以质量求发展,以服务铸品牌

Journal of Nursing ›› 2018, Vol. 25 ›› Issue (24): 29-32.doi: 10.16460/j.issn1008-9969.2018.24.029

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Combined Effects of Influence Factors of Resilience of 122 Clinical Nurses by fs/QCA

WANG Hong-pan, JIN Bei, XIE Cheng, YANG Si-yue, WU Xiao-dong   

  1. West China Hospital, Sichuan University, Chengdu 610041, China
  • Received:2018-08-10 Online:2018-12-25 Published:2020-07-09

Abstract: Objective To evaluate the influence of different factors of resilience of Chinese clinical nurses and to provide theoretical basis for targeted intervention. Methods A cross-sectional study was carried out and 122 clinical nurses were enrolled in a second-class hospital in Chengdu from October to November by cluster sampling and they were surveyed by using the general information questionnaire and the Connor-Davidson Resilience Scale (CD-RISC). The influential factors were analyzed using fuzzy-set qualitative comparative analysis (fs/QCA). Results The total score of resilience of clinical nurses was (62.44±15.05) and 55.7% of the nurses had moderate level of resilience. Fs/QCA showed nurses in the study were with higher frequency of weekly night shift, longer working hours but lower monthly income (<3,000 yuan). Higher resilience was observed among nurses being single, with relatively high frequency of night shift and average monthly income more than 3,000 yuan, being in good health or more workdays with working hour longer than10h; among nurses being single, and with average monthly income less than 3,000 yuan and with relatively high frequency of night shift and among nurses with average monthly income less than 3,000 yuan, relatively low frequency of night shift and rmore workdays with working hour longer than10h. Only the improvement of all the factors led to the promotion of resilience of nurses. Conclusion The resilience of clinical nurses is influenced by many factors and various and targeted measures will benefit nurses with lower resilience. Fs/QCA could be used in assessing resilience and offering the candidate optimal solutions to improve the resilience of clinical nurses.

Key words: fuzzy-set qualitative comparative analyses, resilience, clinic nurse

CLC Number: 

  • R47
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