Franchak John M, Hospodar Christina M, Adolph Karen E
Department of Psychology, University of California, Riverside, United States of America.
Department of Psychology, New York University, United States of America.
Acta Psychol (Amst). 2025 Mar;253:104703. doi: 10.1016/j.actpsy.2025.104703. Epub 2025 Jan 21.
We describe the difficulties of measuring variability in performance, a critical but largely ignored problem in studies of risk perception. The problem seems intractable if a large number of successful and unsuccessful trials are infeasible. We offer a solution based on estimates of task-specific variability pooled across the sample. Using a dataset of adult performance in throwing and walking tasks, we show that mischaracterizing the slope leads to unacceptably large errors in estimates of performance levels that undermine analyses of risk perception. We introduce a "pooled-slope" solution that approximates estimates of individual variability in performance and outperforms arbitrary assumptions about performance variability within and across tasks. We discuss the advantages of objectively measuring performance based on the rate of successful attempts-modeled via psychometric functions-for improving comparisons of risk across participants, tasks, and studies.
我们描述了衡量表现变异性的困难，这是风险认知研究中一个关键但很大程度上被忽视的问题。如果进行大量成功和不成功的试验不可行，这个问题似乎难以解决。我们基于对样本中特定任务变异性的估计提供了一种解决方案。使用一个关于成年人投掷和行走任务表现的数据集，我们表明错误地描述斜率会导致表现水平估计中出现大到不可接受的误差，从而破坏风险认知分析。我们引入了一种“合并斜率”解决方案，该方案近似于表现中个体变异性的估计，并且优于对任务内和任务间表现变异性的任意假设。我们讨论了基于成功尝试率（通过心理测量函数建模）客观衡量表现对于改善参与者、任务和研究之间风险比较的优势。
