Paired or Pooled Analyses in Continuing Medical Education, Which One is Better?

Jessica H Robles, Kathleen J Harb, Sarah A Nisly
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引用次数: 1

Abstract

In data analyses, pairing participant responses is often thought to yield the purest results. However, ensuring all participants answer all questions can be challenging. Concerns exist that pooling all responses together may diminish the robustness of a statistical analysis, but the practical insights may still exist. Data from a live, in-person, continuing education series for health professionals was analysed. For each topic, identical questions were asked prior to the educational content (pre), immediately following the content (post), and on a rolling 4 to 6 week follow-up survey (follow-up). For each educational topic, responses were matched by participant for a paired analysis and aggregated for a pooled analysis. A paired analysis was done for matched responses on pre vs post and pre vs follow-up questions. A pooled analysis was done for the aggregate responses on pre vs post and pre vs follow-up questions. Responses from 55 questions were included in the analysis. In both the paired and pooled pre vs post analyses, all questions yielded a statistically significant improvement in correct responses. In the paired pre vs follow-up analysis, 59% (n = 33) of questions demonstrated a statistically significant improvement in correct responses, compared to 62% (n = 35) in the pooled pre vs follow-up analysis. Paired and pooled data yielded similar results at the immediate post-content and follow-up time periods.

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继续医学教育中的配对或汇总分析,哪个更好?
在数据分析中,配对参与者的回答通常被认为是产生最纯粹的结果。然而,确保所有参与者回答所有问题可能具有挑战性。人们担心,将所有的反应集中在一起可能会降低统计分析的稳健性,但实际的见解可能仍然存在。对卫生专业人员现场、面对面继续教育系列的数据进行了分析。对于每个主题,在教育内容之前(pre),内容之后(post)以及滚动4至6周的随访调查(follow-up)中询问相同的问题。对于每个教育主题,参与者的回答进行配对分析,并进行汇总分析。对前后、前后和后续问题的匹配回答进行配对分析。对调查前与调查后、调查前与调查后的问题进行汇总分析。分析中包含了55个问题的回答。在配对和合并的前后分析中,所有问题的正确回答都有统计学上的显著提高。在配对前与随访分析中,59% (n = 33)的问题在正确回答方面表现出统计学上显著的改善,而在合并前与随访分析中,这一比例为62% (n = 35)。配对和汇总数据在内容后和随访期间产生了类似的结果。
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