Department of Psychiatry and Medical Psychology, Federal University of São Paulo, São Paulo, Brazil.
Department of Education, ICT and Learning, Østfold University College, Halden, Norway.
Int J Methods Psychiatr Res. 2023 Sep;32(3):e1969. doi: 10.1002/mpr.1969. Epub 2023 Apr 25.
Cohen's d conventional effect size cutoffs [small (0.2), medium (0.5), and large (0.8)] might not be representative of the reported distribution of effect sizes across the different areas of health. Effect size cutoffs might vary not only depending on the area of research, but also on the type of intervention and population. That is, they are context dependent. Therefore, we present strategies to redefine small, medium, and large effect size based on 25, 50, and 75th percentile, respectively.
We illustrate these techniques applying them to 72 effect sizes, derived from 65 randomized controlled trials described in a recent meta-analysis (10.1016/j.smrv.2021.101556) of improving sleep quality on composite mental health. Such percentiles are equally distanced from the average effect size as suggested by Jacob Cohen and checked for potential attenuation effects (via weight selection model) and outliers (via OutRules).
new cutoffs for effect size distribution of -0.177, -0.329, and -0.557, for small, medium, and large effect size were found, respectively. applying Cohen's effect size thresholds (0.2, 0.5, and 0.8) for trials of improving sleep quality on composite mental health might over-estimate effect sizes compared to the real-world context, especially around medium and large effect sizes.
科恩（Cohen）传统的效应量截断值[小（0.2）、中（0.5）和大（0.8）]可能无法代表不同健康领域报告的效应量分布。效应量截断值不仅可能因研究领域而异，还可能因干预措施和人群类型而异。也就是说，它们是依赖于上下文的。因此，我们提出了基于第 25、50 和 75 百分位数重新定义小、中、大效应量的策略。
我们通过将这些技术应用于最近一项荟萃分析（10.1016/j.smrv.2021.101556）中描述的 65 项随机对照试验得出的 72 个效应量，说明了这些技术。该荟萃分析旨在提高复合心理健康的睡眠质量。这些百分位与雅各布·科恩（Jacob Cohen）建议的平均效应量等距，以检查潜在的衰减效应（通过权重选择模型）和异常值（通过 OutRules）。
分别为小、中、大效应量找到新的效应量分布截断值-0.177、-0.329 和-0.557。对于改善复合心理健康睡眠质量的试验，应用科恩的效应量阈值（0.2、0.5 和 0.8）可能会高估与现实世界背景相比的效应量，尤其是在中大和大效应量附近。
