Construction and validation of an updated perfect automation schema (uPAS) scale

IF 1.4 Q4 ERGONOMICS
Anthony M. Gibson, August A. Capiola, Gene M. Alarcon, Michael A. Lee, Sarah A. Jessup, Izz Aldin Hamdan
{"title":"Construction and validation of an updated perfect automation schema (uPAS) scale","authors":"Anthony M. Gibson, August A. Capiola, Gene M. Alarcon, Michael A. Lee, Sarah A. Jessup, Izz Aldin Hamdan","doi":"10.1080/1463922X.2022.2081375","DOIUrl":null,"url":null,"abstract":"Abstract The perfect automation schema is described as a representation people hold regarding the performance of automated systems, comprising initial high expectations for automated systems’ performance and low forgiveness after automated systems fail. Merritt, Unnerstall, Lee, and Huber have created a self-report measure of perfect automation schema comprising the two aforementioned factors, but this measure has demonstrated poor internal consistency estimates. In the present research, we created an updated perfect automation schema (uPAS) scale that showed acceptable reliability and validity estimates. In Study 1, we generated items that described both factors of perfect automation schema and conducted an exploratory factor analysis. In Study 2, we conducted a confirmatory factor analysis to confirm the uPAS scale composition and examined the scale’s convergent, discriminant, and criterion validity. We found acceptable reliability estimates for the new scale across both studies. In Study 2, however, we found the uPAS scale factors and the factors from Merritt and colleagues’ scale showed similar criterion validity across three trust-related criteria (trustworthiness perceptions, reliance intentions, and use endorsement). We conclude by offering a reliable uPAS scale to assess the perfect automation schema, which showed comparable criterion-related validity to Merritt and colleagues’ scale.","PeriodicalId":22852,"journal":{"name":"Theoretical Issues in Ergonomics Science","volume":"24 1","pages":"241 - 266"},"PeriodicalIF":1.4000,"publicationDate":"2022-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Theoretical Issues in Ergonomics Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/1463922X.2022.2081375","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ERGONOMICS","Score":null,"Total":0}
引用次数: 1

Abstract

Abstract The perfect automation schema is described as a representation people hold regarding the performance of automated systems, comprising initial high expectations for automated systems’ performance and low forgiveness after automated systems fail. Merritt, Unnerstall, Lee, and Huber have created a self-report measure of perfect automation schema comprising the two aforementioned factors, but this measure has demonstrated poor internal consistency estimates. In the present research, we created an updated perfect automation schema (uPAS) scale that showed acceptable reliability and validity estimates. In Study 1, we generated items that described both factors of perfect automation schema and conducted an exploratory factor analysis. In Study 2, we conducted a confirmatory factor analysis to confirm the uPAS scale composition and examined the scale’s convergent, discriminant, and criterion validity. We found acceptable reliability estimates for the new scale across both studies. In Study 2, however, we found the uPAS scale factors and the factors from Merritt and colleagues’ scale showed similar criterion validity across three trust-related criteria (trustworthiness perceptions, reliance intentions, and use endorsement). We conclude by offering a reliable uPAS scale to assess the perfect automation schema, which showed comparable criterion-related validity to Merritt and colleagues’ scale.
构建和验证更新的完美自动化模式(uPAS)规模
完美自动化图式是人们对自动化系统性能的一种表征,包括最初对自动化系统性能的高期望和自动化系统故障后的低宽恕。Merritt, ununstall, Lee和Huber已经创建了一个包含上述两个因素的完美自动化方案的自我报告度量,但是该度量显示了较差的内部一致性估计。在本研究中,我们创建了一个更新的完美自动化图式(uPAS)量表,显示出可接受的信度和效度估计。在研究1中,我们生成了描述完美自动化图式的两个因素的条目,并进行了探索性因素分析。在研究2中,我们进行了验证性因子分析来确认uPAS量表的组成,并检验了量表的收敛效度、判别效度和标准效度。我们在两项研究中都找到了新量表可接受的信度估计。然而,在研究2中,我们发现uPAS量表因子和Merritt及其同事的量表因子在三个与信任相关的标准(可信度感知、信赖意图和使用认可)上显示出相似的标准效度。最后,我们提供了一个可靠的uPAS量表来评估完美的自动化方案,它显示了与Merritt和同事的量表相当的标准相关的效度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
CiteScore
4.10
自引率
6.20%
发文量
38
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信