急诊创伤患者预检评估量表的编制及信效度检验
Preparation and Validity Test of the Pre-examination Evaluation Scale for Emergency Trauma Patients
邹军 1张宏宇 1陈胜 1陈雯1
作者信息
- 1. 常州市第一人民医院急诊医学科,江苏 常州 213000
- 折叠
摘要
目的 编制急诊创伤患者预检评估量表,并进行信效度检验,为预检分诊快速准确评估创伤患者病情提供有效的测评工具.方法 采用德尔菲专家函询法构建条目池,形成初始评估量表,采用Cronbach's a系数、折半信度和重测信度进行信度检验.采用内容效度、探索性因子分析、验证性因子分析进行效度检验.结果 量表总的Cronbach's α系数为0.941,折半信度为0.721,重测信度为 0.927;S-CVI/UA 为 0.846,S-CVI/Ave 为 0.975;KMO=0.960,x2=5904.207,P＜0.05;x2/df 为 1.154,GFI 为1.154,RMSEA为0.023,RMR为0.048,AVE平方根值分别为0.786、0.823、0.749.结论 最终形成了包括来院体征评估、受伤机制评估、来院方式评估3个维度,共26个条目的急诊创伤患者预检评估量表,具有良好的信效度,可以应用于预检分诊快速评估创伤患者的病情.
Abstract
Objective To compile a pre-examination assessment scale for emergency trauma patients and test its reliability and validity,so as to provide an effective assessment tool for rapid and accurate assessment of trauma patients'condition.Methods The Delphi expert correspondence method was used to construct the entry pool and form the initial evaluation scale.Cronbach's a coefficient,split half reliability and retest reliability were used for reliability test.Content validity,exploratory factor analysis and confirmatory factor analysis were used to test the validity.Results The total Cronbach's α coefficient was 0.941,the broken half reliability was 0.721,and the retest reliability was 0.927.S-CVI/UA was 0.846,and S-CVI/Ave was 0.975.KM0=0.960,x2=5904.207,P＜0.05;x2/df was 1.154,GFI was 1.154,RMSEA was 0.023,RMR was 0.048,and AVE square root values were 0.786,0.823,and 0.749,respectively.Conclusion A pre-examination and evaluation scale for emergency trauma patients with 26 items is finally formed,including 3 dimensions of admission signs evaluation,injury mechanism evaluation and admission mode evaluation.It has good reliability and validity,and can be applied to pre-examination and triage to quickly evaluate the condition of trauma patients.
关键词
预检分诊/创伤/量表/信效度Key words
Pre-examination and triage/Trauma/Scale/Reliability and validity引用本文复制引用
基金项目
常州市第一人民医院护理专项预研基金(yy2020014)
常州市第一人民医院护理专项预研基金(yy2021004)
出版年
2024
国家科技期刊平台
NSTL
维普
万方数据