A secondary data analysis on hypotheses generated by inexperienced clinical researchers: Cases from a randomized controlled study.

IF 2.3 3区 医学 Q2 HEALTH CARE SCIENCES & SERVICES
Health Informatics Journal Pub Date : 2025-07-01 Epub Date: 2025-08-06 DOI:10.1177/14604582251353587
Mytchell A Ernst, Brooke N Draghi, James J Cimino, Vimla L Patel, Yuchun Zhou, Jay H Shubrook, Sonsoles De Lacalle, Aneesa Weaver, Chang Liu, Xia Jing
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引用次数: 0

Abstract

Objectives: To obtain insights about inexperienced clinical researchers' hypothesis quality and associated factors. The findings inform the development of informatics tools to aid the hypothesis generation process. Methods: We analyzed an existing dataset collected through a randomized controlled study, focusing on individual hypotheses and participants. We invited clinical researchers to analyze datasets and develop hypotheses using the think-aloud method. Participants' screen activity and audio were recorded, transcribed, coded, and analyzed to measure the time and cognitive events (a granular unit of thought processes used by the participants while generating hypotheses). Hypotheses were rated by an expert panel. Here we analyzed (1) the top 5-rated hypotheses, (2) the bottom 5-rated hypotheses, and (3) the participants who generated them. Results: Participants who generated the top 5-rated hypotheses utilized fewer cognitive events and a shorter range of time per hypothesis; their hypotheses presented a higher valid rate, and they were more experienced. Conclusion: Having more experience is positively associated with higher quality and valid rates of the generated hypotheses. The higher-rated hypotheses seem to be positively associated with slightly fewer cognitive events and shorter time. The effect may not be linear. These analyses provide evidence for customized study designs or tool development based on these associated factors.

对缺乏经验的临床研究人员提出的假设的二次数据分析:来自随机对照研究的病例。
目的:了解临床无经验科研人员的假设质量及其相关因素。研究结果为信息学工具的发展提供了信息,以帮助假设生成过程。方法:通过随机对照研究对现有数据集进行分析,重点关注个体假设和参与者。我们邀请了临床研究人员来分析数据集,并使用出声思考的方法提出假设。参与者的屏幕活动和音频被记录、转录、编码和分析,以测量时间和认知事件(参与者在产生假设时使用的思维过程的颗粒单位)。一个专家小组对假设进行了评级。在这里,我们分析了(1)排名前5位的假设,(2)排名后5位的假设,以及(3)产生这些假设的参与者。结果:产生前5级假设的参与者使用更少的认知事件和更短的时间范围每个假设;他们的假设有更高的有效性,而且他们更有经验。结论:经验越多,生成的假设质量和有效率越高。评分较高的假设似乎与较少的认知事件和较短的时间呈正相关。这种影响可能不是线性的。这些分析为基于这些相关因素的定制研究设计或工具开发提供了证据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Health Informatics Journal
Health Informatics Journal HEALTH CARE SCIENCES & SERVICES-MEDICAL INFORMATICS
CiteScore
7.80
自引率
6.70%
发文量
80
审稿时长
6 months
期刊介绍: Health Informatics Journal is an international peer-reviewed journal. All papers submitted to Health Informatics Journal are subject to peer review by members of a carefully appointed editorial board. The journal operates a conventional single-blind reviewing policy in which the reviewer’s name is always concealed from the submitting author.
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