Objective Admissions Data and In-State Practice: What Can We Really Predict?

IF 1.7 4区 医学 Q2 MEDICINE, GENERAL & INTERNAL
Marlene P Ballejos, Jamie Riera, Robert L Williams, Robert E Sapién
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引用次数: 0

Abstract

Background and objectives: Despite the widespread adoption of the holistic review initiative in medical school admissions, admissions committees continue to struggle with identifying applicant attributes that predict future practice location. This challenge has significant practical implications, particularly for institutions committed to addressing regional health care shortages.

Methods: We analyzed eight cohorts of applicants who matriculated between 2006 and 2013 and then completed residency. We used univariate and multiple regression models to identify applicant objective attributes linked to later in-state practice. Objective data available in applications included high school location, legal state of residence, Medical College Admissions Test (MCAT) scores, grade point average, college details, graduate school, race/ethnicity, and gender; these were compared by posttraining practice location.

Results: Of 509 graduates in practice, 212 (41.7%) were in-state. In-state graduates were older (P<.001), predominately underrepresented in medicine (42% vs 33%, P<.01), graduated from urban high schools (28% vs 18%, P<.05), attended in-state colleges (66% vs 55%, P<.05), and had lower MCAT scores (56th vs 67th percentile, P<.001). Regression analysis revealed that only age, urban high school, and MCAT score significantly contributed to the model (R 2=0.064, P=.004).

Conclusions: This study shows the limited value of applicant objective data to admissions committees in predicting future in-state practice. The findings emphasize the importance of a holistic admissions process and the value of considering subjective applicant data in efforts to predict future practice location. Additional research may help identify which subjective aspects of an applicant can assist admissions committees in this effort.

客观招生数据和州内实践:我们能真正预测什么?
背景和目的:尽管在医学院招生中广泛采用了整体审查倡议,但招生委员会仍在努力确定申请人的属性,以预测未来的实习地点。这一挑战具有重大的实际影响,特别是对致力于解决区域保健短缺问题的机构而言。方法:我们分析了2006年至2013年间入学并完成住院治疗的八组申请人。我们使用单变量和多元回归模型来确定申请人的客观属性,这些属性与后来的州内实践相关联。申请中可用的客观数据包括高中位置、合法居住地、医学院入学考试(MCAT)分数、平均绩点、大学详细信息、研究生院、种族/民族和性别;通过训练后练习地点进行比较。结果:509名实习毕业生中,有212名(41.7%)在州内实习。州内毕业生年龄较大(p < 0.01),在医学领域的比例偏低(p < 0.01),毕业于城市高中(p < 28% vs . 18%, p < 0.01),就读于州内大学(p < 66% vs . 55%, p < 0.01), MCAT分数较低(p < 0.05) (p < 0.01)。回归分析显示,只有年龄、城市高中和MCAT成绩对模型有显著影响(r2 =0.064, P= 0.004)。结论:本研究表明申请人客观数据对招生委员会预测未来州内实践的价值有限。研究结果强调了整体录取过程的重要性,以及在努力预测未来实习地点时考虑主观申请人数据的价值。额外的研究可能有助于确定申请人的哪些主观方面可以帮助招生委员会进行这项工作。
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
Family Medicine
Family Medicine 医学-医学:内科
CiteScore
2.40
自引率
21.10%
发文量
0
审稿时长
6-12 weeks
期刊介绍: Family Medicine, the official journal of the Society of Teachers of Family Medicine, publishes original research, systematic reviews, narrative essays, and policy analyses relevant to the discipline of family medicine, particularly focusing on primary care medical education, health workforce policy, and health services research. Journal content is not limited to educational research from family medicine educators; and we welcome innovative, high-quality contributions from authors in a variety of specialties and academic fields.
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