Meiners Kelly M, Rush Douglas K
Rockhurst University, 1100 Rockhurst Road, Kansas City, MO 64110, USA. Tel 816-501-4138.
J Allied Health. 2017 Fall;46(3):164-170.
Prior studies have explored variables that had predictive relationships with National Physical Therapy Examination (NPTE) score or NPTE failure. The purpose of this study was to explore whether certain variables were predictive of test-takers' first-time score on the NPTE.
The population consisted of 134 students who graduated from the university's Professional DPT Program in 2012 to 2014.
This quantitative study used a retrospective design. Two separate data analyses were conducted. First, hierarchical linear multiple regression (HMR) analysis was performed to determine which variables were predictive of first-time NPTE score. Second, a correlation analysis was performed on all 18 Physical Therapy Clinical Performance Instrument (PT CPI) 2006 category scores obtained during the first long-term clinical rotation, overall PT CPI 2006 score, and NPTE passage.
With all variables entered, the HMR model predicted 39% of the variance seen in NPTE scores. The HMR results showed that physical therapy program first-year GPA (1PTGPA) was the strongest predictor and explained 24% of the variance in NPTE scores (b=0.572, p<0.001). The correlational analysis found no statistically significant correlation between the 18 PT CPI 2006 category scores, overall PT CPI 2006 score, and NPTE passage.
As 1PTGPA had the most significant contribution to prediction of NPTE scores, programs need to monitor first-year students who display academic difficulty. PT CPI version 2006 scores were significantly correlated with each other, but not with NPTE score or NPTE passage. Both tools measure many of the same professional requirements but use different modes of assessment, and they may be considered complementary tools to gain a full picture of both the student's ability and skills.
先前的研究探讨了与国家物理治疗考试(NPTE)分数或NPTE未通过存在预测关系的变量。本研究的目的是探讨某些变量是否能预测考生在NPTE上的首次考试分数。
研究对象为134名于2012年至2014年从该大学专业物理治疗博士项目毕业的学生。
本定量研究采用回顾性设计。进行了两项独立的数据分析。首先,进行分层线性多元回归(HMR)分析,以确定哪些变量可预测NPTE首次考试分数。其次,对在第一次长期临床轮转期间获得的所有18项物理治疗临床绩效工具(PT CPI)2006类别分数、PT CPI 2006总体分数和NPTE通过率进行了相关性分析。
纳入所有变量后,HMR模型预测了NPTE分数中39%的方差。HMR结果表明,物理治疗项目一年级平均绩点(1PTGPA)是最强的预测因素,解释了NPTE分数中24%的方差(b = 0.572,p < 0.001)。相关性分析发现,18项PT CPI 2006类别分数、PT CPI 2006总体分数与NPTE通过率之间无统计学显著相关性。
由于1PTGPA对NPTE分数预测的贡献最大,各项目需要监测表现出学业困难的一年级学生。PT CPI 2006版本的分数之间存在显著相关性,但与NPTE分数或NPTE通过率无关。这两种工具都衡量了许多相同的专业要求,但使用不同的评估方式,它们可被视为互补工具,以全面了解学生的能力和技能。