Establishing Face and Content Validity of a Survey to Assess Users’ Perceptions of Automated Vehicles

Fully automated vehicles hold promise for providing numerous societal benefits, including drastically reducing road fatalities. However, we know little about the adoption practices of individuals related to automated vehicles. To assess transportation users’ perceptions of automated vehicles, a 40-item survey was designed using guidance from several technology acceptance models. A focus group was used to assess face validity to ensure the items appeared credible and understandable to the layperson. Seven subject-matter experts rated items for their relevance to provide a content validity index for each item and for the overall survey. The final scale had a scale content validity index rating of 1.00, with 32 of 32 items rated greater than or equal to 0.86 and a scale content validity index of 0.96 (mean content validity index of all items), indicating acceptable content validity. The approach adopted in this study ensured the face and content validity of the survey and enhanced the items’ relevance, concision, and clarity. Future validation is required to assess scale reliability and validity. The paper provides an overview of models used for determining acceptance and adoption of technology and describes in detail the methodology used to establish face and content validity of the questionnaire survey developed for assessing adults’ perceptions of automated vehicles.

• Record URL:
  https://doi.org/10.1177/0361198120930225
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/03611981
• Supplemental Notes:
  • © National Academy of Sciences: Transportation Research Board 2020.
• Authors:
  • Mason, Justin
  • Classen, Sherrilene
  • Wersal, James
  • Sisiopiku, Virginia P
• Publication Date: 2020-9

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: pp 538-547
• Serial:
  • Transportation Research Record: Journal of the Transportation Research Board
  • Volume: 2674
  • Issue Number: 9
  • Publisher: Sage Publications, Incorporated
  • ISSN: 0361-1981
  • EISSN: 2169-4052
  • Serial URL: http://journals.sagepub.com/home/trr

Subject/Index Terms

• TRT Terms: Acceptance; Focus groups; Intelligent vehicles; Perception; Surveys; Validity
• Subject Areas: Data and Information Technology; Highways; Safety and Human Factors; Vehicles and Equipment;

Filing Info

• Accession Number: 01744823
• Record Type: Publication
• Files: TRIS, TRB, ATRI
• Created Date: Jul 9 2020 1:44PM