Objective:To construct a quality evaluation index system for nursing simulation teaching, and determine the weight of each index.Methods:The research team was established on January 1, 2018. The first draft of the quality evaluation index system for nursing simulation teaching was constructed based on extensive literature and Jeffries simulation theory model. The Delphi method was used to conduct 2 rounds of consultation with 27 experts. We calculated the experts' active coefficient, authority coefficient, Kendall harmony coefficient and the concentration degree of opinion. The analytic hierarchy process was used to determine the weight of each index in the index system.Results:The effective questionnaire response rates for the 2 rounds of expert consultation were 96.30% and 100.00%, and the expert authority coefficient was 0.89. The Kendall harmony coefficients of the second and third levels in the second round of expert consultation were 0.515 and 0.589 respectively, and the difference was statistically significant ( P<0.01) . The final quality evaluation index system for nursing simulation teaching included 5 first-level indicators, 14 second-level indicators and 62 third-level indicators. Conclusions:The weight distribution of the quality evaluation index system for nursing simulation teaching is scientific and reliable. This system has guiding significance for high-quality nursing simulation teaching and is an effective tool for evaluating the quality of nursing simulation teaching.

Objective To perform theory construction and empirical study of the competency model of rural general practitioners. Methods Through literature study, job analysis, interviews, and expert team discussion, the questionnaire of rural general practitioners competency was constructed. A total of 1458 rural general practitioners were surveyed by the questionnaire in 6 central provinces. The common factors were constructed using the principal component method of exploratory factor analysis and confirmatory factor analysis. The influence of the competency characteristics on the working performance was analyzed using regression equation analysis. Results The Cronbach 's alpha coefficient of the questionnaire was 0.974. The model consisted of 9 dimensions and 59 items. The 9 competency dimensions included basic public health service ability, basic clinical skills, system analysis capability, information management capability, communication and cooperation ability, occupational moral ability, non- medical professional knowledge, personal traits and psychological adaptability. The rate of explained cumulative total variance was 76.855%. The model fitting index were X2/df 1.88, GFI=0.94, NFI=0.96, NNFI=0.98, PNFI=0.91, RMSEA=0.068, CFI=0.97, IFI=0.97, RFI=0.96, suggesting good model fitting. Regression analysis showed that the competency characteristics had a significant effect on job performance. Conclusion The rural general practitioners competency model provides reference for rural doctor training, rural order directional cultivation of medical students, and competency performance management of the rural general practitioners.

Objective To perform theory construction and empirical study of the competency model of rural general practitioners. Methods Through literature study, job analysis, interviews, and expert team discussion, the questionnaire of rural general practitioners competency was constructed. A total of 1458 rural general practitioners were surveyed by the questionnaire in 6 central provinces. The common factors were constructed using the principal component method of exploratory factor analysis and confirmatory factor analysis. The influence of the competency characteristics on the working performance was analyzed using regression equation analysis. Results The Cronbach 's alpha coefficient of the questionnaire was 0.974. The model consisted of 9 dimensions and 59 items. The 9 competency dimensions included basic public health service ability, basic clinical skills, system analysis capability, information management capability, communication and cooperation ability, occupational moral ability, non- medical professional knowledge, personal traits and psychological adaptability. The rate of explained cumulative total variance was 76.855%. The model fitting index were X2/df 1.88, GFI=0.94, NFI=0.96, NNFI=0.98, PNFI=0.91, RMSEA=0.068, CFI=0.97, IFI=0.97, RFI=0.96, suggesting good model fitting. Regression analysis showed that the competency characteristics had a significant effect on job performance. Conclusion The rural general practitioners competency model provides reference for rural doctor training, rural order directional cultivation of medical students, and competency performance management of the rural general practitioners.