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Open Access 01.12.2025 | Research

Turnover intention among nurses in Iranian hospitals: a systematic review and meta-analysis

verfasst von: Alireza Hajizadeh, Edris Kakemam, Morteza Arab-Zozani, Zahra Najafpoor, Hossein Dargahi, Jalal Saeidpour

Erschienen in: BMC Nursing | Ausgabe 1/2025

Abstract

Background

The turnover intention of nurses from their current positions have become a critical global public health challenge. In Iran, as a country facing with several of healthcare challenges, understanding the rate of nurses’ turnover intention is of paramount importance. This study aimed to determine the pooled proportion of turnover intention among Iranian hospital nurses through systematic review and meta-analysis.

Methods

This systematic review and meta-analysis adhered to PRISMA guidelines. Relevant studies were identified through a comprehensive search of English and Persian databases, including Web of Science, PubMed, Scopus, Science Information Database, IranMedex, and Magiran from January 2000 to November 2024. The Joanna Briggs Institute checklist was employed to assess the methodological quality of included studies. Pooled mean and standard error with 95% CI were calculated using a random effect model. Data analysis was performed using Comprehensive Meta-Analysis software, with the I² statistic used to evaluate heterogeneity among studies and Egger’s test and visual inspection of funnel plots used to investigate the publication bias.

Results

Overall, 42 studies were included in this systematic review and meta-analysis. In total, 12,898 nurses participated in the 42 included studies. The overall turnover intention was 2.96 ± 0.056 (95% CI: 2.85–3.07, P = 0.001). Based on subgroup analysis, the turnover intention was 2.95 ± 0.123 and 2.96 ± 0.064 before and after the implementing of health transformation plan (HTP). Also, subgroup analysis by COVID-19 pandemic showed that the turnover intention was 2.97 ± 0.072 and 2.94 ± 0.095 after and before COVID-19 pandemic, respectively. Based on visual inspection of the funnel plot, and egger’s test (2.04 ± 2.96, p = 0.45), no evidence of publication bias was observed.

Conclusion

Nurses turnover intention in Iran are at a moderate level, in general and, before and after the implementation of the HTP and the COVID-19 pandemic. These results support the need to formulate evidence-based policies and plans to enhance nurse retention, contributing to the overall stability of the Iranian health system.
Hinweise

Supplementary Information

The online version contains supplementary material available at https://​doi.​org/​10.​1186/​s12912-025-02801-x.

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Introduction

Healthcare systems, particularly hospitals, are critical components of sustainable development, significantly impacting human health. Hospitals, which consume approximately half of healthcare budgets [1] are tasked with delivering high-quality diagnostic, therapeutic, and rehabilitative services. To fulfill this mission, hospitals rely on a skilled and motivated workforce, with nurses constituting the largest professional group [2]. Nurses play a pivotal role in patient care, contributing to approximately 80% of patient interactions [3].
Nurses occupy a central position within healthcare systems, interacting extensively with patients, families, and other healthcare professionals [4]. Effective communication is essential to their role in monitoring patients and fulfilling their professional duties [5]. Given the multifaceted nature of their work, nurses are uniquely positioned to address significant health challenges, including epidemics, chronic diseases, emerging and re-emerging infections, and violence. Their contributions are vital to achieving overall health system goals [6, 7]. Furthermore, nurses are key stakeholders in healthcare system transformations, influencing policymaking, planning, and the implementation of health services. To optimize their impact, it is imperative to provide nurses with the necessary working conditions [8]. Despite their critical role, many nurses experience job stress, fatigue, and burnout, leading to increased turnover rates [9].
Iran, like many other developing countires, faces significant challenges in the healthcare sector, particularly a shortage of nursing staff. This shortage has led to job dissatisfaction and burnout among experienced nurses, hindering the Ministry of Health and Medical Education’s efforts to provide quality care [10]. The shortage of nursing staff is a longstanding human resource issue, with the country falling short of international standards in nursing education. The Coronavirus disease 2019 (COVID-19) pandemic exacerbated this problem, with nurse-to-patient ratios reaching critically low levels, often below one nurse per hospital bed [11]. In a systematic review of systematic reviews, stress and dissatisfaction at the individual level and management style and supportive factors at the organizational level identified as the main factors that cause nurses to leave their jobs [12].
The COVID-19 pandemic exacerbated an existing trend of nurse attrition. For example, a study conducted in Isfahan found that nurses’ intention to leave their job was a moderate to high level, with external factors were more influential than organizational factors in nurses’ intention to leave [13]. Nurse turnover has detrimental consequences for healthcare organizations, impacting service quality, safety, and overall performance. Voluntary turnover incurs direct costs associated with recruitment and training new staff, as well as indirect costs such as reduced productivity, increased dissatisfaction, and the depletion of human capital [14]. Additionally, increased workloads for remaining nurses can lead to reduced morale, job stress, and heightened workplace tension [15].
The national employment association of the United States has reported significant turnover and attrition rates among nurses, reaching 32% and 40%, respectively. These high rates impose substantial costs on the nation’s healthcare system [16]. While case studies conducted in Iran suggest a more moderate turnover rate among hospital employees, it remains a concern that necessitates proactive management strategies to mitigate its impact [1719]. With the implementation of the Health Transformation Plan (HTP), shortage of manpower, increased workload and pressure, dissatisfaction with payment methods and financial issues, lack of status and job security have been some of the problems faced by nurses [20]. The results of a study in Tehran hospitals showed that after the implementation of the health system transformation plan, nurses’ job satisfaction decreased, nurses’ intention to leave increased, and nurses’ burnout remained constant [21].
A comprehensive review of domestic and international literature reveals a substantial body of research investigating nurse turnover in Iranian hospitals. However, these studies, often conducted with varying sample sizes, have yielded conflicting results regarding the magnitude of nurse turnover. To synthesize and critically evaluate these results, a systematic review and meta-analysis approach was employed. The current study aims to utilize this rigorous approach to quantify the extent of nurse turnover in Iranian hospitals and provide valuable insights for policymakers, healthcare managers, and researchers.

Methods

Study design

This systematic review and meta-analysis was conducted adhering to the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) framework, a widely recognized protocol for conducting such studies (See supplementary file 1) [22]. The primary research question of this study was to determine the rate of turnover intention among nurses employed in Iranian hospitals. By combining data from multiple studies, this methodology enhances statistical power and reduces the margin of error, thereby providing a more accurate and reliable estimate of the overall tendency of nurses to leave Iranian hospitals.

Eligibility criteria

Full-text review was performed to assess each studies eligibility based on the following.

Inclusion criteria

  • Publication Year and Language: Studies published between 2000 and 2024 in either English or Persian.
  • Target Population: Studies focused on Iranian nurses working in hospital wards.
  • Study Design: Observational research designs, including cross-sectional, longitudinal, and correlational studies.
  • Measurement Tool: Utilization of a validated instrument to assess nurses’ turnover intention.
  • Data Reporting: Transparent reporting of mean and standard deviation for the nurses’ turnover intention.

Exclusion criteria

  • Studies published in languages other than English or Persian.
  • Studies for which full-text access was unavailable.
  • Review articles, interventional studies, letters to the editor, and similar article types.

Information sources

A comprehensive literature search was conducted using relevant keywords across multiple databases. English-language databases, including PubMed, Web of Science (WoS), and Scopus, were systematically searched to identify relevant studies. Additionally, Iranian databases such as Scientific Information Database (SID), Magiran, and IranMedex were searched to include Persian-language publications. Google Scholar was also utilized to broaden the search scope. To ensure a comprehensive search, a manual search of Google and reference lists of included studies was conducted to identify any relevant articles not indexed in the aforementioned databases. We emailed the corresponding author or first author for full text that was not available or only abstracts or unpublished documents.

Search strategy

A comprehensive search was performed using the following search terms: “nurs*”, “turnover”, “intention to leave”, “intention to quit”, “leaving intention”, “intent to leave”, “intent to quit”, and “Iran”. Boolean operators (AND, OR, NOT) were employed to refine the keyword search within titles and abstracts. A panel of experts in the field was consulted to select appropriate keywords and optimize the search strategy across various databases. We also sought an experienced librarian’s help to refine each database’s search strategy. The PubMed database search strategy is outlined in supplementary file 2.

Selection process

The search results were initially imported into EndNote 20, where duplicate records were removed. Subsequently, a title and abstract screening process was conducted to eliminate studies that were not relevant to current review objectives. Two independent researchers (AH and ZN) conducted the selection and screening of studies. Any discrepancies were resolved through discussion and consensus (EK).

Data collection process

Data extraction was conducted using a structured data extraction form developed by the research team in Microsoft Word. The extracted data included author names, publication year, study design, sample size, hospital type (Educational, non-educational, military, private, or government), mean total score of turnover intention, and standard deviation. Two researchers independently extracted data from the selected studies, and any discrepancies were resolved through consultation with the research team.

Study risk of bias assessment

To assess the methodological quality of the included studies, the Joanna Briggs Institute (JBI) Critical Appraisal Checklist for Quantitative Studies was employed [23]. This checklist, comprised of 10 items evaluating factors such as (list the factors), has been widely used in international research [2426]. Each item was scored on a three-point scale: Yes (1 point), Unclear/ Not Applicable (0.5 points), and No (0 point). Studies scoring below 30% were categorized as weak, those scoring between 30% and 70% as moderate, and those scoring above 70% as strong. Two independent reviewers assessed the quality of each study. Disagreements were resolved through discussion or consultation with a third reviewer.

Synthesis methods

Pooled mean and standard error with 95% Confidence Interval (CI) were calculated using a random effect model. Data analysis was performed using Comprehensive Meta-Analysis (CMA) software, with the I² statistic used to evaluate heterogeneity among studies and egger’s test and visual inspection of funnel plot used to investigate the publication bias. Based on the results of the I² test and the observed heterogeneity, a random-effects model was employed to pool the study results. Also, we conducted subgroup analysis based on HTP (Before, after), and COVID-19 pandemic (Before, after).

Results

Study selection

A comprehensive systematic search yielded 365 records from various online databases and additional sources. After eliminating 123 duplicate records, a title and abstract screening process was conducted, resulting in 56 studies that advanced to full-text review. Ultimately, 42 studies were included in this systematic review and meta-analysis. Figure 1 shows the general details of the screening and selection of studies.

Studies characteristics

The included studies were conducted between 2011 and 2024 in various provinces of Iran. All of these studies were cross-sectional and used different instruments to collect data on the turnover intention among nurses in Iranian hospitals. In total, 12,898 nurses participated in the 42 included studies. Most studies were conducted in teaching hospitals affiliated with the Iranian Ministry of Health and Medical Education. Table 1 illustrate the details of the included studies.
Table 1
Characteristics of included studies
First author (Year)
Sample size
Turnover intention
Health Transformation plan (Before or After? )
COVID-19
(Before or After? )
Type of hospital
Mean
SD
Alipour (2018) [27]
455
3.14
0.95
After
Before
Government
Ariapooran (2021) [28]
312
2.33
NR
After
After
Public
Alipour (2023) [29]
300
4.54
1.22
After
After
Government
Mirzaei (2022) [30]
287
3.38
1.05
After
After
Government
Mortazavi (2011) [31]
292
2.95
0.90
Before
Before
Public
Hashemi (2020) [32]
130
2.88
1.19
After
After
Government
Taghavi Larijani (2020) [33]
117
3.44
0.95
After
After
Public
Kazemi (2023) [34]
416
2.98
0.52
After
After
Public and private
Ghaderi (2018) [35]
165
3.04
0.34
After
Before
Teaching
Sharifzadeh (2014) [36]
257
2.725
0.96
Before
Before
Public and private
Mohamadzadeh (2014) [37]
248
2.88
0.88
Before
Before
Teaching
Haji (2021) [38]
140
3.15
0.66
After
After
Public
Nikbakht Nasrabadi (2024) [39]
187
2.95
0.50
After
After
Training
Omid Zadi Akhuleh (2020) [40]
250
2.89
0.44
After
After
Public
Atashzadeh Shorideh (2013) [41]
159
3.03
0.70
Before
Before
Teaching
Ashofteh (2023) [42]
212
2.94
0.83
After
After
Teaching
Sadeghi (2018) [43]
319
2.92
1.06
After
Before
Teaching
Hariri (2012) [44]
350
3.35
0.93
Before
Before
Teaching
Heidari (2023) [45]
293
2.66
0.81
After
After
Public
Abasszadeh (2014) [46]
300
1.9
1.44
Before
Before
Teaching
Shams (2022) [47]
270
2.56
0.89
After
After
Teaching
Abedi Jafari (2014) [48]
110
3.73
0.99
Before
Before
Teaching
Sharififard (2019) [49]
207
2.73
NR
After
After
Teaching
Gharibi (2024) [50]
281
3.13
0.69
After
After
Public and private
Solaimani (2023) [51]
90
2.59
0.75
After
After
Military
Sabokroo (2011) [52]
494
2.98
1.16
Before
Before
Teaching
Mosadeghrad (2013) [53]
296
3.01
NR
Before
Before
Public and private
Alsadat Nasabi (2018) [54]
395
3.49
0.82
After
Before
Teaching
Hatamizadeh (2018) [55]
267
2.15
0.51
After
Before
Private and public
Pishgooie (2018) [56]
1617
2.86
0.60
After
Before
Governmental
Cakal (2021) [57]
462
2.94
1.93
After
After
Private and public
Hoseini (2021) [58]
216
2.44
NT
After
After
Public
Zahednezhad (2020) [59]
317
3.27
1.01
After
After
Teaching
Fasih Far (2020) [60]
300
2.46
NT
After
After
NR
Karimi (2022) [61]
170
2.70
1.07
After
After
Public
Lotf (2022) [62]
190
2.78
0.74
After
After
Public
Maleki (2023) [63]
377
3.05
0.50
After
After
NR
Mousavi (2023) [64]
300
3.96
0.91
After
After
Public
Ahangari Nonehkaran (2023) [65]
551
2.71
0.802
After
After
Teaching
Mirzaei (2024) [66]
354
2.82
1.44
After
After
Public
Naserian (2024) [67]
145
3.19
1.07
After
After
Public
Yazdanirad (2024) [68]
300
2.88
NT
After
After
Public
NR: Not reported

Risk of bias in studies

Our systematic review and meta-analysis included 42 studies that were assessed using the JBI tool. The quality of the studies assessed was generally high. 34 studies (81%) were of good quality and 8 (19%) were of moderate quality. Also, one study was excluded based on quality level.

Results of meta-analysis

Overall, 42 studies are included in this systematic review and meta-analyses. In total, 12,898 nurses participated in the 42 included studies. The overall turnover intention was 2.96 ± 0.056 (95% CI: 2.85–3.07, P = 0.001) (Fig. 2). Based on visual inspection of the funnel plot, and egger’s test (2.04 ± 2.96, p = 0.45), no evidence of publication bias was observed (Fig. 3).
Based on subgroup analysis the turnover intention was 2.95 ± 0.123 and 2.96 ± 0.064 before and after of implementing of HTP in Iran. Also, subgroup analysis by COVID-19 pandemic showed that the turnover intention was 2.97 ± 0.072 and 2.94 ± 0.095 after and before COVID-19 pandemic, respectively (Table 2).
Table 2
Subgroup’s analysis of the included studies based on the time before and after of health transformation plan and COVID-19 pandemic
Subgroup
Time
Number of studies
Point estimate
Standard error
95% CI
P-value
I2
Upper
Lower
HTP
Before
9
2.95
0.123
3.19
2.71
0.0001
98.65
After
33
2.96
0.064
3.09
2.84
0.0001
97.42
COVID-19
Before
15
2.94
0.095
3.13
2.75
0.0001
98.80
After
27
2.97
0.072
3.11
2.83
0.0001
98.25

Discussion

The present study aimed to perform a systematic review and meta-analysis on turnover intention among nurses in Iranian hospital settings. Overall, 42 studies with a sample size of 12,898 published between 2011 and 2024 were analyzed.
The overall turnover intention of 2.96 out of 5 indicates that the level of intention among Iranian nurses is sensitive level and requires attention. In the health system, nursing has always been one of the careers that has its ups and downs from the time of education to retirement due to its difficulties. They mainly face challenges such as staff shortages, job dissatisfaction, poor social position, the gap between theory and practice, lack of community-based nursing care, lack of an appropriate student recruiting system, improper monitoring and evaluation, weak recruiting and retaining nurses, the aging of the nursing workforce and shortages in the nursing educational curriculums [6870].
Similar to our study, a 2024 meta-analysis on the turnover intention among Ethiopian nurses found that the pooled proportion was 53.35%, posing a significant challenge to healthcare managers in this country [24]. Also, the meta-analysis results showed that the pooled proportion of nurses’ intention to leave their jobs in sub-Saharan Africa was 50.74%, with the highest pooled proportion of intention to leave in East Africa and the lowest pooled estimate in South Africa [71]. Unlike Iran, turnover intention rates among hospital nurses have been reported at much lower rates in Israel (9%) [72], Brazil (21.1%) [73], and 12 European countries (33%) [74]. Furthermore, rates of intention to leave can also vary across nursing settings, with the results of a meta-analysis showed that intensive care nurses from 23 countries had intention rates ranging from 3.0 to 75.0%, with a pooled prevalence of intention to leave of 27.7% [75]. These discrepancies between our study’s results and previous studies, might be the consequence of variations in organizational factors such as management/ leadership styles, workload, infrastructure in the health institutions, organizational climate, organizational policies and cultural issues in healthcare systems.
A pressing issue for nurse and human resource managers in developed economies is to introduce interventions which are effective in addressing those determinants, reducing nurses turnover and increasing nurses retention [76]. A series of policy initiatives and strategies are recommended in the literature to prevent or minimize the nurses’ turnover intention [7779]. A systematic review identified some interventions including preceptorship, internships, residencies, and structured orientation programs and mentorship for new graduates; transformational or relational leadership; clinical sabbaticals; and teamwork [78]. Likewise, a meta analysis carried out by Nei et al. (2015) revealed that supportive and communicative leadership, network centrality, organizational commitment, job strain, role tension, work-family conflict, job control, job complexity, rewards/ recognition, and team cohesion were the predictors of nurses turnover intentions [79].
This meta-analysis also showed that despite all the efforts and costs made to reduce nurses’ turnover intentions, especially after the health transformation plan in Iran, the results of these policies have not led to improved retention. Based on subgroup analysis the turnover intention among Iranian nurses was 2.95 ± 0.123 and 2.96 ± 0.064 before and after of implementing of health transformation plan. The HTP in 2014, as the latest reform of Iran’s health system, has been implemented gradually in several phases to facilitate the achievement of universal health coverage, financial protection of households, ensure justice in access to health services for the society members and efficiency of the health system [80, 81]. Despite the achievements of this plan, discrimination in payments between physicians and nurses, job dissatisfaction among nurses, declining moral values, and increasing expectations of nurses are the main challenges of this plan [82]. In addition, the number of patients referred to the emergency department increased following the implementation of the health transformation plan [83, 84] which led to a high workload for nurses in hospitals [85]. Such reforms put more pressure on health workers, especially nurses [55, 86]. In such situations the likelihood of a turnover intention in the profession [87].
The results of a study conducted during the COVID-19 pandemic in Iran showed that there was a statistically significant relationship between the variables of fear of COVID-19 and job stress, job stress and intention to leave, and resilience and job stress. Also, in low resilience and high job stress with a probability of 100%, the variable of intention to leave increased by 20%, while in high resilience and low job stress with a probability of 100%, the intention to leave decreased by 32% [67]. In a study among nurses in Iran (2022), 79.4% had a moderate to low tendency and 20.6% had a high tendency to leave the service during COVID-19 pandemic [19]. This increase was not unique to Iran, as the rate of turnover intention was also higher among Qatari nurses compared to pre-COVID-19 pandemic, and nurse characteristics and stress levels played an important role in nurses’ turnover intentions during COVID-19 pandemic. Also, the previous literature showed that nurses’ turnover intention increased significantly after the COVID-19 pandemic, which researches after the COVID-19 pandemic mostly focusing on predicting nurses’ turnover intention through the negative impact of the pandemic on nurses’ psychological wellbeing [88].
The challenging conditions of caring for COVID-19 patients and the physical and mental stress imposed on nurses during the pandemic may cause them to quit their jobs. This was also evident in the present meta-analysis, as 65% of the included studies in Iran were conducted after the COVID-19 pandemic [89]. In the past 5 years and after the COVID-19 pandemic, the Iranian government’s efforts to solve the problem of hospital nurses’ turnover intention have focused mostly on resolving problems related to the welfare of nurses, including increasing salaries, implementing nursing service tariffs, and establishing other financial options. Analysis conducted based on the COVID-19 pandemic subgroup showed that after this pandemic, the turnover intention among Iranian nurses has increased. Through a variety of policies, understanding the environmental, relational, and individual factors that influence nurse satisfaction and commitment can help prevent nurses’ turnover intention and enhance their retention in clinical settings [90].

Recommendations for future research

In the conceptualizing stage of this study, the research team intended to conduct further analyses based on subgroups of hospital type, department of work, type of employment of nurses, gender, age, and other demographic and work environment characteristics. However, the results reported in the included studies did not allow for further analysis. Also, as a future study, we propose a large-scale study that comprehensively analyzes the effect size of determinants on nurses’ intention to leave their jobs worldwide and in Iran, including its analysis according to work environment and workforce conditions. Understanding the challenges that nurses face in different settings will help develop more targeted interventions to prevent turnover.

Limitations of study

This meta-analysis also has several limitations. First, the sample size of some of the studies included in our review and meta-analysis was small. Second, the present study included studies that used multiple-item instruments to measure nurses’ turnover intention. Also, due to difficulties in identifying and retrieving grey literature, it was decided to include only published studies in this review, however, most meta-analyses are characterized by this limitation. Finally, the studies included in the present review did not use similar instruments to collect data, and we were unable to control for this difference, which can be considered another limitation of this review.

Conclusions

The present meta-analysis attempted to provide a clear image of turnover intention among nurses in Iran by systematically reviewing and collecting studies conducted in recent years. Based on the analysis, nurses’ turnover intention in Iran is at a moderate level, in general, before and after implementing the HTP and the COVID-19 pandemic. This study has good and bad news for health policymakers and nurse managers in Iran. The good news is that overall the level of turnover intention among nurses is moderate. Still, the bad news is that in recent years turnover intentions have increased, especially after the COVID-19 pandemic and societal problems. Hence, due to the negative consequences of turnover intention on patients, nurses and organizations, health policymakers and managers should intervene to prevent and reduce turnover intention among nurses in Iran. Policy attention should focus on developing effective interventions to prevent and minimize the prevalence of turnover intention among nurses in Iran.

Acknowledgements

Not applicable.

Declarations

This study was approved by the Research Ethics Committee of Tehran University of Medical Sciences (ID: IR.TUMS.SPH.REC.1403.169).
Not applicable.

Competing interests

The authors declare no competing interests.

Clinical trial number

Not applicable.
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Metadaten
Titel
Turnover intention among nurses in Iranian hospitals: a systematic review and meta-analysis
verfasst von
Alireza Hajizadeh
Edris Kakemam
Morteza Arab-Zozani
Zahra Najafpoor
Hossein Dargahi
Jalal Saeidpour
Publikationsdatum
01.12.2025
Verlag
BioMed Central
Erschienen in
BMC Nursing / Ausgabe 1/2025
Elektronische ISSN: 1472-6955
DOI
https://doi.org/10.1186/s12912-025-02801-x