Cognition, technology & work (Online) · 2022
Older Drivers' Attitudes and Preferences about Instrument Cluster Designs in Vehicles Revealed by the Dashboard Questionnaire.
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Swain Thomas A, Snyder Scott W, McGwin Gerald, Huisingh Carrie E, Seder Thomas, Owsley Cynthia
Аннотация
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.
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.