Tanguy Depauw, Jared Boasen, Pierre-Majorique Léger, Sylvain Sénécal
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One potential candidate is the Trail Making Test (TMT).</p><p><strong>Objective: </strong>This study investigated the usefulness of a digital TMT as a cognitive profiling tool in IT-related UX research by assessing its predictive validity on general IT task performance and exploring its discriminant validity according to discrete cognitive functions required to perform the IT task.</p><p><strong>Methods: </strong>A digital TMT (parts A and B) named Axon was administered to 27 healthy participants, followed by administration of 5 IT tasks in the form of CAPTCHAs (Completely Automated Public Turing tests to Tell Computers and Humans Apart). The discrete cognitive functions required to perform each CAPTCHA were rated by trained evaluators. To further explain and cross-validate our results, the original TMT and 2 psychological assessments of visuomotor and short-term memory function were administered.</p><p><strong>Results: </strong>Axon A and B were administrable in less than 5 minutes, and overall performance was significantly predictive of general IT task performance (F<sub>5,19</sub>=6.352; P=.001; Λ=0.374). This result was driven by performance on Axon B (F<sub>5,19</sub>=3.382; P=.02; Λ=0.529), particularly for IT tasks involving the combination of executive processing with visual object and pattern recognition. Furthermore, Axon was cross-validated with the original TMT (P<sub>corr</sub>=.001 and P<sub>corr</sub>=.017 for A and B, respectively) and visuomotor and short-term memory tasks.</p><p><strong>Conclusions: </strong>The results demonstrate that variance in IT task performance among an age-homogenous neurotypical population can be related to intersubject variance in cognitive function as assessed by Axon. Although Axon's predictive validity seemed stronger for tasks involving the combination of executive function with visual object and pattern recognition, these cognitive functions are arguably relevant to the majority of IT interfaces. Considering its short administration time and remote implementability, the Axon digital TMT demonstrates the potential to be a useful cognitive profiling tool for IT-based UX research.</p>","PeriodicalId":36351,"journal":{"name":"JMIR Human Factors","volume":"11 ","pages":"e49992"},"PeriodicalIF":2.6000,"publicationDate":"2024-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11214028/pdf/","citationCount":"0","resultStr":"{\"title\":\"Assessing the Relationship Between Digital Trail Making Test Performance and IT Task Performance: Empirical Study.\",\"authors\":\"Tanguy Depauw, Jared Boasen, Pierre-Majorique Léger, Sylvain Sénécal\",\"doi\":\"10.2196/49992\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Cognitive functional ability affects the accessibility of IT and is thus something that should be controlled for in user experience (UX) research. However, many cognitive function assessment batteries are long and complex, making them impractical for use in conventional experimental time frames. Therefore, there is a need for a short and reliable cognitive assessment that has discriminant validity for cognitive functions needed for general IT tasks. One potential candidate is the Trail Making Test (TMT).</p><p><strong>Objective: </strong>This study investigated the usefulness of a digital TMT as a cognitive profiling tool in IT-related UX research by assessing its predictive validity on general IT task performance and exploring its discriminant validity according to discrete cognitive functions required to perform the IT task.</p><p><strong>Methods: </strong>A digital TMT (parts A and B) named Axon was administered to 27 healthy participants, followed by administration of 5 IT tasks in the form of CAPTCHAs (Completely Automated Public Turing tests to Tell Computers and Humans Apart). The discrete cognitive functions required to perform each CAPTCHA were rated by trained evaluators. To further explain and cross-validate our results, the original TMT and 2 psychological assessments of visuomotor and short-term memory function were administered.</p><p><strong>Results: </strong>Axon A and B were administrable in less than 5 minutes, and overall performance was significantly predictive of general IT task performance (F<sub>5,19</sub>=6.352; P=.001; Λ=0.374). This result was driven by performance on Axon B (F<sub>5,19</sub>=3.382; P=.02; Λ=0.529), particularly for IT tasks involving the combination of executive processing with visual object and pattern recognition. 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引用次数: 0
摘要
背景:认知功能能力会影响信息技术的可及性,因此在用户体验(UX)研究中应加以控制。然而,许多认知功能评估工具既长又复杂,不适合在常规实验时间框架内使用。因此,我们需要一种简短而可靠的认知评估方法,它对一般 IT 任务所需的认知功能具有判别效力。其中一个潜在的候选项目就是 "追踪测试"(TMT):本研究通过评估数字 TMT 对一般 IT 任务表现的预测效度,并根据执行 IT 任务所需的离散认知功能探讨其判别效度,从而探讨数字 TMT 作为认知剖析工具在 IT 相关用户体验研究中的实用性:对27名健康参与者进行了名为 "Axon "的数字TMT(A部分和B部分)测试,随后以CAPTCHA(用于区分计算机和人类的完全自动化公共图灵测试)的形式进行了5项IT任务测试。执行每个验证码所需的离散认知功能由训练有素的评估人员进行评定。为了进一步解释和交叉验证我们的结果,还进行了原始 TMT 以及视觉运动和短期记忆功能的两项心理评估:Axon A和B的施测时间不到5分钟,总体成绩对一般IT任务成绩有显著的预测作用(F5,19=6.352;P=.001;Λ=0.374)。这一结果是由 Axon B 的表现(F5,19=3.382;P=.02;Λ=0.529)驱动的,尤其是在涉及执行处理与视觉对象和模式识别相结合的 IT 任务中。此外,Axon还与原始TMT(A和B的Pcorr=.001和Pcorr=.017)以及视觉运动和短时记忆任务进行了交叉验证:结果表明,在年龄相同的神经畸形人群中,IT任务表现的差异与Axon评估的认知功能的受试者间差异有关。虽然Axon对涉及执行功能与视觉对象和模式识别相结合的任务的预测有效性似乎更强,但这些认知功能可以说与大多数信息技术界面相关。考虑到Axon数字TMT管理时间短、可远程实施,它有可能成为基于信息技术的用户体验研究中一种有用的认知分析工具。
Assessing the Relationship Between Digital Trail Making Test Performance and IT Task Performance: Empirical Study.
Background: Cognitive functional ability affects the accessibility of IT and is thus something that should be controlled for in user experience (UX) research. However, many cognitive function assessment batteries are long and complex, making them impractical for use in conventional experimental time frames. Therefore, there is a need for a short and reliable cognitive assessment that has discriminant validity for cognitive functions needed for general IT tasks. One potential candidate is the Trail Making Test (TMT).
Objective: This study investigated the usefulness of a digital TMT as a cognitive profiling tool in IT-related UX research by assessing its predictive validity on general IT task performance and exploring its discriminant validity according to discrete cognitive functions required to perform the IT task.
Methods: A digital TMT (parts A and B) named Axon was administered to 27 healthy participants, followed by administration of 5 IT tasks in the form of CAPTCHAs (Completely Automated Public Turing tests to Tell Computers and Humans Apart). The discrete cognitive functions required to perform each CAPTCHA were rated by trained evaluators. To further explain and cross-validate our results, the original TMT and 2 psychological assessments of visuomotor and short-term memory function were administered.
Results: Axon A and B were administrable in less than 5 minutes, and overall performance was significantly predictive of general IT task performance (F5,19=6.352; P=.001; Λ=0.374). This result was driven by performance on Axon B (F5,19=3.382; P=.02; Λ=0.529), particularly for IT tasks involving the combination of executive processing with visual object and pattern recognition. Furthermore, Axon was cross-validated with the original TMT (Pcorr=.001 and Pcorr=.017 for A and B, respectively) and visuomotor and short-term memory tasks.
Conclusions: The results demonstrate that variance in IT task performance among an age-homogenous neurotypical population can be related to intersubject variance in cognitive function as assessed by Axon. Although Axon's predictive validity seemed stronger for tasks involving the combination of executive function with visual object and pattern recognition, these cognitive functions are arguably relevant to the majority of IT interfaces. Considering its short administration time and remote implementability, the Axon digital TMT demonstrates the potential to be a useful cognitive profiling tool for IT-based UX research.