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

Abstract

<jats:p> 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. </jats:p>

Predicting Autonomous Shuttle Acceptance in Older Drivers Based on Technology Readiness/Use/Barriers, Life Space, Driving Habits, and Cognition

“…The Autonomous Vehicle User Perception Survey [AVUPS; ( 36 , 38 )] contains three subscales (i.e., intention to use, perceived barriers , and well-being ) and a total acceptance score. The AVUPS showed acceptable face validity and the mean content validity index was 96% ( 38 ).…”

Construct Validity and Test–Retest Reliability of the Automated Vehicle User Perception Survey

“…During initial scale development ( Mason et al, 2020 ), nine AVUPS items were negatively worded and EFA results indicated one item did not scale, one item loaded on IU (Factor 1), and seven items loaded on barriers (Factor 2). The items were developed to avoid response biases associated with multi-item scales that are worded in a single direction (i.e., acquiescence) as suggested by several psychometricians ( Churchill, 1979 ; Baumgartner and Steenkamp, 2001 ).…”

“…The approach adopted in this study and the initial survey development ( Mason et al, 2020 ) ensured that the survey instrument design included items that were relevant, concise, and clear. Specifically, the conceptual model guided item generation from the extant literature, followed by an assessment to determine face validity, and two rounds of reviews from subject-matter experts to establish content validity.…”

“…The AVUPS developed by Mason et al (2020) , measures adults’ perceptions of AVs to assess the effects of being exposed to AV technology. Items were ordered thematically in relation to the domains they were intended to represent, to enhance internal consistency reliability ( Melnick, 1993 ).…”

“…In order to understand adults’ (≥18 years old) perceptions and attitudes toward AV technology adoption, the AVUPS was constructed to quantify such perceptions. Face and content validity for the AVUPS was previously established via focus groups and subject-matter experts ( Mason et al, 2020 ). Survey items were self-generated and adapted from previous models including the Technology Acceptance Model (TAM; Davis, 1989 ), Unified Theory of Acceptance and Use of Technology (UTAUT; Venkatesh et al, 2003 ), Car Technology Acceptance Model (CTAM; Osswald et al, 2012 ), 4P Acceptance Model ( Nordhoff et al, 2016 ), Safety Critical Technology Acceptance Model (SCTAM; Hutchins and Hook, 2017 ), Self-driving Car Acceptance Scale (SCAS; Nees, 2016 ).…”