Department of Psychology, Drexel University, Philadelphia, PA 19104, USA.
Arch Phys Med Rehabil. 2010 Mar;91(3):465-73. doi: 10.1016/j.apmr.2009.09.026.
To identify cognitive predictors of driving performance after multiple sclerosis (MS).
Prospective design examining predictive value of cognitive measures on driving performance.
All data were collected in an outpatient research setting and an outpatient driver rehabilitation program.
Participants were community-dwelling persons (N=66) with clinically defined MS (86% relapsing-remitting, 14% progressive) with a mean age of 43.47 years. All were active drivers who met vision requirements established by their respective states, and none required adaptive driving equipment.
Not applicable.
Participants were administered a comprehensive neuropsychologic assessment and a clinical behind-the-wheel (BTW) driving evaluation. Additional measures of driving performance included history of traffic violations and collisions (since MS onset).
Logistic regression indicated that information processing speed (Symbol Digit Modality Test [SDMT]) was the strongest predictor of BTW performance. A logistic regression revealed that the strongest predictors of collision and violation frequency were visuospatial learning and recall (7/24 Spatial Recall Test [SPART 7/24]).
These findings indicate that information processing and visuospatial skills are predictive of driving performance among persons with MS. These measures (SDMT and SPART 7/24) may serve as screening methods for identifying the potential impact of cognitive impairment on driving. Furthermore, the findings raise questions regarding the appropriateness of the BTW evaluation to evaluate driving difficulties accurately among individuals with MS.
确定多发性硬化症(MS)后驾驶表现的认知预测因子。
前瞻性设计,检查认知测量对驾驶表现的预测价值。
所有数据均在门诊研究环境和门诊驾驶员康复计划中收集。
参与者为具有临床定义的 MS(86%缓解-复发,14%进行性)的社区居住者(N=66),平均年龄为 43.47 岁。所有人都是活跃的驾驶员,符合各自州规定的视力要求,且无需使用适应性驾驶设备。
不适用。
参与者接受了全面的神经心理学评估和临床路考(BTW)驾驶评估。驾驶表现的其他测量指标包括交通违规和碰撞史(自 MS 发病以来)。
逻辑回归表明,信息处理速度(符号数字模态测试[SDMT])是 BTW 表现的最强预测因子。逻辑回归表明,碰撞和违规频率的最强预测因子是视空间学习和记忆(7/24 空间回忆测试[SPART 7/24])。
这些发现表明,信息处理和视空间技能是 MS 患者驾驶表现的预测因子。这些措施(SDMT 和 SPART 7/24)可作为识别认知障碍对驾驶影响的筛查方法。此外,这些发现引发了关于 BTW 评估是否适合准确评估 MS 患者驾驶困难的问题。