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BMC Nurs
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BioMed Central London

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10.1186/s12912-024-02329-6
Research
The association between occupational stress, sleep quality and premenstrual syndrome among clinical nurses
Wang Xin 1
Ge Yuanhui 2
Liu Yuxiu 2
Hu Wei 2
Wang Yuecong 3
Yu Shanshan jinmaoer@jlu.edu.cn

4
1 Department of Nursing, Huaian Hospital of Huaian City, Huaian, China
2 https://ror.org/02yd1yr68 grid.454145.5 0000 0000 9860 0426 Department of Nursing, Jinzhou Medical University, Jinzhou, China
3 https://ror.org/04mvpxy20 grid.411440.4 0000 0001 0238 8414 Department of Nursing, Huzhou University, Huzhou, China
4 https://ror.org/034haf133 grid.430605.4 0000 0004 1758 4110 Department of Hematology, The First Hospital of Jilin University, Changchun, China
18 9 2024
18 9 2024
2024
23 6614 7 2024
5 9 2024
© The Author(s) 2024
2024
https://creativecommons.org/licenses/by-nc-nd/4.0/ Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
Objective

Premenstrual Syndrome is also known as premenstrual tension syndrome because of the pronounced premenstrual mental and emotional anomalies. This study focuses on the association between occupational stress, sleep quality and premenstrual syndrome in clinical nurses and the mediating role of sleep quality.

Methods

A cross-sectional study was conducted to measure occupational stress, sleep quality and premenstrual syndrome in 415 clinical nurses using the Chinese Nurses Stressor Scale, the Pittsburgh Sleep Quality Index Scale, and the Premenstrual Syndrome Scale. SPSS was used to explore the relationship between the variables, and AMOS was used to explore the mediating role between the variables.

Results

Nurses’ occupational stress positively predicted PMS (β = 0.176, p < 0.001), and the regression coefficients for sleep quality were significantly different for both paths of nurses’ occupational stress (β = 0.665, p < 0.001) and PMS (β = 0.261, p < 0.001). The mediation effect accounts for 49.57% of the total effect.

Conclusion

This study revealed a notably high incidence of PMS among clinical nurses in China, with occupational stress and sleep quality significantly correlated with PMS. Sleep quality played an intermediary role between occupational stress and PMS. Consequently, managers should prioritize addressing occupational stress, mitigating PMS symptoms, enhancing nurses’ health and nursing quality, and preventing nursing risks through mental health support and improving sleep quality.

Keywords

Clinical nurses
Premenstrual syndrome
Sleep quality
Occupational stress
Mediating effect
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pmcBackground

Premenstrual Syndrome (PMS) refers to a comprehensive syndrome characterized by cyclic changes in spiritual, physical, and behavioral aspects that occur during the luteal phase of the menstrual cycle (specifically 7–14 days before menstruation) in women of reproductive age [1]. Anxiety, lack of concentration, abdominal and breast pain, and irritability are the main symptoms, which are alleviated after menstruation [1]. Globally, approximately 47.8% of women of childbearing age suffer from PMS [2], a condition that can adversely impact their work performance to varying degrees [3]. Research has highlighted that PMS is more prevalent among working women, and the nature of one’s occupation is intimately tied to both the occurrence and severity of PMS symptoms [4]. Notably, in China, an overwhelming 96.6% of professional nursing personnel are women [5], emphasizing the importance of understanding and addressing PMS in this critical workforce. As a special group of women of childbearing age, nurses are under increasing competitive pressure in society, and the potential cumulative effects of PMS on their physical and mental well-being are significant and cannot be ignored [6].

Occupational Stress is a state of physical and mental stress that occurs when practitioners are faced with an imbalance between occupational demands and their perceptions and a mismatch between their work abilities in an occupational setting [7]. Nurses are already one of the three groups with the highest occupational stress [8]. Nursing staff, as the cornerstone of nursing career development, face persistent high workloads that frequently result in a sudden surge of work pressure, this sustained stress can lead to job burnout and occupational fatigue, posing a significant challenge to the progress and well-being of the nursing profession [9]. The study has shown a connection between stress and the initiation and advancement of PMS in women [10]. The etiology and pathogenesis of PMS are not clearly defined, and clinical practice focuses on symptomatic treatment. However, with the rise of the biopsychosocial medicine model, the leading roles of psychological, as well as sociocultural factors, in the onset, development, and transformation of PMS have gradually gained attention. It has been found that women are prone to negative emotions and avoidance attitudes when faced with negative stressful life events, which indirectly act on the route of operation of the hypothalamic-pituitary-ovarian axis, leading to disorders of hormone metabolism in the body, and subsequently inducing or exacerbating PMS [11]. Therefore, as a group of nurses with high occupational stress, it is crucial to comprehend the status and correlation of PMS in nurses.

Sleep is the fundamental physiological requirement for human survival, and a sound sleep state effectively alleviates both physical and mental exhaustion, regulates the body’s immune system, and enhances overall physical and mental wellbeing [12]. The quality of sleep directly influences an individual’s work performance, quality of work, and productivity [13]. Nursing shifts are often irregular, characterized by a high prevalence of night shifts and intensified workloads, thereby rendering nurses a vulnerable group prone to poor sleep quality [14]. Multiple factors contribute to nurses’ sleep quality, including depression, fatigue, and alterations in lifestyle. Notably, occupational stress stands out as a significant factor that cannot be overlooked [15, 16]. Furthermore, a Korean study also underscored the significance of healthy sleep hygiene in managing dysmenorrhea and PMS. Poor subjective sleep quality, prolonged sleep latency, recurrent sleep disturbances, increased daytime dysfunction, and frequent reliance on sleeping aids were identified as components of sleep quality that exacerbate dysmenorrhea and PMS [17].

Currently, the majority of research on PMS primarily focuses on university students [18, 19], with relatively limited studies investigating the prevalence of PMS among nursing staff and its associated occupational factors. A study by Chen et al. in 2022 showed that the incidence of PMS in emergency nurses was 67.64%, and PMS symptoms were positively correlated with occupational stress and anxiety scores, while negatively correlated with educational level [20]. A 2023 study by Li et al. identified several predictors of PMS in nurses, including tea or coffee consumption, trait coping styles, anxiety, depression, and perceived stress levels [6]. Prior studies conducted by Hungarian scholars on PMS in women have demonstrated that those experiencing higher levels of perceived stress are more likely to suffer from PMS [10]. Similarly, Turkish researchers have uncovered that sleep quality significantly influences the occurrence of PMS among medical and nursing students [21]. Consequently, this study hypothesizes that sleep quality serves as a mediating factor between occupational stress and the onset of PMS.

In summary, this study aims to investigate the relationship between occupational stress, sleep quality and PMS among clinical nurses, and whether sleep quality serves as a mediator between occupational stress and the occurrence of PMS. It is hoped that nursing managers can take effective measures from the perspective of occupational stress and sleep quality, provide a new direction for the management of nurses in clinical work, and provide a theoretical basis for clinical nurses to carry out targeted preventive healthcare measures in the premenstrual period.

Methods

Study design

The study was a cross-sectional investigation.

Sample and data collection

This study adopted a convenient sampling method and selected nurses from 26 departments of a tertiary hospital in Huaian City, Jiangsu Province as the study participants. The survey was conducted from September 2023 to October 2023. Inclusion criteria: (1) Female nurses with the qualification of nurse practitioner; (2)18–45 years old; (3) Regular menstrual cycle; (4) Informed consent and voluntary participation in this study. Exclusion criteria: (1) Menopausal individuals; (2) Pregnant women; (3) Individuals who had used hormones, contraceptive pills, and other medication in the last three months. The study was approved by the hospital administration and relevant department heads prior to its execution, ensuring that the research content adhered to ethical principles. The paper version of the questionnaire was distributed face-to-face. There are clear guidelines at the beginning of the questionnaire, and the investigators will introduce the basic information of the questionnaire in detail during the questionnaire issuance process. Clinical nurses will conduct self-assessment based on their full understanding of the relevant contents of the questionnaire. The investigators recovered the questionnaires on the spot after the nurses completed them and checked that they were filled in in a timely manner.

The questionnaire for this study comprised a total of 32 variables. According to the rough estimation of the sample size method proposed by Kendall [22], the sample size should be at least 5–10 times the number of variables. Taking into account the potential convenience sampling error and a 20% sample loss, the required sample size should range between 192 and 384. In this study, 450 questionnaires were distributed, and 426 were collected. After excluding invalid questionnaires with substandard answers and those with more than average consecutive identical responses [23], a total of 415 valid questionnaires were finally obtained, yielding a validity rate of 92.2%.

Measures

General information questionnaire

It was designed by the researchers and included age, marital status, education, professional title, working department, presence of night shifts, and average monthly income.

Chinese Nurses Stressor Scale(CNSS)

The scale was developed by Li in 2000 [24]. It is the most commonly utilized instrument to measure occupational stress among nurses in China and comprises 35 items distributed across 5 dimensions: nursing specialty and nursing work (7 items), time distribution and work quantity (5 items), work environment and equipment (3 items), nursing care of patients (11 items), and management and interpersonal relations (9 items). A 4-point Likert scale was used, ranging from “no stress” to “severe stress” on a scale of 1–4, with a total possible score of 35–140, where higher scores signify elevated levels of stress. Of these, 36–70 are classified as mild stress, 71–105 as moderate stress, and 106–140 are classified as severe stress. The Cronbach’s α coefficient of the scale in this study was 0.932, the KMO value was 0.957, and the approximate chi-square value of Bartlett’s test of sphericity was 5355.236 (p < 0.001), indicating good reliability and validity.

Pittsburgh Sleep Quality Index (PSQI)

The scale was developed by Buysse et al. in 1989 [25]. It is a commonly used scale for the summative assessment of sleep quality and quantity, allowing for the evaluation of the quality of sleep of the study participants in the past month. It comprises 18 self-assessment items and 5 other-assessment items, with scores ranging from 0 to 21. It consists of 7 dimensions: subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbance, use of sleep medication, and daytime dysfunction, and 5 other rated items are not involved in the scoring. A higher score indicates poorer sleep quality. A total PSQI score greater than 7 indicates poor sleep quality. The Chinese version of the PSQI scale has undergone good reliability and validity analysis [26]. The Cronbach’s α coefficient of the scale in this study was 0.834, the KMO value was 0.838, and the approximate chi-square value of Bartlett’s test of sphericity was 769.583(P<0.001), indicating good reliability and validity.

Premenstrual Syndrome Scale (PSS)

The scale was developed by Zhao [27] based on Bancroft’s diagnostic criteria [28] and serves as a simple and rapid screening tool for PMS, which is more commonly used in China. A total of 12 physical and psychological symptoms related to PMS were used to investigate the symptoms in women during the 14 days preceding their most recent menstrual period. These symptoms include excitability, depression, anxiety, bloating and diarrhea, inattention, lethargy, nervousness, fidgeting, migraine, insomnia, hand and foot swelling, and neuroticism. A 4-point Likert scale ranging from 0 (no symptoms) to 3 (symptoms so severe that they interfere with life, school, work, and require treatment) was employed, with a total possible score of 0–36. A score of < 6 indicates no symptoms, 6–10 indicates mild PMS, 11–20 indicates moderate PMS, and > 20 indicates severe PMS. The Cronbach’s α coefficient for the PSS was 0.862 in previous studies, while in this study, it was 0.855. Additionally, the KMO value was 0.902, and the approximate chi-square value of Bartlett’s test of sphericity was 1144.867 (P < 0.001), all indicating good reliability and validity.

Data analysis

The study analyzed the data using SPSS 27.0 and AMOS 24.0. Descriptive statistics were employed to estimate the general characteristics of the participants and the means of the variables. The Pearson correlation coefficient was utilized to investigate the correlation between occupational stress, sleep quality, and PMS. A structural equation model (SEM) was employed to test the mediating effect of sleep quality between occupational stress and PMS. Furthermore, the fit indices [29] (including the chi-square degrees of freedom ratio, goodness-of-fit index, adjusted goodness-of-fit index, incremental fit index, comparative fit index, non-normal fit index, and root mean square error of approximation) were used to assess the fit of the model. A p-value of < 0.05 was considered statistically significant.

Ethics approval

The Ethics Committee of Jinzhou Medical University approved this study (approval number: JZMULL2023105). All participants have completed and signed an informed consent form. The research procedures complied with the ethical standards of the Declaration of Helsinki.

Results

General characteristics

A total of 415 nurses completed questionnaires for the statistical analysis. This study showed that nurses aged 26–30 years old (N = 128, 30.8%), married nurses (N = 266, 64.1%), nurses with bachelor’s degree or above (N = 297, 71.6%), nurse practitioners (N = 158, 38.1%), internal medicine nurses (N = 158, 38.1%), night shift nurses (N = 260, 62.7%), with an average monthly income of more than 5000 yuan (N = 295, 71.1%), moderate occupational stress (N = 211, 50.9%), poor sleep quality (N = 232, 55.9%), and mild PMS (N = 209, 50.4%), which had a high percentage of general characteristics. See Table 1 for details.

Table 1 General characteristics of participants (N = 415)

Characteristics	Categories	N	%	
Age(years)	18–25	67	16.1	
26–30	128	30.8	
31–35	108	26.0	
36–40	63	15.2	
41–45	49	11.8	
Marital status	Unmarried	129	31.1	
Married	266	64.1	
Divorced or widowed	20	4.8	
Education	Junior college degree and below	118	28.4	
Bachelor’s degree and above	297	71.6	
Professional title	Nurse	71	17.1	
Nurse Practitioner	158	38.1	
Supervisor Nurse	152	36.6	
Associate Nurse Practitioner and above	34	8.2	
Working department	Internal medicine	158	38.1	
Surgery	156	37.6	
Emergency	35	8.4	
Gynaecology and paediatrics	41	9.9	
ICU Intensive care unit	25	6.0	
Having night shift	No	155	37.3	
Yes	260	62.7	
Average monthly income (RMB)	<5000	120	28.9	
≥ 5000	295	71.1	
Occupational stress	Mild stress	181	43.6	
Moderate stress	211	50.9	
Severe stress	23	5.5	
Sleep quality	≤ 7	183	44.1	
>7	232	55.9	
PMS	No	132	31.8	
Mild	209	50.4	
Moderate	69	16.6	
Severe	5	1.2	

Occupational stress, sleep quality and PMS of participants

The total occupational stress score of clinical nurses was (73.83 ± 18.18), the total sleep quality score was (8.30 ± 4.16), and the total PMS score was (7.00 ± 4.73). See Table 2 for details.

Table 2 Stress, sleep quality and PMS of nurses (n = 415)

Variables	Score range	Mean	SD	
Total score of occupational stress	35–140	73.83	18.18	
Time distribution and work quantity	1–4	2.23	0.57	
Management and interpersonal relations	1–4	2.12	0.60	
Nursing care of patients	1–4	2.10	0.55	
Work environment and equipment	1–4	2.09	0.70	
Nursing specialty and nursing work	1–4	2.02	0.51	
Total score of sleep quality	1–19	8.30	4.16	
Daytime dysfunction	0–3	1.60	0.95	
Sleep disturbance	0–3	1.31	0.86	
Sleep latency	0–3	1.29	0.84	
Sleep duration	0–3	1.27	0.79	
Subjective sleep quality	0–3	1.25	0.96	
Habitual sleep efficiency	0–3	1.05	0.81	
Use of sleep medication	0–3	0.53	0.66	
Total score of PMS	0–29	7.00	4.73	
Excitable	0–3	0.85	0.70	
Anxiety	0–3	0.73	0.70	
Nervousness	0–2	0.65	0.59	
Inattention	0–3	0.63	0.67	
lethargy	0–3	0.60	0.69	
Bloating and diarrhoea	0–3	0.58	0.72	
Depression	0–3	0.56	0.66	
Neuroticism	0–3	0.53	0.61	
Hand and foot swelling	0–3	0.52	0.57	
Migraine	0–2	0.49	0.62	
Insomnia	0–2	0.49	0.56	
Fidgeting	0–2	0.41	0.53	
Abbreviations: SD, standard deviation.

Correlational analysis of variables

Clinical nurses’ sleep quality was positively correlated with occupational stress (r = 0.437, p < 0.01), sleep quality showed a positive correlation with PMS (r = 0.578, p < 0.01), occupational stress showed a positive correlation with PMS (r = 0.492, p < 0.01). The results are displayed in Table 3.

Table 3 Correlational analysis of variables (n = 415)

Variables	Sleep Quality	Occupational Stress	PMS	
Sleep Quality	 1			
Occupational Stress	0.437**	1		
PMS	0.578**	0.492**	1	
∗∗Significant correlation at 0.01 level (bilateral).

Common method deviation check

The Harman single-factor test was utilized in this study. All variables were included in the analysis to test the results of non-rotational factor analysis. The analysis revealed 12 factors with eigenvalues exceeding 1. The first factor accounts for 19.07% of the total variance, which falls below the critical threshold of 40%. Consequently, there are no substantial methodological deviations in this study.

The mediating role of sleep quality

As depicted in Fig. 1, a structural equation model was constructed with occupational stress as the predictor variable, sleep quality as the mediator variable, and PMS as the outcome variable. The Amos bias-corrected non-parametric percentile bootstrap program was utilized to evaluate the significance of the mediating effect. A random sample of 2000 observations was drawn from the original sample (n = 415) to mitigate the risk of Type I errors in statistical inference. The results indicate a good fit of the model, as detailed in Table 4.

Nurses’ occupational stress positively predicted PMS (β = 0.176, p < 0.001), and the regression coefficients for sleep quality were significantly different for both paths of nurses’ occupational stress (β = 0.665, p < 0.001) and PMS (β = 0.261, p < 0.001). See Table 5; Fig. 1 for details.

Sleep quality played an indirect predictive role in the effect of occupational stress on PMS in nurses with a standardized path coefficient of (0.665)*(0.261) = 0.173. The total effect value of occupational stress on PMS was (0.173 + 0.176) = 0.349. The results indicated that sleep quality played a partial mediating role between occupational stress and PMS, with a mediating effect of 49.57% of the total effect. See Table 6 for details.

Table 4 Structural equation model fit index (n = 415)

Fit index	CMIN/DF	GFI	IFI	TLI	CFI	AGFI	RMSEA	
Judgment criteria	<5	>0.8	>0.8	>0.8	>0.8	>0.8	≤ 0.08	
Measured value	2.278	0.892	0.931	0.923	0.930	0.870	0.056	
The chi-square degrees of freedom ratio (CMIN/DF), goodness-of-fitindex (GFI), adjusted goodness-of-fit index (AGFI), incremental fit index (IFI), comparative fit index (CFI), non-normal fit index (TLI), and root mean square error of approximation(RMSEA).

Table 5 Estimated parameters and 95% CI between occupational stress, sleep quality and PMS of nurses (n = 415)

Path	Estimate	S.E.	C.R.	P	
Sleep quality<---occupational stress	0.665	0.073	9.160	p<0.001	
PMS<---sleep quality	0.261	0.035	7.393	p<0.001	
PMS<---occupational stress	0.176	0.036	4.888	p<0.001	

Table 6 Total, direct and indirect effects of the pathway model

	Effect value	Lower	Upper	P	Effect proportion	
Total effect	0.349	0.267	0.432	0.001		
Direct effect	0.176	0.106	0.254	0.001	50.43%	
Indirect effect	0.173	0.124	0.234	0.001	49.57%	
The bootstrap method estimates the standard error of indirect effects and the lower and upper limits of 95% confidence intervals.

Fig. 1 A mediated model of occupational stress, sleep quality and PMS of nurses. Note: CNSS: Chinese Nurses Stressor Scale. PSQI: Pittsburgh Sleep Quality Index. PSS: Premenstrual Syndrome Scale

Discussions

The results of this study showed that the total occupational stress score of clinical nurses was (73.83 ± 18.18), which was moderate according to the scale rating criteria and lower than the results of the study by Wu et al. [30]. It may be because the workplace of the subjects of this study is a small tertiary hospital, which is less intensive than top-ranking hospitals, thus resulting in a relatively low level of occupational stress. Among them, time distribution and work quantity allocation scored the highest, probably because the concept of “patient-centered” nursing has become increasingly popular, the demands on the quality of nurses’ work have become higher and more difficult, and the occupational pressure faced by nurses has also increased. It also illustrates the inadequacy of nursing human resources and the lack of adequate protection for nurses.

The total score of sleep quality was (8.30 ± 4.16), and 55.9% of the nurses had poor sleep quality, indicating that clinical nurses had prominent sleep problems, which was similar to the results of the study by Wang [31]. The daytime dysfunction dimension has the highest score, which may be related to the “shift system” work pattern that makes nurses prone to biological rhythm and endocrine disturbance, resulting in affected sleep quality [32]. It is suggested that nursing managers should prioritize the negative effects of sleep quality on nurses and arrange working hours reasonably considering individual characteristics.

The total score of PMS was (7.00 ± 4.73), and the prevalence of PMS among nurses in this study was 68.2% (mild: 50.4%, moderate: 16.6%, and severe: 1.2%), which was high compared to the prevalence of PMS among 18–25 year old females in Turkey (49.2%) [33], and was close to the prevalence of PMS among female university students in China (67.0%) [18]. In this study, nurses with PMS had more psychiatric symptoms than somatic symptoms and psychiatric symptoms were dominated by symptoms of excitability and anxiety. It suggests that the mental state of nurses should be paid attention to, and it is important to explore new management methods to reduce the mental influence of PMS in nurses. This includes providing regular mental health education and training specifically for PMS, in order to enhance nurses’ cognition and coping abilities. Additionally, implementing flexible working arrangements can help reduce the physical and mental burden on nurses. Strengthening team communication and cooperation is also crucial, so that nurses can receive support and assistance from their colleagues when facing PMS symptoms. Furthermore, the hospital should consider setting up a relaxation area, equipped with yoga mats, meditation music, and other facilities, and encourage nurses to engage in relaxation training, such as deep breathing and meditation, during breaks to alleviate tension.

This study found a positive correlation between occupational stress and sleep quality among clinical nurses, which supports the results of Yu et al. [34]. This means that the more occupational stress felt by clinical nurses, the poorer their sleep quality. When individuals are continuously stimulated by occupational stress and fail to experience high-quality sleep over a long period, role conflict and loss of coping control can gradually develop [35]. In China’s tense medical environment, clinical nurses, due to the specificity of their work and societal expectations, have to stand for long periods during their shifts. The alarm fatigue from various instruments and equipment, combined with the impact of the “shift system” work pattern, generates significant occupational stress and markedly affects their sleep quality. Chronic sleep deprivation among clinical nurses may lead to slower reactions, impaired thinking, and depersonalization, making them more vulnerable to nursing errors and medical malpractice [36]. It is suggested that nursing managers should provide clinical nurses with decompression training and psychological support in time, improve and reduce the degree of physical and mental stress of nurses from multiple angles, and promote the occupational health of nurses.

Secondly, the study demonstrated a positive association between sleep quality and PMS in clinical nurses, the worse the quality of sleep, the more severe the degree of PMS. The findings align with prior studies on female medical students [37] and Korean high school students [17]. Good sleep can relieve PMS-related symptoms and anxiety, improve learning and work efficiency, and enhance physical health. On the contrary, Poor sleep quality can cause dysfunction of the neuroendocrine system (hypothalamic-pituitary-ovarian axis) and disruption of estrogen and progesterone secretion, increase the number of awakenings, and reduce sleep efficiency, which directly predicts the severity of PMS. It leads to their emotional instability and makes them more prone to all kinds of physical discomforts. Sleep is recognized as an important variable in PMS interventions [38], progesterone therapy and vitamin supplementation are also commonly used clinically to reduce PMS symptoms [39]. It is suggested that high-quality sleep management for clinical nurses should receive more attention and that nursing managers should rationalize the frequency and number of night shifts.

Furthermore, this research demonstrated a direct correlation between occupational stress and the incidence of PMS among clinical nurses. This was consistent with the findings of Sun et al. that stress is a major contributor to PMS [40]. When Yi et al. investigated the incidence of PMS and its influencing factors in 143 female college students, they found that the severity of PMS was directly related to stress and that individual stress, depression, and dietary attitudinal problems all led to an increased likelihood of PMS [19]. Nursing staff experience high occupational stress due to workload, high-intensity and high-risk work characteristics, complex interpersonal relationships, patient care, and other factors [41]. This stressful environment may cause nurses to experience emotional fluctuations and trigger physical and mental tension responses. When these reactions become too strong or persistent, exceeding the individual’s ability to self-regulate, they may lead to a series of pathological signs that ultimately affect both physical and mental health, including increasing the risk of PMS.

This study showed that sleep quality mediates the relationship between occupational stress and the development of PMS in clinical nurses, with a mediation effect value of 0.173 and a mediation effect of 49.57% of the total effect. That is, occupational stress can influence the occurrence or aggravation of PMS in clinical nurses through sleep quality.

Clinical nurses, as a special category of people in their profession, face all kinds of patients every day and are under the high pressure of high work intensity and heavy workload for a long time. The overloaded workload and rigorous nature of the job inevitably affect the quality of sleep. The organism is prone to symptoms such as easy fatigue, poor concentration, memory loss, and emotional instability due to poor sleep quality [42]. The circadian rhythm of sleep affects the regularity and function of the reproductive system and has important implications for women’s health. Therefore, poor sleep quality due to occupational stress felt by clinical nurses, indirectly increases the occurrence of PMS, both physically and psychologically, which seriously affects the efficiency of clinical nurses and increases the occurrence of nursing risk events. Nurses themselves can prevent or alleviate PMS by regulating negative emotions and routines, being physically active, and taking vitamin supplements. Nursing managers can help them release stress by carrying out targeted health education and preventive health care measures, rationalizing shift scheduling, enhancing nursing interpersonal resources, improving treatment, and paying more attention to whether nurses have sleep problems and their mental state, to reduce the incidence of PMS and thus maintain physical and mental health.

There are some limitations to this study: Firstly, this study suffers from the inherent shortcomings of cross-sectional studies such as recall bias and difficulties in inferring causal conclusions. Secondly, the questionnaire was selected using a convenience sampling method, which may have affected the representativeness of the sample. Finally, the survey object of this study was confined to a single hospital in Huaian City, Jiangsu Province, which may limit the generalizability of the findings to clinical nurses nationwide. The sampling scope thus requires further expansion. Furthermore, the study did not differentiate between job roles, such as shift workers versus full-time employees, managers versus general staff. As such, differences in work pressure and time arrangements, which can significantly impact sleep quality by, for instance, disrupting sleep-wake cycles or causing chronic stress, may not have been fully captured. Therefore, the results may not be entirely comprehensive. It is recommended that future research endeavors analyze the specific causes of differences by job position and develop targeted intervention strategies for hospital administrators to enhance nurses’ working environment, job satisfaction, and ultimately, sleep quality.

Conclusions

This study demonstrated a high incidence of PMS among clinical nurses. There was a significant interaction between occupational stress, sleep quality and PMS, with sleep quality mediating the relationship between occupational stress and PMS. This is of great significance to carry out and deepen the research on the relationship between occupational stress and PMS among clinical nurses. This suggests that while paying attention to the physical health of nurses, managers should attach great importance to the influence of psychosocial factors such as occupational stress, and comprehensively improve the occupational environment and health status of nurses by implementing specific strategies such as stress reduction training, optimizing the scheduling system, providing mental health support, and improving sleep quality, thereby reducing the occurrence of PMS and improving the level of health management. And ensure the quality of nursing, thus providing strong support for the overall development of nursing and avoiding nursing risk events.

Acknowledgements

We extend our profound appreciation to all participants who contributed to our study. Furthermore, we warmly thank the reviewers for their insightful feedback and the editorial team for their diligent efforts.

Author contributions

All authors contributed to the study conception and design. X-W drafted the initial manuscript and performed the data analysis. YH-G, YX-L, W-H and YC-W were responsible for material preparation and data collection. SS-Y made key modifications to the manuscript to enhance its academic content. All authors have reviewed and approved the final manuscript.

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Data availability

The data included in this study are available from the corresponding author upon reasonable request.

Declarations

Ethics approval and consent to participate

The Declaration of Helsinki was adhered to during this study. All eligible participants completed written informed consent forms before the study phase. The study was approved by the Ethics Committee of Jinzhou Medical University (JZMULL2023105).

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Publisher’s note

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