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物理治疗博士课程申请人个人陈述的可重复性定量分析:一项横断面分析。

Recurrence Quantification Analysis of Personal Statements from Applicants to a Physical Therapy Doctoral Program: A Cross-Sectional Analysis.

机构信息

Dep. of Physical Medicine and Rehabilitation, Mayo Clinic College of Medicine and Science, 200 First Street SW, Siebens 11, Rochester, MN 55905, USA. Tel 507-284-9547.

出版信息

J Allied Health. 2022 Summer;51(2):136-142.

PMID:35640293
Abstract

PURPOSE

We examined lexical sophistication of written personal statements from physical therapy applicants to determine whether recurrence quantification analysis (RQA) indices distinguish higher- versus lower-scored candidates and correlate with other admissions variables.

METHODS

Written personal statements were extracted from 152 applications, coded numerically, and analyzed with RQA. Along with other RQA indices, determinism-representing predictability of words and phrases-was quantified. A receiver operating characteristic (ROC) curve analysis was used to examine discriminative validity of RQA indices to distinguish between top-10 and bottom-10 candidates. Correlation coefficients between RQA indices and other admissions variables (grade point averages, standardized exam, behavioral interview, and cumulative admissions scores) were also examined.

RESULTS

Determinism in personal statements was lower in top-scored (mean 7.38%) than bottom-scored candidates (mean 11.29%, p = 0.015), differentiated between them with 70% sensitivity (95% CI 34.8%-93.3%) and 100% specificity (95% CI 69.2%-100%), and correlated negatively with candidates' behavioral interview scores (r = -0.168, p = 0.039).

DISCUSSION

The greater expressive lexical sophistication characterized by lower determinism in personal statements provides information about candidates' writing proficiency as a component of their communication abilities that may not otherwise be assessed in traditional admissions variables.

摘要

目的

我们检查了物理治疗申请人的书面个人陈述的词汇复杂性,以确定递归量化分析(RQA)指数是否可以区分得分较高和较低的候选人,并与其他入学变量相关。

方法

从 152 份申请中提取书面个人陈述,进行数字编码,并使用 RQA 进行分析。除了其他 RQA 指数外,确定性还量化了单词和短语的可预测性。接收器操作特性(ROC)曲线分析用于检查 RQA 指数区分前 10 名和后 10 名候选人的判别有效性。还检查了 RQA 指数与其他入学变量(平均绩点、标准化考试、行为面试和累积入学分数)之间的相关系数。

结果

在最高得分(平均 7.38%)和最低得分(平均 11.29%)的候选人中,个人陈述中的确定性较低(p = 0.015),具有 70%的敏感性(95%CI 34.8%-93.3%)和 100%的特异性(95%CI 69.2%-100%),与候选人的行为面试分数呈负相关(r = -0.168,p = 0.039)。

讨论

个人陈述中表达更丰富的词汇复杂性,表现为较低的确定性,为候选人的写作水平提供了信息,作为其沟通能力的一个组成部分,这在传统的入学变量中可能无法评估。

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