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学术录取面试的有效性:一项探索性元分析。

The effectiveness of academic admission interviews: an exploratory meta-analysis.

作者信息

Goho James, Blackman Ashley

机构信息

Red River College, Winnipeg, Manitoba, Canada.

出版信息

Med Teach. 2006 Jun;28(4):335-40. doi: 10.1080/01421590600603418.

DOI:10.1080/01421590600603418
PMID:16807172
Abstract

Admission to health-related professions is very competitive and selecting candidates with the best prospects for success is critical. A variety of measures are used to assess candidates to predict success. The purpose of this research was to assess the effectiveness of using selection interviews for admissions. Meta-analysis was applied to a sample of 20 studies examined in a comprehensive review article on the use of interviews in healthcare academic disciplines. Nineteen of these studies examined the relationship between performance in an interview situation and academic performance, while 10 examined the relationship between performance in an interview situation and clinical performance. A separate meta-analysis was conducted for each category of performance measure. The mean sample-size-effect size for studies examining the predictive power of interviews for academic success was 0.06 (95% confidence intervals 0.03-0.08), indicating a very small effect. The sample of studies was homogeneous using a fixed-effect model. The sample of studies for predicting clinical success had a mean effect size of 0.17 (95% confidence intervals 0.11-0.22), indicating modest positive predictive power. Using a random-effects model, this sample of studies was also homogeneous. Future research should investigate a larger sample of primary studies.

摘要

进入与健康相关的专业竞争非常激烈,挑选最有可能成功的候选人至关重要。人们采用多种措施来评估候选人以预测其成功可能性。本研究的目的是评估使用选拔面试进行招生的有效性。荟萃分析应用于一篇关于医疗学术学科面试使用情况的综合综述文章中所考察的20项研究样本。其中19项研究考察了面试表现与学业成绩之间的关系,10项研究考察了面试表现与临床成绩之间的关系。对每类绩效指标都进行了单独的荟萃分析。考察面试对学业成功预测能力的研究的平均样本量效应大小为0.06(95%置信区间0.03 - 0.08),表明效应非常小。使用固定效应模型时,研究样本具有同质性。预测临床成功的研究样本的平均效应大小为0.17(95%置信区间0.11 - 0.22),表明具有适度的正向预测能力。使用随机效应模型时,该研究样本也具有同质性。未来的研究应调查更大样本量的原始研究。

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