The Development And Psychometric Properties Of Core Competencies In Disaster Nursing Scale Of General Professional Nurse (CCDNS-GPN)

ObjectiveBased on the Core Competencies in Disaster Nursing Version 2.0(CCDN2.0)issued by the International Council of Nurses,this study aimed to develop the Core Competencies in Disaster Nursing Scale for General Professional Nurse(CCDNS-GPN)and initially validate the measurability and validity ofthe scale in China.To provide a measurement tool for disaster nursing managers and educators that meets both international standards and the realities of our country.Methods1.Referring to the Beaton Assessment Tool cross-cultural translation process,a total of four bilinguals were invited to participate in this study in the direct translation,synthesis,back translation,and group discussion processes for the 8 dimensions and 35 general nurse competency indicators in the CCDN 2.0 guidelines.2.The Chinese version ofthe 35 general nurse competency items was used as the item pool for the CCDNS-GPN test version.(1)10 emergency department nurses were selected in the first round and 15 cases ofnurses from various departments were selected in the second round by convenience sampling method to provide modification opinions;(2)8disaster nursing experts were invited to conduct content validity consultation and calculate expert reliability,Item-Content Validity Index(I-CVI).The content ofthe entries will be edited according to the Scale-Content Validity Index(S-CVI)and textual comments.3.In this study,registered nurses at all levels of hospitals in Guangzhou were selected using a convenience sampling method.After the first round of survey,some ofthe study subjects will be tested for the second retest reliability test.The total sample was used for item analysis(including item distribution analysis,t-test method,and correlation coefficient method)and internal consistency test;the total sample was randomly divided into sample I and sample II,sample I was used for exploratory factor analysis,by using WLSMV and Geomin oblique rotation method to extract common factors,then deleted items with cross-factor loadings higher than 0.4.Subsequently,the number of factors was determined by parallel analysis and Velicer’s Minimum Average Partial analysis;sample II was subjected to confirmatory factor analysis,with WLSMV method.The model fit indices included the Comparative Fit Index(CFI),Tucker-Lewis Index(TLI),Root Mean Square Error of Approximation(RMSEA),and Standardized Root Mean Square Residual(SRMR).Results1.In the process of Chinese translation of CCDN 2.0 guidelines,a university English lecturer and an advanced practice nurse in the direction of emergency nursing were invited in the direct translation part to form two version of direct translations;15 differences in the expression of some terms and 10 differences in the connotation ofindicators in the direct translation were discussed and resolved in the comprehensive part.In the back-translation section,a native English-speaking translator from Hong Kong,China and an advanced practice nurse who has been practicing surgical nursing in Australia for 8 years were invited to produce two version ofback-translations.The group discussion revised 10 discrepancies in the back-translation,resulting in an initial pool of 35 items and 8dimensions for the CCDNS-GPN.2.(1)The pre-survey found that the study participantsm had difficulty deciding between the "not sure" and "very unlikely" options when faced with the unknown competencies,and suggested 13 content changes to the items.(2)In the first round of content validity,the positive coefficient ofexperts was 100%,the authority coefficient ofexperts was 0.94,experts provided 43 opinions,the total S-CVI was 0.51,and the average S-CVI was 0.90.In the second round ofcontent validity,the positive coefficient ofexperts was 87.5%.The total S-CVI was 0.94,the average S-CVI was 0.99,and the range of I-CVI was 0.86～1.00.3.This survey was conducted from December 2022 to February 2023,and a total of1357 cases were collected,of which 1057 cases in sample I were used for exploratory factor analysis and 300 cases in sample II were used for validation factor analysis.Thirty-five entries were retained after item analysis;the first exploratory factor analysis removed two entries with cross-factor loadings >0.4,and the second exploratory factor analysis recommended the extraction of three common factors,with entry factor loadings between 0.530-0.937,all greater than 0.4,and a cumulative variance explained of64.938%;the modified CFA model fit index(χ2 = 1413.301,df=490 CFI =0.969,TLI=0.967,RMSEA=0.079,SRMR=0.045)met the statistical criteria;the CCDNS-GPN Cronbach’s α was 0.973 and retest reliability was 0.902.Conclusion1.This study used the Beaton cross-cultural translation process to make the 35 indicators in the CCDN 2.0 guidelines characterized by Chinese culture..2.The test version of the CCDNS-GPN’s items could cover the research concepts and can be understood by nurses.3.The official version of CCDNS-GPN includes three dimensions of "Pre-disaster knowledge reserve and communication","On-site emergency response" and "Post-disaster management and legal ethics",with a total of 33 items.The model is a good fit for the data and has a reasonable structure,which can measure the core competency level of nurses in disaster care stably and accurately.