The mediating role of job burnout in the relationship between career plateau and turnover intention among nurses

High turnover rates can hinder hospitals and the healthcare system from achieving their goals of providing high-quality medical services. Consequently, turnover intention (TI) has emerged as a critical issue within healthcare environments, adversely affecting the quality of care delivered to patients. This study investigates the relationship between career plateau (CP) and TI among nurses, with job burnout (JB) serving as a mediating factor. This cross-sectional study was conducted from February to November 2021. The population comprised 1,289 nurses from Qazvin University of Medical Sciences (QUMS) teaching hospitals. According to Morgan's sample size table, the required sample size was determined to be 297 nurses. A stratified sampling method was employed to ensure a representative sample. We utilized standardized questionnaires, including Milliman's CP Scale, Maslach's JB Inventory, and Kim-Leong's TI Scale. Statistical analyses were performed using Structural Equation Modeling (SEM), t-tests, ANOVA, Pearson correlation tests, and regression analyses to explore the relationships among the variables. The results were analyzed using R software version 4.1.1. The means and standard deviations for the study variables were as follows: CP (M = 38.08, SD = 5.75), JB (M = 65.99, SD = 16.68), and TI (M = 8.20, SD = 3.31). The results indicated that CP has an indirect relationship with TI, mediated by job burnout. Significant positive correlations were observed among the variables: JB with TI, JB with CP, and CP with TI (p < 0.05), both content plateau and hierarchical plateau scores were higher in female nurses. Additionally, mean scores for job burnout, emotional exhaustion, depersonalization, and TI were also higher among female nurses. Our findings demonstrate that CP significantly influences JB and TI among nurses. The implications of TI are substantial, as they incur high costs related to recruitment, training, and employee retention. Therefore, healthcare managers should adopt human resource management strategies aimed at alleviating workload and working hours, promoting physical and mental health, reducing stress levels, and enhancing communication skills. Implementing these strategies can improve job satisfaction among nurses and ultimately reduce burnout and TI.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2025-10-10
DOI
https://doi.org/10.1038/s41598-025-19518-1
Citations
1
Primary Topic
Healthcare professionals’ stress and burnout
Type
article
Field-Weighted Citation Impact
2.82
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The mediating role of job burnout in the relationship between career plateau and turnover intention among nurses

Ahad Alizadeh, Saeideh Moosavi, Mohammad Amerzadeh, Rohollah Kalhor et al.
1 citations
Scientific Reports
Healthcare professionals’ stress and burnout
2.82
article

The mediating role of job burnout in the relationship between career plateau and turnover intention among nurses

Ahad Alizadeh, Saeideh Moosavi, Mohammad Amerzadeh, Rohollah Kalhor, Shaghyegh Arzani
article en
1 citations

Abstract

High turnover rates can hinder hospitals and the healthcare system from achieving their goals of providing high-quality medical services. Consequently, turnover intention (TI) has emerged as a critical issue within healthcare environments, adversely affecting the quality of care delivered to patients. This study investigates the relationship between career plateau (CP) and TI among nurses, with job burnout (JB) serving as a mediating factor. This cross-sectional study was conducted from February to November 2021. The population comprised 1,289 nurses from Qazvin University of Medical Sciences (QUMS) teaching hospitals. According to Morgan's sample size table, the required sample size was determined to be 297 nurses. A stratified sampling method was employed to ensure a representative sample. We utilized standardized questionnaires, including Milliman's CP Scale, Maslach's JB Inventory, and Kim-Leong's TI Scale. Statistical analyses were performed using Structural Equation Modeling (SEM), t-tests, ANOVA, Pearson correlation tests, and regression analyses to explore the relationships among the variables. The results were analyzed using R software version 4.1.1. The means and standard deviations for the study variables were as follows: CP (M = 38.08, SD = 5.75), JB (M = 65.99, SD = 16.68), and TI (M = 8.20, SD = 3.31). The results indicated that CP has an indirect relationship with TI, mediated by job burnout. Significant positive correlations were observed among the variables: JB with TI, JB with CP, and CP with TI (p < 0.05), both content plateau and hierarchical plateau scores were higher in female nurses. Additionally, mean scores for job burnout, emotional exhaustion, depersonalization, and TI were also higher among female nurses. Our findings demonstrate that CP significantly influences JB and TI among nurses. The implications of TI are substantial, as they incur high costs related to recruitment, training, and employee retention. Therefore, healthcare managers should adopt human resource management strategies aimed at alleviating workload and working hours, promoting physical and mental health, reducing stress levels, and enhancing communication skills. Implementing these strategies can improve job satisfaction among nurses and ultimately reduce burnout and TI.

Scientific ReportsVol. 15(1)
Qazvin University of Medical Sciences (IR)
Openalex Percentile: Top 8%
Healthcare professionals’ stress and burnout
2.82
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.