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损耗风险预测工具的开发。

Development of an attrition risk prediction tool.

作者信息

Fowler John, Norrie Peter

机构信息

Health and Life Sciences, De Montfort University, Leicester, UK.

出版信息

Br J Nurs. 2009;18(19):1194-200. doi: 10.12968/bjon.2009.18.19.44831.

DOI:10.12968/bjon.2009.18.19.44831
PMID:19966747
Abstract

AIM

To review lecturers' and students' perceptions of the factors that may lead to attrition from pre-registration nursing and midwifery programmes and to identify ways to reduce the impact of such factors on the student's experience.

BACKGROUND

Comparable attrition rates for nursing and midwifery students across various universities are difficult to monitor accurately; however, estimates that there is approximately a 25% national attrition rate are not uncommon. The financial and human implications of this are significant and worthy of investigation.

METHOD

A study was carried out in one medium-sized UK school of nursing and midwifery, aimed at identifying perceived factors associated with attrition and retention. Thirty-five lecturers were interviewed individually; 605 students completed a questionnaire, and of these, 10 were individually interviewed. Attrition data kept by the student service department were reviewed. Data were collected over an 18-month period in 2007-2008.

FINDINGS

Regression analysis of the student data identified eight significant predictors. Four of these were 'positive' factors in that they aided student retention and four were 'negative' in that they were associated with students' thoughts of resigning.

CONCLUSION

Student attrition and retention is multifactorial, and, as such, needs to be managed holistically. One aspect of this management could be an attrition risk prediction tool.

摘要

目的

回顾讲师和学生对可能导致注册前护理和助产课程学生流失的因素的看法,并确定减少这些因素对学生体验影响的方法。

背景

准确监测各大学护理和助产专业学生的可比流失率很困难;然而,估计全国约有25%的流失率并不罕见。这在财务和人力方面的影响重大,值得研究。

方法

在英国一所中等规模的护理和助产学院开展了一项研究,旨在确定与流失和留存相关的感知因素。对35名讲师进行了单独访谈;605名学生完成了一份问卷,其中10名学生接受了单独访谈。审查了学生服务部门保存的流失数据。数据在2007年至2008年的18个月期间收集。

结果

对学生数据的回归分析确定了八个重要预测因素。其中四个是“积极”因素,因为它们有助于学生留存;四个是“消极”因素,因为它们与学生的退学想法相关。

结论

学生的流失和留存是多因素的,因此需要进行整体管理。这种管理的一个方面可以是一个流失风险预测工具。

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