临床研究人员如何生成数据驱动的科学假设?运用出声思维法的认知事件。

How do clinical researchers generate data-driven scientific hypotheses? Cognitive events using think-aloud protocol.

作者信息

Jing Xia, Draghi Brooke N, Ernst Mytchell A, Patel Vimla L, Cimino James J, Shubrook Jay H, Zhou Yuchun, Liu Chang, De Lacalle Sonsoles

机构信息

Department of Public Health Sciences, Clemson University, Clemson, SC.

Cognitive Studies in Medicine and Public Health, The New York Academy of Medicine, New York City, NY.

出版信息

medRxiv. 2023 Oct 31:2023.10.31.23297860. doi: 10.1101/2023.10.31.23297860.

Abstract

OBJECTIVES

This study aims to identify the cognitive events related to information use (e.g., "Analyze data", "Seek connection") during hypothesis generation among clinical researchers. Specifically, we describe hypothesis generation using cognitive event counts and compare them between groups.

METHODS

The participants used the same datasets, followed the same scripts, used VIADS (a visual interactive analysis tool for filtering and summarizing large data sets coded with hierarchical terminologies) or other analytical tools (as control) to analyze the datasets, and came up with hypotheses while following the think-aloud protocol. Their screen activities and audio were recorded and then transcribed and coded for cognitive events.

RESULTS

The VIADS group exhibited the lowest mean number of cognitive events per hypothesis and the smallest standard deviation. The experienced clinical researchers had approximately 10% more valid hypotheses than the inexperienced group. The VIADS users among the inexperienced clinical researchers exhibit a similar trend as the experienced clinical researchers in terms of the number of cognitive events and their respective percentages out of all the cognitive events. The highest percentages of cognitive events in hypothesis generation were "Using analysis results" (30%) and "Seeking connections" (23%).

CONCLUSION

VIADS helped inexperienced clinical researchers use fewer cognitive events to generate hypotheses than the control group. This suggests that VIADS may guide participants to be more structured during hypothesis generation compared with the control group. The results provide evidence to explain the shorter average time needed by the VIADS group in generating each hypothesis.

摘要

目的

本研究旨在识别临床研究人员在假设生成过程中与信息使用相关的认知事件(例如,“分析数据”、“寻找联系”)。具体而言,我们使用认知事件计数来描述假设生成,并在不同组之间进行比较。

方法

参与者使用相同的数据集,遵循相同的脚本,使用VIADS(一种用于过滤和汇总用分层术语编码的大数据集的可视化交互分析工具)或其他分析工具(作为对照)来分析数据集,并在遵循出声思维协议的同时提出假设。记录他们的屏幕活动和音频,然后进行转录并对认知事件进行编码。

结果

VIADS组每个假设的认知事件平均数量最低,标准差最小。经验丰富的临床研究人员比经验不足的组产生的有效假设多约10%。在经验不足的临床研究人员中,VIADS用户在认知事件数量及其在所有认知事件中所占的各自百分比方面,与经验丰富的临床研究人员表现出相似的趋势。假设生成中认知事件的最高百分比是“使用分析结果”(30%)和“寻找联系”(23%)。

结论

与对照组相比,VIADS帮助经验不足的临床研究人员在生成假设时使用更少的认知事件。这表明与对照组相比,VIADS可能会引导参与者在假设生成过程中更具条理性。研究结果为解释VIADS组生成每个假设所需的平均时间较短提供了证据。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9a3d/10635246/734be35eaf3b/nihpp-2023.10.31.23297860v1-f0001.jpg

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