经验不丰富的临床研究人员产生的数据驱动假设的质量:一个案例研究
Mytchell A Ernst1, Brooke N Draghi1, James J Cimino2
1Department of Public Health Sciences, Clemson University, Clemson, SC.
medRxiv : the preprint server for health sciences
|August 26, 2024
概括
生成高质量的科学假设与最佳的时间投资和研究人员经验有关. 没有经验的研究人员分析健康数据,当他们花费一定的时间和先前的临床研究经验时,他们产生了更好的假设.
科学领域:
- 生物医学研究生物医学研究
- 临床研究方法论 临床研究方法论
- 在医疗保健中的数据分析.
背景情况:
- 假设生成是科学发现的一个关键步骤.
- 了解影响假设质量的因素对于提高研究效率至关重要.
- 缺乏经验的研究人员可能会从数据分析和假设制定中的结构化指导中受益.
研究的目的:
- 检查与缺乏经验的临床研究人员产生的假设质量相关的上下文因素.
- 识别高质量与低质量假设的特征以及生成它们的参与者.
- 分析时间,认知事件,研究人员经验和假设质量之间的关系.
主要方法:
- 缺乏经验的临床研究人员在2小时的会议中分析了编码的健康数据集.
- 使用大声思考方法记录和转录参与者的假设生成过程.
- 专家使用标准化指标对假设进行了评分;分析了每假设的认知事件和时间.
- 分析的因素包括时间,认知事件,假设有效性和参与者的研究经验.
主要成果:
- 与较低评级的假设相比,具有更高质量评级的假设是在更一致的时间框架中生成的.
- 产生更高评级假设的参与者平均每假设使用的认知事件较少.
- 评分较高的假设与更高的有效率百分比和更多的研究人员经验有关.
结论:
- 假设质量与投资生成的时间有关;过长或过短的持续时间可能是有害的.
- 临床研究经验与更高的假设评级和有效性正相关.
- 假设生成是一个由多个因素影响的复杂过程,需要进一步调查.
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