Establishing Face and Content Validity of a Survey to Assess Users' Perceptions of Automated Vehicles. Issue 9 (September 2020)

• Record Type: Journal Article
• Authors: Mason, Justin; Classen, Sherrilene; Wersal, James; Sisiopiku, Virginia P.
• Is Part Of: Transportation research record. Volume 2674:Issue 9(2020)
• Page Start: 538
• Page End: 547
• Publication Date: 2020-09
• Subjects: Transportation -- Periodicals; Roads; Transport -- Périodiques; Routes -- Périodiques; Routes -- Conception et construction -- Périodiques; Roads; Transportation; 388.05
• DOI: 10.1177/0361198120930225
• Languages: English
• ISSNs: 0361-1981

Abstract

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.