Insomnia Severity Among Anesthesia Nurses in a Resource-Limited Province of Southwest China: A Cross-Sectional Study

Insomnia Severity Among Anesthesia Nurses in a Resource-Limited Province of Southwest China: A Cross-Sectional Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Insomnia Severity Among Anesthesia Nurses in a Resource-Limited Province of Southwest China: A Cross-Sectional Study Jia Fu, Yan Chen, Jiaying Han, Jiyun Meng, Chunfei Wei, Yan Jiang, and 12 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9035718/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Background: Anesthesia nurses are exposed to sustained occupational stress, shift work, and high clinical demands, which may increase the risk of sleep disturbance. However, limited evidence has specifically examined insomnia severity and its psychological correlates within this specialty, particularly in resource-constrained regions of China. Methods: A cross-sectional survey was held between December 2025 and January 2026 among 444 anesthesia nurses in Guizhou Province, China. Participants completed validated instruments assessing sleep-related worry, self-regulatory fatigue, perceived stress, insomnia severity (Athens Insomnia Scale), and perceived social support. Descriptive statistics, independent-samples tests, Pearson correlation analysis, and stepwise multiple linear regression were performed. Results: A substantial proportion of participants reported clinically significant insomnia symptoms. Insomnia severity was positively correlated with sleep-related worry (r = 0.794), self-regulatory fatigue (r = 0.728), and perceived stress (r = 0.903) (all P < 0.001), and negatively correlated with perceived social support (r = − 0.303, P < 0.001). In multiple regression analysis, sleep-related worry (β = 0.644, P < 0.001), self-regulatory fatigue (β = 0.386, P < 0.001), and perceived stress (β = 0.338, P < 0.001) were significant positive predictors of insomnia severity, whereas perceived social support was a significant negative predictor (β = −0.222, P < 0.001). The final model explained 51.1% of the variance. Conclusions: Insomnia severity is highly prevalent among anesthesia nurses and is strongly associated with cognitive worry, stress perception, and self-regulatory fatigue. Enhancing organizational support and implementing stress-targeted interventions may contribute to the improvement of sleep health in this population. Longitudinal studies are taken to clarify causal pathways. Trial registration Not applicable. Anesthesia nurses Sleep-related worry Perceived stress Self-regulatory fatigue Social support Cross-sectional study Background The department of anesthesiology undertakes emergency care and perioperative management of critically ill patients. This specialty requires advanced technical expertise, high-precision monitoring equipment, and sustained vigilance. Consequently, anesthesiology is characterized by substantial occupational risk and high work intensity [ 1 – 3 ] . Anesthesia nurses frequently assist in multiple concurrent surgical procedures, manage emergency case insertions, and provide perioperative nursing care. They must remain highly alert to respond promptly to hemodynamic instability and airway emergencies while simultaneously conducting postoperative pain management and monitoring for adverse events. These cumulative responsibilities impose sustained cognitive and emotional demands. Shift work and night shifts are common in anesthesiology and are known to disrupt circadian rhythms and sleep architecture [ 4 ] . Many anesthesia nurses report difficulty initiating sleep, frequent nocturnal awakenings, and non-restorative sleep. Sleep disturbance may interact bidirectionally with psychological stress, potentially impairing cognitive function, reducing alertness, and affecting clinical decision-making capacity [ 5 ] , thereby posing risks to perioperative patient safety. Previous studies have demonstrated substantial psychological burden among operating room nurses [ 6 ] . In Guizhou Province, uneven distribution of medical resources and shortages of healthcare personnel may further intensify occupational demands. Some anesthesia nurses participate in cross-regional clinical support and technical training, which may increase workload and professional uncertainty [ 7 ] . Although anxiety and sleep problems among healthcare workers in China have been documented [ 8 ] , relatively few studies have focused specifically on anesthesia nurses. Moreover, limited research has simultaneously incorporated specialty-related stressors and regional healthcare disparities into a unified analytical framework [ 9 ] . Therefore, this study aimed to assess insomnia severity among anesthesia nurses in Guizhou Province and to examine its associations with sleep-related worry, self-regulatory fatigue, perceived stress, and perceived social support. Methods Study Design and Participants This cross-sectional study was conducted between December 2025 and February 2026. A structured anonymous electronic questionnaire was distributed to anesthesia nurses working in tertiary and selected secondary hospitals in Guizhou Province. Eligible participants were registered nurses working in anesthesia-related positions with at least six months of continuous clinical experience and at least three months of night shift or rotating shift experience. Nurses undergoing short-term training, those detached from front line clinical duties, and those previously diagnosed with severe psychiatric disorders or currently using sedative-hypnotic medications were excluded. Ethical approval was obtained from the Ethics Committee of Guiyang Fourth People’s Hospital. The first page of the questionnaire described the study objectives, procedures, confidentiality measures, and voluntary nature of participation. Electronic informed consent was obtained prior to survey access. All data were anonymized and stored in coded form for research purposes only. Measures Sociodemographic and Occupational Characteristics A self-developed questionnaire collected 22 items, including sex, age, ethnicity, marital status, education level, employment type, professional title, years of work experience, hospital level, night shift frequency, weekly overtime hours, experience of workplace violence, electronic device use before sleep, caffeine consumption habits, history of anxiety or depression, and self-rated health status. Sleep-Related Worry Scale Sleep-related worry was measured using the Chinese version of the Sleep-Related Worry Scale [ 10 ] , developed based on Harvey’s cognitive model of insomnia and the Anxiety and Preoccupation about Sleep Questionnaire. The scale contains 10 items across two dimensions: worry about sleep consequences and worry about uncontrollability of sleep. Items are rated on a 5-point Likert scale, with total scores ranging from 10 to 50. Higher scores indicate greater sleep-related worry. The scale has demonstrated good reliability and structural validity in insomnia patients and shift-working nurses. Self-Regulatory Fatigue Scale Self-regulatory fatigue was measured using the Chinese revised version of the Self-Regulatory Fatigue Scale (SRF-S), based on ego depletion theory proposed by Baumeister et al. The scale comprises 16 items across cognitive, emotional, and behavioral dimensions. Each item is rated on a 5-point Likert scale. Higher scores reflect greater self-regulatory fatigue. Previous studies have reported satisfactory reliability (Cronbach’s α > 0.80) [ 11 ] . Perceived Stress Scale Perceived stress was evaluated using the 10-item Perceived Stress Scale (PSS-10) [ 12 ] . Items are rated on a 5-point Likert scale from 0 (never) to 4 (very often), with total scores ranging from 0 to 40. Higher scores indicate greater perceived stress. The Chinese version has demonstrated good psychometric properties in healthcare populations [ 13 ] . Athens Insomnia Scale Insomnia severity was assessed using the Athens Insomnia Scale (AIS) [ 14 ] . The AIS consists of eight items evaluating sleep induction, awakenings, early morning awakening, total sleep duration, overall sleep quality, and daytime functioning. Each item is rated on a 4-point scale (0–3), yielding total scores ranging from 0 to 24. Higher scores indicate more severe insomnia. The AIS has demonstrated reliable diagnostic accuracy and reliability [ 15 , 16 ] . Multidimensional Scale of Perceived Social Support Perceived social support was evaluated using the Chinese version of the Multidimensional Scale of Perceived Social Support (MSPSS) [ 17 ] . The scale includes 12 items across family, friends, and significant other support dimensions. Items are rated on a 7-point Likert scale, with total scores ranging from 12 to 84. Higher scores indicate greater perceived social support. The Chinese version has demonstrated strong reliability and structural validity [ 18 ] . Statistical analysis Statistical analyses were conducted using SPSS software. Descriptive statistics summarized participant characteristics and scale distributions. Independent-samples t tests and one-way analysis of variance were used to compare differences in insomnia severity across subgroups. Pearson correlation analysis examined associations between insomnia severity and psychological variables. Variables with statistical significance in univariate analyses, together with core psychological variables, were entered into a stepwise multiple linear regression model to identify independent predictors of insomnia severity. Multicollinearity was assessed using variance inflation factors (VIF), with values < 5 indicating acceptable levels. A two-sided P value < 0.05 was considered statistically significant. Results Participant Characteristics A total of 444 anesthesia nurses participated. The majority were female (83.8%) and aged 30–40 years (50.9%). Half reported regular monthly night shifts. Most participants reported weekly overtime, and 8.6% had a prior diagnosis of anxiety or depression. The majority rated their health as good (72.5%) (Table 1 ). Table 1 Demographic and Occupational Characteristics of Participants (N = 444) Variable Category n (%) Sex Male 72 (16.2) Female 372 (83.8) Age (years) 40 100 (22.5) Employment Type Contract nurse 332 (74.8) Permanent staff 108 (24.3) Labor dispatch 4 (0.9) Monthly Night Shift Yes 222 (50.0) No 222 (50.0) Weekly Overtime None 192 (43.2) 20 h 15 (3.4) Diagnosed Anxiety/Depression Yes 38 (8.6) No 406 (91.4) Self-Rated Health Good 322 (72.5) Fair 116 (26.1) Poor 6 (1.4) Univariate Analysis Insomnia severity differed significantly by job satisfaction (F = 13.172, P < 0.001), monthly night shift status (t = 6.014, P = 0.015), weekly overtime hours (F = 9.094, P < 0.001), electronic device use before sleep (t = 7.109, P = 0.008), prior diagnosis of anxiety or depression (t = 26.644, P < 0.001), and self-rated health status (F = 42.273, P < 0.001) (Table 2 ). Additional demographic variables were not significantly associated (Supplementary Table S1 ). Table 2 Univariate Analysis of Significant Factors Associated With Insomnia-Related Worry Variable Category Mean ± SD t/F P value Job Satisfaction Very satisfied 13.53 ± 4.53 13.172 < 0.001 Moderate 15.92 ± 5.19 13.172 < 0.001 Dissatisfied 12.00 ± 5.65 13.172 < 0.001 Monthly Night Shift Yes 15.00 ± 5.52 6.014 0.015 No 13.86 ± 4.51 6.014 0.015 Weekly Overtime None 13.25 ± 4.41 9.094 < 0.001 < 10 h 15.03 ± 4.68 9.094 < 0.001 10–20 h 16.16 ± 6.94 9.094 20 h 18.13 ± 6.65 9.094 < 0.001 Electronic Device Use Yes 14.69 ± 4.97 7.109 0.008 No 13.00 ± 4.42 7.109 0.008 Diagnosed Anxiety/Depression Yes 18.26 ± 4.92 26.644 < 0.001 No 14.07 ± 4.77 26.644 < 0.001 Self-Rated Health Good 13.30 ± 4.23 42.273 < 0.001 Fair 17.09 ± 5.14 42.273 < 0.001 Poor 23.50 ± 6.50 42.273 < 0.001 Note:Detailed univariate results are presented in Supplementary Table S1 . Multiple Linear Regression Analysis Sleep-related worry (β = 0.644, P < 0.001), self-regulatory fatigue (β = 0.386, P < 0.001), and perceived stress (β = 0.338, P < 0.001) were independently associated with higher insomnia severity. Perceived social support was independently associated with lower insomnia severity (β = −0.222, P < 0.001). The final model explained 51.1% of the variance in insomnia severity (adjusted R² = 0.511) (Table 3 ). Table 3 Multiple Linear Regression Analysis of Factors Associated With Athens Insomnia Scale Score Variable B SE β t P value 95% CI Sleep-related worry total score 0.323 0.018 0.644 17.696 < 0.001 0.288–0.359 Self-regulatory fatigue total score 0.259 0.029 0.386 8.801 < 0.001 0.201–0.317 Perceived stress total score 0.303 0.04 0.338 7.561 < 0.001 0.224–0.382 Perceived social support total score −0.082 0.017 −0.222 −4.785 < 0.001 −0.115–−0.048 Note:Adjusted R² = 0.511 Correlation Analysis Insomnia severity was positively correlated with sleep-related worry (r = 0.794), self-regulatory fatigue (r = 0.728), and perceived stress (r = 0.903) (all P < 0.001). A negative correlation was observed between insomnia severity and perceived social support (r = − 0.303, P < 0.001) (Table 4 ). Table 4 Correlation Between Psychological Variables and Athens Insomnia Scale Score Variable Mean ± SD r P value Sleep-related worry total score 14.13 ± 4.92 0.794 < 0.001 Self-regulatory fatigue total score 15.41 ± 7.35 0.728 < 0.001 Perceived stress total score 24.16 ± 5.49 0.903 < 0.001 Perceived social support total score 59.76 ± 13.40 −0.303 < 0.001 Discussion This study demonstrated that insomnia severity is prevalent among anesthesia nurses in Guizhou Province. Approximately half of the variance in insomnia severity was explained by psychological and social variables. Consistent with prior research among nurses in high-acuity clinical settings [ 19 , 20 ] , occupational stress and fatigue were strongly associated with sleep disturbance. Recent latent profile analyses have identified co-occurring patterns of insomnia, fatigue, and psychological distress among hospital nurses [ 21 ] . The strong association between sleep-related worry and insomnia severity supports the cognitive model of insomnia [ 22 ] , which posits that maladaptive sleep-related cognitions increase cognitive arousal and disrupt sleep initiation and maintenance. Self-regulatory fatigue may reflect diminished emotional regulation capacity under prolonged stress exposure [ 11 ] . Perceived stress was a major correlate of insomnia severity. Although causal inferences cannot be drawn from this cross-sectional design, the findings suggest that stress perception may play an important role in sleep disturbance [ 22 ] . Perceived social support demonstrated a buffering association, consistent with previous evidence indicating that social resources mitigate stress-related sleep problems [ 23 , 24 ] . Regional disparities in healthcare resources in Guizhou Province may further amplify occupational strain. Cross-regional support duties and persistent night shifts may disrupt circadian rhythm stability [ 25 ] , potentially exacerbating insomnia severity. Comparing these findings with studies from other provinces in China and internationally, the prevalence of insomnia among anesthesia nurses in Guizhou appears higher than in urban tertiary hospitals in Eastern China, where prevalence rates ranged from 30–40% [ 26 , 20 ] . This difference may reflect the compounded effect of resource limitations, staffing shortages, and heavier on-call burdens in less developed regions. Internationally, studies in Europe and North America report insomnia prevalence among critical care nurses ranging from 25% to 50%, depending on work intensity and shift patterns [ 27 , 28 ] . The similarity in associations between occupational stress, fatigue, and insomnia across diverse healthcare systems suggests that the underlying mechanisms—cognitive arousal, stress perception, and circadian disruption—may be universally relevant. However, variations in work culture, nurse-to-patient ratios, and social support systems could modulate the magnitude of sleep disturbance. Moreover, comparative studies indicate that interventions such as structured stress management, resilience training, and shift scheduling optimization show efficacy in mitigating insomnia among nurses in higher-resource settings [ 29 – 31 ] . These findings highlight the potential for adopting targeted psychosocial and organizational interventions in Guizhou to address region-specific occupational challenges. In summary, while anesthesia nurses worldwide experience significant sleep disturbance related to occupational stress, the severity and contributing factors may be intensified in resource-limited regions. Future multi-center and longitudinal studies are needed to delineate these differences further and evaluate context-specific interventions. Limitations This study employed a cross-sectional design, precluding causal inference. All measures were self-reported and may be subject to recall and reporting bias. The sample was primarily drawn from tertiary hospitals and included a high proportion of female nurses, which may limit generalizability. Future longitudinal studies incorporating objective sleep assessments are warranted to further clarify the temporal relationships among psychological factors and insomnia severity. Conclusion Insomnia severity is prevalent among anesthesia nurses in Guizhou Province and is significantly associated with sleep-related worry, perceived stress, and self-regulatory fatigue, whereas perceived social support shows a protective association. These findings underscore the importance of addressing psychological stressors and strengthening organizational support systems to promote sleep health in this high-demand clinical specialty. Further longitudinal research is needed to clarify temporal relationships and inform targeted interventions. Abbreviations AIS Athens Insomnia Scale MSPSS Multidimensional Scale of Perceived Social Support PSS-10 Perceived Stress Scale SRF-S Self-Regulatory Fatigue Scale VIF Variance Inflation Factor Declarations Ethics approval and consent to participate This study was approved by the Ethics Committee of Guiyang Fourth People’s Hospital. Electronic informed consent was obtained from all participants prior to participation. All procedures performed were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. Consent for publication Not applicable, as the manuscript does not contain any individual person’s data. Competing interests The authors declare that they have no competing interests. Funding This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. Author Contribution J.F. and Y.C. contributed to study design, data collection, data analysis, and manuscript drafting. JY.H., JY.M., and CF.W. contributed to data analysis and interpretation. Y.J., ZM.F., H.F., X.C., H.H., Q.Z., GY.L., JR.Z., Y.C., YL.X., and SL.X. contributed to data collection and manuscript revision. QL.Y. and YQ.L. supervised the study, contributed to interpretation, and critically revised the manuscript. All authors read and approved the final manuscript. Acknowledgement The authors wish to thank the participating nurses and hospital staff for their cooperation and support during data collection. All authors would like to express their sincere gratitude to Professor Xiaokang Jia of Hainan Medical University for his valuable academic guidance and constructive suggestions in research design, data interpretation and manuscript revision. Data Availability The datasets generated and/or analysed during the current study are not publicly available due to privacy concerns but are available from the corresponding author on reasonable request. References Veale PM, Vayalumkal JV. McLaughlin K.Sickness presenteeism in clinical clerks: Negatively reinforced behavior or an issue of patient safety?[J]. Am J Infect Control. 2016;44(8):892–7. Lemos CdS,Poveda VdB. Role of perioperative nursing in anesthesia: a national overview[J]. Revista da Escola de Enfermagem da USP; 2022. p. 56. Totonchilar S, Aarabi A, Eftekhari N, et al. Examining workload variations among different surgical team roles, specialties, and techniques: a multicenter cross-sectional descriptive study[J]. Perioper Med (Lond). 2024;13(1):1. Ganesan S, Magee M, Stone JE, et al. The Impact of Shift Work on Sleep, Alertness and Performance in Healthcare. Workers[J] Sci Rep. 2019;9(1):4635. Xue Y, Wang WD, Liu YJ et al. Sleep disturbances in generalized anxiety Disorder: The central role of insomnia[J].Sleep Med,2025, 132:106545. Yang C, Cheng J, Xiao L et al. Current status and influencing factors of sleep-related worry among nurses in the department of anesthesiology: a cross-sectional study[J].BMC Nurs,2025, 24(1):197. Maryam ARA, Petro B, et al. Nurses Contribution in Research: Barriers and Solutions[J]. J Nurs Healthc. 2020;5(4):1–4. Yang X, Chen D, Chen Y, et al. Geographical distribution and prevalence of mental disorders among healthcare workers in China: A cross-sectional country-wide survey: A cross-sectional study to assess mental disorders of healthcare workers in China[J]. Int J Health Plann Manage. 2021;36(5):1561–74. Cheng J, Xia X, Hong M et al. Relationship between job burnout and presenteeism in anesthesia nurses: mediating effect of psychological capital[J].BMC Nurs,2024, 23(1):853. Jansson-Frojmark M, Harvey AG, Lundh LG, et al. Psychometric properties of an insomnia-specific measure of worry: the Anxiety and Preoccupation about Sleep Questionnaire[J]. Cogn Behav Ther. 2011;40(1):65–76. Zeng Q, Zhang Y, Liang H et al. The mediating role of self-regulatory fatigue on the relationship between insomnia and sleep-related worry among shift nurses: a cross-sectional study[J].BMC Nurs,2025, 25(1):105. Cohen S, Kamarck T. Mermelstein R.A global measure of perceived stress[J]. J Health Soc Behav. 1983;24(4):385–96. Wang Z, Chen J, Boyd JE et al. Psychometric properties of the Chinese version of the Perceived Stress Scale in policewomen[J].PLoS One,2011, 6(12):e28610. Soldatos CR, Dikeos DG, Paparrigopoulos TJA. Insomnia Scale: validation of an instrument based on ICD-10 criteria[J]. J Psychosom Res. 2000;48(6):555–60. Chiu HY, Chang LY, Hsieh YJ, et al. A meta-analysis of diagnostic accuracy of three screening tools for insomnia[J]. J Psychosom Res. 2016;87:85–92. Chung KF, Kan KK. Yeung WF.Assessing insomnia in adolescents: comparison of Insomnia Severity Index. Athens Insomnia Scale Sleep Qual Index[J] Sleep Med. 2011;12(5):463–70. Zimet GD, Powell SS, Farley GK et al. Psychometric characteristics of the Multidimensional Scale of Perceived Social Support[J].J Pers Assess,1990, 55(3–4):610–7. Ma CMS. Measurement Invariance of the Multidimensional Scale of Perceived Social Support Among Chinese and South Asian Ethnic Minority Adolescents in Hong Kong[J].Front Psychol,2020, 11:596737. Alameri RA, Almulla HA, Al Swyan AH et al. Sleep quality and fatigue among nurses working in high-acuity clinical settings in Saudi Arabia: a cross-sectional study[J].BMC Nurs,2024, 23(1):51. Cao Q, Wu H, Tang X et al. Effect of occupational stress and resilience on insomnia among nurses during COVID-19 in China: a structural equation modelling analysis[J].BMJ Open,2024, 14(7):e080058. Cho H, Sagherian K. Steege LM.Latent Profiles of Nurses' Insomnia, Fatigue, Recovery, Psychological Distress and Burnout During the COVID-19 Pandemic: Examining the Role of Organisational Support[J]. J Adv Nurs. 2026;82(3):2216–31. Palagini L, Hertenstein E, Riemann D, et al. Sleep, insomnia and mental health[J]. J Sleep Res. 2022;31(4):e13628. Nyaaba E, Abass K. Gyasi RM.Association of social support with sleep and subjective health outcomes in Ghanaian artisanal miners[J]. Sci Rep. 2025;15(1):43923. Xu L, Gao Y, Shi D et al. Social support moderates the relationship between sleep quality and mental health: A Chinese Fangcang shelter hospital-based study in asymptomatic COVID-19 carriers[J].Heliyon,2024, 10(11):e31782. Zhao H, Li Q, Huang H, et al. Circadian rhythm types and shift work demands shape sleep quality and depressive symptoms in shift-working nurses[J]. Front Public Health. 2025;13:1667778. Bin C, Li X, Tian Y, et al. Prevalence of sleep disturbance and associated factors among nurses in Chinese tertiary public hospitals: a national cross-sectional study. Front Public Health. 2026;13:1735543. An FR, Qi YK, Zeng JY, et al. The prevalence of insomnia, its demographic correlates, and treatment in nurses working in Chinese psychiatric and general hospitals. Perspect Psychiatr Care. 2016;52(2):88–94. Gao Y, Ma X, Wang Y, et al. Relationship between occupational stress and sleep quality among emergency nurses. Front Public Health. 2025;13:1699441. Chen X, Wang B, Wang Y, et al. Prevalence and associated factors of insomnia symptoms among doctors and nurses in general hospitals. Front Public Health. 2024;12:1423216. Horyza A, Antón-Ruiz JA, Iniesta-Sepúlveda M, et al. Insomnia among healthcare professionals during and after the COVID-19 pandemic: a systematic review and meta-analysis. Curr Psychol. 2026;45(5):436. Kang J, Noh W, Lee Y, et al. Sleep quality among shift-work nurses: a systematic review. Appl Nurs Res. 2020;52:151227. Additional Declarations No competing interests reported. Supplementary Files SupplementaryTables.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviewers invited by journal 03 Apr, 2026 Editor invited by journal 13 Mar, 2026 Editor assigned by journal 11 Mar, 2026 Submission checks completed at journal 11 Mar, 2026 First submitted to journal 04 Mar, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9035718","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":619863631,"identity":"a24fde0f-9777-4892-9c83-236ecd18211e","order_by":0,"name":"Jia Fu","email":"","orcid":"","institution":"Guiyang Fourth People’s Hospital","correspondingAuthor":false,"prefix":"","firstName":"Jia","middleName":"","lastName":"Fu","suffix":""},{"id":619863632,"identity":"b9b94bee-bb5c-4644-be24-321e3e3ea393","order_by":1,"name":"Yan Chen","email":"","orcid":"","institution":"Guiyang Fourth People’s Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yan","middleName":"","lastName":"Chen","suffix":""},{"id":619863636,"identity":"a41737bf-469f-4565-845f-71d68de332c2","order_by":2,"name":"Jiaying Han","email":"","orcid":"","institution":"Guiyang Fourth People’s Hospital","correspondingAuthor":false,"prefix":"","firstName":"Jiaying","middleName":"","lastName":"Han","suffix":""},{"id":619863640,"identity":"22fb3cc6-a38f-43ad-8dde-eaa7723cd9bb","order_by":3,"name":"Jiyun Meng","email":"","orcid":"","institution":"Guiyang Fourth People’s Hospital","correspondingAuthor":false,"prefix":"","firstName":"Jiyun","middleName":"","lastName":"Meng","suffix":""},{"id":619863648,"identity":"d531309c-c446-42a3-a833-c66d20b62b34","order_by":4,"name":"Chunfei Wei","email":"","orcid":"","institution":"Guiyang Fourth People’s Hospital","correspondingAuthor":false,"prefix":"","firstName":"Chunfei","middleName":"","lastName":"Wei","suffix":""},{"id":619863653,"identity":"3c176729-b239-45e7-8cda-9dc4b6595633","order_by":5,"name":"Yan Jiang","email":"","orcid":"","institution":"Guiyang Fourth People’s Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yan","middleName":"","lastName":"Jiang","suffix":""},{"id":619863659,"identity":"f8de8d31-fb6d-4315-91ed-922da7da74c1","order_by":6,"name":"Zhimin Feng","email":"","orcid":"","institution":"Guiyang Fourth People’s Hospital","correspondingAuthor":false,"prefix":"","firstName":"Zhimin","middleName":"","lastName":"Feng","suffix":""},{"id":619863660,"identity":"b3e3fc6b-de0c-4ddd-ba2f-60d35910c336","order_by":7,"name":"Hong Fang","email":"","orcid":"","institution":"Guiyang Fourth People’s Hospital","correspondingAuthor":false,"prefix":"","firstName":"Hong","middleName":"","lastName":"Fang","suffix":""},{"id":619863661,"identity":"ae0d7708-6a2a-4165-b4be-7f95d7e974d3","order_by":8,"name":"Xuan Chen","email":"","orcid":"","institution":"Guiyang Fourth People’s Hospital","correspondingAuthor":false,"prefix":"","firstName":"Xuan","middleName":"","lastName":"Chen","suffix":""},{"id":619863662,"identity":"76f98052-9f69-46d4-9619-f9063b25718c","order_by":9,"name":"Hui Hu","email":"","orcid":"","institution":"Affiliated Cancer Hospital of Guizhou Medical University","correspondingAuthor":false,"prefix":"","firstName":"Hui","middleName":"","lastName":"Hu","suffix":""},{"id":619863663,"identity":"d1076b1f-dcca-4219-8267-8bc5e95ade69","order_by":10,"name":"Qin Zhou","email":"","orcid":"","institution":"Guiyang First People's Hospital","correspondingAuthor":false,"prefix":"","firstName":"Qin","middleName":"","lastName":"Zhou","suffix":""},{"id":619863664,"identity":"3194b004-399f-4299-835f-f2220067a2a4","order_by":11,"name":"Gongying Luo","email":"","orcid":"","institution":"Affiliated Hospital of Zunyi Medical University","correspondingAuthor":false,"prefix":"","firstName":"Gongying","middleName":"","lastName":"Luo","suffix":""},{"id":619863666,"identity":"4cc5b27a-7435-46f7-92b7-0f2a3315c4f8","order_by":12,"name":"Jiangrong Zhang","email":"","orcid":"","institution":"Affiliated Hospital of Zunyi Medical University","correspondingAuthor":false,"prefix":"","firstName":"Jiangrong","middleName":"","lastName":"Zhang","suffix":""},{"id":619863667,"identity":"584f422d-c74b-4fae-9889-34fc84456bea","order_by":13,"name":"Ying Chen","email":"","orcid":"","institution":"The First Affiliated Hospital of Guizhou University of Traditional Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Ying","middleName":"","lastName":"Chen","suffix":""},{"id":619863670,"identity":"08aa7ea1-20f1-4772-aecb-e289b91ed740","order_by":14,"name":"Shuanglong Xian","email":"","orcid":"","institution":"People's Hospital of Qianxinan Prefecture","correspondingAuthor":false,"prefix":"","firstName":"Shuanglong","middleName":"","lastName":"Xian","suffix":""},{"id":619863671,"identity":"6344da88-0cf3-4602-a006-d70c8bd06080","order_by":15,"name":"Yongle Xiong","email":"","orcid":"","institution":"Guizhou Provincial People's Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yongle","middleName":"","lastName":"Xiong","suffix":""},{"id":619863672,"identity":"4f1cd7d0-ae33-4b66-a0be-238b31093c0a","order_by":16,"name":"Qianglin Yi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/ElEQVRIie3PQUoDMRSA4QyBrN50thkcbY/woFApFL3KlMKsBHsALYFCdu6nxxBBunxDoN2IPYCrHkDILIUKPrpyY6bLgvkJBML7EiJELHaOSSGIt0IJSeRxAllmTiOghJru63lV5DWd9hjwGg7BuwmaMjyKW/lMX+tH6F2YkQbcAQpKfHsXIE7Nm6e3LaiCKq3xA66lkfnqNUQAKbUbULrcaGQyNqRk2kGa7yOZWl3iO99QdhOX2gcmM4mE1E1y/ou7tMSkSvYGZ5DXzTL4l97OvbSfdnHVr++9OxxubrNs2fg2QAYkkDf3+ywxf89zfXMki+BQLBaL/fN+ABWWVGl6vyAeAAAAAElFTkSuQmCC","orcid":"","institution":"Guiyang Fourth People’s Hospital","correspondingAuthor":true,"prefix":"","firstName":"Qianglin","middleName":"","lastName":"Yi","suffix":""},{"id":619863675,"identity":"c9d2dc79-7cdd-439b-8fed-55c1811ee01e","order_by":17,"name":"Yanqiu Liu","email":"","orcid":"","institution":"Guiyang Fourth People’s Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yanqiu","middleName":"","lastName":"Liu","suffix":""}],"badges":[],"createdAt":"2026-03-05 04:24:47","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9035718/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9035718/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":106727169,"identity":"7bc21bd3-0e00-4c0b-8eb1-efc68ebb5e04","added_by":"auto","created_at":"2026-04-12 18:38:16","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":848019,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9035718/v1/d71589fd-dfc3-4cb7-9ce0-a2320ab7ef3e.pdf"},{"id":106725433,"identity":"a4c1d79e-cfab-4b83-b6f3-de5d435bd5aa","added_by":"auto","created_at":"2026-04-12 18:32:53","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":22953,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTables.docx","url":"https://assets-eu.researchsquare.com/files/rs-9035718/v1/83b085f0535dcd2b02cab23e.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Insomnia Severity Among Anesthesia Nurses in a Resource-Limited Province of Southwest China: A Cross-Sectional Study","fulltext":[{"header":"Background","content":"\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThe department of anesthesiology undertakes emergency care and perioperative management of critically ill patients. This specialty requires advanced technical expertise, high-precision monitoring equipment, and sustained vigilance. Consequently, anesthesiology is characterized by substantial occupational risk and high work intensity \u003csup\u003e[\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eAnesthesia nurses frequently assist in multiple concurrent surgical procedures, manage emergency case insertions, and provide perioperative nursing care. They must remain highly alert to respond promptly to hemodynamic instability and airway emergencies while simultaneously conducting postoperative pain management and monitoring for adverse events. These cumulative responsibilities impose sustained cognitive and emotional demands.\u003c/p\u003e\u003cp\u003eShift work and night shifts are common in anesthesiology and are known to disrupt circadian rhythms and sleep architecture \u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e. Many anesthesia nurses report difficulty initiating sleep, frequent nocturnal awakenings, and non-restorative sleep. Sleep disturbance may interact bidirectionally with psychological stress, potentially impairing cognitive function, reducing alertness, and affecting clinical decision-making capacity \u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e, thereby posing risks to perioperative patient safety.\u003c/p\u003e\u003cp\u003ePrevious studies have demonstrated substantial psychological burden among operating room nurses \u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e. In Guizhou Province, uneven distribution of medical resources and shortages of healthcare personnel may further intensify occupational demands. Some anesthesia nurses participate in cross-regional clinical support and technical training, which may increase workload and professional uncertainty \u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eAlthough anxiety and sleep problems among healthcare workers in China have been documented \u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e, relatively few studies have focused specifically on anesthesia nurses. Moreover, limited research has simultaneously incorporated specialty-related stressors and regional healthcare disparities into a unified analytical framework \u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eTherefore, this study aimed to assess insomnia severity among anesthesia nurses in Guizhou Province and to examine its associations with sleep-related worry, self-regulatory fatigue, perceived stress, and perceived social support.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design and Participants\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThis cross-sectional study was conducted between December 2025 and February 2026. A structured anonymous electronic questionnaire was distributed to anesthesia nurses working in tertiary and selected secondary hospitals in Guizhou Province.\u003c/p\u003e \u003cp\u003eEligible participants were registered nurses working in anesthesia-related positions with at least six months of continuous clinical experience and at least three months of night shift or rotating shift experience. Nurses undergoing short-term training, those detached from front line clinical duties, and those previously diagnosed with severe psychiatric disorders or currently using sedative-hypnotic medications were excluded.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eEthical approval\u003c/strong\u003e \u003cp\u003e was obtained from the Ethics Committee of Guiyang Fourth People\u0026rsquo;s Hospital. The first page of the questionnaire described the study objectives, procedures, confidentiality measures, and voluntary nature of participation. Electronic informed consent was obtained prior to survey access. All data were anonymized and stored in coded form for research purposes only.\u003c/p\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eMeasures\u003c/h3\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eSociodemographic and Occupational Characteristics\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eA self-developed questionnaire collected 22 items, including sex, age, ethnicity, marital status, education level, employment type, professional title, years of work experience, hospital level, night shift frequency, weekly overtime hours, experience of workplace violence, electronic device use before sleep, caffeine consumption habits, history of anxiety or depression, and self-rated health status.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSleep-Related Worry Scale\u003c/h3\u003e\n\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eSleep-related worry was measured using the Chinese version of the Sleep-Related Worry Scale \u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e, developed based on Harvey\u0026rsquo;s cognitive model of insomnia and the Anxiety and Preoccupation about Sleep Questionnaire. The scale contains 10 items across two dimensions: worry about sleep consequences and worry about uncontrollability of sleep. Items are rated on a 5-point Likert scale, with total scores ranging from 10 to 50. Higher scores indicate greater sleep-related worry. The scale has demonstrated good reliability and structural validity in insomnia patients and shift-working nurses.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eSelf-Regulatory Fatigue Scale\u003c/h3\u003e\n\u003cp\u003eSelf-regulatory fatigue was measured using the Chinese revised version of the Self-Regulatory Fatigue Scale (SRF-S), based on ego depletion theory proposed by Baumeister et al. The scale comprises 16 items across cognitive, emotional, and behavioral dimensions. Each item is rated on a 5-point Likert scale. Higher scores reflect greater self-regulatory fatigue. Previous studies have reported satisfactory reliability (Cronbach\u0026rsquo;s α\u0026thinsp;\u0026gt;\u0026thinsp;0.80) \u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003ePerceived Stress Scale\u003c/h2\u003e \u003cp\u003ePerceived stress was evaluated using the 10-item Perceived Stress Scale (PSS-10) \u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e. Items are rated on a 5-point Likert scale from 0 (never) to 4 (very often), with total scores ranging from 0 to 40. Higher scores indicate greater perceived stress. The Chinese version has demonstrated good psychometric properties in healthcare populations \u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eAthens Insomnia Scale\u003c/h3\u003e\n\u003cp\u003eInsomnia severity was assessed using the Athens Insomnia Scale (AIS) \u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e. The AIS consists of eight items evaluating sleep induction, awakenings, early morning awakening, total sleep duration, overall sleep quality, and daytime functioning. Each item is rated on a 4-point scale (0\u0026ndash;3), yielding total scores ranging from 0 to 24. Higher scores indicate more severe insomnia. The AIS has demonstrated reliable diagnostic accuracy and reliability \u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\n\u003ch3\u003eMultidimensional Scale of Perceived Social Support\u003c/h3\u003e\n\u003cp\u003ePerceived social support was evaluated using the Chinese version of the Multidimensional Scale of Perceived Social Support (MSPSS) \u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e. The scale includes 12 items across family, friends, and significant other support dimensions. Items are rated on a 7-point Likert scale, with total scores ranging from 12 to 84. Higher scores indicate greater perceived social support. The Chinese version has demonstrated strong reliability and structural validity \u003csup\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eStatistical analyses were conducted using SPSS software. Descriptive statistics summarized participant characteristics and scale distributions. Independent-samples t tests and one-way analysis of variance were used to compare differences in insomnia severity across subgroups.\u003c/p\u003e \u003cp\u003ePearson correlation analysis examined associations between insomnia severity and psychological variables. Variables with statistical significance in univariate analyses, together with core psychological variables, were entered into a stepwise multiple linear regression model to identify independent predictors of insomnia severity. Multicollinearity was assessed using variance inflation factors (VIF), with values\u0026thinsp;\u0026lt;\u0026thinsp;5 indicating acceptable levels.\u003c/p\u003e \u003cp\u003eA two-sided P value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eParticipant Characteristics\u003c/h2\u003e \u003cp\u003eA total of 444 anesthesia nurses participated. The majority were female (83.8%) and aged 30\u0026ndash;40 years (50.9%). Half reported regular monthly night shifts. Most participants reported weekly overtime, and 8.6% had a prior diagnosis of anxiety or depression. The majority rated their health as good (72.5%) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDemographic and Occupational Characteristics of Participants (N\u0026thinsp;=\u0026thinsp;444)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCategory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e72 (16.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e372 (83.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e118 (26.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30\u0026ndash;40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e226 (50.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e100 (22.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEmployment Type\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eContract nurse\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e332 (74.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePermanent staff\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e108 (24.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLabor dispatch\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4 (0.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMonthly Night Shift\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e222 (50.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e222 (50.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeekly Overtime\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e192 (43.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;10 h\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e213 (48.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10\u0026ndash;20 h\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24 (5.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;20 h\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e15 (3.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiagnosed Anxiety/Depression\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e38 (8.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e406 (91.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSelf-Rated Health\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGood\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e322 (72.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFair\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e116 (26.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePoor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6 (1.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eUnivariate Analysis\u003c/h2\u003e \u003cp\u003eInsomnia severity differed significantly by job satisfaction (F\u0026thinsp;=\u0026thinsp;13.172, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), monthly night shift status (t\u0026thinsp;=\u0026thinsp;6.014, P\u0026thinsp;=\u0026thinsp;0.015), weekly overtime hours (F\u0026thinsp;=\u0026thinsp;9.094, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), electronic device use before sleep (t\u0026thinsp;=\u0026thinsp;7.109, P\u0026thinsp;=\u0026thinsp;0.008), prior diagnosis of anxiety or depression (t\u0026thinsp;=\u0026thinsp;26.644, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and self-rated health status (F\u0026thinsp;=\u0026thinsp;42.273, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Additional demographic variables were not significantly associated (Supplementary Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eUnivariate Analysis of Significant Factors Associated With Insomnia-Related Worry\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCategory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003et/F\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJob Satisfaction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVery satisfied\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e13.53\u0026thinsp;\u0026plusmn;\u0026thinsp;4.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e13.172\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e15.92\u0026thinsp;\u0026plusmn;\u0026thinsp;5.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e13.172\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDissatisfied\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e12.00\u0026thinsp;\u0026plusmn;\u0026thinsp;5.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e13.172\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMonthly Night Shift\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e15.00\u0026thinsp;\u0026plusmn;\u0026thinsp;5.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.015\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e13.86\u0026thinsp;\u0026plusmn;\u0026thinsp;4.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.015\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeekly Overtime\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e13.25\u0026thinsp;\u0026plusmn;\u0026thinsp;4.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9.094\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;10 h\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e15.03\u0026thinsp;\u0026plusmn;\u0026thinsp;4.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9.094\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10\u0026ndash;20 h\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e16.16\u0026thinsp;\u0026plusmn;\u0026thinsp;6.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9.094\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;20 h\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e18.13\u0026thinsp;\u0026plusmn;\u0026thinsp;6.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9.094\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eElectronic Device Use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e14.69\u0026thinsp;\u0026plusmn;\u0026thinsp;4.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7.109\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e13.00\u0026thinsp;\u0026plusmn;\u0026thinsp;4.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7.109\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiagnosed Anxiety/Depression\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e18.26\u0026thinsp;\u0026plusmn;\u0026thinsp;4.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e26.644\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e14.07\u0026thinsp;\u0026plusmn;\u0026thinsp;4.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e26.644\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSelf-Rated Health\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGood\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e13.30\u0026thinsp;\u0026plusmn;\u0026thinsp;4.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e42.273\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFair\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e17.09\u0026thinsp;\u0026plusmn;\u0026thinsp;5.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e42.273\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePoor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e23.50\u0026thinsp;\u0026plusmn;\u0026thinsp;6.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e42.273\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eNote:Detailed univariate results are presented in Supplementary Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eMultiple Linear Regression Analysis\u003c/h2\u003e \u003cp\u003eSleep-related worry (β\u0026thinsp;=\u0026thinsp;0.644, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), self-regulatory fatigue (β\u0026thinsp;=\u0026thinsp;0.386, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and perceived stress (β\u0026thinsp;=\u0026thinsp;0.338, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) were independently associated with higher insomnia severity. Perceived social support was independently associated with lower insomnia severity (β = \u0026minus;0.222, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003cp\u003eThe final model explained 51.1% of the variance in insomnia severity (adjusted R\u0026sup2; = 0.511) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMultiple Linear Regression Analysis of Factors Associated With Athens Insomnia Scale Score\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eβ\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003et\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSleep-related worry total score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.323\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.644\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e17.696\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.288\u0026ndash;0.359\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSelf-regulatory fatigue total score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.259\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.029\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.386\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e8.801\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.201\u0026ndash;0.317\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePerceived stress total score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.303\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.338\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7.561\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.224\u0026ndash;0.382\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePerceived social support total score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;0.082\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;0.222\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026minus;4.785\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026minus;0.115\u0026ndash;\u0026minus;0.048\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eNote:Adjusted R\u0026sup2; = 0.511\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eCorrelation Analysis\u003c/h2\u003e \u003cp\u003eInsomnia severity was positively correlated with sleep-related worry (r\u0026thinsp;=\u0026thinsp;0.794), self-regulatory fatigue (r\u0026thinsp;=\u0026thinsp;0.728), and perceived stress (r\u0026thinsp;=\u0026thinsp;0.903) (all P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). A negative correlation was observed between insomnia severity and perceived social support (r\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;0.303, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCorrelation Between Psychological Variables and Athens Insomnia Scale Score\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSleep-related worry total score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e14.13\u0026thinsp;\u0026plusmn;\u0026thinsp;4.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.794\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSelf-regulatory fatigue total score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e15.41\u0026thinsp;\u0026plusmn;\u0026thinsp;7.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.728\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePerceived stress total score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e24.16\u0026thinsp;\u0026plusmn;\u0026thinsp;5.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.903\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePerceived social support total score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e59.76\u0026thinsp;\u0026plusmn;\u0026thinsp;13.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;0.303\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study demonstrated that insomnia severity is prevalent among anesthesia nurses in Guizhou Province. Approximately half of the variance in insomnia severity was explained by psychological and social variables.\u003c/p\u003e \u003cp\u003eConsistent with prior research among nurses in high-acuity clinical settings \u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/sup\u003e, occupational stress and fatigue were strongly associated with sleep disturbance. Recent latent profile analyses have identified co-occurring patterns of insomnia, fatigue, and psychological distress among hospital nurses \u003csup\u003e[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe strong association between sleep-related worry and insomnia severity supports the cognitive model of insomnia \u003csup\u003e[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/sup\u003e, which posits that maladaptive sleep-related cognitions increase cognitive arousal and disrupt sleep initiation and maintenance. Self-regulatory fatigue may reflect diminished emotional regulation capacity under prolonged stress exposure \u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003ePerceived stress was a major correlate of insomnia severity. Although causal inferences cannot be drawn from this cross-sectional design, the findings suggest that stress perception may play an important role in sleep disturbance \u003csup\u003e[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/sup\u003e. Perceived social support demonstrated a buffering association, consistent with previous evidence indicating that social resources mitigate stress-related sleep problems \u003csup\u003e[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eRegional disparities in healthcare resources in Guizhou Province may further amplify occupational strain. Cross-regional support duties and persistent night shifts may disrupt circadian rhythm stability \u003csup\u003e[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]\u003c/sup\u003e, potentially exacerbating insomnia severity.\u003c/p\u003e \u003cp\u003eComparing these findings with studies from other provinces in China and internationally, the prevalence of insomnia among anesthesia nurses in Guizhou appears higher than in urban tertiary hospitals in Eastern China, where prevalence rates ranged from 30\u0026ndash;40% \u003csup\u003e[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/sup\u003e. This difference may reflect the compounded effect of resource limitations, staffing shortages, and heavier on-call burdens in less developed regions.\u003c/p\u003e \u003cp\u003eInternationally, studies in Europe and North America report insomnia prevalence among critical care nurses ranging from 25% to 50%, depending on work intensity and shift patterns \u003csup\u003e[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/sup\u003e. The similarity in associations between occupational stress, fatigue, and insomnia across diverse healthcare systems suggests that the underlying mechanisms\u0026mdash;cognitive arousal, stress perception, and circadian disruption\u0026mdash;may be universally relevant. However, variations in work culture, nurse-to-patient ratios, and social support systems could modulate the magnitude of sleep disturbance.\u003c/p\u003e \u003cp\u003eMoreover, comparative studies indicate that interventions such as structured stress management, resilience training, and shift scheduling optimization show efficacy in mitigating insomnia among nurses in higher-resource settings \u003csup\u003e[\u003cspan additionalcitationids=\"CR30\" citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]\u003c/sup\u003e. These findings highlight the potential for adopting targeted psychosocial and organizational interventions in Guizhou to address region-specific occupational challenges.\u003c/p\u003e \u003cp\u003eIn summary, while anesthesia nurses worldwide experience significant sleep disturbance related to occupational stress, the severity and contributing factors may be intensified in resource-limited regions. Future multi-center and longitudinal studies are needed to delineate these differences further and evaluate context-specific interventions.\u003c/p\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eLimitations\u003c/h2\u003e \u003cp\u003eThis study employed a cross-sectional design, precluding causal inference. All measures were self-reported and may be subject to recall and reporting bias. The sample was primarily drawn from tertiary hospitals and included a high proportion of female nurses, which may limit generalizability.\u003c/p\u003e \u003cp\u003eFuture longitudinal studies incorporating objective sleep assessments are warranted to further clarify the temporal relationships among psychological factors and insomnia severity.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eInsomnia severity is prevalent among anesthesia nurses in Guizhou Province and is significantly associated with sleep-related worry, perceived stress, and self-regulatory fatigue, whereas perceived social support shows a protective association. These findings underscore the importance of addressing psychological stressors and strengthening organizational support systems to promote sleep health in this high-demand clinical specialty. Further longitudinal research is needed to clarify temporal relationships and inform targeted interventions.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAIS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAthens Insomnia Scale\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMSPSS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMultidimensional Scale of Perceived Social Support\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePSS-10\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePerceived Stress Scale\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSRF-S\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSelf-Regulatory Fatigue Scale\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eVIF\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eVariance Inflation Factor\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e \u003cp\u003e This study was approved by the Ethics Committee of Guiyang Fourth People\u0026rsquo;s Hospital. Electronic informed consent was obtained from all participants prior to participation. All procedures performed were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent for publication\u003c/strong\u003e \u003cp\u003eNot applicable, as the manuscript does not contain any individual person\u0026rsquo;s data.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eCompeting interests\u003c/h2\u003e \u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eJ.F. and Y.C. contributed to study design, data collection, data analysis, and manuscript drafting. JY.H., JY.M., and CF.W. contributed to data analysis and interpretation. Y.J., ZM.F., H.F., X.C., H.H., Q.Z., GY.L., JR.Z., Y.C., YL.X., and SL.X. contributed to data collection and manuscript revision. QL.Y. and YQ.L. supervised the study, contributed to interpretation, and critically revised the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThe authors wish to thank the participating nurses and hospital staff for their cooperation and support during data collection. All authors would like to express their sincere gratitude to Professor Xiaokang Jia of Hainan Medical University for his valuable academic guidance and constructive suggestions in research design, data interpretation and manuscript revision.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets generated and/or analysed during the current study are not publicly available due to privacy concerns but are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eVeale PM, Vayalumkal JV. McLaughlin K.Sickness presenteeism in clinical clerks: Negatively reinforced behavior or an issue of patient safety?[J]. Am J Infect Control. 2016;44(8):892\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLemos CdS,Poveda VdB. Role of perioperative nursing in anesthesia: a national overview[J]. Revista da Escola de Enfermagem da USP; 2022. p. 56.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTotonchilar S, Aarabi A, Eftekhari N, et al. Examining workload variations among different surgical team roles, specialties, and techniques: a multicenter cross-sectional descriptive study[J]. Perioper Med (Lond). 2024;13(1):1.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGanesan S, Magee M, Stone JE, et al. The Impact of Shift Work on Sleep, Alertness and Performance in Healthcare. Workers[J] Sci Rep. 2019;9(1):4635.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXue Y, Wang WD, Liu YJ et al. Sleep disturbances in generalized anxiety Disorder: The central role of insomnia[J].Sleep Med,2025, 132:106545.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYang C, Cheng J, Xiao L et al. Current status and influencing factors of sleep-related worry among nurses in the department of anesthesiology: a cross-sectional study[J].BMC Nurs,2025, 24(1):197.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMaryam ARA, Petro B, et al. Nurses Contribution in Research: Barriers and Solutions[J]. J Nurs Healthc. 2020;5(4):1\u0026ndash;4.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYang X, Chen D, Chen Y, et al. Geographical distribution and prevalence of mental disorders among healthcare workers in China: A cross-sectional country-wide survey: A cross-sectional study to assess mental disorders of healthcare workers in China[J]. Int J Health Plann Manage. 2021;36(5):1561\u0026ndash;74.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCheng J, Xia X, Hong M et al. Relationship between job burnout and presenteeism in anesthesia nurses: mediating effect of psychological capital[J].BMC Nurs,2024, 23(1):853.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJansson-Frojmark M, Harvey AG, Lundh LG, et al. Psychometric properties of an insomnia-specific measure of worry: the Anxiety and Preoccupation about Sleep Questionnaire[J]. Cogn Behav Ther. 2011;40(1):65\u0026ndash;76.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZeng Q, Zhang Y, Liang H et al. The mediating role of self-regulatory fatigue on the relationship between insomnia and sleep-related worry among shift nurses: a cross-sectional study[J].BMC Nurs,2025, 25(1):105.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCohen S, Kamarck T. Mermelstein R.A global measure of perceived stress[J]. J Health Soc Behav. 1983;24(4):385\u0026ndash;96.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang Z, Chen J, Boyd JE et al. Psychometric properties of the Chinese version of the Perceived Stress Scale in policewomen[J].PLoS One,2011, 6(12):e28610.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSoldatos CR, Dikeos DG, Paparrigopoulos TJA. Insomnia Scale: validation of an instrument based on ICD-10 criteria[J]. J Psychosom Res. 2000;48(6):555\u0026ndash;60.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChiu HY, Chang LY, Hsieh YJ, et al. A meta-analysis of diagnostic accuracy of three screening tools for insomnia[J]. J Psychosom Res. 2016;87:85\u0026ndash;92.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChung KF, Kan KK. Yeung WF.Assessing insomnia in adolescents: comparison of Insomnia Severity Index. Athens Insomnia Scale Sleep Qual Index[J] Sleep Med. 2011;12(5):463\u0026ndash;70.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZimet GD, Powell SS, Farley GK et al. Psychometric characteristics of the Multidimensional Scale of Perceived Social Support[J].J Pers Assess,1990, 55(3\u0026ndash;4):610\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMa CMS. Measurement Invariance of the Multidimensional Scale of Perceived Social Support Among Chinese and South Asian Ethnic Minority Adolescents in Hong Kong[J].Front Psychol,2020, 11:596737.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlameri RA, Almulla HA, Al Swyan AH et al. Sleep quality and fatigue among nurses working in high-acuity clinical settings in Saudi Arabia: a cross-sectional study[J].BMC Nurs,2024, 23(1):51.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCao Q, Wu H, Tang X et al. Effect of occupational stress and resilience on insomnia among nurses during COVID-19 in China: a structural equation modelling analysis[J].BMJ Open,2024, 14(7):e080058.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCho H, Sagherian K. Steege LM.Latent Profiles of Nurses' Insomnia, Fatigue, Recovery, Psychological Distress and Burnout During the COVID-19 Pandemic: Examining the Role of Organisational Support[J]. J Adv Nurs. 2026;82(3):2216\u0026ndash;31.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePalagini L, Hertenstein E, Riemann D, et al. Sleep, insomnia and mental health[J]. J Sleep Res. 2022;31(4):e13628.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNyaaba E, Abass K. Gyasi RM.Association of social support with sleep and subjective health outcomes in Ghanaian artisanal miners[J]. Sci Rep. 2025;15(1):43923.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXu L, Gao Y, Shi D et al. Social support moderates the relationship between sleep quality and mental health: A Chinese Fangcang shelter hospital-based study in asymptomatic COVID-19 carriers[J].Heliyon,2024, 10(11):e31782.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhao H, Li Q, Huang H, et al. Circadian rhythm types and shift work demands shape sleep quality and depressive symptoms in shift-working nurses[J]. Front Public Health. 2025;13:1667778.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBin C, Li X, Tian Y, et al. Prevalence of sleep disturbance and associated factors among nurses in Chinese tertiary public hospitals: a national cross-sectional study. Front Public Health. 2026;13:1735543.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAn FR, Qi YK, Zeng JY, et al. The prevalence of insomnia, its demographic correlates, and treatment in nurses working in Chinese psychiatric and general hospitals. Perspect Psychiatr Care. 2016;52(2):88\u0026ndash;94.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGao Y, Ma X, Wang Y, et al. Relationship between occupational stress and sleep quality among emergency nurses. Front Public Health. 2025;13:1699441.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen X, Wang B, Wang Y, et al. Prevalence and associated factors of insomnia symptoms among doctors and nurses in general hospitals. Front Public Health. 2024;12:1423216.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHoryza A, Ant\u0026oacute;n-Ruiz JA, Iniesta-Sep\u0026uacute;lveda M, et al. Insomnia among healthcare professionals during and after the COVID-19 pandemic: a systematic review and meta-analysis. Curr Psychol. 2026;45(5):436.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKang J, Noh W, Lee Y, et al. Sleep quality among shift-work nurses: a systematic review. Appl Nurs Res. 2020;52:151227.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-nursing","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"nurs","sideBox":"Learn more about [BMC Nursing](http://bmcnurs.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/nurs/default.aspx","title":"BMC Nursing","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Anesthesia nurses, Sleep-related worry, Perceived stress, Self-regulatory fatigue, Social support, Cross-sectional study","lastPublishedDoi":"10.21203/rs.3.rs-9035718/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9035718/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground:\u003c/h2\u003e \u003cp\u003eAnesthesia nurses are exposed to sustained occupational stress, shift work, and high clinical demands, which may increase the risk of sleep disturbance. However, limited evidence has specifically examined insomnia severity and its psychological correlates within this specialty, particularly in resource-constrained regions of China.\u003c/p\u003e\u003ch2\u003eMethods:\u003c/h2\u003e \u003cp\u003eA cross-sectional survey was held between December 2025 and January 2026 among 444 anesthesia nurses in Guizhou Province, China. Participants completed validated instruments assessing sleep-related worry, self-regulatory fatigue, perceived stress, insomnia severity (Athens Insomnia Scale), and perceived social support. Descriptive statistics, independent-samples tests, Pearson correlation analysis, and stepwise multiple linear regression were performed.\u003c/p\u003e\u003ch2\u003eResults:\u003c/h2\u003e \u003cp\u003eA substantial proportion of participants reported clinically significant insomnia symptoms. Insomnia severity was positively correlated with sleep-related worry (r\u0026thinsp;=\u0026thinsp;0.794), self-regulatory fatigue (r\u0026thinsp;=\u0026thinsp;0.728), and perceived stress (r\u0026thinsp;=\u0026thinsp;0.903) (all P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and negatively correlated with perceived social support (r\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;0.303, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). In multiple regression analysis, sleep-related worry (β\u0026thinsp;=\u0026thinsp;0.644, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), self-regulatory fatigue (β\u0026thinsp;=\u0026thinsp;0.386, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and perceived stress (β\u0026thinsp;=\u0026thinsp;0.338, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) were significant positive predictors of insomnia severity, whereas perceived social support was a significant negative predictor (β = \u0026minus;0.222, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The final model explained 51.1% of the variance.\u003c/p\u003e\u003ch2\u003eConclusions:\u003c/h2\u003e \u003cp\u003eInsomnia severity is highly prevalent among anesthesia nurses and is strongly associated with cognitive worry, stress perception, and self-regulatory fatigue. Enhancing organizational support and implementing stress-targeted interventions may contribute to the improvement of sleep health in this population. Longitudinal studies are taken to clarify causal pathways.\u003c/p\u003e\u003ch2\u003eTrial registration\u003c/h2\u003e \u003cp\u003eNot applicable.\u003c/p\u003e","manuscriptTitle":"Insomnia Severity Among Anesthesia Nurses in a Resource-Limited Province of Southwest China: A Cross-Sectional Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-09 12:08:23","doi":"10.21203/rs.3.rs-9035718/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewersInvited","content":"","date":"2026-04-03T12:39:37+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-03-13T09:17:50+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-12T02:29:18+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-12T02:28:20+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Nursing","date":"2026-03-05T04:08:31+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-nursing","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"nurs","sideBox":"Learn more about [BMC Nursing](http://bmcnurs.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/nurs/default.aspx","title":"BMC Nursing","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"3ded6e2d-f1f6-4d18-b745-b804744425bd","owner":[],"postedDate":"April 9th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-09T12:08:23+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-09 12:08:23","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9035718","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9035718","identity":"rs-9035718","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}