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A systematic review and meta-analysis of the effectiveness of social support on turnover intention in clinical nurses

Background: Nurse turnover has become a salient issue in healthcare system worldwide and seriously compromises patient outcomes.

A systematic review and meta-analysis of the effectiveness of social support on turnover intention in clinical nurses

Social support is considered an effective contributor to alleviate nurse turnover intention (TI). However, the degree of correlation between social support and nurse TI remains elusive. Aims: This study aims to evaluate the strength of the effectiveness of social support on TI among nurses as well as its potential moderators. Design: This systematic review and meta-analysis followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses. Methods: To obtained qualified studies, two researchers searched Embase, PubMed, Web of science, CINAHL, CNKI, WanFang, and Chinese Medical Journal Full Text Database from inception to January 6, 2024. Meta-analysis, publication bias, and sensitivity analysis were carried out on the included studies using CMA 3.0 software, and the moderating effect was verified through meta-analysis of variance (ANOVA). Results: A total of 38 studies were obtained, involving 63,989 clinical nurses.

The comprehensive effect size of the random effect model showed a significant medium negative correlation between social support and TI among nurses (p < 0.001).

The sample size and TI measurement tools significantly moderated the correlation between social support and TI. (p < 0.050). However, nurse department, gender, data collection time, and social support measurement tools did not moderate the correlation between the two variables. Conclusion: Social support is negatively associated with TI in nurses. Nursing administrators and the medical community should fully recognize the importance of social support for nurses and take corresponding measures to enhance it, thereby reducing TI and ensuring the stability of the nursing team. .

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