logistic regression to predict drivers whose driving behavior was questioned by others. In particular, three variables reference compromised decision-making abilities: general daily decisions, a recent decline in ability to make daily decisions, and ability to manage medications. Two additional measures assess cognitive status: short-term memory problem and a diagnosis of non-Alzheimers dementia. Functional measures reflect restrictions and general frailty, including receiving help in transportation, use of a locomotion appliance, having an unsteady gait, fatigue, and not going out on most days. The final three clinical measures reflect compromised vision, little interest or pleasure in things normally enjoyed, and diarrhea. The DRI focuses the review process on drivers with multiple cognitive and functional problems, including a significant segment of potentially troubled drivers who had not yet been publicly identified by others. There is a need for simple and quickly identified screening tools to identify those older adults whose driving should be reviewed. The DRI, based on the interRAI CHA, fills this void. Assessment at the individual level needs to be part of the backdrop of science as society seeks to target policy to identify high risk drivers instead of simply age-based testing.
本项目使用基于 interRAI 的社区健康评估 (CHA) 来开发一种模型,以确定当前驾驶行为应接受审查的老年驾驶员。评估由 COLLAGE 中的独立住房站点完成,COLLAGE 是一个非营利性的全国性老年住房联盟。对来自美国 COLLAGE 站点的老年人数据进行二次分析,使用 8042 名受试者的基线评估和 3840 名受试者的年度随访评估。使用逻辑回归根据 CHA 评估中可用的多项措施中最有用的项目来开发驾驶审查指数 (DRI)。逻辑回归确定了 13 个项目,用于预测其他人为其驾驶行为提出质疑的驾驶员。特别是,三个变量反映了受损的决策能力:日常决策、最近决策能力下降和管理药物的能力。另外两个衡量标准评估认知状态:短期记忆问题和非阿尔茨海默病痴呆症的诊断。功能措施反映了限制和一般虚弱,包括在交通方面得到帮助、使用助行器、步态不稳定、疲劳和大多数日子不外出。最后三个临床措施反映了视力受损、对通常喜欢的事物缺乏兴趣或乐趣以及腹泻。DRI 将审查过程集中在有多种认知和功能问题的驾驶员上,包括一大部分潜在有问题的驾驶员,他们尚未被其他人公开识别。需要简单且快速识别的筛选工具来确定那些需要审查驾驶能力的老年人。基于 interRAI CHA 的 DRI 填补了这一空白。在社会寻求针对高风险驾驶员制定政策而不是仅仅基于年龄进行测试的情况下,需要在个人层面进行评估,以作为科学背景的一部分。