Effect of Chronotype and Social Jetlag on Depression in Shift Nurses

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Methods From October to November 2024, a total of 301 shift nurses from a tertiary A general hospital in Sichuan, China were selected as the investigation objects by purposeful sampling method, and the investigation was conducted using the Morning and Evening Type Scale 5 (MEQ-5), the Munich Chronotype Questionnaire (MCTQ), and the Patient Health Questionaire-9 (PHQ-9). The influencing factors of depression were analyzed by multiple linear regression. Results The detection rate of depression in shift nurses was 20.1%, the proportion of morning type, middle type and night type was 16.7%, 76.4% and 6.9%, respectively, and the proportion of high social jetlag was 49.7%. Factors such as age, alcohol consumption, exercise persistence, chronic disease, health status, the chronotype is middle type and night type can pose danger to depression nurses ( P < 0.05). Conclusions The chronotype of middle type and night type is the risk factor of depressive symptoms for shift nurses. It is suggested that nursing managers should take chronotype as the theoretical basis when formulating the intervention plan for depression in shift nurses, which can reduce the risk of depressive symptoms. Shift nurse Chronotype Social jetlag Depression China PHQ-9 1. Introduction Statistics show that China has more than 5.637 million registered nurses [ 1 ] who play a vital role in the healthcare system. Nurses not only provide daily care and assistance for patients but also actively participate in the rehabilitation of patients by providing necessary support and health education for patients and their families. Because patients require 24 h of continuous care, shift work is inevitable. However, it can lead to a negative impact on physical and mental health [ 2 , 3 ]. Studies have reported that around 20% of shift nurses experience depression [ 4 , 5 ], significantly impacting their mental well-being. The chronotype is a unique personal biological clock system that reflects a person’s favorite activity or sleep time during a 24-hour period [ 6 ]. These are generally divided into three types: morning, intermediate, and night [ 7 ]. When shift work time conflicts with an individual’s chronotype, it may disturb their biological rhythm, thereby reducing sleep quality [ 8 ]. In addition, shift nurses have a later chronotype owing to the nature of their work [ 9 ], and previous studies have shown that it is closely associated with depression [ 10 , 11 ]. Social jetlag is a relatively new indicator of circadian rhythm disruption, measured by the absolute difference between the midpoint of sleep on days off and the midpoint of sleep on weekdays [ 12 , 13 ]. The literature review found that scholars paid more attention to the social jetlag of children, adolescents and other student groups [ 14 , 15 , 16 ]. Some studies have shown that shift workers have greater social jetlag [ 17 ]; however, there is a lack of reports on the social jetlag of shift nurses. In addition, studies have reported that high social jetlag is an independent predictor of depression [ 14 ]. However, this has not been effectively verified in Chinese shift nurses. In summary, most studies have focused on chronotype as a single factor when examining its link to depression in shift nurses. However, the causal relationship between chronotype, social jetlag, and depression remains unclear. This one-year, ongoing longitudinal study aimed to investigate the prevalence of chronotype, social jetlag, and depressive symptoms among shift nurses. It also sought to analyze the trajectory of chronotype changes, examine the strength of the correlation between severe social jetlag and depressive symptoms, and provide a theoretical basis for improving depressive symptoms in shift nurses. The current study reports only the baseline research findings. 2. Methods 2.1 Design and participants From October to November 2024, a survey of shift nurses, in a Grade 3 A hospital in the north of Chengdu, Sichuan Province, was conducted using purposeful sampling, and data were collected using an online survey ( https://www.wjx.cn/ ). The QR code of the questionnaire was placed in the head nurse group of the hospital and forwarded by the head nurse to the nurse group of each ward, who were invited to fill in the questionnaire if they met the following inclusion criteria: (1) Shift nurses (at least 3 night shifts per month) [ 18 , 19 ]; (2) Age 22–45 years old(because nurses in this hospital hold bachelor's degrees and have completed two years of standardized nursing training, and nurses over the age of 45 are not required to work night shifts); (3) Working life ≥ 1 year. Those who had experienced major psychological stress, severe trauma, or major surgery in the past year were excluded from the study. The statistical method used in this study adopted a latent category growth model, which lacks a specific method for sample size estimation. Based on existing research, when the Bayesian Information Criterion and Entropy are the main factors in model selection, the sample size should be n > 200 [ 20 ]. Accounting for a 30% follow-up loss rate, the minimum required sample size for this study was determined to be 286 cases. 2.2 Research Tools 2.2.1 General information questionnaire The questionnaire used self-designed survey content, including general demographic data, lifestyle, health status, shift type, and other relevant data. 2.2.2 Morning and Evening Questionnaire 5 (MEQ-5) This study employed a 5-item version of the classical 19-item MEQ to evaluate chronotypes [ 21 ]. The total scores for the five items were calculated, with higher scores indicating an earlier chronotype. The validity and reliability of the Chinese version of the MEQ-5 used in this study have been previously verified [ 22 ]. 2.2.3 The Munich Chronotype Questionnaire (MCTQ) The questionnaire was used to estimate social jetlag and average weekly sleep time. Social jetlag is the absolute difference between midpoint of sleep on working days (MSW) and midpoint of sleep on rest days (MSF) (social jetlag = |MSW-MSF|, midpoint of sleep = (wake-up time - night sleep time)/2). Social jetlag > 1 h indicates the presence of social jetlag. If the social jetlag falls within the median or average range, it is categorized as high social jetlag. Otherwise, it is considered low social jetlag [ 23 ]. However, this tool is not suitable for reliability and validity testing. 2.2.4 Patient Health Questionaire-9 (PHQ-9) This study utilized a globally recognized 9-item depression assessment instrument [ 24 ] designed to evaluate depressive symptoms using a four-point Likert scale (0 = never, 1 = several days, 2 = more than half the time, 3 = nearly every day). In prior studies [ 25 ], a total score of ≥ 10 was frequently employed as the cut-off value for screening depressive symptoms. Accordingly, this threshold was adopted in the present study to diagnose depressive symptoms. The Cronbach’s coefficient for this scale in this study was 0.907. 2.3 Statistical Analysis SPSS 23.0 (IBM, Chicago, IL, USA) was used for statistical analysis. Measurement data conforming to normal distribution were ‾x ± s . The measurement data of non-normal distribution were described by M (P25, P75). Counting data were described as frequencies and percentages. One-way ANOVA, t -test, and multiple linear regression were used for factor analysis. Statistical significance was set at P < 0.05. 2.4 Ethics This study was approved by the Ethics Committee of the First Affiliated Hospital of Chengdu Medical College, China (No: LXKY00168) and was performed in accordance with the principles of the Declaration of Helsinki. All participants signed a consent form before completing the questionnaire, and their personal information was kept confidential. 3. Results 3.1 General data, chronotype, social jetlag, depression and single factor analysis of shift nurses A total of 301 questionnaires were distributed, with 288 (95.7%) valid responses, including 12 from males and 276 from females. Among the respondents, 55.2% of nurses reported being frequently awakened by phone calls or alarms on their rest days. The chronotype distribution was as follows: 16.7% in the early morning, 76.4% in the middle of the morning, and 6.9% in the evening. In this study, social jetlag was found to be abnormal, with an average duration of 70.00 (36.25, 120.00) min. Of the participants, 64.6% reported social jetlag ≥ 1 hr, and 49.7% reported social jetlag ≥ 70 min. Additionally, 20.1% of nurses experienced depression. A one-way ANOVA analyzing general data, chronotype, and social jetlag among shift nurses revealed no statistically significant differences in factors such as ethnicity, educational level, marital status, current residence, family care burden, time spent outdoors in daylight, smoking, monthly income, frequent wake-ups due to phone or alarm clock on rest days, or shift type ( P > 0.05). The remaining data are listed in Table 1 . Table 1 One-way ANOVA with Depression in Shift Nurses ( n = 288) Variables Number of people [n (%)] Depression level (x̅ ± s) t / F P Age (years) 8.660 0.004 20–29 116(40.3) 4.97 ± 4.55 30–45 172(59.7) 6.83 ± 5.40 Daily working hours (h) 4.546 0.034 ≤ 8 177(61.5) 5.42 ± 4.57 >8 111(38.5) 7.13 ± 5.81 Daily sleeping hours (h) 13.599 0.000 <8h 207(71.9) 6.69 ± 5.18 ≥ 8 81(28.1) 4.51 ± 4.74 Tipple 3.960 0.048 Yes 15(5.2) 8.80 ± 5.46 No 273(94.8) 5.93 ± 5.10 Keep exercising 6.415 0.012 Yes 32(11.1) 4.12 ± 4.78 No 256(88.9) 6.32 ± 5.15 Chronic disease 9.331 0.002 Yes 28(9.7) 7.25 ± 4.67 No 260(90.3) 5.95 ± 5.19 Health status 18.992 0.000 Good and above 253(87.8) 5.33 ± 4.51 Not good 35(12.2) 11.51 ± 6.18 Chronotype 15.497 0.000 Morning type 48(16.7) 3.95 ± 4.99 Middle type 220(76.4) 6.31 ± 4.96 a Night type 20(6.9) 8.60 ± 5.99 a Social jetlag 4.020 0.046 No social jetlag 102(35.4) 5.99 ± 5.47 Low social jetlag 43(14.9) 5.77 ± 4.17 High social jetlag 143(49.7) 6.31 ± 5.13 b a : P < 0.05, compare with the first layer; b ༚ P < 0.05, compare with the second layer 3.2 Analysis of multiple factors affecting depression in shift nurses With the total score of depression as the dependent variable, multiple linear regression analysis was performed on the independent variables with statistical significance in the univariate analysis, and the assignment of independent variables was shown in Table 2 . The results showed that the variables entered into the regression equation were age, triple, exercise, chronic disease, health status, and chronotype (Table 3 ). Table 2 Assignment of Argument Variables Variables Assignment Age 20–29 year = 0,30–45 year = 1 Daily working hours ≤ 8h = 0, >8h = 1 Daily sleeping hours < 8h = 0, ≥8h = 1 Tipple Yes = 0, No = 1 Keep exercising Yes = 0, No = 1 Chronic disease Yes = 0, No = 1 Health status Good and above = 0, Not good = 1 Chronotype Morning type = 1, Middle type = 2, Night type = 3 Social jetlag No Social jetlag = 1, Low Social jetlag = 2, High Social jetlag = 3 Table 3 Analysis of Multiple Factors Affecting Depression in Shift Nurses ( n = 288) Variables B SE B’ t P Constant 5.121 1.723 — 2.972 0.003 Age 1.325 0.571 0.126 2.318 0.021 Tipple -3.009 1.240 -0.130 -2.426 0.016 Keep exercising 1.966 0.858 0.120 2.290 0.023 Chronic disease 2.114 0.994 0.122 2.126 0.034 Health status 5.947 0.897 0.378 6.630 0.000 Chronotype -1.593 0.578 -0.148 -2.758 0.006 R 2 = 0.258, adjust R 2 = 0.234, F = 10.745, P < 0.001 4. Discussion 4.1 Depression in shift nurses needs attention The results showed that the depression rate among shift nurses was 20.1%. Ghawadra [ 4 ] investigated nurses in a teaching hospital in Malaysia and found that the prevalence rate of depression was 18.8%, while Hsiao [ 5 ] reported that the depression detection rate among female nurses in a hospital in northern Taiwan was 22.6%, which is consistent with the results of this study. The depression detection rate among nurses was higher than that of other groups [ 26 , 27 ], highlighting a concerning trend in their mental health. Depression can lead to dysbiosis [ 28 ] and vascular events such as macrovascular disease [ 29 ]. It may also negatively impact body weight [ 30 ], disrupt daily routines, impair work performance, and reduce the quality of care provided. These effects ultimately burden the health care system and society as a whole [ 31 ]. Thus, addressing and mitigating depressive symptoms among shift nurses is a pressing priority. 4.2 The chronotype of shift nurses was mostly middle type, and social jet lag was common In this study, the chronotype distribution of shift nurses was mostly of the middle type. This may have been related to age and sex. It is well known that chronotypes change in late adolescence, reaching the latest around the age of 20 years, and then slowly advancing [ 32 ]. Women generally have an earlier chronotype and less variability compared with men before the age of 40 [ 33 ]. In this study, 59.7% of shift nurses were 30 years old and above, and most of them were female. The late chronotype manifests in late sleep and late rise and has been confirmed to be closely related to a variety of physical and mental diseases [ 34 ]. Therefore, nursing managers should focus on improving nurses’ sleep patterns. In this study, 64.6% of shift nurses experienced social jetlag, which is lower than the results of a Korean study on shift nurses [ 35 ]. Based on the analysis, nurses in the study area are less available compared to those in economically developed regions [ 36 ]. As a result, the 'DN' shift schedule is extensively utilized by nursing units (64.2%). This schedule divides shifts into two periods: D (8:00–20:00) and N (20:00–8:00). Compared with the APN schedule (8:00–16:00, 16:00–24:00, 0:00–8:00), this mode offers some advantages in maintaining a normal work-rest pattern on working days to a certain extent. However, 55.2% of nurses in this study reported being awakened by phone calls or alarms on rest days, disrupting their sleep-wake rhythm and preventing adequate sleep compensation. This may explain why the social jetlag observed in this study was lower than that reported in similar studies. In addition, night-type nurses were more likely to compensate for sleep compared with morning- and middle-type nurses [ 37 ]. However, only 6.9% of the nurses in this study were night-type, which could also account for the relatively low social jetlag. Notably, a large-scale study of non-shift nurses in China showed that the rate of social jetlag among healthy adults was 31.5% [ 38 ], significantly lower than the rate observed in this study, emphasizing the severity of social jetlag among shift nurses. 4.3 Analysis of the influence of chronotype on depression of shift nurses Previous studies have examined the correlation between chronotype and depressive symptoms and have shown that the more nocturnal the chronotype, the higher the incidence of depression [ 39 , 40 , 41 ], which is consistent with the findings of this study. The risk of depression among night-shift nurses was significantly higher than that among morning-shift nurses, which may be related to emotional regulation mechanisms. Studies have shown that eveningness is positively associated with non-adaptive mood regulation, which is a risk factor for depression. As a result, individuals with eveningness are more prone to experiencing depression [ 42 ]. Moreover, melatonin can inhibit dopamine signaling, leading to positive symptoms of depression in shift nurses with melatonin dysregulation [ 43 ]. However, Druiven [ 44 ] did not find that nocturnal chronotype could predict the progression of depression in patients with depressive symptoms through a 4-year follow-up, which may be related to the difference in study subjects and sample size. 5. Conclusions In this study, intermediate and evening sleep patterns were significantly correlated with depression in shift nurses, but social jetlag had no effect on depression. Nursing managers should intervene with middle- and night-shift nurses to reduce the risk of depression. Limitations and advantages This study has some limitations. First, the study site was limited to one hospital, hence the sample was under representative. Second, the study data were collected through self-reporting by shift nurses rather than using more objective methods. Shift nurses in this study area had low social jetlag, which may explain why social jetlag was not an influencing factor for depression in this study. A key strength of this study lies in its high participant response rate, which enhances the reliability of the research data. Furthermore, this research incorporates a one-year longitudinal design to further investigate the strength of correlations and potential causal relationships between chronotype, social jetlag, and depressive symptoms among shift nurses. The studies reported here were limited by baseline results. Abbreviations MEQ-5 Morning and Evening Type Scale 5 MCTQ Munich Chronotype Questionnaire PHQ-9 Patient Health Questionaire-9 Declarations Author’s contributions Hongxia Tang investigated and wrote the original draft. Jixin Hou: Writing the original draft and investigation. Zhenzhen Xiong: Project administration, writing, reviewing, and editing. Wuqing Wu: Investigation, Writing, review, and editing. Lan Wen: Methodology, Supervision, Writing, review, and editing. Kun Zhang: Project administration, writing, reviewing, and editing. Funding This research was supported by the Sichuan Pension Elderly Health Collaborative Innovation Center Open Project (23LHPDZYB24) and the Chengdu Medical College 2024 Science and Technology Fund Psychological Blood Special Project (CYXLZX2401). Data availability The raw data supporting the conclusions of this article will be made available by the authors without undue reservation. Ethics approval and consent to participate Ethics approval was obtained from the Ethics committee of The First Affiliated Hospital of Chengdu Medical College (No: LXKY00168). The informed consent was obtained from all of the subjects through an online questionnaire. Participants were also informed that they had the option to withdraw at any time. All methods in this study were carried out in accordance with relevant guidelines and regulations of the declaration of Helsinki. Competing interests The authors report no conflicts of interest in this work. Consent for publication Not applicable. Acknowledgments We express our gratitude to the nurses who participated in this study. References The Central People's Government of the People's Republic of China. Statistical Bulletin on the Development of Health and Wellness in 2023. [2024-08-29]. https://www.gov.cn/lianbo/bumen/202408/content_6971241.htm. Cheung T, Yip PS. 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Cite Share Download PDF Status: Published Journal Publication published 09 Feb, 2026 Read the published version in BMC Nursing → Version 1 posted Editorial decision: Revision requested 01 Sep, 2025 Reviews received at journal 22 Aug, 2025 Reviewers agreed at journal 11 Aug, 2025 Reviewers agreed at journal 25 Jul, 2025 Reviews received at journal 19 Jul, 2025 Reviewers agreed at journal 09 Jul, 2025 Reviewers invited by journal 09 Jul, 2025 Editor invited by journal 08 Jul, 2025 Editor assigned by journal 26 Jun, 2025 Submission checks completed at journal 26 Jun, 2025 First submitted to journal 26 Jun, 2025 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. 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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-6942551","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":484281203,"identity":"639b670a-fe2e-455f-b856-abb90cd289c6","order_by":0,"name":"Hongxia Tang","email":"","orcid":"","institution":"The First Affiliated Hospital of Chengdu Medical College","correspondingAuthor":false,"prefix":"","firstName":"Hongxia","middleName":"","lastName":"Tang","suffix":""},{"id":484281206,"identity":"6b238641-b4a9-4472-b6d2-f4ae27504c4d","order_by":1,"name":"Jixin Hou","email":"","orcid":"","institution":"The First Affiliated Hospital of Chengdu Medical College","correspondingAuthor":false,"prefix":"","firstName":"Jixin","middleName":"","lastName":"Hou","suffix":""},{"id":484281209,"identity":"5dead30e-f1e4-4ac6-962c-86f7f301139a","order_by":2,"name":"Zhenzhen Xiong","email":"","orcid":"","institution":"Chengdu Medical College","correspondingAuthor":false,"prefix":"","firstName":"Zhenzhen","middleName":"","lastName":"Xiong","suffix":""},{"id":484281211,"identity":"71ae7bb5-c4d8-424b-a8c6-9604696f92e4","order_by":3,"name":"Yuqing Wu","email":"","orcid":"","institution":"Chengdu Medical College","correspondingAuthor":false,"prefix":"","firstName":"Yuqing","middleName":"","lastName":"Wu","suffix":""},{"id":484281214,"identity":"c57b218c-ac19-4cd4-a444-4c4805b4fbf3","order_by":4,"name":"Lan Wen","email":"","orcid":"","institution":"The First Affiliated Hospital of Chengdu Medical College","correspondingAuthor":false,"prefix":"","firstName":"Lan","middleName":"","lastName":"Wen","suffix":""},{"id":484281216,"identity":"d44d0de7-0aaa-4eb1-8d7e-8e459ef8acdb","order_by":5,"name":"Kun Zhang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA2UlEQVRIiWNgGAWjYBACfvbm4x8SKv7X2x9vPkCcFsmeY2kMD84wJzCcOZZAnBaDGzlmjA9bgFpu5BgQ6bIzZ8weJDaw5THOyPl44w2DnZxuAwEdjO1t5QaJO3iKmXnebracw5BsbHaAgBZmnsMbJBLPSDC2seduk+ZhOJC4jZAWNokEA4nENgPGHoacZ8Rp4ZFIMQNqSUicwZHDRpwWCZ5jyQYJZw4YG/AcM7acY0CEX4AxePDhj4oDcgbszQ9vvKmwkyOoBc1KYqMGSQupOkbBKBgFo2BEAACSEkheuV/oIgAAAABJRU5ErkJggg==","orcid":"","institution":"The First Affiliated Hospital of Chengdu Medical College","correspondingAuthor":true,"prefix":"","firstName":"Kun","middleName":"","lastName":"Zhang","suffix":""}],"badges":[],"createdAt":"2025-06-21 04:23:22","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6942551/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6942551/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12912-026-04403-7","type":"published","date":"2026-02-09T15:57:47+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":102785459,"identity":"0725354d-f292-453b-b8ca-1e4f22b0a9c5","added_by":"auto","created_at":"2026-02-16 16:07:01","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":881071,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6942551/v1/b0c08a9e-6b65-4c1d-9776-a0de82d37f29.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Effect of Chronotype and Social Jetlag on Depression in Shift Nurses","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eStatistics show that China has more than 5.637\u0026nbsp;million registered nurses [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e] who play a vital role in the healthcare system. Nurses not only provide daily care and assistance for patients but also actively participate in the rehabilitation of patients by providing necessary support and health education for patients and their families. Because patients require 24 h of continuous care, shift work is inevitable. However, it can lead to a negative impact on physical and mental health [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Studies have reported that around 20% of shift nurses experience depression [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], significantly impacting their mental well-being.\u003c/p\u003e\u003cp\u003eThe chronotype is a unique personal biological clock system that reflects a person\u0026rsquo;s favorite activity or sleep time during a 24-hour period [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. These are generally divided into three types: morning, intermediate, and night [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. When shift work time conflicts with an individual\u0026rsquo;s chronotype, it may disturb their biological rhythm, thereby reducing sleep quality [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. In addition, shift nurses have a later chronotype owing to the nature of their work [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], and previous studies have shown that it is closely associated with depression [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eSocial jetlag is a relatively new indicator of circadian rhythm disruption, measured by the absolute difference between the midpoint of sleep on days off and the midpoint of sleep on weekdays [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. The literature review found that scholars paid more attention to the social jetlag of children, adolescents and other student groups [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Some studies have shown that shift workers have greater social jetlag [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]; however, there is a lack of reports on the social jetlag of shift nurses. In addition, studies have reported that high social jetlag is an independent predictor of depression [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. However, this has not been effectively verified in Chinese shift nurses.\u003c/p\u003e\u003cp\u003eIn summary, most studies have focused on chronotype as a single factor when examining its link to depression in shift nurses. However, the causal relationship between chronotype, social jetlag, and depression remains unclear. This one-year, ongoing longitudinal study aimed to investigate the prevalence of chronotype, social jetlag, and depressive symptoms among shift nurses. It also sought to analyze the trajectory of chronotype changes, examine the strength of the correlation between severe social jetlag and depressive symptoms, and provide a theoretical basis for improving depressive symptoms in shift nurses. The current study reports only the baseline research findings.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Design and participants\u003c/h2\u003e\u003cp\u003eFrom October to November 2024, a survey of shift nurses, in a Grade 3 A hospital in the north of Chengdu, Sichuan Province, was conducted using purposeful sampling, and data were collected using an online survey (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.wjx.cn/\u003c/span\u003e\u003cspan address=\"https://www.wjx.cn/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The QR code of the questionnaire was placed in the head nurse group of the hospital and forwarded by the head nurse to the nurse group of each ward, who were invited to fill in the questionnaire if they met the following inclusion criteria: (1) Shift nurses (at least 3 night shifts per month) [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]; (2) Age 22\u0026ndash;45 years old(because nurses in this hospital hold bachelor's degrees and have completed two years of standardized nursing training, and nurses over the age of 45 are not required to work night shifts); (3) Working life\u0026thinsp;\u0026ge;\u0026thinsp;1 year. Those who had experienced major psychological stress, severe trauma, or major surgery in the past year were excluded from the study. The statistical method used in this study adopted a latent category growth model, which lacks a specific method for sample size estimation. Based on existing research, when the Bayesian Information Criterion and Entropy are the main factors in model selection, the sample size should be n\u0026thinsp;\u0026gt;\u0026thinsp;200 [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Accounting for a 30% follow-up loss rate, the minimum required sample size for this study was determined to be 286 cases.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Research Tools\u003c/h2\u003e\u003cdiv id=\"Sec5\" class=\"Section3\"\u003e\u003ch2\u003e2.2.1 General information questionnaire\u003c/h2\u003e\u003cp\u003eThe questionnaire used self-designed survey content, including general demographic data, lifestyle, health status, shift type, and other relevant data.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section3\"\u003e\u003ch2\u003e2.2.2 Morning and Evening Questionnaire 5 (MEQ-5)\u003c/h2\u003e\u003cp\u003eThis study employed a 5-item version of the classical 19-item MEQ to evaluate chronotypes [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. The total scores for the five items were calculated, with higher scores indicating an earlier chronotype. The validity and reliability of the Chinese version of the MEQ-5 used in this study have been previously verified [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section3\"\u003e\u003ch2\u003e2.2.3 The Munich Chronotype Questionnaire (MCTQ)\u003c/h2\u003e\u003cp\u003eThe questionnaire was used to estimate social jetlag and average weekly sleep time. Social jetlag is the absolute difference between midpoint of sleep on working days (MSW) and midpoint of sleep on rest days (MSF) (social jetlag = |MSW-MSF|, midpoint of sleep = (wake-up time - night sleep time)/2). Social jetlag\u0026thinsp;\u0026gt;\u0026thinsp;1 h indicates the presence of social jetlag. If the social jetlag falls within the median or average range, it is categorized as high social jetlag. Otherwise, it is considered low social jetlag [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. However, this tool is not suitable for reliability and validity testing.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section3\"\u003e\u003ch2\u003e2.2.4 Patient Health Questionaire-9 (PHQ-9)\u003c/h2\u003e\u003cp\u003eThis study utilized a globally recognized 9-item depression assessment instrument [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] designed to evaluate depressive symptoms using a four-point Likert scale (0\u0026thinsp;=\u0026thinsp;never, 1\u0026thinsp;=\u0026thinsp;several days, 2\u0026thinsp;=\u0026thinsp;more than half the time, 3\u0026thinsp;=\u0026thinsp;nearly every day). In prior studies [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], a total score of \u0026ge;\u0026thinsp;10 was frequently employed as the cut-off value for screening depressive symptoms. Accordingly, this threshold was adopted in the present study to diagnose depressive symptoms. The Cronbach\u0026rsquo;s coefficient for this scale in this study was 0.907.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Statistical Analysis\u003c/h2\u003e\u003cp\u003eSPSS 23.0 (IBM, Chicago, IL, USA) was used for statistical analysis. Measurement data conforming to normal distribution were\u003cem\u003e\u0026oline;x\u003c/em\u003e\u0026thinsp;\u0026plusmn;\u0026thinsp;\u003cem\u003es\u003c/em\u003e. The measurement data of non-normal distribution were described by M (P25, P75). Counting data were described as frequencies and percentages. One-way ANOVA, \u003cem\u003et\u003c/em\u003e-test, and multiple linear regression were used for factor analysis. Statistical significance was set at \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e2.4 Ethics\u003c/h2\u003e\u003cp\u003e This study was approved by the Ethics Committee of the First Affiliated Hospital of Chengdu Medical College, China (No: LXKY00168) and was performed in accordance with the principles of the Declaration of Helsinki. All participants signed a consent form before completing the questionnaire, and their personal information was kept confidential.\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e3.1 General data, chronotype, social jetlag, depression and single factor analysis of shift nurses\u003c/h2\u003e\u003cp\u003eA total of 301 questionnaires were distributed, with 288 (95.7%) valid responses, including 12 from males and 276 from females. Among the respondents, 55.2% of nurses reported being frequently awakened by phone calls or alarms on their rest days. The chronotype distribution was as follows: 16.7% in the early morning, 76.4% in the middle of the morning, and 6.9% in the evening. In this study, social jetlag was found to be abnormal, with an average duration of 70.00 (36.25, 120.00) min. Of the participants, 64.6% reported social jetlag\u0026thinsp;\u0026ge;\u0026thinsp;1 hr, and 49.7% reported social jetlag\u0026thinsp;\u0026ge;\u0026thinsp;70 min. Additionally, 20.1% of nurses experienced depression. A one-way ANOVA analyzing general data, chronotype, and social jetlag among shift nurses revealed no statistically significant differences in factors such as ethnicity, educational level, marital status, current residence, family care burden, time spent outdoors in daylight, smoking, monthly income, frequent wake-ups due to phone or alarm clock on rest days, or shift type (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). The remaining data are listed in 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\u003eOne-way ANOVA with Depression in Shift Nurses (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;288)\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=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" 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\u003eVariables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNumber of people [n (%)]\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDepression level\u003c/p\u003e\u003cp\u003e(x̅\u0026thinsp;\u0026plusmn;\u0026thinsp;\u003cem\u003es)\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003et\u003c/em\u003e/\u003cem\u003eF\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge (years)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e8.660\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.004\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e20\u0026ndash;29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e116(40.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.97\u0026thinsp;\u0026plusmn;\u0026thinsp;4.55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e30\u0026ndash;45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e172(59.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.83\u0026thinsp;\u0026plusmn;\u0026thinsp;5.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDaily working hours (h)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e4.546\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.034\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026le;\u0026thinsp;8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e177(61.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.42\u0026thinsp;\u0026plusmn;\u0026thinsp;4.57\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026gt;8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e111(38.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7.13\u0026thinsp;\u0026plusmn;\u0026thinsp;5.81\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDaily sleeping hours (h)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e13.599\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026lt;8h\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e207(71.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.69\u0026thinsp;\u0026plusmn;\u0026thinsp;5.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e81(28.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.51\u0026thinsp;\u0026plusmn;\u0026thinsp;4.74\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTipple\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.960\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.048\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e15(5.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8.80\u0026thinsp;\u0026plusmn;\u0026thinsp;5.46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e273(94.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.93\u0026thinsp;\u0026plusmn;\u0026thinsp;5.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKeep exercising\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e6.415\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.012\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e32(11.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.12\u0026thinsp;\u0026plusmn;\u0026thinsp;4.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e256(88.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.32\u0026thinsp;\u0026plusmn;\u0026thinsp;5.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eChronic disease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e9.331\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.002\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e28(9.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7.25\u0026thinsp;\u0026plusmn;\u0026thinsp;4.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e260(90.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.95\u0026thinsp;\u0026plusmn;\u0026thinsp;5.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHealth status\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e18.992\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGood and above\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e253(87.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.33\u0026thinsp;\u0026plusmn;\u0026thinsp;4.51\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNot good\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e35(12.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11.51\u0026thinsp;\u0026plusmn;\u0026thinsp;6.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eChronotype\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e15.497\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMorning type\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e48(16.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.95\u0026thinsp;\u0026plusmn;\u0026thinsp;4.99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMiddle type\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e220(76.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.31\u0026thinsp;\u0026plusmn;\u0026thinsp;4.96\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNight type\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e20(6.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8.60\u0026thinsp;\u0026plusmn;\u0026thinsp;5.99\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSocial jetlag\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e4.020\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.046\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo social jetlag\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e102(35.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.99\u0026thinsp;\u0026plusmn;\u0026thinsp;5.47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLow social jetlag\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e43(14.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.77\u0026thinsp;\u0026plusmn;\u0026thinsp;4.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHigh social jetlag\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e143(49.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.31\u0026thinsp;\u0026plusmn;\u0026thinsp;5.13\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003ea\u003c/sup\u003e: \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05, compare with the first layer;\u003csup\u003eb\u003c/sup\u003e༚\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05, compare with the second layer\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003e3.2 Analysis of multiple factors affecting depression in shift nurses\u003c/h2\u003e\u003cp\u003eWith the total score of depression as the dependent variable, multiple linear regression analysis was performed on the independent variables with statistical significance in the univariate analysis, and the assignment of independent variables was shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. The results showed that the variables entered into the regression equation were age, triple, exercise, chronic disease, health status, and chronotype (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\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\u003eAssignment of Argument Variables\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\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\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAssignment\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e20\u0026ndash;29 year\u0026thinsp;=\u0026thinsp;0,30\u0026ndash;45 year\u0026thinsp;=\u0026thinsp;1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDaily working hours\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026le;\u0026thinsp;8h\u0026thinsp;=\u0026thinsp;0, \u0026gt;8h\u0026thinsp;=\u0026thinsp;1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDaily sleeping hours\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;8h\u0026thinsp;=\u0026thinsp;0, \u0026ge;8h\u0026thinsp;=\u0026thinsp;1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTipple\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u0026thinsp;=\u0026thinsp;0, No\u0026thinsp;=\u0026thinsp;1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKeep exercising\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u0026thinsp;=\u0026thinsp;0, No\u0026thinsp;=\u0026thinsp;1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eChronic disease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u0026thinsp;=\u0026thinsp;0, No\u0026thinsp;=\u0026thinsp;1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHealth status\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGood and above =\u0026thinsp;0, Not good\u0026thinsp;=\u0026thinsp;1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eChronotype\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMorning type\u0026thinsp;=\u0026thinsp;1, Middle type\u0026thinsp;=\u0026thinsp;2, Night type\u0026thinsp;=\u0026thinsp;3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSocial jetlag\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo Social jetlag\u0026thinsp;=\u0026thinsp;1, Low Social jetlag\u0026thinsp;=\u0026thinsp;2, High Social jetlag\u0026thinsp;=\u0026thinsp;3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\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\u003eAnalysis of Multiple Factors Affecting Depression in Shift Nurses (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;288)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\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=\"left\" 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\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eB\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eSE\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eB\u0026rsquo;\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003et\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eConstant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e5.121\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.723\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e2.972\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.003\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.325\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.571\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.126\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e2.318\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.021\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTipple\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-3.009\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.240\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.130\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-2.426\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.016\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKeep exercising\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.966\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.858\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.120\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e2.290\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.023\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eChronic disease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2.114\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.994\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.122\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e2.126\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.034\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHealth status\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e5.947\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.897\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.378\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e6.630\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eChronotype\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-1.593\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.578\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.148\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-2.758\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.006\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003cem\u003eR\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.258, adjust \u003cem\u003eR\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.234, \u003cem\u003eF\u003c/em\u003e\u0026thinsp;=\u0026thinsp;10.745, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003e4.1 Depression in shift nurses needs attention\u003c/h2\u003e\u003cp\u003eThe results showed that the depression rate among shift nurses was 20.1%. Ghawadra [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] investigated nurses in a teaching hospital in Malaysia and found that the prevalence rate of depression was 18.8%, while Hsiao [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e] reported that the depression detection rate among female nurses in a hospital in northern Taiwan was 22.6%, which is consistent with the results of this study. The depression detection rate among nurses was higher than that of other groups [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], highlighting a concerning trend in their mental health. Depression can lead to dysbiosis [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] and vascular events such as macrovascular disease [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. It may also negatively impact body weight [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e], disrupt daily routines, impair work performance, and reduce the quality of care provided. These effects ultimately burden the health care system and society as a whole [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Thus, addressing and mitigating depressive symptoms among shift nurses is a pressing priority.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003e4.2 The chronotype of shift nurses was mostly middle type, and social jet lag was common\u003c/h2\u003e\u003cp\u003eIn this study, the chronotype distribution of shift nurses was mostly of the middle type. This may have been related to age and sex. It is well known that chronotypes change in late adolescence, reaching the latest around the age of 20 years, and then slowly advancing [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Women generally have an earlier chronotype and less variability compared with men before the age of 40 [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. In this study, 59.7% of shift nurses were 30 years old and above, and most of them were female. The late chronotype manifests in late sleep and late rise and has been confirmed to be closely related to a variety of physical and mental diseases [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Therefore, nursing managers should focus on improving nurses\u0026rsquo; sleep patterns.\u003c/p\u003e\u003cp\u003eIn this study, 64.6% of shift nurses experienced social jetlag, which is lower than the results of a Korean study on shift nurses [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Based on the analysis, nurses in the study area are less available compared to those in economically developed regions [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. As a result, the 'DN' shift schedule is extensively utilized by nursing units (64.2%). This schedule divides shifts into two periods: D (8:00\u0026ndash;20:00) and N (20:00\u0026ndash;8:00). Compared with the APN schedule (8:00\u0026ndash;16:00, 16:00\u0026ndash;24:00, 0:00\u0026ndash;8:00), this mode offers some advantages in maintaining a normal work-rest pattern on working days to a certain extent. However, 55.2% of nurses in this study reported being awakened by phone calls or alarms on rest days, disrupting their sleep-wake rhythm and preventing adequate sleep compensation. This may explain why the social jetlag observed in this study was lower than that reported in similar studies. In addition, night-type nurses were more likely to compensate for sleep compared with morning- and middle-type nurses [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. However, only 6.9% of the nurses in this study were night-type, which could also account for the relatively low social jetlag. Notably, a large-scale study of non-shift nurses in China showed that the rate of social jetlag among healthy adults was 31.5% [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e], significantly lower than the rate observed in this study, emphasizing the severity of social jetlag among shift nurses.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003e4.3 Analysis of the influence of chronotype on depression of shift nurses\u003c/h2\u003e\u003cp\u003ePrevious studies have examined the correlation between chronotype and depressive symptoms and have shown that the more nocturnal the chronotype, the higher the incidence of depression [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e], which is consistent with the findings of this study. The risk of depression among night-shift nurses was significantly higher than that among morning-shift nurses, which may be related to emotional regulation mechanisms. Studies have shown that eveningness is positively associated with non-adaptive mood regulation, which is a risk factor for depression. As a result, individuals with eveningness are more prone to experiencing depression [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. Moreover, melatonin can inhibit dopamine signaling, leading to positive symptoms of depression in shift nurses with melatonin dysregulation [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. However, Druiven [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e] did not find that nocturnal chronotype could predict the progression of depression in patients with depressive symptoms through a 4-year follow-up, which may be related to the difference in study subjects and sample size.\u003c/p\u003e\u003c/div\u003e"},{"header":"5. Conclusions","content":"\u003cp\u003eIn this study, intermediate and evening sleep patterns were significantly correlated with depression in shift nurses, but social jetlag had no effect on depression. Nursing managers should intervene with middle- and night-shift nurses to reduce the risk of depression.\u003c/p\u003e\u003cp\u003e\u003cb\u003eLimitations and advantages\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThis study has some limitations. First, the study site was limited to one hospital, hence the sample was under representative. Second, the study data were collected through self-reporting by shift nurses rather than using more objective methods. Shift nurses in this study area had low social jetlag, which may explain why social jetlag was not an influencing factor for depression in this study. A key strength of this study lies in its high participant response rate, which enhances the reliability of the research data. Furthermore, this research incorporates a one-year longitudinal design to further investigate the strength of correlations and potential causal relationships between chronotype, social jetlag, and depressive symptoms among shift nurses. The studies reported here were limited by baseline results.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eMEQ-5 \u0026nbsp;Morning and Evening Type Scale 5\u003c/p\u003e\n\u003cp\u003eMCTQ \u0026nbsp; Munich Chronotype Questionnaire\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePHQ-9 \u0026nbsp; Patient Health Questionaire-9\u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor\u0026rsquo;s contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHongxia Tang investigated and wrote the original draft.\u0026nbsp;Jixin Hou: Writing the original draft and investigation. Zhenzhen Xiong: Project administration, writing, reviewing, and editing. Wuqing Wu: Investigation, Writing, review, and editing. Lan Wen: Methodology, Supervision, Writing, review, and editing. Kun Zhang: Project administration, writing, reviewing, and editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was supported by the Sichuan Pension Elderly Health Collaborative Innovation Center Open Project (23LHPDZYB24)\u0026nbsp;and the Chengdu Medical College 2024 Science and Technology Fund Psychological Blood Special Project (CYXLZX2401).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe raw data supporting the conclusions of this article will be made available by the authors without undue reservation.\u003c/p\u003e\n\u003cp\u003eEthics approval and consent to participate\u003c/p\u003e\n\u003cp\u003eEthics approval was obtained from the Ethics committee of\u0026nbsp;The First Affiliated Hospital of Chengdu Medical College\u0026nbsp;(No:\u0026nbsp;LXKY00168). The informed consent was obtained from all of the subjects through an online questionnaire. Participants were also informed that they had the option to withdraw at any time. All methods in this study were carried out in accordance with relevant guidelines and regulations of the declaration of Helsinki.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors report no conflicts of interest in this work.\u003c/p\u003e\n\u003cp\u003eConsent for publication\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe express our gratitude to the nurses who participated in this study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eThe Central People\u0026apos;s Government of the People\u0026apos;s Republic of China. Statistical Bulletin on the Development of Health and Wellness in 2023. 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Front Neurol. 2020 Jun 5;11:416. \u003c/li\u003e\n\u003cli\u003eChen Y, Huang H, Zhi K, Zhang S, Lin Q, Wang Q, et al. The relationship between sleep chronotype and depression and its mechanisms. Advances in Psychological Science. 2020, 28(10): 1713 \u0026ndash; 1722.\u003c/li\u003e\n\u003cli\u003eDolsen EA, Harvey AG. Dim light melatonin onset and affect in adolescents with an evening circadian preference. Journal of Adolescent Health. 2018, 62(1): 94 \u0026ndash; 99.\u003c/li\u003e\n\u003cli\u003eDruiven SJM, Knapen SE, Penninx BWJH, Antypa N, Schoevers RA, Riese H, et al. Can chronotype function as predictor of a persistent course of depressive and anxiety disorder? J Affect Disord. 2019 Jan 1;242:159-164. \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"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":"Shift nurse, Chronotype, Social jetlag, Depression, China, PHQ-9","lastPublishedDoi":"10.21203/rs.3.rs-6942551/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6942551/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective\u003c/h2\u003e\u003cp\u003eTo investigate the status quo of chronotype, social jetlag and depression in shift nurses, and to explore the relationship between chronotype, social jetlag and depressive symptoms.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eFrom October to November 2024, a total of 301 shift nurses from a tertiary A general hospital in Sichuan, China were selected as the investigation objects by purposeful sampling method, and the investigation was conducted using the Morning and Evening Type Scale 5 (MEQ-5), the Munich Chronotype Questionnaire (MCTQ), and the Patient Health Questionaire-9 (PHQ-9). The influencing factors of depression were analyzed by multiple linear regression.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eThe detection rate of depression in shift nurses was 20.1%, the proportion of morning type, middle type and night type was 16.7%, 76.4% and 6.9%, respectively, and the proportion of high social jetlag was 49.7%. Factors such as age, alcohol consumption, exercise persistence, chronic disease, health status, the chronotype is middle type and night type can pose danger to depression nurses (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eThe chronotype of middle type and night type is the risk factor of depressive symptoms for shift nurses. It is suggested that nursing managers should take chronotype as the theoretical basis when formulating the intervention plan for depression in shift nurses, which can reduce the risk of depressive symptoms.\u003c/p\u003e","manuscriptTitle":"Effect of Chronotype and Social Jetlag on Depression in Shift Nurses","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-14 08:24:47","doi":"10.21203/rs.3.rs-6942551/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-09-01T13:03:24+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-22T11:33:30+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"79478451373828703947024823325092813350","date":"2025-08-11T07:44:49+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"170299626742389657161892429143105836986","date":"2025-07-25T06:33:35+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-19T16:41:24+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"319355408312418162469342986044477837246","date":"2025-07-10T01:56:16+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-07-10T01:20:19+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-07-08T21:41:44+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-06-26T20:41:42+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-06-26T06:43:18+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Nursing","date":"2025-06-26T06:39:45+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":"c79ec10d-1590-4fd4-a264-bb1a92cd0b6e","owner":[],"postedDate":"July 14th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-02-16T16:04:12+00:00","versionOfRecord":{"articleIdentity":"rs-6942551","link":"https://doi.org/10.1186/s12912-026-04403-7","journal":{"identity":"bmc-nursing","isVorOnly":false,"title":"BMC Nursing"},"publishedOn":"2026-02-09 15:57:47","publishedOnDateReadable":"February 9th, 2026"},"versionCreatedAt":"2025-07-14 08:24:47","video":"","vorDoi":"10.1186/s12912-026-04403-7","vorDoiUrl":"https://doi.org/10.1186/s12912-026-04403-7","workflowStages":[]},"version":"v1","identity":"rs-6942551","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6942551","identity":"rs-6942551","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}