Department of Neurology, University of Utah School of Medicine, Salt Lake City, UT, USA.
Division of Epidemiology, University of Utah, Salt Lake City, UT, USA.
Sci Rep. 2024 Oct 16;14(1):24289. doi: 10.1038/s41598-024-72968-x.
Investigators in neuroscience have turned to Big Data to address replication and reliability issues by increasing sample size. These efforts unveil new questions about how to integrate data across distinct sources and instruments. The goal of this study was to link scores across common auditory verbal learning tasks (AVLTs). This international secondary analysis aggregated multisite raw data for AVLTs across 53 studies totaling 10,505 individuals. Using the ComBat-GAM algorithm, we isolated and removed the component of memory scores associated with site effects while preserving instrumental effects. After adjustment, a continuous item response theory model used multiple memory items of varying difficulty to estimate each individual's latent verbal learning ability on a single scale. Equivalent raw scores across AVLTs were then found by linking individuals through the ability scale. Harmonization reduced total cross-site score variance by 37% while preserving meaningful memory effects. Age had the largest impact on scores overall (- 11.4%), while race/ethnicity variable was not significant (p > 0.05). The resulting tools were validated on dually administered tests. The conversion tool is available online so researchers and clinicians can convert memory scores across instruments. This work demonstrates that global harmonization initiatives can address reproducibility challenges across the behavioral sciences.
神经科学研究人员通过增加样本量来解决复制和可靠性问题，他们转而采用大数据方法。这些努力揭示了有关如何整合来自不同来源和仪器的数据的新问题。本研究的目的是链接常见听觉言语学习任务（AVLT）的分数。这项国际二次分析汇总了 53 项研究中共有 10505 人的 AVLT 多地点原始数据。使用 ComBat-GAM 算法，我们分离并去除了与站点效应相关的记忆分数成分，同时保留了仪器效应。调整后，使用具有不同难度的多个记忆项目的连续项目反应理论模型，在单个量表上估计每个个体的潜在言语学习能力。然后通过能力量表将个体联系起来，找到 AVLT 之间的等效原始分数。协调化将总跨站点得分方差降低了 37%，同时保留了有意义的记忆效果。年龄对总体分数的影响最大（-11.4%），而种族/民族变量则不显著（p>0.05）。对双重管理测试进行了验证。转换工具可在线获取，因此研究人员和临床医生可以在不同仪器之间转换记忆分数。这项工作表明，全球协调化举措可以解决行为科学中的可重复性挑战。
