Older drivers’ attitudes and preferences about instrument cluster designs in vehicles revealed by the Dashboard Questionnaire
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 o...
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| Veröffentlicht in: | Cognition, technology & work technology & work, 2023-02, Vol.25 (1), p.65-74 |
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| creator | Swain, Thomas A. Snyder, Scott W. McGwin, Gerald Huisingh, Carrie E. Seder, Thomas Owsley, Cynthia |
| description | 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. |
| doi_str_mv | 10.1007/s10111-022-00710-6 |
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Snyder, Scott W. ; McGwin, Gerald ; Huisingh, Carrie E. ; Seder, Thomas ; Owsley, Cynthia</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c431t-a8bde121037dfc099836bb564d6f4a01669f321008b4e4facc60d5b424d8ce3f3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Aerospace Technology and Astronautics</topic><topic>Automotive Engineering</topic><topic>Cognitive Psychology</topic><topic>Computer Science</topic><topic>Industrial and Organizational Psychology</topic><topic>Medicine/Public Health</topic><topic>Original Article</topic><topic>Pattern recognition</topic><topic>Questionnaires</topic><topic>Rasch model</topic><topic>User Interfaces and Human Computer Interaction</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Swain, Thomas A.</creatorcontrib><creatorcontrib>Snyder, Scott W.</creatorcontrib><creatorcontrib>McGwin, Gerald</creatorcontrib><creatorcontrib>Huisingh, Carrie E.</creatorcontrib><creatorcontrib>Seder, Thomas</creatorcontrib><creatorcontrib>Owsley, Cynthia</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Social Sciences Premium Collection【Remote access available】</collection><collection>ProQuest Central (Corporate)</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Psychology Database (Alumni)</collection><collection>Social Science Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Research Library (Alumni Edition)</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Social Science Premium Collection (Proquest) (PQ_SDU_P3)</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>ProQuest Psychology</collection><collection>ProQuest Research Library</collection><collection>Social Science Database (ProQuest)</collection><collection>Research Library (Corporate)</collection><collection>Research Library China</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest One Psychology</collection><collection>ProQuest Central Basic</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Cognition, technology & work</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Swain, Thomas A.</au><au>Snyder, Scott W.</au><au>McGwin, Gerald</au><au>Huisingh, Carrie E.</au><au>Seder, Thomas</au><au>Owsley, Cynthia</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Older drivers’ attitudes and preferences about instrument cluster designs in vehicles revealed by the Dashboard Questionnaire</atitle><jtitle>Cognition, technology & work</jtitle><stitle>Cogn Tech Work</stitle><addtitle>Cogn Technol Work</addtitle><date>2023-02-01</date><risdate>2023</risdate><volume>25</volume><issue>1</issue><spage>65</spage><epage>74</epage><pages>65-74</pages><issn>1435-5558</issn><eissn>1435-5566</eissn><abstract>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). 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| subjects | Aerospace Technology and Astronautics Automotive Engineering Cognitive Psychology Computer Science Industrial and Organizational Psychology Medicine/Public Health Original Article Pattern recognition Questionnaires Rasch model User Interfaces and Human Computer Interaction |
| title | Older drivers’ attitudes and preferences about instrument cluster designs in vehicles revealed by the Dashboard Questionnaire |
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