Swain Thomas A, Snyder Scott W, McGwin Gerald, Huisingh Carrie E, Seder Thomas, Owsley Cynthia
Department of Ophthalmology and Visual Sciences, School of Medicine, University of Alabama at Birmingham, 1720 University Boulevard, Suite 609, Birmingham AL 35233 USA.
Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, 1665 University Blvd., Birmingham AL 35294-0022 USA.
Cogn Technol Work. 2023 Feb;25(1):65-74. doi: 10.1007/s10111-022-00710-6. Epub 2022 Jul 30.
Older drivers are a rapidly growing demographic group worldwide; many have visual processing impairments. Little is known about their preferences about vehicle instrument cluster design.
We evaluated the psychometric properties of a questionnaire on "dashboard" design for a population-based sample of 1000 older drivers. Topics included gauges, knobs/switches, and interior lighting; items were statements about their visual design. Response options used a Likert-scale ("Definitely True" to "Definitely False"). Factor and Rasch analyses identified underlying subscales.
Driver responses revealed four thematic subscales fitting the Rasch model: cognitive processing, lighting, pattern recognition, and obstructions. Internal consistency of subscales was acceptable (0.70-0.87); all possessed a sufficiently unidimensional structure. Opportunities for improvement were identified (item scope, category ordering, discrimination of respondents' perception levels).
Assessment of motor vehicle dashboard preferences indicated cognitive processing, lighting, pattern recognition, and obstructions are areas relevant to older drivers. Future work will examine the relationship between older drivers' visual function (e.g., contrast sensitivity, visual processing speed) and their design preferences as revealed by the Dashboard Questionnaire, with the aim to optimize instrument cluster displays for older drivers.
在全球范围内，老年驾驶员这一人口群体正在迅速增长；许多人存在视觉处理障碍。关于他们对车辆仪表盘设计的偏好却知之甚少。
我们针对1000名老年驾驶员的基于人群的样本，评估了一份关于“仪表盘”设计问卷的心理测量特性。主题包括仪表、旋钮/开关和车内照明；项目是关于其视觉设计的陈述。回答选项采用李克特量表（“绝对正确”到“绝对错误”）。因子分析和拉施分析确定了潜在的子量表。
驾驶员的回答揭示了符合拉施模型的四个主题性子量表：认知处理、照明、模式识别和障碍物。子量表的内部一致性是可接受的（0.70 - 0.87）；所有子量表都具有足够的单维结构。确定了改进的机会（项目范围、类别排序、受访者感知水平的区分）。
对机动车仪表盘偏好的评估表明，认知处理、照明、模式识别和障碍物是与老年驾驶员相关的领域。未来的工作将研究老年驾驶员的视觉功能（如对比敏感度、视觉处理速度）与仪表盘问卷所揭示的他们的设计偏好之间的关系，旨在为老年驾驶员优化仪表盘显示。
