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

Mason, Justin; Classen, Sherrilene; Wersal, James; Sisiopiku, Virginia P.

doi:10.3389/fpsyg.2021.626791

Cited by 25 publications

(33 citation statements)

References 44 publications

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“…We enrolled participants who were recruited from community partner interactions, older driver stakeholders, flyers placed in community settings, and Facebook groups. Detailed methodology and research protocol are discussed in our previous publications ( 15 , 36 , 38 ).…”

Section: Methodsmentioning

confidence: 99%

“…We are only discussing the procedure relevant to this analysis. As such, during the first visit, participants completed a demographic medical history form ( 61 ), TRI 2.0 ( 37 ), TAM ( 33 ), Automated Vehicle User Perception Survey [AVUPS; ( 36 , 38 )], Life Space Questionnaire [LSQ: ( 12 )], DHQ ( 50 ), and the TMT A and B ( 62 ). Prior to riding in the AS, participants were instructed to remain seated while the shuttle operated.…”

Section: Methodsmentioning

confidence: 99%

“…The total AVUPS scores for test-retest reliability ( N = 84) were significantly and strongly correlated with excellent reliability (ρ = 0.76, p < 0.001, ICC = 0.95). The separate Mokken scale scores for test-retest were also significantly and strongly correlated with excellent reliability: i.e., intention to use (ρ = 0.80, p < 0.001, ICC = 0.93), perceived barriers (ρ = 0.73, p < 0.001, ICC = 0.87), and well-being (ρ = 0.72, p < 0.001, ICC = 0.84) ( 36 ). Because the construct validity indicated that either of the three separate Mokken subscales (i.e., intention to use, perceived barriers, and well-being), and/or the total acceptance score can be used to quantify users' perceptions of AVs ( 36 ), this tool may be used as a valid indicator for assessing older adults' perceived barriers, as well as their intention to use AVs.…”

Section: Literature Reviewmentioning

confidence: 97%

“…The literature indicates that four constructs are important to consider for older adults' acceptance and adoption practices pertaining to AV technology (32)(33)(34)(35)(36). These are: technology readiness, perceived ease of use, perceived barriers, and intention to use the technology, next discussed.…”

Section: Older Drivers' Acceptance and Adoption Practices Of Technologymentioning

confidence: 99%

“…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 ).…”

Section: Literature Reviewmentioning

confidence: 99%

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

et al. 2021

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Shared autonomous vehicle services (i. e., automated shuttles, AS) are being deployed globally and may improve older adults (>65 years old) mobility, independence, and participation in the community. However, AS must be user friendly and provide safety benefits if older drivers are to accept and adopt this technology. Current potential barriers to their acceptance of AS include a lack of trust in the systems and hesitation to adopt emerging technology. Technology readiness, perceived ease of use, perceived barriers, and intention to use the technology, are particularly important constructs to consider in older adults' acceptance and adoption practices of AS. Likewise, person factors, i.e., age, life space mobility, driving habits, and cognition predict driving safety among older drivers. However, we are not sure if and how these factors may also predict older adults' intention to use the AS. In the current study, we examined responses from 104 older drivers (Mage = 74.3, SDage = 5.9) who completed the Automated Vehicle User Perception Survey (AVUPS) before and after riding in an on-road automated shuttle (EasyMile EZ10). The study participants also provided information through the Technology Readiness Index, Technology Acceptance Measure, Life Space Questionnaire, Driving Habits Questionnaire, Trail-making Test Part A and Part B (TMT A and TMT B). Older drivers' age, cognitive scores (i.e., TMT B), driving habits (i.e., crashes and/or citations, exposure, and difficulty of driving) and life space (i.e., how far older adults venture from their primary dwelling) were entered into four models to predict their acceptance of AVs—operationalized according to the subscales (i.e., intention to use, perceived barriers, and well-being) and the total acceptance score of the AVUPS. Next, a partial least squares structural equation model (PLS-SEM) elucidated the relationships between, technology readiness, perceived ease of use, barriers to AV acceptance, life space, crashes and/or citations, driving exposure, driving difficulty, cognition, and intention to use AS. The regression models indicated that neither age nor cognition (TMT B) significantly predicted older drivers' perceptions of AVs; but their self-reported driving difficulty (p = 0.019) predicted their intention to use AVs: R2 = 6.18%, F (2,101) = 4.554, p = 0.040. Therefore, intention to use was the dependent variable in the subsequent PLS-SEM. Findings from the PLS-SEM (R2 = 0.467) indicated the only statistically significant predictors of intention to use were technology readiness (β = 0.247, CI = 0.087-0.411) and barriers to AV acceptance (β = −0.504, CI = 0.285-0.692). These novel findings provide evidence suggesting that technology readiness and barriers must be better understood if older drivers are to accept and adopt AS.

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Section: Methodsmentioning

confidence: 99%