Older Drivers' Attitudes and Preferences about Instrument Cluster Designs in Vehicles Revealed by the Dashboard Questionnaire.

IF 2.4 3区工程技术 Q2 ENGINEERING, INDUSTRIAL

Cognition Technology & Work Pub Date : 2023-02-01 Epub Date: 2022-07-30 DOI:10.1007/s10111-022-00710-6

Thomas A Swain, Scott W Snyder, Gerald McGwin, Carrie E Huisingh, Thomas Seder, Cynthia Owsley

{"title":"Older Drivers' Attitudes and Preferences about Instrument Cluster Designs in Vehicles Revealed by the Dashboard Questionnaire.","authors":"Thomas A Swain, Scott W Snyder, Gerald McGwin, Carrie E Huisingh, Thomas Seder, Cynthia Owsley","doi":"10.1007/s10111-022-00710-6","DOIUrl":null,"url":null,"abstract":"Background: 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.Methods: 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.Results: 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).Conclusions: 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.","PeriodicalId":49090,"journal":{"name":"Cognition Technology & Work","volume":null,"pages":null},"PeriodicalIF":2.4000,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10956641/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cognition Technology & Work","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1007/s10111-022-00710-6","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2022/7/30 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"ENGINEERING, INDUSTRIAL","Score":null,"Total":0}

引用次数: 0

Abstract

Background: 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.

Methods: 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.

Results: 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).

Conclusions: 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.

查看原文本刊更多论文

仪表板问卷显示的老年驾驶员对车辆仪表盘设计的态度和偏好

背景：老年驾驶员是全球迅速增长的人口群体，其中许多人有视觉处理障碍。我们对他们对汽车仪表盘设计的偏好知之甚少：方法：我们以 1000 名老年驾驶员为样本，对 "仪表盘 "设计问卷的心理测量特性进行了评估。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（"肯定为真 "到 "肯定为假"）。因子和 Rasch 分析确定了潜在的子量表：驾驶员的回答显示了四个符合 Rasch 模型的主题子量表：认知处理、照明、模式识别和障碍物。各分量表的内部一致性均可接受（0.70-0.87）；所有分量表都具有足够的单维结构。发现了需要改进的地方（项目范围、类别排序、受访者感知水平的区分度）：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）与仪表盘问卷显示的设计偏好之间的关系，目的是为老年驾驶员优化仪表盘显示。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Cognition Technology & Work ENGINEERING, INDUSTRIAL-

CiteScore

6.90

自引率

7.70%

发文量

审稿时长

>12 weeks

期刊介绍： Cognition, Technology & Work focuses on the practical issues of human interaction with technology within the context of work and, in particular, how human cognition affects, and is affected by, work and working conditions. The aim is to publish research that normally resides on the borderline between people, technology, and organisations. Including how people use information technology, how experience and expertise develop through work, and how incidents and accidents are due to the interaction between individual, technical and organisational factors. The target is thus the study of people at work from a cognitive systems engineering and socio-technical systems perspective. The most relevant working contexts of interest to CTW are those where the impact of modern technologies on people at work is particularly important for the users involved as well as for the effects on the environment and plants. Modern society has come to depend on the safe and efficient functioning of a multitude of technological systems as diverse as industrial production, transportation, communication, supply of energy, information and materials, health and finance.