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Construct validity of multiple mini interviews ? Investigating the role of stations, skills, and raters using Bayesian G-theory

机译:构建多个迷你访谈的有效性? 调查使用贝叶斯G-理论的站点,技能和评估者的作用

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Background: One popular procedure in the medical student selection process are multiple mini-interviews (MMIs), which are designed to assess social skills (e.g., empathy) by means of brief interview and role-play stations. However, it remains unclear whether MMIs reliably measure desired social skills or rather general performance differences that do not depend on specific social skills. Here, we provide a detailed investigation into the construct validity of MMIs, including the identification and quantification of performance facets (social skill-specific performance, station-specific performance, general performance) and their relations with other selection measures. Methods: We used data from three MMI samples (N?=?376 applicants, 144 raters) that included six interview and role-play stations and multiple assessed social skills. Results: Bayesian generalizability analyses show that, the largest amount of reliable MMI variance was accounted for by station-specific and general performance differences between applicants. Furthermore, there were low or no correlations with other selection measures. Discussion: Our findings suggest that MMI ratings are less social skill-specific than originally conceptualized and are due more to general performance differences (across and within-stations). Future research should focus on the development of skill-specific MMI stations and on behavioral analyses on the extents to which performance differences are based on desirable skills versus undesired aspects.
机译:背景:医学学生选择过程中的一种流行程序是多个迷你访谈(MMIS),旨在通过简要访谈和角色游戏站评估社交技能(例如,同理心)。然而,仍然不清楚MMIS是否可靠地衡量所需的社交技能或相当一般的性能差异,这些差异不依赖于特定的社交技能。在这里,我们对MMI的构建有效性提供了详细的调查,包括识别和量化性能方面(社会技能特定表现,站特定性能,一般性,普通绩效)及其与其他选择措施的关系。方法:我们使用来自三个MMI样本的数据(N?= 376申请人,144名评估者),其中包括六个面试和角色游戏站和多种评估的社交技能。结果:贝叶斯普遍性分析表明,申请人之间的专用和一般性能差异占了最大的可靠MMI方差。此外,与其他选择措施较低或没有相关性。讨论:我们的研究结果表明,MMI评级比最初概念化的社会技能较少,并且主要是归因于一般性差异(跨越式局域)。未来的研究应专注于技能特异性MMI站的发展以及性能差异基于所需技能与不期望的方面的行为分析。

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