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多站式面试(MMI)在基于价值观的护理、助产和急救护理实践项目招聘中的可靠性和有效性:一项评估研究的结果。

The reliability and validity of multiple mini interviews (MMIs) in values based recruitment to nursing, midwifery and paramedic practice programmes: Findings from an evaluation study.

机构信息

School of Health Sciences, University of Surrey, Guildford, Surrey, GU2 7XH, UK.

Centre for Critical Research in Nursing and Midwifery, School of Health and Education, Middlesex University, UK.

出版信息

Int J Nurs Stud. 2018 Jan;77:138-144. doi: 10.1016/j.ijnurstu.2017.10.003. Epub 2017 Oct 6.

Abstract

BACKGROUND

Universities in the United Kingdom (UK) are required to incorporate values based recruitment (VBR) into their healthcare student selection processes. This reflects an international drive to strengthen the quality of healthcare service provision. This paper presents novel findings in relation to the reliability and predictive validity of multiple mini interviews (MMIs); one approach to VBR widely being employed by universities.

OBJECTIVES

To examine the reliability (internal consistency) and predictive validity of MMIs using end of Year One practice outcomes of under-graduate pre-registration adult, child, mental health nursing, midwifery and paramedic practice students.

DESIGN

Cross-discipline evaluation study.

SETTING

One university in the United Kingdom.

PARTICIPANTS

Data were collected in two streams: applicants to A) The September 2014 and 2015 Midwifery Studies programmes; B) September 2015 adult; Child and Mental Health Nursing and Paramedic Practice programmes. Fifty-seven midwifery students commenced their programme in 2014 and 69 in 2015; 47 and 54 agreed to participate and completed Year One respectively. 333 healthcare students commenced their programmes in September 2015. Of these, 281 agreed to participate and completed their first year (180 adult, 33 child and 34 mental health nursing and 34 paramedic practice students).

METHODS

Stream A featured a seven station four-minute model with one interviewer at each station and in Stream B a six station model was employed. Cronbach's alpha was used to assess MMI station internal consistency and Pearson's moment correlation co-efficient to explore associations between participants' admission MMI score and end of Year one clinical practice outcomes (OSCE and mentor grading).

RESULTS

Stream A: Significant correlations are reported between midwifery applicant's MMI scores and end of Year One practice outcomes. A multivariate linear regression model demonstrated that MMI score significantly predicted end of Year One practice outcomes controlling for age and academic entry level: coefficients 0.195 (p=0.002) and 0.116 (p=0.002) for OSCE and mentor grading respectively. In Stream B no significant correlations were found between MMI score and practice outcomes measured by mentor grading. Internal consistency for each MMI station was 'excellent' with values ranging from 0.966-0.974 across Streams A and B.

CONCLUSION

This novel, cross-discipline study shows that MMIs are reliable VBR tools which have predictive validity when a seven station model is used. These data are important given the current international use of different MMI models in healthcare student selection processes.

摘要

背景

英国的大学被要求将基于价值观的招聘(VBR)纳入其医疗保健学生选拔过程。这反映了国际上加强医疗保健服务质量的努力。本文提出了关于多迷你面试(MMI)可靠性和预测效度的新发现;这是大学广泛采用的 VBR 方法之一。

目的

使用本科前注册成人、儿童、心理健康护理、助产和护理人员实践学生的第一年年末实践结果,检验 MMI 的可靠性(内部一致性)和预测效度。

设计

跨学科评估研究。

地点

英国的一所大学。

参与者

数据分为两部分收集:A)2014 年 9 月和 2015 年助产研究计划的申请人;B)2015 年 9 月成人、儿童和心理健康护理以及护理人员实践计划的申请人。2014 年有 57 名助产士学生开始他们的课程,2015 年有 69 名;47 名和 54 名分别同意参加并完成了第一年。2015 年 9 月有 333 名医疗保健学生开始他们的课程。其中,281 名同意参加并完成了他们的第一年(180 名成人、33 名儿童和 34 名心理健康护理和 34 名护理人员实践学生)。

方法

流 A 采用了一个七站四分钟的模型,每个站有一名面试官,而在流 B 中则采用了六站模型。使用克朗巴赫的 alpha 来评估 MMI 站的内部一致性,并用皮尔逊矩相关系数来探索参与者的入学 MMI 分数与第一年年末临床实践结果(OSCE 和导师评分)之间的关系。

结果

A 流:报告了助产士申请人的 MMI 分数与第一年年末实践结果之间的显著相关性。多元线性回归模型表明,在控制年龄和学术入学水平的情况下,MMI 分数可以显著预测第一年年末的实践结果:OSCE 为 0.195(p=0.002),导师评分为 0.116(p=0.002)。在 B 流中,MMI 分数与导师评分衡量的实践结果之间没有发现显著相关性。每个 MMI 站的内部一致性都很好,A 流和 B 流的数值范围在 0.966-0.974 之间。

结论

这项新颖的跨学科研究表明,MMI 是可靠的 VBR 工具,当使用七站模型时具有预测效度。鉴于当前国际上在医疗保健学生选拔过程中使用不同的 MMI 模型,这些数据非常重要。

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