Using academic admissions data to predict PA training attrition and academic difficulties: a survival analysis approach.

IF 4.4 2区 医学 Q1 EDUCATION & EDUCATIONAL RESEARCH
Medical Education Online Pub Date : 2026-12-31 Epub Date: 2026-10-16 DOI:10.1080/10872981.2026.2745370
Joshua Waynick, Sobia Shariff Hussaini, Ethan Stonerook, Tiffany Hiatt, Caroline Sisson, Brian Peacock, Sarah O'Neal, Andrea McKinnond, Laiton Steele, Chris Gillette
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引用次数: 0

Abstract

Background: Research studying health professions' student attrition and academic difficulties generally treat these outcomes as dichotomous variables that obscure important time-varying aspects. Scant attention has been paid to incorporating time-varying methods, such as survival analysis, to model attrition and academic difficulties in health professions trainees.

Objective: The objectives of this study are to (1) identify when students were most likely to attrit from the program and/or experience academic probation and (2) identify predictors of time to attrition and academic probation using undergraduate student performance metrics.

Design: Using a database of physician associate (PA) student admissions variables and academic performance, we examined the relationship between time-to-attrition and time-to-first-probation using semi-parametric multivariable Cox Proportional Hazards models. Results are presented in adjusted Hazards Ratios (HR) with 95% Confidence Intervals (CI).

Results: The rate at which students experienced at least one probation event was 131 per 19,563.5 person-weeks. The rate of students who experienced an attrition event was 32 per 22,210 person-weeks. Overall GPA (aHR = 0.16, 95% CI = 0.08-0.33), verbal GRE scores (aHR = 0.91, 95% CI = 0.87-0.94), having a science major in undergraduate studies (aHR = 0.43, 95% CI = 0.26-0.69) and number of undergraduate course withdrawals (aHR = 1.14, 95% CI = 1.05-1.24) were associated with time to first probation. Verbal GRE scores (aHR = 0.87, 95% CI = 0.80-0.94) and number of undergraduate course withdrawals (aHR = 1.24, 95% CI = 1.08-1.43) were associated with time to attrition.

Conclusions: We employed a novel application of survival analysis to predict PA school attrition and academic probation using an entire cohort of students. Our work informs admissions policies by identifying students at-risk of academic probation and attrition who may need more academic support prior to program matriculation.

使用学术录取数据预测私人助理训练损耗和学术困难:生存分析方法。
背景:研究卫生专业的学生流失和学业困难通常将这些结果视为二分类变量,模糊了重要的时变方面。很少注意将生存分析等时变方法纳入卫生专业受训人员的流失和学业困难模型。目的:本研究的目的是:(1)确定学生最有可能从项目中流失和/或经历学术试用期的时间;(2)使用本科生绩效指标确定流失时间和学术试用期的预测因素。设计:利用医师助理(PA)学生入学变量和学习成绩的数据库,我们使用半参数多变量Cox比例风险模型检验了流失时间和首次试用时间之间的关系。结果以校正后的风险比(HR)和95%置信区间(CI)表示。结果:学生经历至少一次缓刑事件的比率为每19,563.5人周131人。经历人员流失事件的学生比率为每22210人周32人。总GPA (aHR = 0.16, 95% CI = 0.08-0.33)、GRE语言成绩(aHR = 0.91, 95% CI = 0.87-0.94)、本科主修理科(aHR = 0.43, 95% CI = 0.26-0.69)和本科退课次数(aHR = 1.14, 95% CI = 1.05-1.24)与第一次试用的时间有关。GRE语言成绩(aHR = 0.87, 95% CI = 0.80-0.94)和本科课程退学人数(aHR = 1.24, 95% CI = 1.08-1.43)与流失时间相关。结论:我们采用了一种新颖的生存分析方法来预测PA学校的流失率和学术留校观察。我们的工作通过识别可能在项目入学前需要更多学术支持的有学术留校察看和减员风险的学生,为招生政策提供信息。
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来源期刊
Medical Education Online
Medical Education Online EDUCATION & EDUCATIONAL RESEARCH-
CiteScore
6.00
自引率
2.20%
发文量
97
审稿时长
8 weeks
期刊介绍: Medical Education Online is an open access journal of health care education, publishing peer-reviewed research, perspectives, reviews, and early documentation of new ideas and trends. Medical Education Online aims to disseminate information on the education and training of physicians and other health care professionals. Manuscripts may address any aspect of health care education and training, including, but not limited to: -Basic science education -Clinical science education -Residency education -Learning theory -Problem-based learning (PBL) -Curriculum development -Research design and statistics -Measurement and evaluation -Faculty development -Informatics/web
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