Tech3lab, HEC Montréal, Montréal, QC, Canada.
Faculty of Health Sciences, Hokkaido University, Sapporo, Hokkaido, Japan.
JMIR Hum Factors. 2024 Jun 14;11:e49992. doi: 10.2196/49992.
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).
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.
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.
Axon A and B were administrable in less than 5 minutes, and overall performance was significantly predictive of general IT task performance (F=6.352; P=.001; Λ=0.374). This result was driven by performance on Axon B (F=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=.001 and P=.017 for A and B, respectively) and visuomotor and short-term memory tasks.
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.
认知功能能力会影响到 IT 的可访问性,因此在用户体验 (UX) 研究中应该加以控制。然而,许多认知功能评估电池都很长且复杂,使其在常规实验时间范围内不切实际。因此,需要有一种简短且可靠的认知评估方法,该方法对执行一般 IT 任务所需的认知功能具有判别有效性。一个潜在的候选者是连线测试 (TMT)。
本研究通过评估其对一般 IT 任务性能的预测有效性,并根据执行 IT 任务所需的离散认知功能探索其判别有效性,来研究数字 TMT 在与 IT 相关的 UX 研究中的认知分析工具的有用性。
对 27 名健康参与者进行数字 TMT(A 部分和 B 部分)Axon 的测试,然后以验证码 (Completely Automated Public Turing tests to Tell Computers and Humans Apart,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 5 项 IT 任务。执行每个验证码所需的离散认知功能由经过培训的评估人员进行评分。为了进一步解释和交叉验证我们的结果,还进行了原始 TMT 和 2 项视觉运动和短期记忆功能的心理评估。
Axon A 和 B 的测试时间均不到 5 分钟,整体表现与一般 IT 任务表现呈显著正相关 (F=6.352;P=.001;Λ=0.374)。这一结果是由 Axon B 的表现驱动的 (F=3.382;P=.02;Λ=0.529),特别是对于涉及执行处理与视觉对象和模式识别相结合的 IT 任务。此外,Axon 与原始 TMT(A 和 B 分别为 P=.001 和 P=.017)以及视觉运动和短期记忆任务进行了交叉验证。
结果表明,在年龄均一的神经典型人群中,IT 任务表现的差异可以与 Axon 评估的认知功能的个体差异相关。尽管 Axon 的预测有效性对于涉及执行功能与视觉对象和模式识别相结合的任务似乎更强,但这些认知功能对于大多数 IT 界面都是相关的。考虑到其简短的管理时间和远程实施能力,Axon 数字 TMT 有可能成为一种有用的基于 IT 的 UX 研究认知分析工具。