Williams Brett, Brown Ted, Boyle Malcolm, Webb Vanessa
Department of Community Emergency Health and Paramedic Practice, Faculty of Medicine, Nursing and Health Sciences, Monash University, Victoria, Australia.
Nurse Educ Today. 2013 Sep;33(9):938-43. doi: 10.1016/j.nedt.2012.11.010. Epub 2012 Dec 6.
Understanding students' attitudes towards certain medical conditions and diagnoses is an important part of the foundational education that students receive prior to their progression into the health care workforce. Therefore having instruments such as the Medical Condition Regard Scale (MCRS) with strong measurement properties is important for health care professions.
The objective of this paper was to examine the factor structure of the MCRS when completed by a group of undergraduate paramedic and paramedic/nursing students.
Data from the MCRS completed by 783 paramedic students were analysed using exploratory factor analysis (EFA) followed by a maximum likelihood confirmatory factor analysis (CFA) to test goodness-of-fit to the sample data.
Two factors emerged from the EFA labelled Positive Regard and Negative Regard that accounted for 52.67% of the total variance. The 10-item 2-factor model produced good model-fit and good reliability estimates. One MCRS item was discarded since it loaded on a single factor and was not considered to be viable as a stand-alone subscale.
Findings from the CFA suggest that the new 10-item version of the MCRS is a valid and reliable measure for determining undergraduate paramedic students' regard for medical conditions. The new 2-factor model appears to be defined by Positive Regard and Negative Regard factors.
了解学生对某些医疗状况和诊断的态度是他们进入医疗保健行业之前接受的基础教育的重要组成部分。因此,拥有诸如医疗状况尊重量表(MCRS)之类具有强大测量属性的工具对医疗保健专业来说很重要。
本文的目的是研究一组本科护理人员及护理人员/护理专业学生完成MCRS后的因素结构。
对783名护理专业学生完成的MCRS数据进行探索性因素分析(EFA),然后进行最大似然验证性因素分析(CFA),以检验与样本数据的拟合优度。
EFA得出两个因素,分别标记为积极尊重和消极尊重,占总方差的52.67%。10项2因素模型产生了良好的模型拟合和良好的信度估计。一个MCRS项目被舍弃,因为它仅加载在一个因素上,不被认为是一个可行的独立子量表。
CFA的结果表明,新的10项版MCRS是确定本科护理专业学生对医疗状况尊重程度的有效且可靠的测量工具。新的2因素模型似乎由积极尊重和消极尊重因素定义。