Study on construction of training standard of pension nursing staff in Zhejiang Province
Diao Wenhua
Xu Hong
Abstract:Objective:To construct training standard of pension nursing staff in Zhejiang province,to provide references for pension nursing staff training in Zhejiang province,and to promote continuous improvement of pension nursing staff training in China.Methods:Through field trip of status quo of pension nursing staff training in Zhejiang province,in combination with literature data method,and organizing expert group meetings,15 experts received 2 rounds of expert consultation through the Delphy expert consultation method,and Zhejiang province pension nursing staff training standards were formulated finally.Results:Effective recovery rate of 2 rounds of expert consultation questionnaire were 94% and 100% respectively,authority of experts in 2 rounds of consultation were 0.812 and 0.867 respectively,overall importance coordination coefficient of 2 rounds of consultation were 0.201 and 0.311,overall operational coordination coefficient were 0.162 and 0.303,by x2 test,P<0.01,importance of each index and operability variation coefficient of second round of expert consultation was 0.00~0.14.Finally,pension nursing staff training standard included 11 first level indicators,31 second level indicators and 50 third level indicators.Conclusions:Zhejiang province pension nursing staff training standard was more scientific,comprehensive and practicalit reflected requirements of pension nursing staff training and school it running conditions in Zhejiang province,and was more in line with development trend of Zhejiang province pension nursing training.It had great importance in improving quality of training of pension nursing staff in Zhejiang province.
Keywords:pension nursing stafftrainingstandardDelphi method
Publication Date:2017-01-01
Online Publishing Date:2025-08-15(First online date of this platform, not the publication date of the document)
Pages:6( 677-682 )
Chinese Nursing Research

Chinese Nursing Research

PKUISTIC
ISSN:1009-6493
Year, Vol.(Issue):2017,31(6)