Evidence map›Paper›PMID 41257851›Full record

ArticleBMC nursing2025

Application of the SWARA-TOPSIS method for prioritizing turnover intention factors among nurses: a case study in an Isfahan hospital, Iran.

Mahsa Jahadi Naeini, Mahnaz Shakerian, Saeid Yazdanirad, Seyed Mahdi Mousavi

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Article in BMC nursing, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Mahsa Jahadi NaeiniStudent Research Committee, Department of Occupational Health and Safety Engineering, School of Health, Isfahan University of Medical Sciences, Isfahan, Iran.
Mahnaz ShakerianDepartment of Occupational Health and Safety Engineering, School of Health, Isfahan University of Medical Sciences, Isfahan, Iran.
Saeid YazdaniradSchool of Health, Shahrekord University of Medical Sciences, Shahrekord, Iran. saeedyazdanirad@gmail.com.
Seyed Mahdi MousaviStudent Research Committee, Department of Occupational Health and Safety Engineering, School of Health, Isfahan University of Medical Sciences, Isfahan, Iran. Mahdi.mousavi90@yahoo.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionNurse turnover intention poses a significant challenge to healthcare systems, particularly in hospitals. So, it disrupts clinical care and reduces patient satisfaction. This study aimed to identify and prioritize factors influencing turnover intention among nurses in a hospital to provide actionable insights for improving nurse retention.

methodsThis study employed a hybrid Fuzzy Delphi-SWARA-TOPSIS methodology. First, a systematic literature review and the Fuzzy Delphi Technique were used to identify key factors. These factors were categorized into four groups: individual (e.g., age, education), organizational (e.g., salary, benefits), job-related (e.g., job security), and managerial (e.g., leadership style). The SWARA method was then applied to determine the relative weights of these factors, followed by the TOPSIS technique to rank them based on their impact on turnover intention.

resultsThe findings revealed that managerial factors, particularly leadership style (closeness coefficient: 0.44), had the strongest effect on nurses' turnover intention. Organizational factors such as salary and job-related factors such as job security placed in next ranks. These results highlight the need for interventions focusing on effective leadership, competitive compensation, and job security to reduce nurse turnover.

conclusionThis study provides a comprehensive analytical framework for understanding and addressing nurse turnover intention. The findings suggest that hospital administrators should develop effective leadership, reform compensation structures, and improve job security to enhance nurse retention. These strategies can not only reduce turnover rates but also stabilize the workforce and improve healthcare service quality. The results offer valuable insights for policymakers and healthcare managers.

Indexed as

HealthcareHospitalSWARATOPSISTurnover intention

Identifiers

PMID41257851
PMCPMC12628974

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