The Cross-Level Influence of Medical Students’ Perception of Stress on Sleep Quality—A Moderated Mediation Model

The Cross-Level Influence of Medical Students’ Perception of Stress on Sleep Quality—A Moderated Mediation Model | 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 Article The Cross-Level Influence of Medical Students’ Perception of Stress on Sleep Quality—A Moderated Mediation Model Hao Xu, Talante Juma, Yongping Cao This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5415327/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract Background Medical students, the healthcare practitioners in the future, are under greater pressure and prone to physical and mental health problems such as anxiety, depression, and sleep disorders compared with other non-medical specialties. Methods This study investigated the perceived stress of medical students in China and the relationship between their sleep quality. Based on the Cognitive Appraisal Theory and the Perseverative Cognition Hypothesis, we constructed a cross-sectional structural equation model (SEM) with stress perception as a predictor, sleep quality as an outcome variable, and work rumination and social support as buffer moderators. An online survey of 350 medical students from a medical university were collected, 318 of the participants were defined as study objects. Results The results of the study found that medical student’s stress perception negatively affects sleep quality; work rumination plays a mediating role in the relationship between stress perception and sleep quality; perceived social support plays a negative cross-level moderating role between stress perception and work rumination, and also plays a positive cross-level moderating role between work rumination and sleep quality. Conclusions This study provided evidence for the design of stress regulation methods for medical students as well as intervention techniques to improve sleep quality among medical students. Biological sciences/Psychology Health sciences/Health occupations Medical students Perceived Stress Sleep quality Multilevel model Figures Figure 1 Figure 2 Figure 3 1. Introduction and Hypotheses Compared with those in other professions, medical students face unique challenges. They often contend with a heavy course load, high entry requirements, extended school years, challenging employment situations, complex doctor‒patient relationships, and high expectations from their families and society. As a result, medical students experience considerable pressure and are more prone to physical and mental health problems, such as anxiety, depression, and sleep disorders, than students in other fields are [ 1 ]. Previous studies have shown that the incidence of sleep disorders among Chinese medical students is greater than that among nonmedical students and the general population [ 2 ]. However, existing research has focused primarily on identifying stress and coping styles [ 3 ], with limited evidence specifically demonstrating how stress perception affects sleep quality among medical students. To address this gap, this study investigated the mechanisms linking stress perception and sleep quality among medical students. This study also provides empirical evidence to inform the design of stress management strategies and interventions to improve sleep quality within the context of Chinese medical education. Additionally, this study uses cognitive appraisal theory and the cognitive fixation hypothesis, and considers work rumination as a mediating variable to explore the moderating role of perceived social support in this relationship. This study offers several important contributions. First, it provides empirical evidence on how medical students' stress perceptions affect their sleep quality. Second, it clarifies the mediating role of work rumination and explores the intrinsic link between stress perception and sleep quality. Finally, it develops a moderated mediation model showing how reducing stress perceptions and rumination while enhancing social support can improve sleep quality. 1.1 Perceived Stress and Sleep Quality in Medical Students Perceived stress refers to how an individual evaluates or interprets an external event as stressful. Individuals may perceive the same event differently due to subjective interpretations. According to Cohen et al. [ 4 ], perceived stress reflects the subjective evaluation of how unpredictable, uncontrollable, or overwhelming life circumstances are, shaped by an individual’s interpretation of various stressors and risk factors in life. Although the impact of perceived stress on health is well documented, most research has focused on its direct effects, with limited investigations into the underlying mechanisms involved. Empirical studies have demonstrated that perceived stress is negatively associated with sleep quality [ 5 ]. According to cognitive appraisal theory, emotions result from complex interactions between a person and the environment rather than being generated in isolation [ 6 ]. This study explores how these interactions influence sleep quality. Variations in cognitive appraisal mechanisms cause individuals to evaluate external stimuli differently, leading to diverse coping responses. Exposure to stress can elicit a range of responses in individuals. When individuals perceive stress as a significant burden on their psychological and physiological state, they may experience difficulty achieving and maintaining relaxation for sleep, which can contribute to insomnia symptoms [ 7 ]. This study aims to expand the understanding of the negative impact of perceived stress by examining the sleep quality of medical students. Drawing on cognitive appraisal theory, this study proposes the following hypothesis: Hypothesis 1 Medical students' stress perceptions negatively affect sleep quality. 1.2 Mediating Role of Work Rumination Kollarik et al. [ 8 ] defined rumination as "a type of thought that is manifested by the repetition of memories, feelings, and the frequent occurrence of such thoughts in situations that do not require them very much." According to this definition, rumination is generally understood as a negative thought process focused on repeating negative experiences. Firoozabadi et al. [ 9 ] identified two dimensions of work rumination: emotional rumination and problem-solving contemplation. Emotional rumination is characterized by pervasive, intrusive, and repetitive thoughts focused on work-related problems, often triggering negative emotions such as worry and distress. In contrast, problem-solving contemplation involves finding solutions to work-related problems by thinking about them over an extended period without considering emotional factors. According to the perseverative cognition hypothesis, persistent thinking with different characteristics can have various physiological and psychological effects. Stress can induce cognitive fixation [ 10 ], causing individuals to continuously dwell on or recall past work experiences during nonwork time. This cognitive fixation leads to the investment of more resources in negative work rumination, which reactivates psychological and physiological stress responses and affects sleep quality [ 11 ]. Harvey et al. [ 12 ] reported that individuals with insomnia were more preoccupied with anxiety and problems and more likely to recall daytime events than those with good sleep quality. In summary, stress leads to persistent cognitive fixation, which in turn induces job rumination. Excessive job rumination creates a chain reaction that exacerbates insomnia, anxiety, and other physical and mental health issues. While previous studies on stress and work rumination have focused mainly on job performance, employee innovation behavior, leadership, and related fields [ 13 ], there has been limited research on medical students. Therefore, investigating the mechanisms linking stress cognition to sleep quality among medical students is crucial. Thus, the cognitive fixation hypothesis aims to determine whether job rumination consistently triggers psychological and physiological responses and to evaluate its subsequent effects. The theory discussed provides a strong framework for understanding how job rumination impacts individuals' physiological and psychological health, as well as job performance. Consequently, Hypothesis 2 is proposed: Hypothesis 2 Job rumination plays a mediating role in the relationship between stress perception and sleep quality. 1.3 Perceived Moderating Role of Social Support Social support refers to the assistance an individual receives from significant others in stressful situations, such as family members, friends, or neighbors. This support can take various forms, including socioemotional support, informational support, and practical help [ 14 ]. According to Gottlieb et al. [ 15 ], social support encompasses the resources perceived to be available to an individual, whether from formal support groups or informal sources [ 16 ]. Research indicates that social support involves a provider offering resources such as emotional support, recognition, and practical help to meet the recipient's personal needs. For medical students, social support typically comes from family, friends, classmates, and teachers. Previous studies have identified social support as a crucial factor influencing stress perception and work rumination [ 17 ]. In teams with high perceived social support, stress perception can be heightened, presenting as a competitive and conflictual condition influenced by the overall environment. However, such teams also exhibit a modulation of work rumination and sleep quality. Perceived social support can offer emotional, informational, and material resources that help reduce stress perceptions and enhance an individual's psychological coping skills. Investigating the moderating role of perceived social support in the relationship between stress perceptions and work rumination can provide deeper insights into how social support aids in managing stress and work-related rumination. Exploring methods to mitigate the negative effects of stress on work rumination can offer future insights into how social support contributes to an individual's psychological adjustment process. Hypothesis 3 Perceived social support negatively moderates the relationship between stress perceptions and work rumination and positively moderates the relationship between work rumination and sleep quality. 2. Methodology 2.1 Survey Participants and Administration Procedures We selected 350 medical students from a medical university in China to participate in a questionnaire survey via the timed interval-based experience sampling methodology (TISM). All procedures performed involving human participants were in accordance with the ethical standards of the 1964 Helsinki declaration and its later amendments or comparable ethical standards. The study protocol was reviewed by the Ethics Committee of the Clinical Trial Management, Peking University First Hospital of China (approval No. 2024RES-602-001), informed consent was obtained from all individual participants included in the study. Since the respondents were from a single source, the questionnaires were based on individual subjective self-assessments. To reduce common variance, the questionnaire was administered in three phases: Phase 1 (T1 time point: June 2023): Basic demographic information and stress levels of 350 medical students were investigated. Phase 2 (T2 time point: July 2023): Four weeks later, the students who returned valid questionnaires in Phase 1 were followed up to assess work rumination and social support. Phase 3 (T3 time point: August 2023): Another four weeks later, the students who returned valid questionnaires in Phase 2 were surveyed to measure their sleep patterns. After the three rounds of surveys, the questionnaire results were double-checked and cleaned. The criteria for data cleaning included deleting samples with identical selection results for all Likert scale indicators, excluding samples with response times exceeding ± 3 standard deviations from the mean, and correcting logical errors, such as implausible ages or graduation years. After this process, 318 valid samples were retained, resulting in a recovery rate of 90.86%. By verifying the basic personal information provided by the matched medical students, this study obtained a total of 43 department–individual paired clusters with 318 valid individual questionnaires, averaging 7.5 samples per cluster. The descriptive statistics of the variables (Table 1 ) showed there were 120 males and 198 females, indicating a greater proportion of females. The mean age of the participants was 27.12 ± 2.47 years. Among the participants, 269 (84.6%) were unmarried, and 123 (38.7%) were in their senior year. The proportions of only children and non-only children were similar. The highest proportion of students were academic doctoral students (37.4%), followed by professional doctoral students (25.2%) and professional master’s students (22.0%). Academic master’s degree students constituted the lowest proportion (15.4%). 2.2 Measurements All the scales were translated into Chinese. [ 18 ]. Perceived Stress The Perceived Stress Scale (PSS), developed by [ 4 ], is a widely used instrument for measuring perceived stress. It evaluates situational stress, the effectiveness of stress reduction interventions, and stress-related psychosomatic disorders. Examples of items include "feeling upset when something unexpected happens" and "feeling that I can deal effectively with issues such as important changes in my life." The questionnaire uses a 5-point Likert scale ranging from 0 (never) to 4 (very often). The total or mean score of the items reflects the individual’s level of perceived stress, with higher scores indicating greater stress. The Cronbach's alpha coefficient for this scale is 0.84. Sleep Quality The Pittsburgh Sleep Quality Index (PSQI), developed by Buysse et al. [ 19 ], assesses sleep quality over the previous month. 0It comprises 24 items, of which 18 self-report items are used for scoring. These items are categorized into 7 components, including sleep duration, subjective sleep quality, and sleep disturbances. Each component is scored on a 0–3 scale, and the total PSQI score is obtained by summing the component scores. Higher total scores indicate poorer sleep quality, with a PSQI score of ≥ 8, of a sleep disordeindicative r. The Cronbach's alpha coefficient for this scale is 0.83. Work Rumination The Work Rumination Rating Scale (WRRQ), developed by [ 20 ], originally included three subscales: emotional rumination, problem-solving rumination, and disengagement. However, subsequent studies have discarded the disengagement subscale because of its lack of accuracy in measuring work rumination. The current methodology employs two subscales, emotional rumination and problem-solving contemplation, each with five items. The respondents used a 5-point scale to indicate the frequency of their thoughts, ranging from 1 (hardly ever) to 5 (all the time), with higher scores reflecting greater work rumination. The Cronbach's α coefficients for emotional rumination and problem-solving contemplation are 0.90 and 0.81, respectively. Perceived Social Support The Perceived Social Support Scale, developed by [ 21 ], assesses an individual's self-perceived social support from family, friends, and others. The scale includes 12 items divided into three dimensions, with specific items related to support from each source: family (Items 11, 3, 4, and 8), friends (Items 6, 7, 9, and 12), and others (Items 1, 2, 5, and 10). The responses are rated on a 1–7 scale ranging from strongly disagree to strongly agree. The Cronbach's alpha coefficient for this scale is 0.85. Control Variables The choice of control variables is crucial [ 22 ]. This study's control variables included gender, age, marital status, whether the participants were only children, type of education, night shift work, and recent major life changes. These variables were selected because college students' personal routines and demographic characteristics can significantly affect their sleep quality [ 23 ]. 2.3 Statistical Analysis In this study, Harman's one-way analysis of variance [ 24 ] was employed to test for common method bias. Since "sleep quality" was measured via objective indicators, its reliability and validity were not assessed. Consequently, all variables except "sleep quality" were included in the analysis. A common method factor was also incorporated into the baseline model to further test for common method bias. Descriptive statistics and correlation analyses were subsequently conducted. Pearson's correlation coefficient was used to determine the relationships between medical students' stress perceptions and sleep quality, as well as between work rumination and sleep quality. Finally, tests for mediation effects, moderation effects, and mediation effects with moderation and cross-level moderation models (individual-level mediation path analysis, individual-level moderation effects analysis, cross-level mediation model test, and cross-level moderation model test) were conducted [ 25 ]. The above data were analyzed via SPSS 26.0 and Mplus 8.3 software. 3. Results 3.1 Factor Analysis Validation In the 3-factor model, a common method variance (CMV) factor was added. The model fit parameters were as follows: χ²/df = 1.191, RMSEA = 0.024, SRMR = 0.036, CFI = 0.984, TLI = 0.983. These fit parameters did not improve compared with those of the baseline model (χ²/df = 1.191, RMSEA = 0.024, SRMR = 0.036, CFI = 0.984, TLI = 0.983), suggesting that common method bias had a limited effect. Among the models presented in Table 1 , only the 3-factor model met the fit criteria, with parameters of χ²/df = 1.191, RMSEA = 0.024, SRMR = 0.036, CFI = 0.984, and TLI = 0.983. In contrast, at least one fit parameter of the 2-factor and 1-factor models did not meet the threshold criteria. This finding indicates that the 3-factor model provided the best fit and demonstrated differential validity. Table 1 Fit indices for measurement models (Fit indices for measurement models) Model χ 2 df χ 2 / df RMSEA CFI TLI SRMR Parameter < 3 < 0.08 < 0.9 < 0.9 < 0.05 Factor 3 + CMV 697.777 586 1.191 0.024 0.984 0.983 0.036 3-Factor (Baseline Model) 697.777 586 1.191 0.024 0.984 0.983 0.036 Factor 2 1779.319 861 2.067 0.058 0.882 0.876 0.128 Factor 1 4915.370 860 5.716 0.122 0.477 0.451 0.140 Table 1 Factor 3 + CMV: Work Rumination Scale, Perceived Social Support Scale, Perceived Stress Scale + Common Method Variance (CMV); 3-Factor (Baseline Model): Work Rumination Scale, Perceived Social Support Scale, Perceived Stress Scale. Factor 2 model: Work Rumination Scale + Perceived Social Support Scale, Stress Perception Scale. Factor 1 model: Work Rumination Scale + Perceived Social Support Scale + Stress Perception Scale. 3.2 Description and Correlation Analysis of Variables This study employed the timed interval-based experience sampling methodology (TISM) for the questionnaire survey. To mitigate common variance, the survey was administered in three phases. In the first phase (T1: June 2023), 350 medical students from one university were surveyed to collect basic demographic information and stress perceptions. Four weeks later, in the second phase (T2: July 2023), the students who returned valid questionnaires in the first phase were followed up to assess work rumination and social support. Another four weeks later, in the third phase (T3: August 2023), the same group was surveyed again to measure sleep quality. After the three survey rounds, the data were double-checked and cleaned, resulting in 318 valid questionnaires, yielding a recovery rate of 90.86%. By verifying the matched medical students’ basic personal information, such as departmental affiliation, 43 department–individual paired clusters with an average sample size of 7.5 per group were obtained. The descriptive statistics of the variables (see Table 2 ) indicated that 120 participants were male and 198 were female, indicating a greater proportion of females. The mean age of the participants was 27.12 ± 2.47 years. Among them, 269 were unmarried (84.6%), and 123 were college graduates (38.7%). The proportions of only children and non-only children were nearly equal. The highest proportion of participants were academic doctoral students (37.4%), followed by professional doctoral students (25.2%) and professional master's students (22.0%), with the lowest proportion being academic master's students (15.4%). Table 2 Descriptive statistics of variables Variable Category Number Proportion(%) Gender Man 120 37.7 Woman 198 62.3 Marriage Unmarried 269 84.6 Married 49 15.4 Only-Child Yes 155 48.7 No 163 51.3 Grade Graduating class 123 38.7 non-Graduating class 195 61.3 Education Academic master's degree program 49 15.4 Doctor of Philosophy 119 37.4 Professional Master 70 22.0 Doctor of Medicine 80 25.2 Location Cities 156 49.1 Town 78 24.5 Rural 84 26.4 Night duty Yes 146 45.9 No 172 54.1 Chief resident Yes 53 16.7 No 265 83.3 Major assessments Yes 115 36.2 No 203 63.8 Spearman's rank correlation coefficient was used to analyze the correlation of the variables in the study, and the results of the correlation coefficient matrix of the variables are shown in Table 3 . The data in the table indicate that among the four variables, the correlations of stress perception, work rumination, and sleep quality are significant, meeting the requirements of regression analysis. In contrast, the correlations between the moderating variables of social support and work rumination are not significant. Because the moderating effect test focuses only on whether the intensity of influence between variables is related to the value of the moderating variable, it does not need to consider the relationship between the moderating variable and other variables; thus, the correlation between social support and work rumination is not significant and does not affect the subsequent analysis link. Table 3 Correlation analysis of variables Perceived Stress Work rumination Social support Sleep quality Perceived Stress 1 Work rumination 0.535** 1 Social support -0.226** -0.069 1 Sleep quality Gender-based Marriage Only-Child Grade Education Location Night duty Chief resident Major assessments Accident -0.468** 0.118* 0.07 0.03 0.05 0.02 -0.01 0.02 -0.08 -0.03 -0.05 -0.391** -0.06 0.05 -0.03 0.01 0.06 0.13* -0.01 -0.02 -0.03 -0.00 0.352** 0.00 -0.03 -0.10 0.03 -0.01 -0.11 -0.02 -0.00 0.04 0.10 1 0.02 -0.03 -0.09 -0.01 0.05 0.02 -0.07 0.04 0.07 0.10 * p < 0.05, ** p < 0.01, *** p < 0.001 3.3 Regression Analysis Analysis of Moderating Effects at the Individual Level As shown in Table 4 , to examine the effect of perceived stress on work rumination, with gender, age, and other variables as control variables, a hierarchical linear model (HLM) was used. In Model 1, perceived stress was added to the control variables. The results indicated that the regression coefficient for perceived stress on work rumination was b = 0.293, with a significance level of p < 0.001, indicating a significant positive effect of perceived stress on work rumination. Similarly, we used hierarchical linear modeling to test the influence of perceived stress on sleep quality, with gender and age as control variables and work rumination and sleep quality as the mediator and dependent variables, respectively. In Model 2, which included control variables, the regression coefficient for perceived stress on sleep quality was b = -0.138, with a significance level of p < 0.001, indicating a significant negative effect of perceived stress on sleep quality. In Model 3, the regression coefficient for work rumination on sleep quality was b = -0.118, with p < 0.001, indicating a significant negative effect of work rumination on sleep quality. Since the relationships in Model 1 (independent variable to mediator) and Model 3 (mediator to dependent variable) were both significant, a mediation model was tested with perceived stress as the predictor variable, sleep quality as the outcome variable, and work rumination as the mediator. The results revealed significant mediation effects, with an indirect effect of 0.224, confirming that work rumination significantly mediated the relationship between perceived stress and sleep quality. Model 3 also revealed a significant direct effect of perceived stress on sleep quality, with coefficients of b = -0.104 and p < 0.001, indicating that the mediation model reflects a partial mediation effect. This means that the effect of perceived stress on sleep quality occurs both directly and indirectly through work rumination. When social support was used as a moderator, the interaction term "perceived stress × social support" revealed a significant negative regression effect on work rumination, with coefficients of b = -0.913 and p = 0.003. These findings suggest that social support significantly moderates the effect of perceived stress on work rumination. Furthermore, the interaction term "work rumination × social support" had a significant positive regression effect on sleep quality, with coefficients of b = 0.734 and p < 0.001. These findings indicate that social support plays a significant positive moderating role in the relationship between work rumination and sleep quality. The specific calculation results are detailed in Models 4 and 5. Table 4 Individual-level moderation Model 1 Model 2 Model 3 Model 4 Model 5 λ SE t p λ SE t p λ SE t p λ SE t p λ SE t p Intercept 6.934 5.944 1.166 0.244 12.352 3.364 3.671 0.000 13.167 3.304 3.986 0.000 14.511 5.791 2.506 0.013 6.451 3.038 2.123 0.035 Gender 0.759 0.655 1.158 0.248 0.074 0.371 0.200 0.842 0.163 0.364 0.449 0.654 0.605 0.65 0.932 0.352 0.292 0.338 0.864 0.388 Age 0.363 0.154 2.354 0.019 0.035 0.087 0.399 0.690 0.077 0.086 0.899 0.370 0.333 0.153 2.181 0.03 0.074 0.08 0.919 0.359 Marriage -0.757 0.921 -0.822 0.412 -0.095 0.521 -0.182 0.856 -0.184 0.511 -0.36 0.719 -0.449 0.914 -0.491 0.624 -0.251 0.475 -0.527 0.598 One Child 0.959 0.73 1.313 0.190 1.008 0.413 2.440 0.015 1.121 0.406 2.761 0.006 0.976 0.723 1.349 0.178 0.925 0.378 2.447 0.015 Grade 0.819 0.695 1.179 0.239 0.126 0.393 0.320 0.749 0.222 0.386 0.575 0.565 0.984 0.687 1.431 0.153 0.295 0.358 0.822 0.412 Education -0.726 0.517 -1.403 0.162 0.053 0.293 0.181 0.857 -0.032 0.288 -0.112 0.911 -0.655 0.511 -1.281 0.201 0.009 0.267 0.035 0.972 Location -0.356 0.432 -0.825 0.410 -0.256 0.245 -1.046 0.296 -0.298 0.24 -1.241 0.216 -0.332 0.427 -0.776 0.438 -0.244 0.223 -1.096 0.274 Night duty -1.020 1.009 -1.011 0.313 0.195 0.571 0.341 0.733 0.075 0.561 0.134 0.894 -1.09 0.998 -1.093 0.275 -0.122 0.521 -0.234 0.815 Chief resident 0.259 1.069 0.242 0.809 0.295 0.605 0.487 0.627 0.325 0.593 0.548 0.584 0.299 1.057 0.283 0.778 0.633 0.552 1.146 0.253 Major assessments 0.351 0.689 0.509 0.611 -0.289 0.39 -0.74 0.460 -0.247 0.382 -0.647 0.518 0.445 0.684 0.651 0.515 -0.112 0.357 -0.313 0.754 Accident 0.443 1.035 0.428 0.669 -0.808 0.586 -1.379 0.169 -0.756 0.574 -1.317 0.189 0.298 1.03 0.289 0.772 -0.416 0.536 -0.777 0.438 Perceived Stress 0.293 0.026 11.162 < 0.001 -0.138 0.015 -9.283 0.000 -0.104 0.017 -5.989 0.000 3.49 0.315 11.097 0.000 -0.874 0.196 -4.47 0.000 Work rumination -0.118 0.032 -3.703 0.000 -0.775 0.191 -4.063 0.000 Social support 0.432 0.322 1.342 0.181 0.906 0.166 5.446 0.000 Perceived Stress*Social support -0.913 0.300 -3.041 0.003 Work rumination*Social support 0.734 0.157 4.68 0.000 R 2 0.311 0.242 0.274 0.333 0.379 Adjust R 2 0.284 0.212 0.243 0.302 0.349 F 11.463 8.094 8.837 10.810 12.308 p < 0.001 0.000 0.000 0.000 0.000 Simple slope analysis at the individual level To better compare the moderating effects, simple slope analyses were conducted to examine the slopes of the effects of perceived stress on work rumination and work rumination on sleep quality at different levels of the moderating variables. The details of these moderating effects are illustrated in Fig. 1 . As the values of the moderating variables increase, the positive effect of perceived stress on work rumination diminishes, whereas the negative effect of work rumination on sleep quality weakens. Furthermore, the effect of work rumination on sleep quality is attenuated. Results of single-level path analysis According to the regression analysis and the mediation adjustment test, the individual-level path coefficients are illustrated in Fig. 2 . 3.4 Cross-Level Path Analysis The cross-level moderating model test revealed a significant negative regression effect of perceived stress × social support on work rumination, with regression coefficients of \(b = -0.551 \) and \(p = 0.015 \). These findings indicate that social support significantly moderates the effect of perceived stress on work rumination, with the positive effect of perceived stress on work rumination decreasing as social support increases. Additionally, there was a significant positive regression effect of work rumination × social support on sleep quality, with regression coefficients of \(b = 0.840 \) and \(p < 0.001 \). These findings suggest that social support significantly moderates the effect of work rumination on sleep quality, with the negative effect of work rumination on sleep quality diminishing as social support increases. The results of the cross-level path analysis are illustrated in Fig. 3 . 4. Discussion This study revealed that when medical students are under relatively high levels of stress, stress directly affects the quality of their sleep. The study also found that work rumination interferes with an individual's state of relaxation by increasing cognitive load and psychological tension, affecting sleep quality. Additionally, sleep quality and perceived stress among medical students were strongly associated with social support, with social support moderating the relationship between stress and sleep quality. Our study was analyzed at both the individual and group levels. At the individual level, psychological stress and negative emotions are inevitable when medical students are faced with a new medical environment, complex social relationships, and important role transitions. However, as the level of social support increases, medical students become concerned with and encouraged by others, reducing their study and life stress and, thus, preventing them from falling into work rumination. Additionally, our study revealed that social support moderated the role of work rumination in the relationship between perceived stress and sleep quality. In the cultural environment of colleges and universities, the concerns of family, friends, faculty, and students provide important psychological support to medical students by diverting their attention, relaxing them, and avoiding excessive emotional rumination, thus improving their sleep quality. However, individuals with low perceived social support may engage in work-related rumination, contributing to poor sleep quality. Through group-level analyses, we found a moderating effect of social support on the mediating role of work rumination between perceived stress and sleep quality. Our results show that the effect of perceived stress on sleep quality among medical students varies across departments. This phenomenon can be explained in several ways: First, the intensity of work stress and the nature of work faced by medical students in different departments vary. Significant differences exist in the intensity and nature of work in different departments. For example, departments such as the emergency room and surgery usually have high work intensity and require quick decision-making and long hours of intensive work, which tends to cause high mental stress among medical students. This stress can lead to difficulty falling asleep, shorter sleep duration, and poorer sleep quality. On the other hand, medical students in departments with relatively lower work intensity, such as internal medicine or pathology, may have relatively better sleep quality because of relatively lower stress. Additionally, different types of medical students have different training goals: some aim to train applied clinicians, while others emphasize the cultivation of scientific research ability and scientific thinking, resulting in different requirements for clinical and scientific research ability. Finally, rotation schedules in different departments may affect medical students' sleep quality differently. For example, when they rotate in the emergency department or intensive care unit (ICU), medical students are usually required to work night shifts, disrupting circadian rhythms and affecting sleep quality. In some departments with relatively regular daily routines, medical students may have more stable routines, and their sleep may be less affected. In summary, the differences in stress levels among medical students in different departments can be explained by a variety of factors, such as work intensity, type of study, and rotation time. These differences ultimately lead to significant differences in sleep quality among medical students in different departments. Perceived social support at the group level may have a negative cross-level moderating effect on the relationship between stress and work rumination. Thus, groups that perceive more social support are more likely to resist stress, reducing the level of work rumination and improving sleep quality. Limitations and Outlook This study utilized medical students from a specific medical school as research subjects and supplemented the relevant literature with correlation, regression, and cross-level analyses. The proposed research hypotheses were verified by examining the relationship between perceived stress and sleep quality among students, and corresponding results were obtained. However, there are several limitations to this study: First, the study predominantly relied on self-report questionnaires for data collection and analysis. Although the scales used were highly reliable, some subjects may have intentionally concealed their true feelings due to social approval bias or self-defense mechanisms. Consequently, the actual situation of the subjects may not be accurately and objectively reflected. Additionally, as all the data were self-reported, they may be subject to recall bias. Second, owing to practical constraints, only a subset of medical students was included in the study. The sample may not sufficiently represent the entire medical student population, and the findings may not be generalizable to students in other specialties. Furthermore, the sample had a relatively high proportion of gender differences, affecting the results' external validity and applicability. Future research should aim to increase the sample's representativeness by broadening the sampling range, conducting multicenter and multidisciplinary studies, and including a more balanced gender ratio. Expanding the research to encompass a wider range of disciplines and universities could also improve the generalizability of the findings. 5. Conclusions Reducing stress, managing work rumination effectively, and increasing social support are crucial strategies for improving medical students' sleep quality. By implementing these measures, can help students manage stress more effectively, enhance emotional support, and improve both sleep quality and overall quality of life. 6. Application Perspectives Theoretical Value Previous studies have highlighted a bidirectional relationship between sleep quality and stress perception [ 26 ]. This study confirms that excessive stress perception predicts poor sleep quality, identifies work rumination as a risk factor for poor sleep quality, and establishes that stress perception also predicts work rumination. Furthermore, this study reveals the mediating role of work rumination in the relationship between stress perception and sleep quality. It also examines the cross-level moderating effect of perceived social support on this relationship among medical students and analyzes demographic differences such as gender, grade level, and place of origin within this specific population. Based on these findings, the following three contributions and innovations can be summarized: First, the study revealed a positive correlation between medical students' perceptions of stress and work rumination. This finding is important for understanding how stress perceptions impact mental health among medical students. By revealing this positive correlation, this study provides a foundation for developing effective coping strategies. Interventions targeting work rumination could reduce stress perceptions and improve psychological well-being. Second, the study revealed a negative correlation between work rumination and sleep quality. This contributes to understanding mental health issues among medical students, emphasizing the importance of good sleep quality for overall physical and mental health. The negative correlation highlights the need for intervention programs that address work rumination to enhance sleep quality among medical students. Third, perceived social support was found to play a crucial moderating role between stress perception and work rumination, as well as between work rumination and sleep quality. This finding is innovative and suggests that perceived social support may buffer the effects of stress perceptions on work rumination, thereby reducing psychological distress. Additionally, it may increase emotional support, mitigate work rumination, and improve sleep quality. This insight underscores the importance of enhancing social support systems to promote the mental health of medical students. These three research contributions and innovations are pivotal not only for improving the mental health of medical students but also for guiding the development of effective interventions and support systems. The results of this study offer valuable references for further exploration and solutions to address the perceptions of stress and mental health among medical students. Management Implications According to the current stress levels and sleep status of medical students, college administrators can implement several measures to enhance stress coping mechanisms and improve sleep quality. First, reducing the degree of psychological pressure on medical students is crucial. Research indicates a negative correlation between stress perception, work rumination, and sleep quality. Colleges and universities should provide psychological counseling and support services, establish counseling centers staffed with psychotherapists or trained counselors, offer professional psychological interventions, and develop comprehensive sleep management plans. Monitoring students' stress levels and psychological states can also help provide timely emotional support. Second, improving the management of work rumination is essential. Given the negative correlation between work rumination and sleep quality and how stress perception influences sleep quality through increased work rumination, administrators should encourage students to express their emotions openly and establish effective emotion management mechanisms. Promoting mutual support and communication between teachers and students, as well as among peers, can help reduce work rumination. Finally, increasing social support is vital for improving sleep quality. Higher levels of perceived social support weaken the relationship between stress perception and work rumination, as well as between work rumination and sleep quality. Administrators should help students identify and utilize social support resources effectively. Establishing a social support network that includes family and school and fostering a supportive school environment through strong teacher–student and peer relationships can enhance students' sense of belonging and social support. Encouraging teamwork within classes and departments, organizing diverse student and extracurricular activities, and addressing long shifts and working hours are also important. Hospital administrators and policy-makers should limit shift work and weekly hours to ensure quality sleep for medical students and support their overall well-being. Declarations Conflicts of Interest: The authors declare no conflicts of interest. Funding: This study is supported by the Innovation Research Fund of the Peking University First Hospital (No. 2022SF90). Author Contribution Conceptualization, Y-P.C.; methodology, H.X. and T.J.; software, H.X.; validation, T.J.; formal analysis, H.X. and T.J.; investigation, H.X.; resources,T.J.; data curation, H.X.; writing—original draft preparation, H.X.; writing—review and editing, Y-P.C. and T.J.; visualization, H.X.; supervision, Y-P.C.; project administration, Y-P.C.; funding acquisition, H.X. and Y-P.C. Acknowledgement We gratefully acknowledge professor YingWu Li at Renmin University of China for study design, and Shu-Duo Zhou at Medical Statistics Office of Peking University First Hospital for assisting data analysis. Data Availability All the raw data were submitted as supplementary data, and also available upon request to the corresponding author. References Coskun, O., Ocalan, A. O., Ocbe, C. B., Semiz, H. O. & Budakoglu, I. Depression and hopelessness in pre-clinical medical students. Clin. Teach. 16 (4), 345–351 (2019). Yu, D., Ren, Q., Dong, B., Zhao, D. & Sun, Y. The sleep quality of medical students in China: a meta-analysis. Sleep. Biol. Rhythms . 15 , 299–310 (2017). Li, T., Chen, X. & Liao, M. Mediating Role of Social Support System in Academic Stressors and Coping Strategies in Middle School Students. Res. Inst. Educ. Sci. 23 (1), 35–40 (2007). Cohen, S., Kamarck, T. & Mermelstein, R. A global measure of perceived stress. J. Health Soc. Behav. 24 (4), 385–396 (1983). Eskildsen, A. et al. Perceived stress, disturbed sleep, and cognitive impairments in patients with work-related stress complaints: A longitudinal study. Stress 20 (4), 371–378 (2017). Folkman, S., Lazarus, R. S., Dunkel-Schetter, C., DeLongis, A. & Gruen, R. J. Dynamics of a stressful encounter: cognitive appraisal, coping, and encounter outcomes. J. Personal. Soc. Psychol. 50 (5), 992–1003 (1986). Liang, Z., Suntrayuth, S., Sun, X. & Su, J. Positive Verbal Rewards, Creative Self-Efficacy, and Creative Behavior: A Perspective of Cognitive Appraisal Theory. (2023). Behavioral sciences (Basel, Switzerland), 13 (3): pp. 229–235. Kollarik, M. et al. Effects of rumination on unwanted intrusive thoughts: A replication and extension. J. Experimental Psychopathol. 11 (1), 7–13 (2020). Firoozabadi, A., Uitdewilligen, S. & Zijlstra, F. R. Solving problems or seeing troubles? A day-level study on the consequences of thinking about work on recovery and well-being, and the moderating role of self-regulation. Eur. J. Work Organizational Psychol. 27 (5), 629–641 (2018). Brosschot, J. F., Pieper, S. & Thayer, J. F. Expanding stress theory: prolonged activation and perseverative cognition. Psychoneuroendocrinology 30 (10), 1043–1049 (2005). Berset, M., Elfering, A., Lüthy, S., Lüthi, S. & Semmer, N. K. Work stressors and impaired sleep: rumination as a mediator. Stress health: J. Int. Soc. Invest. Stress . 27 (2), 71–82 (2011). Harvey, A. G. Pre-sleep cognitive activity: a comparison of sleep-onset insomniacs and good sleepers. Br. J. Clin. Psychol. 39 (3), 275–286 (2000). Zhu, Y., Lyu, Y., Wang, Y. & Wang, L. Coaching leadership effect on employees' creativity: Multilevel moderated mediator analysis. Acta Physiol. Sinica . 50 (3), 327–336 (2018). Li, X., Liu, P., Li, A., Wang, X. & Zhang, J. A multipath model of leader after-hours electronic communication expectations and employee job performance. Acta Physiol. Sinica . 54 (8), 964–978 (2022). Kozel, E., Barnoy, S. & Itzhaki, M. Emotion management of women at risk for premature birth: The association with optimism and social support. Appl. Nurs. research: ANR . 64 , 151568–151577 (2022). Gottlieb, B. H., Maitland, S. B. & Brown, J. Social support and adjustment among wives of men with prostate cancer. J. Psychosoc. Oncol. 32 (1), 16–36 (2014). Acoba, E. F. Social support and mental health: the mediating role of perceived stress. Front. Psychol. 15 , 1330–1340 (2024). Brislin, R. W. Back-translation for cross-cultural research. J. CrossCultural Psychol. 1 (3), 185–216 (1970). Buysse, D. J., Reynolds, C. F., Monk, T. H., Berman, S. R. & Kupfer, D. J. The Pittsburgh Sleep Quality Index: a new instrument for psychiatric practice and research. Psychiatry Res. 28 (2), 193–213 (1989). Querstret, D. & Cropley, M. Exploring the relationship between work-related rumination, sleep quality, and work-related fatigue. J. Occup. Health Psychol. 17 (3), 341–353 (2012). Van Laethem, M., Beckers, D. G. J., De Bloom, J., Sianoja, M. & Kinnunen, U. Challenge and hindrance demands in relation to self-reported job performance and the role of restoration, sleep quality, and affective rumination. J. Occup. Organizational Psychol. 92 (2), 225–254 (2019). Zimet, G. D., Dahlem, N. W., Zimet, S. G. & Farley, G. K. The multidimensional scale of perceived social support. J. Pers. Assess. 52 (1), 30–41 (1988). Zhou, J. et al. The underlying characteristics of sleep behavior and its relationship to sleep-related cognitions: a latent class analysis of college students in Wuhu city, China. Psychol. health Med. 25 (7), 887–897 (2020). Podsakoff, P. M., MacKenzie, S. B. & Podsakoff, N. P. Sources of method bias in social science research and recommendations on how to control it. Ann. Rev. Psychol. 63 , 539–569 (2012). Preacher, K. J. & Selig, J. P. Advantages of Monte Carlo Confidence Intervals for Indirect Effects. Communication Methods Measures . 6 (2), 77–98 (2012). Alvaro, P. K., Roberts, R. M. & Harris, J. K. A Systematic Review Assessing Bidirectionality between Sleep Disturbances, Anxiety, and Depression. Sleep 36 (7), 1059–1068 (2013). Additional Declarations No competing interests reported. Supplementary Files Rawdataofmedicalstudentsmanuscipt.zip Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 06 Jun, 2025 Reviews received at journal 27 May, 2025 Reviewers agreed at journal 26 May, 2025 Reviews received at journal 29 Dec, 2024 Reviewers agreed at journal 23 Dec, 2024 Reviewers invited by journal 10 Dec, 2024 Editor assigned by journal 10 Dec, 2024 Editor invited by journal 15 Nov, 2024 Submission checks completed at journal 14 Nov, 2024 First submitted to journal 08 Nov, 2024 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-5415327","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":388997125,"identity":"c7cb386e-dc4f-4201-ad24-2c9cf7595f51","order_by":0,"name":"Hao Xu","email":"","orcid":"","institution":"Peking University First Hospital","correspondingAuthor":false,"prefix":"","firstName":"Hao","middleName":"","lastName":"Xu","suffix":""},{"id":388997126,"identity":"667d8bd3-7d32-41a4-a091-9704398f577a","order_by":1,"name":"Talante Juma","email":"","orcid":"","institution":"Peking University First Hospital","correspondingAuthor":false,"prefix":"","firstName":"Talante","middleName":"","lastName":"Juma","suffix":""},{"id":388997127,"identity":"523063b0-568a-4976-abb1-f8b82bf1071c","order_by":2,"name":"Yongping Cao","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA2ElEQVRIiWNgGAWjYBAC9gYGBmYIq/ngg4SKGsJaeA7AtPAcSzZ4cOYYKVokfNQkH7YwE6FF+vDBxwUV9+z5JXjYKhIb2Bj427sT8GvhS0s2nnGmOHHm7N5jNxJ3yDBInDm7Aa8Wex4eM2netoQEgzvn0m4knmFjMJDIxa+Fh4f/+2+gFnv7GzlmBYltzMRo4WFjBmph3CCRY8ZApBY2Y2meMwmJM84cS5ZIOHOMh6BfeHiYH37mqUiw529vPvjxR0WNHH97L34tmGaQpnwUjIJRMApGAVYAAHNiRJBaVSlRAAAAAElFTkSuQmCC","orcid":"","institution":"Peking University First Hospital","correspondingAuthor":true,"prefix":"","firstName":"Yongping","middleName":"","lastName":"Cao","suffix":""}],"badges":[],"createdAt":"2024-11-08 09:23:18","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5415327/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5415327/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":71730039,"identity":"567ef76f-9ee8-4c6f-91a4-e114bf142367","added_by":"auto","created_at":"2024-12-18 06:42:14","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":76220,"visible":true,"origin":"","legend":"\u003cp\u003eModerating effect analysis of social support. A. Simple slope analysis of the moderating effect of social support on the relationship between perceived stress and work rumination. B. Simple slope analysis of the moderating effect of social support on the relationship between work rumination and sleep quality.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-5415327/v1/b53a2617c1771762d17e6973.png"},{"id":71730840,"identity":"853a3229-a622-4860-b3a3-b770d36702d9","added_by":"auto","created_at":"2024-12-18 06:50:14","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":18595,"visible":true,"origin":"","legend":"\u003cp\u003eIndividual-level path analysis, *p＜ 0.05, **p＜ 0.01, ***p\u0026lt; 0.001.\u003c/p\u003e","description":"","filename":"groupimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-5415327/v1/04f38060c31baa064fe68577.jpeg"},{"id":71732140,"identity":"ddc90718-ef86-4f48-9237-46825cda10ea","added_by":"auto","created_at":"2024-12-18 06:58:14","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":23494,"visible":true,"origin":"","legend":"\u003cp\u003eCross-level path analysis, *p＜ 0.05, **p＜ 0.01, ***p\u0026lt; 0.001.\u003c/p\u003e","description":"","filename":"groupimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-5415327/v1/f5975f27b2bb739d64b628f2.jpeg"},{"id":71732670,"identity":"123ff64d-7c61-4729-9898-944d7bef34f8","added_by":"auto","created_at":"2024-12-18 07:06:15","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":991519,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5415327/v1/f91d09d6-e952-4342-9d91-3f249b9cbaec.pdf"},{"id":71730043,"identity":"9b343432-dfa1-4afe-be0f-26934bbcf912","added_by":"auto","created_at":"2024-12-18 06:42:14","extension":"zip","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":206158,"visible":true,"origin":"","legend":"","description":"","filename":"Rawdataofmedicalstudentsmanuscipt.zip","url":"https://assets-eu.researchsquare.com/files/rs-5415327/v1/063cac218e15f6f3cb170d0c.zip"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Cross-Level Influence of Medical Students’ Perception of Stress on Sleep Quality—A Moderated Mediation Model","fulltext":[{"header":"1. Introduction and Hypotheses","content":"\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eCompared with those in other professions, medical students face unique challenges. They often contend with a heavy course load, high entry requirements, extended school years, challenging employment situations, complex doctor‒patient relationships, and high expectations from their families and society. As a result, medical students experience considerable pressure and are more prone to physical and mental health problems, such as anxiety, depression, and sleep disorders, than students in other fields are [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Previous studies have shown that the incidence of sleep disorders among Chinese medical students is greater than that among nonmedical students and the general population [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. However, existing research has focused primarily on identifying stress and coping styles [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e], with limited evidence specifically demonstrating how stress perception affects sleep quality among medical students.\u003c/p\u003e \u003cp\u003eTo address this gap, this study investigated the mechanisms linking stress perception and sleep quality among medical students. This study also provides empirical evidence to inform the design of stress management strategies and interventions to improve sleep quality within the context of Chinese medical education. Additionally, this study uses cognitive appraisal theory and the cognitive fixation hypothesis, and considers work rumination as a mediating variable to explore the moderating role of perceived social support in this relationship. This study offers several important contributions. First, it provides empirical evidence on how medical students' stress perceptions affect their sleep quality. Second, it clarifies the mediating role of work rumination and explores the intrinsic link between stress perception and sleep quality. Finally, it develops a moderated mediation model showing how reducing stress perceptions and rumination while enhancing social support can improve sleep quality.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec2\" class=\"Section2\"\u003e \u003ch2\u003e1.1 Perceived Stress and Sleep Quality in Medical Students\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003ePerceived stress refers to how an individual evaluates or interprets an external event as stressful. Individuals may perceive the same event differently due to subjective interpretations. According to Cohen et al. [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], perceived stress reflects the subjective evaluation of how unpredictable, uncontrollable, or overwhelming life circumstances are, shaped by an individual\u0026rsquo;s interpretation of various stressors and risk factors in life. Although the impact of perceived stress on health is well documented, most research has focused on its direct effects, with limited investigations into the underlying mechanisms involved. Empirical studies have demonstrated that perceived stress is negatively associated with sleep quality [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. According to cognitive appraisal theory, emotions result from complex interactions between a person and the environment rather than being generated in isolation [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. This study explores how these interactions influence sleep quality. Variations in cognitive appraisal mechanisms cause individuals to evaluate external stimuli differently, leading to diverse coping responses. Exposure to stress can elicit a range of responses in individuals. When individuals perceive stress as a significant burden on their psychological and physiological state, they may experience difficulty achieving and maintaining relaxation for sleep, which can contribute to insomnia symptoms [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. This study aims to expand the understanding of the negative impact of perceived stress by examining the sleep quality of medical students. Drawing on cognitive appraisal theory, this study proposes the following hypothesis:\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eHypothesis 1\u003c/strong\u003e \u003cp\u003eMedical students' stress perceptions negatively affect sleep quality.\u003c/p\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e1.2 Mediating Role of Work Rumination\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eKollarik et al. [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] defined rumination as \"a type of thought that is manifested by the repetition of memories, feelings, and the frequent occurrence of such thoughts in situations that do not require them very much.\" According to this definition, rumination is generally understood as a negative thought process focused on repeating negative experiences. Firoozabadi et al. [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] identified two dimensions of work rumination: emotional rumination and problem-solving contemplation. Emotional rumination is characterized by pervasive, intrusive, and repetitive thoughts focused on work-related problems, often triggering negative emotions such as worry and distress. In contrast, problem-solving contemplation involves finding solutions to work-related problems by thinking about them over an extended period without considering emotional factors. According to the perseverative cognition hypothesis, persistent thinking with different characteristics can have various physiological and psychological effects. Stress can induce cognitive fixation [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], causing individuals to continuously dwell on or recall past work experiences during nonwork time. This cognitive fixation leads to the investment of more resources in negative work rumination, which reactivates psychological and physiological stress responses and affects sleep quality [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Harvey et al. [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] reported that individuals with insomnia were more preoccupied with anxiety and problems and more likely to recall daytime events than those with good sleep quality. In summary, stress leads to persistent cognitive fixation, which in turn induces job rumination. Excessive job rumination creates a chain reaction that exacerbates insomnia, anxiety, and other physical and mental health issues. While previous studies on stress and work rumination have focused mainly on job performance, employee innovation behavior, leadership, and related fields [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], there has been limited research on medical students. Therefore, investigating the mechanisms linking stress cognition to sleep quality among medical students is crucial. Thus, the cognitive fixation hypothesis aims to determine whether job rumination consistently triggers psychological and physiological responses and to evaluate its subsequent effects. The theory discussed provides a strong framework for understanding how job rumination impacts individuals' physiological and psychological health, as well as job performance. Consequently, Hypothesis \u003cspan refid=\"FPar2\" class=\"InternalRef\"\u003e2\u003c/span\u003e is proposed:\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eHypothesis 2\u003c/strong\u003e \u003cp\u003eJob rumination plays a mediating role in the relationship between stress perception and sleep quality.\u003c/p\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e1.3 Perceived Moderating Role of Social Support\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eSocial support refers to the assistance an individual receives from significant others in stressful situations, such as family members, friends, or neighbors. This support can take various forms, including socioemotional support, informational support, and practical help [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. According to Gottlieb et al. [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], social support encompasses the resources perceived to be available to an individual, whether from formal support groups or informal sources [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Research indicates that social support involves a provider offering resources such as emotional support, recognition, and practical help to meet the recipient's personal needs. For medical students, social support typically comes from family, friends, classmates, and teachers. Previous studies have identified social support as a crucial factor influencing stress perception and work rumination [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. In teams with high perceived social support, stress perception can be heightened, presenting as a competitive and conflictual condition influenced by the overall environment. However, such teams also exhibit a modulation of work rumination and sleep quality. Perceived social support can offer emotional, informational, and material resources that help reduce stress perceptions and enhance an individual's psychological coping skills. Investigating the moderating role of perceived social support in the relationship between stress perceptions and work rumination can provide deeper insights into how social support aids in managing stress and work-related rumination. Exploring methods to mitigate the negative effects of stress on work rumination can offer future insights into how social support contributes to an individual's psychological adjustment process.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eHypothesis 3\u003c/strong\u003e \u003cp\u003ePerceived social support negatively moderates the relationship between stress perceptions and work rumination and positively moderates the relationship between work rumination and sleep quality.\u003c/p\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"2. Methodology","content":"\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Survey Participants and Administration Procedures\u003c/h2\u003e \u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eWe selected 350 medical students from a medical university in China to participate in a questionnaire survey via the timed interval-based experience sampling methodology (TISM). All procedures performed involving human participants were in accordance with the ethical standards of the 1964 Helsinki declaration and its later amendments or comparable ethical standards. The study protocol was reviewed by the Ethics Committee of the Clinical Trial Management, Peking University First Hospital of China (approval No. 2024RES-602-001), informed consent was obtained from all individual participants included in the study. Since the respondents were from a single source, the questionnaires were based on individual subjective self-assessments. To reduce common variance, the questionnaire was administered in three phases:\u003c/p\u003e\u003cp\u003ePhase 1 (T1 time point: June 2023): Basic demographic information and stress levels of 350 medical students were investigated.\u003c/p\u003e\u003cp\u003ePhase 2 (T2 time point: July 2023): Four weeks later, the students who returned valid questionnaires in Phase 1 were followed up to assess work rumination and social support.\u003c/p\u003e\u003cp\u003ePhase 3 (T3 time point: August 2023): Another four weeks later, the students who returned valid questionnaires in Phase 2 were surveyed to measure their sleep patterns. After the three rounds of surveys, the questionnaire results were double-checked and cleaned. The criteria for data cleaning included deleting samples with identical selection results for all Likert scale indicators, excluding samples with response times exceeding\u0026thinsp;\u0026plusmn;\u0026thinsp;3 standard deviations from the mean, and correcting logical errors, such as implausible ages or graduation years. After this process, 318 valid samples were retained, resulting in a recovery rate of 90.86%. By verifying the basic personal information provided by the matched medical students, this study obtained a total of 43 department\u0026ndash;individual paired clusters with 318 valid individual questionnaires, averaging 7.5 samples per cluster. The descriptive statistics of the variables (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) showed there were 120 males and 198 females, indicating a greater proportion of females. The mean age of the participants was 27.12\u0026thinsp;\u0026plusmn;\u0026thinsp;2.47 years. Among the participants, 269 (84.6%) were unmarried, and 123 (38.7%) were in their senior year. The proportions of only children and non-only children were similar. The highest proportion of students were academic doctoral students (37.4%), followed by professional doctoral students (25.2%) and professional master\u0026rsquo;s students (22.0%). Academic master\u0026rsquo;s degree students constituted the lowest proportion (15.4%).\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Measurements\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eAll the scales were translated into Chinese. [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cb\u003ePerceived Stress\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe Perceived Stress Scale (PSS), developed by [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], is a widely used instrument for measuring perceived stress. It evaluates situational stress, the effectiveness of stress reduction interventions, and stress-related psychosomatic disorders. Examples of items include \"feeling upset when something unexpected happens\" and \"feeling that I can deal effectively with issues such as important changes in my life.\" The questionnaire uses a 5-point Likert scale ranging from 0 (never) to 4 (very often). The total or mean score of the items reflects the individual\u0026rsquo;s level of perceived stress, with higher scores indicating greater stress. The Cronbach's alpha coefficient for this scale is 0.84.\u003c/p\u003e \u003cp\u003e \u003cb\u003eSleep Quality\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe Pittsburgh Sleep Quality Index (PSQI), developed by Buysse et al. [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], assesses sleep quality over the previous month. 0It comprises 24 items, of which 18 self-report items are used for scoring. These items are categorized into 7 components, including sleep duration, subjective sleep quality, and sleep disturbances. Each component is scored on a 0\u0026ndash;3 scale, and the total PSQI score is obtained by summing the component scores. Higher total scores indicate poorer sleep quality, with a PSQI score of \u0026ge;\u0026thinsp;8, of a sleep disordeindicative r. The Cronbach's alpha coefficient for this scale is 0.83.\u003c/p\u003e \u003cp\u003e \u003cb\u003eWork Rumination\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe Work Rumination Rating Scale (WRRQ), developed by [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], originally included three subscales: emotional rumination, problem-solving rumination, and disengagement. However, subsequent studies have discarded the disengagement subscale because of its lack of accuracy in measuring work rumination. The current methodology employs two subscales, emotional rumination and problem-solving contemplation, each with five items. The respondents used a 5-point scale to indicate the frequency of their thoughts, ranging from 1 (hardly ever) to 5 (all the time), with higher scores reflecting greater work rumination. The Cronbach's α coefficients for emotional rumination and problem-solving contemplation are 0.90 and 0.81, respectively.\u003c/p\u003e \u003cp\u003e \u003cb\u003ePerceived Social Support\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe Perceived Social Support Scale, developed by [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], assesses an individual's self-perceived social support from family, friends, and others. The scale includes 12 items divided into three dimensions, with specific items related to support from each source: family (Items 11, 3, 4, and 8), friends (Items 6, 7, 9, and 12), and others (Items 1, 2, 5, and 10). The responses are rated on a 1\u0026ndash;7 scale ranging from strongly disagree to strongly agree. The Cronbach's alpha coefficient for this scale is 0.85.\u003c/p\u003e \u003cp\u003e \u003cb\u003eControl Variables\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe choice of control variables is crucial [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. This study's control variables included gender, age, marital status, whether the participants were only children, type of education, night shift work, and recent major life changes. These variables were selected because college students' personal routines and demographic characteristics can significantly affect their sleep quality [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Statistical Analysis\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eIn this study, Harman's one-way analysis of variance [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] was employed to test for common method bias. Since \"sleep quality\" was measured via objective indicators, its reliability and validity were not assessed. Consequently, all variables except \"sleep quality\" were included in the analysis. A common method factor was also incorporated into the baseline model to further test for common method bias. Descriptive statistics and correlation analyses were subsequently conducted. Pearson's correlation coefficient was used to determine the relationships between medical students' stress perceptions and sleep quality, as well as between work rumination and sleep quality. Finally, tests for mediation effects, moderation effects, and mediation effects with moderation and cross-level moderation models (individual-level mediation path analysis, individual-level moderation effects analysis, cross-level mediation model test, and cross-level moderation model test) were conducted [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. The above data were analyzed via SPSS 26.0 and Mplus 8.3 software.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Factor Analysis Validation\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eIn the 3-factor model, a common method variance (CMV) factor was added. The model fit parameters were as follows: χ\u0026sup2;/df\u0026thinsp;=\u0026thinsp;1.191, RMSEA\u0026thinsp;=\u0026thinsp;0.024, SRMR\u0026thinsp;=\u0026thinsp;0.036, CFI\u0026thinsp;=\u0026thinsp;0.984, TLI\u0026thinsp;=\u0026thinsp;0.983. These fit parameters did not improve compared with those of the baseline model (χ\u0026sup2;/df\u0026thinsp;=\u0026thinsp;1.191, RMSEA\u0026thinsp;=\u0026thinsp;0.024, SRMR\u0026thinsp;=\u0026thinsp;0.036, CFI\u0026thinsp;=\u0026thinsp;0.984, TLI\u0026thinsp;=\u0026thinsp;0.983), suggesting that common method bias had a limited effect.\u003c/p\u003e \u003cp\u003eAmong the models presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, only the 3-factor model met the fit criteria, with parameters of χ\u0026sup2;/df\u0026thinsp;=\u0026thinsp;1.191, RMSEA\u0026thinsp;=\u0026thinsp;0.024, SRMR\u0026thinsp;=\u0026thinsp;0.036, CFI\u0026thinsp;=\u0026thinsp;0.984, and TLI\u0026thinsp;=\u0026thinsp;0.983. In contrast, at least one fit parameter of the 2-factor and 1-factor models did not meet the threshold criteria. This finding indicates that the 3-factor model provided the best fit and demonstrated differential validity.\u003c/p\u003e \u003c/div\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\u003eFit indices for measurement models (Fit indices for measurement models)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\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 \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eχ\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003edf\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eχ\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e/\u003cem\u003edf\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRMSEA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCFI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eTLI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eSRMR\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParameter\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=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFactor 3\u0026thinsp;+\u0026thinsp;CMV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e697.777\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e586\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.191\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.984\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.983\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.036\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3-Factor (Baseline Model)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e697.777\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e586\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.191\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.984\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.983\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.036\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFactor 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1779.319\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e861\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.067\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.058\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.882\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.876\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.128\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFactor 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4915.370\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e860\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.716\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.122\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.477\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.451\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.140\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\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e Factor 3\u0026thinsp;+\u0026thinsp;CMV: Work Rumination Scale, Perceived Social Support Scale, Perceived Stress Scale\u0026thinsp;+\u0026thinsp;Common Method Variance (CMV); 3-Factor (Baseline Model): Work Rumination Scale, Perceived Social Support Scale, Perceived Stress Scale. Factor 2 model: Work Rumination Scale\u0026thinsp;+\u0026thinsp;Perceived Social Support Scale, Stress Perception Scale. Factor 1 model: Work Rumination Scale\u0026thinsp;+\u0026thinsp;Perceived Social Support Scale\u0026thinsp;+\u0026thinsp;Stress Perception Scale.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Description and Correlation Analysis of Variables\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThis study employed the timed interval-based experience sampling methodology (TISM) for the questionnaire survey. To mitigate common variance, the survey was administered in three phases. In the first phase (T1: June 2023), 350 medical students from one university were surveyed to collect basic demographic information and stress perceptions. Four weeks later, in the second phase (T2: July 2023), the students who returned valid questionnaires in the first phase were followed up to assess work rumination and social support. Another four weeks later, in the third phase (T3: August 2023), the same group was surveyed again to measure sleep quality. After the three survey rounds, the data were double-checked and cleaned, resulting in 318 valid questionnaires, yielding a recovery rate of 90.86%. By verifying the matched medical students\u0026rsquo; basic personal information, such as departmental affiliation, 43 department\u0026ndash;individual paired clusters with an average sample size of 7.5 per group were obtained.\u003c/p\u003e \u003cp\u003eThe descriptive statistics of the variables (see Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) indicated that 120 participants were male and 198 were female, indicating a greater proportion of females. The mean age of the participants was 27.12\u0026thinsp;\u0026plusmn;\u0026thinsp;2.47 years. Among them, 269 were unmarried (84.6%), and 123 were college graduates (38.7%). The proportions of only children and non-only children were nearly equal. The highest proportion of participants were academic doctoral students (37.4%), followed by professional doctoral students (25.2%) and professional master's students (22.0%), with the lowest proportion being academic master's students (15.4%).\u003c/p\u003e \u003c/div\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\u003eDescriptive statistics of variables\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=\"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 \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\u003eCategory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNumber\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eProportion(%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e37.7\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\u003eWoman\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e198\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e62.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarriage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnmarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e269\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e84.6\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\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOnly-Child\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\u003e155\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e48.7\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\u003e163\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e51.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGrade\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGraduating class\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e123\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e38.7\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\u003enon-Graduating class\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e195\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e61.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAcademic master's degree program\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15.4\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\u003eDoctor of Philosophy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e119\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e37.4\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\u003eProfessional Master\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e22.0\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\u003eDoctor of Medicine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLocation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e156\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e49.1\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\u003eTown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e24.5\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\u003eRural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e26.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNight duty\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\u003e146\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e45.9\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\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e172\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e54.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChief resident\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\u003e53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e16.7\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\u003e265\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e83.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMajor assessments\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\u003e115\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e36.2\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\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e203\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e63.8\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=\"BlockQuote\"\u003e \u003cp\u003eSpearman's rank correlation coefficient was used to analyze the correlation of the variables in the study, and the results of the correlation coefficient matrix of the variables are shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. The data in the table indicate that among the four variables, the correlations of stress perception, work rumination, and sleep quality are significant, meeting the requirements of regression analysis. In contrast, the correlations between the moderating variables of social support and work rumination are not significant. Because the moderating effect test focuses only on whether the intensity of influence between variables is related to the value of the moderating variable, it does not need to consider the relationship between the moderating variable and other variables; thus, the correlation between social support and work rumination is not significant and does not affect the subsequent analysis link.\u003c/p\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\u003eCorrelation analysis of variables\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=\"left\" 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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePerceived Stress\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWork rumination\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSocial support\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSleep quality\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePerceived Stress\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\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\u003eWork rumination\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.535**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\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 support\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.226**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.069\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \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\u003eSleep quality\u003c/p\u003e \u003cp\u003eGender-based\u003c/p\u003e \u003cp\u003eMarriage\u003c/p\u003e \u003cp\u003eOnly-Child\u003c/p\u003e \u003cp\u003eGrade\u003c/p\u003e \u003cp\u003eEducation\u003c/p\u003e \u003cp\u003eLocation\u003c/p\u003e \u003cp\u003eNight duty\u003c/p\u003e \u003cp\u003eChief resident\u003c/p\u003e \u003cp\u003eMajor assessments\u003c/p\u003e \u003cp\u003eAccident\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.468**\u003c/p\u003e \u003cp\u003e0.118*\u003c/p\u003e \u003cp\u003e0.07\u003c/p\u003e \u003cp\u003e0.03\u003c/p\u003e \u003cp\u003e0.05\u003c/p\u003e \u003cp\u003e0.02\u003c/p\u003e \u003cp\u003e-0.01\u003c/p\u003e \u003cp\u003e0.02\u003c/p\u003e \u003cp\u003e-0.08\u003c/p\u003e \u003cp\u003e-0.03\u003c/p\u003e \u003cp\u003e-0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.391**\u003c/p\u003e \u003cp\u003e-0.06\u003c/p\u003e \u003cp\u003e0.05\u003c/p\u003e \u003cp\u003e-0.03\u003c/p\u003e \u003cp\u003e0.01\u003c/p\u003e \u003cp\u003e0.06\u003c/p\u003e \u003cp\u003e0.13*\u003c/p\u003e \u003cp\u003e-0.01\u003c/p\u003e \u003cp\u003e-0.02\u003c/p\u003e \u003cp\u003e-0.03\u003c/p\u003e \u003cp\u003e-0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.352**\u003c/p\u003e \u003cp\u003e0.00\u003c/p\u003e \u003cp\u003e-0.03\u003c/p\u003e \u003cp\u003e-0.10\u003c/p\u003e \u003cp\u003e0.03\u003c/p\u003e \u003cp\u003e-0.01\u003c/p\u003e \u003cp\u003e-0.11\u003c/p\u003e \u003cp\u003e-0.02\u003c/p\u003e \u003cp\u003e-0.00\u003c/p\u003e \u003cp\u003e0.04\u003c/p\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003e0.02\u003c/p\u003e \u003cp\u003e-0.03\u003c/p\u003e \u003cp\u003e-0.09\u003c/p\u003e \u003cp\u003e-0.01\u003c/p\u003e \u003cp\u003e0.05\u003c/p\u003e \u003cp\u003e0.02\u003c/p\u003e \u003cp\u003e-0.07\u003c/p\u003e \u003cp\u003e0.04\u003c/p\u003e \u003cp\u003e0.07\u003c/p\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e*\u003cem\u003ep\u003c/em\u003e\u0026lt; 0.05, **\u003cem\u003ep\u003c/em\u003e\u0026lt; 0.01, ***\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Regression Analysis\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003e \u003cb\u003eAnalysis of Moderating Effects at the Individual Level\u003c/b\u003e \u003c/p\u003e \u003cp\u003eAs shown in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, to examine the effect of perceived stress on work rumination, with gender, age, and other variables as control variables, a hierarchical linear model (HLM) was used. In Model 1, perceived stress was added to the control variables. The results indicated that the regression coefficient for perceived stress on work rumination was b\u0026thinsp;=\u0026thinsp;0.293, with a significance level of p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, indicating a significant positive effect of perceived stress on work rumination.\u003c/p\u003e \u003cp\u003eSimilarly, we used hierarchical linear modeling to test the influence of perceived stress on sleep quality, with gender and age as control variables and work rumination and sleep quality as the mediator and dependent variables, respectively. In Model 2, which included control variables, the regression coefficient for perceived stress on sleep quality was b = -0.138, with a significance level of p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, indicating a significant negative effect of perceived stress on sleep quality.\u003c/p\u003e \u003cp\u003eIn Model 3, the regression coefficient for work rumination on sleep quality was b = -0.118, with p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, indicating a significant negative effect of work rumination on sleep quality. Since the relationships in Model 1 (independent variable to mediator) and Model 3 (mediator to dependent variable) were both significant, a mediation model was tested with perceived stress as the predictor variable, sleep quality as the outcome variable, and work rumination as the mediator. The results revealed significant mediation effects, with an indirect effect of 0.224, confirming that work rumination significantly mediated the relationship between perceived stress and sleep quality.\u003c/p\u003e \u003cp\u003eModel 3 also revealed a significant direct effect of perceived stress on sleep quality, with coefficients of b = -0.104 and p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, indicating that the mediation model reflects a partial mediation effect. This means that the effect of perceived stress on sleep quality occurs both directly and indirectly through work rumination.\u003c/p\u003e \u003cp\u003eWhen social support was used as a moderator, the interaction term \"perceived stress \u0026times; social support\" revealed a significant negative regression effect on work rumination, with coefficients of b = -0.913 and p\u0026thinsp;=\u0026thinsp;0.003. These findings suggest that social support significantly moderates the effect of perceived stress on work rumination. Furthermore, the interaction term \"work rumination \u0026times; social support\" had a significant positive regression effect on sleep quality, with coefficients of b\u0026thinsp;=\u0026thinsp;0.734 and p\u0026thinsp;\u0026lt;\u0026thinsp;0.001. These findings indicate that social support plays a significant positive moderating role in the relationship between work rumination and sleep quality. The specific calculation results are detailed in Models 4 and 5.\u003c/p\u003e \u003c/div\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\u003eIndividual-level moderation\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"21\"\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=\"left\" 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=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c16\" colnum=\"16\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c17\" colnum=\"17\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c18\" colnum=\"18\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c19\" colnum=\"19\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c20\" colnum=\"20\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c21\" colnum=\"21\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eModel 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c9\" namest=\"c6\"\u003e \u003cp\u003eModel 2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c13\" namest=\"c10\"\u003e \u003cp\u003eModel 3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c17\" namest=\"c14\"\u003e \u003cp\u003eModel 4\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c21\" namest=\"c18\"\u003e \u003cp\u003eModel 5\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eλ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eλ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eλ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003eλ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003eλ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIntercept\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.934\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.944\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.166\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.244\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12.352\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.364\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.671\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e13.167\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e3.304\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e3.986\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e14.511\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e5.791\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e2.506\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e0.013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e6.451\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e3.038\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e2.123\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e0.035\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.759\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.655\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.158\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.248\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.074\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.371\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.842\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.163\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.364\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.449\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.654\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.605\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.932\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e0.352\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e0.292\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e0.338\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e0.864\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e0.388\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=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.363\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.154\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.354\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.035\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.087\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.399\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.690\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.077\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.086\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.899\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.370\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.333\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.153\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e2.181\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e0.074\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e0.919\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e0.359\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarriage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.757\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.921\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.822\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.412\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.095\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.521\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.182\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.856\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.184\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.511\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e-0.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.719\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e-0.449\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.914\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e-0.491\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e0.624\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e-0.251\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e0.475\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e-0.527\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e0.598\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOne Child\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.959\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.313\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.190\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.413\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.440\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.121\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.406\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e2.761\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.976\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.723\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e1.349\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e0.178\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e0.925\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e0.378\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e2.447\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e0.015\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGrade\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.819\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.695\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.179\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.239\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.126\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.393\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.320\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.749\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.222\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.386\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.575\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.565\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.984\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.687\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e1.431\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e0.153\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e0.295\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e0.358\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e0.822\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e0.412\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.726\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.517\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-1.403\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.162\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.053\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.293\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.181\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.857\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.032\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.288\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e-0.112\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.911\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e-0.655\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.511\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e-1.281\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e0.201\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e0.267\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e0.035\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e0.972\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLocation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.356\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.432\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.825\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.410\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.256\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.245\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-1.046\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.296\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.298\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e-1.241\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.216\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e-0.332\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.427\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e-0.776\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e0.438\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e-0.244\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e0.223\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e-1.096\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e0.274\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNight duty\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-1.020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-1.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.313\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.195\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.571\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.341\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.733\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.075\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.561\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.134\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.894\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e-1.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.998\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e-1.093\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e0.275\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e-0.122\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e0.521\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e-0.234\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e0.815\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChief resident\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.259\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.069\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.242\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.809\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.295\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.605\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.487\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.627\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.325\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.593\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.548\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.584\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.299\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e1.057\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.283\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e0.778\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e0.633\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e0.552\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e1.146\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e0.253\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMajor assessments\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.351\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.689\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.509\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.611\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.289\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.460\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.247\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.382\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e-0.647\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.518\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.445\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.684\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.651\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e0.515\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e-0.112\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e0.357\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e-0.313\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e0.754\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAccident\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.443\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.035\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.428\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.669\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.808\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.586\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-1.379\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.169\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.756\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.574\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e-1.317\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.189\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.298\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e1.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.289\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e0.772\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e-0.416\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e0.536\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e-0.777\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e0.438\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePerceived Stress\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.293\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.026\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.162\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.138\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-9.283\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.104\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e-5.989\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e3.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.315\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e11.097\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e-0.874\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e0.196\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e-4.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWork rumination\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=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.118\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.032\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e-3.703\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e-0.775\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e0.191\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e-4.063\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSocial support\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=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.432\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.322\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e1.342\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e0.181\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e0.906\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e0.166\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e5.446\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePerceived Stress*Social support\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=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e-0.913\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e-3.041\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWork rumination*Social support\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=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e0.734\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e0.157\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e4.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eR\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003e0.311\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c9\" namest=\"c6\"\u003e \u003cp\u003e0.242\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c13\" namest=\"c10\"\u003e \u003cp\u003e0.274\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c17\" namest=\"c14\"\u003e \u003cp\u003e0.333\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c21\" namest=\"c18\"\u003e \u003cp\u003e0.379\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eAdjust R\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003e0.284\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c9\" namest=\"c6\"\u003e \u003cp\u003e0.212\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c13\" namest=\"c10\"\u003e \u003cp\u003e0.243\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c17\" namest=\"c14\"\u003e \u003cp\u003e0.302\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c21\" namest=\"c18\"\u003e \u003cp\u003e0.349\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eF\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003e11.463\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c9\" namest=\"c6\"\u003e \u003cp\u003e8.094\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c13\" namest=\"c10\"\u003e \u003cp\u003e8.837\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c17\" namest=\"c14\"\u003e \u003cp\u003e10.810\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c21\" namest=\"c18\"\u003e \u003cp\u003e12.308\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c9\" namest=\"c6\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c13\" namest=\"c10\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c17\" namest=\"c14\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c21\" namest=\"c18\"\u003e \u003cp\u003e0.000\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=\"BlockQuote\"\u003e \u003cp\u003e \u003cb\u003eSimple slope analysis at the individual level\u003c/b\u003e \u003c/p\u003e \u003cp\u003eTo better compare the moderating effects, simple slope analyses were conducted to examine the slopes of the effects of perceived stress on work rumination and work rumination on sleep quality at different levels of the moderating variables. The details of these moderating effects are illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. As the values of the moderating variables increase, the positive effect of perceived stress on work rumination diminishes, whereas the negative effect of work rumination on sleep quality weakens. Furthermore, the effect of work rumination on sleep quality is attenuated.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003e \u003cb\u003eResults of single-level path analysis\u003c/b\u003e \u003c/p\u003e \u003cp\u003eAccording to the regression analysis and the mediation adjustment test, the individual-level path coefficients are illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Cross-Level Path Analysis\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThe cross-level moderating model test revealed a significant negative regression effect of perceived stress \u0026times; social support on work rumination, with regression coefficients of \\(b = -0.551 \\) and \\(p\u0026thinsp;=\u0026thinsp;0.015 \\). These findings indicate that social support significantly moderates the effect of perceived stress on work rumination, with the positive effect of perceived stress on work rumination decreasing as social support increases.\u003c/p\u003e \u003cp\u003eAdditionally, there was a significant positive regression effect of work rumination \u0026times; social support on sleep quality, with regression coefficients of \\(b\u0026thinsp;=\u0026thinsp;0.840 \\) and \\(p\u0026thinsp;\u0026lt;\u0026thinsp;0.001 \\). These findings suggest that social support significantly moderates the effect of work rumination on sleep quality, with the negative effect of work rumination on sleep quality diminishing as social support increases. The results of the cross-level path analysis are illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThis study revealed that when medical students are under relatively high levels of stress, stress directly affects the quality of their sleep. The study also found that work rumination interferes with an individual's state of relaxation by increasing cognitive load and psychological tension, affecting sleep quality. Additionally, sleep quality and perceived stress among medical students were strongly associated with social support, with social support moderating the relationship between stress and sleep quality.\u003c/p\u003e \u003cp\u003eOur study was analyzed at both the individual and group levels. At the individual level, psychological stress and negative emotions are inevitable when medical students are faced with a new medical environment, complex social relationships, and important role transitions. However, as the level of social support increases, medical students become concerned with and encouraged by others, reducing their study and life stress and, thus, preventing them from falling into work rumination. Additionally, our study revealed that social support moderated the role of work rumination in the relationship between perceived stress and sleep quality. In the cultural environment of colleges and universities, the concerns of family, friends, faculty, and students provide important psychological support to medical students by diverting their attention, relaxing them, and avoiding excessive emotional rumination, thus improving their sleep quality. However, individuals with low perceived social support may engage in work-related rumination, contributing to poor sleep quality.\u003c/p\u003e \u003cp\u003eThrough group-level analyses, we found a moderating effect of social support on the mediating role of work rumination between perceived stress and sleep quality. Our results show that the effect of perceived stress on sleep quality among medical students varies across departments. This phenomenon can be explained in several ways:\u003c/p\u003e \u003cp\u003eFirst, the intensity of work stress and the nature of work faced by medical students in different departments vary. Significant differences exist in the intensity and nature of work in different departments. For example, departments such as the emergency room and surgery usually have high work intensity and require quick decision-making and long hours of intensive work, which tends to cause high mental stress among medical students. This stress can lead to difficulty falling asleep, shorter sleep duration, and poorer sleep quality. On the other hand, medical students in departments with relatively lower work intensity, such as internal medicine or pathology, may have relatively better sleep quality because of relatively lower stress. Additionally, different types of medical students have different training goals: some aim to train applied clinicians, while others emphasize the cultivation of scientific research ability and scientific thinking, resulting in different requirements for clinical and scientific research ability. Finally, rotation schedules in different departments may affect medical students' sleep quality differently. For example, when they rotate in the emergency department or intensive care unit (ICU), medical students are usually required to work night shifts, disrupting circadian rhythms and affecting sleep quality. In some departments with relatively regular daily routines, medical students may have more stable routines, and their sleep may be less affected.\u003c/p\u003e \u003cp\u003eIn summary, the differences in stress levels among medical students in different departments can be explained by a variety of factors, such as work intensity, type of study, and rotation time. These differences ultimately lead to significant differences in sleep quality among medical students in different departments. Perceived social support at the group level may have a negative cross-level moderating effect on the relationship between stress and work rumination. Thus, groups that perceive more social support are more likely to resist stress, reducing the level of work rumination and improving sleep quality.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eLimitations and Outlook\u003c/b\u003e \u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThis study utilized medical students from a specific medical school as research subjects and supplemented the relevant literature with correlation, regression, and cross-level analyses. The proposed research hypotheses were verified by examining the relationship between perceived stress and sleep quality among students, and corresponding results were obtained. However, there are several limitations to this study:\u003c/p\u003e \u003cp\u003eFirst, the study predominantly relied on self-report questionnaires for data collection and analysis. Although the scales used were highly reliable, some subjects may have intentionally concealed their true feelings due to social approval bias or self-defense mechanisms. Consequently, the actual situation of the subjects may not be accurately and objectively reflected. Additionally, as all the data were self-reported, they may be subject to recall bias.\u003c/p\u003e \u003cp\u003eSecond, owing to practical constraints, only a subset of medical students was included in the study. The sample may not sufficiently represent the entire medical student population, and the findings may not be generalizable to students in other specialties. Furthermore, the sample had a relatively high proportion of gender differences, affecting the results' external validity and applicability. Future research should aim to increase the sample's representativeness by broadening the sampling range, conducting multicenter and multidisciplinary studies, and including a more balanced gender ratio. Expanding the research to encompass a wider range of disciplines and universities could also improve the generalizability of the findings.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e"},{"header":"5. Conclusions","content":"\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eReducing stress, managing work rumination effectively, and increasing social support are crucial strategies for improving medical students' sleep quality. By implementing these measures, can help students manage stress more effectively, enhance emotional support, and improve both sleep quality and overall quality of life.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e"},{"header":"6. Application Perspectives","content":"\u003cp\u003e \u003cb\u003eTheoretical Value\u003c/b\u003e \u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003ePrevious studies have highlighted a bidirectional relationship between sleep quality and stress perception [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. This study confirms that excessive stress perception predicts poor sleep quality, identifies work rumination as a risk factor for poor sleep quality, and establishes that stress perception also predicts work rumination. Furthermore, this study reveals the mediating role of work rumination in the relationship between stress perception and sleep quality. It also examines the cross-level moderating effect of perceived social support on this relationship among medical students and analyzes demographic differences such as gender, grade level, and place of origin within this specific population.\u003c/p\u003e \u003cp\u003eBased on these findings, the following three contributions and innovations can be summarized:\u003c/p\u003e \u003cp\u003eFirst, the study revealed a positive correlation between medical students' perceptions of stress and work rumination. This finding is important for understanding how stress perceptions impact mental health among medical students. By revealing this positive correlation, this study provides a foundation for developing effective coping strategies. Interventions targeting work rumination could reduce stress perceptions and improve psychological well-being.\u003c/p\u003e \u003cp\u003eSecond, the study revealed a negative correlation between work rumination and sleep quality. This contributes to understanding mental health issues among medical students, emphasizing the importance of good sleep quality for overall physical and mental health. The negative correlation highlights the need for intervention programs that address work rumination to enhance sleep quality among medical students.\u003c/p\u003e \u003cp\u003eThird, perceived social support was found to play a crucial moderating role between stress perception and work rumination, as well as between work rumination and sleep quality. This finding is innovative and suggests that perceived social support may buffer the effects of stress perceptions on work rumination, thereby reducing psychological distress. Additionally, it may increase emotional support, mitigate work rumination, and improve sleep quality. This insight underscores the importance of enhancing social support systems to promote the mental health of medical students.\u003c/p\u003e \u003cp\u003eThese three research contributions and innovations are pivotal not only for improving the mental health of medical students but also for guiding the development of effective interventions and support systems. The results of this study offer valuable references for further exploration and solutions to address the perceptions of stress and mental health among medical students.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eManagement Implications\u003c/b\u003e \u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eAccording to the current stress levels and sleep status of medical students, college administrators can implement several measures to enhance stress coping mechanisms and improve sleep quality.\u003c/p\u003e \u003cp\u003eFirst, reducing the degree of psychological pressure on medical students is crucial. Research indicates a negative correlation between stress perception, work rumination, and sleep quality. Colleges and universities should provide psychological counseling and support services, establish counseling centers staffed with psychotherapists or trained counselors, offer professional psychological interventions, and develop comprehensive sleep management plans. Monitoring students' stress levels and psychological states can also help provide timely emotional support.\u003c/p\u003e \u003cp\u003eSecond, improving the management of work rumination is essential. Given the negative correlation between work rumination and sleep quality and how stress perception influences sleep quality through increased work rumination, administrators should encourage students to express their emotions openly and establish effective emotion management mechanisms. Promoting mutual support and communication between teachers and students, as well as among peers, can help reduce work rumination.\u003c/p\u003e \u003cp\u003eFinally, increasing social support is vital for improving sleep quality. Higher levels of perceived social support weaken the relationship between stress perception and work rumination, as well as between work rumination and sleep quality. Administrators should help students identify and utilize social support resources effectively. Establishing a social support network that includes family and school and fostering a supportive school environment through strong teacher\u0026ndash;student and peer relationships can enhance students' sense of belonging and social support. Encouraging teamwork within classes and departments, organizing diverse student and extracurricular activities, and addressing long shifts and working hours are also important. Hospital administrators and policy-makers should limit shift work and weekly hours to ensure quality sleep for medical students and support their overall well-being.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eConflicts of Interest:\u003c/h2\u003e \u003cp\u003eThe authors declare no conflicts of interest.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding:\u003c/h2\u003e \u003cp\u003eThis study is supported by the Innovation Research Fund of the Peking University First Hospital (No. 2022SF90).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eConceptualization, Y-P.C.; methodology, H.X. and T.J.; software, H.X.; validation, T.J.; formal analysis, H.X. and T.J.; investigation, H.X.; resources,T.J.; data curation, H.X.; writing\u0026mdash;original draft preparation, H.X.; writing\u0026mdash;review and editing, Y-P.C. and T.J.; visualization, H.X.; supervision, Y-P.C.; project administration, Y-P.C.; funding acquisition, H.X. and Y-P.C.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eWe gratefully acknowledge professor YingWu Li at Renmin University of China for study design, and Shu-Duo Zhou at Medical Statistics Office of Peking University First Hospital for assisting data analysis.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eAll the raw data were submitted as supplementary data, and also available upon request to the corresponding author.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eCoskun, O., Ocalan, A. O., Ocbe, C. B., Semiz, H. O. \u0026amp; Budakoglu, I. Depression and hopelessness in pre-clinical medical students. \u003cem\u003eClin. Teach.\u003c/em\u003e \u003cb\u003e16\u003c/b\u003e (4), 345\u0026ndash;351 (2019).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYu, D., Ren, Q., Dong, B., Zhao, D. \u0026amp; Sun, Y. The sleep quality of medical students in China: a meta-analysis. \u003cem\u003eSleep. Biol. Rhythms\u003c/em\u003e. \u003cb\u003e15\u003c/b\u003e, 299\u0026ndash;310 (2017).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi, T., Chen, X. \u0026amp; Liao, M. Mediating Role of Social Support System in Academic Stressors and Coping Strategies in Middle School Students. \u003cem\u003eRes. Inst. Educ. Sci.\u003c/em\u003e \u003cb\u003e23\u003c/b\u003e (1), 35\u0026ndash;40 (2007).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCohen, S., Kamarck, T. \u0026amp; Mermelstein, R. A global measure of perceived stress. \u003cem\u003eJ. Health Soc. Behav.\u003c/em\u003e \u003cb\u003e24\u003c/b\u003e (4), 385\u0026ndash;396 (1983).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEskildsen, A. et al. Perceived stress, disturbed sleep, and cognitive impairments in patients with work-related stress complaints: A longitudinal study. \u003cem\u003eStress\u003c/em\u003e \u003cb\u003e20\u003c/b\u003e (4), 371\u0026ndash;378 (2017).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFolkman, S., Lazarus, R. S., Dunkel-Schetter, C., DeLongis, A. \u0026amp; Gruen, R. J. Dynamics of a stressful encounter: cognitive appraisal, coping, and encounter outcomes. \u003cem\u003eJ. Personal. Soc. Psychol.\u003c/em\u003e \u003cb\u003e50\u003c/b\u003e (5), 992\u0026ndash;1003 (1986).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiang, Z., Suntrayuth, S., Sun, X. \u0026amp; Su, J. Positive Verbal Rewards, Creative Self-Efficacy, and Creative Behavior: A Perspective of Cognitive Appraisal Theory. (2023). Behavioral sciences (Basel, Switzerland), \u003cb\u003e13\u003c/b\u003e(3): pp. 229\u0026ndash;235.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKollarik, M. et al. Effects of rumination on unwanted intrusive thoughts: A replication and extension. \u003cem\u003eJ. Experimental Psychopathol.\u003c/em\u003e \u003cb\u003e11\u003c/b\u003e (1), 7\u0026ndash;13 (2020).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFiroozabadi, A., Uitdewilligen, S. \u0026amp; Zijlstra, F. R. Solving problems or seeing troubles? A day-level study on the consequences of thinking about work on recovery and well-being, and the moderating role of self-regulation. \u003cem\u003eEur. J. Work Organizational Psychol.\u003c/em\u003e \u003cb\u003e27\u003c/b\u003e (5), 629\u0026ndash;641 (2018).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBrosschot, J. F., Pieper, S. \u0026amp; Thayer, J. F. Expanding stress theory: prolonged activation and perseverative cognition. \u003cem\u003ePsychoneuroendocrinology\u003c/em\u003e \u003cb\u003e30\u003c/b\u003e (10), 1043\u0026ndash;1049 (2005).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBerset, M., Elfering, A., L\u0026uuml;thy, S., L\u0026uuml;thi, S. \u0026amp; Semmer, N. K. Work stressors and impaired sleep: rumination as a mediator. \u003cem\u003eStress health: J. Int. Soc. Invest. Stress\u003c/em\u003e. \u003cb\u003e27\u003c/b\u003e (2), 71\u0026ndash;82 (2011).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHarvey, A. G. Pre-sleep cognitive activity: a comparison of sleep-onset insomniacs and good sleepers. \u003cem\u003eBr. J. Clin. Psychol.\u003c/em\u003e \u003cb\u003e39\u003c/b\u003e (3), 275\u0026ndash;286 (2000).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhu, Y., Lyu, Y., Wang, Y. \u0026amp; Wang, L. Coaching leadership effect on employees' creativity: Multilevel moderated mediator analysis. \u003cem\u003eActa Physiol. Sinica\u003c/em\u003e. \u003cb\u003e50\u003c/b\u003e (3), 327\u0026ndash;336 (2018).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi, X., Liu, P., Li, A., Wang, X. \u0026amp; Zhang, J. A multipath model of leader after-hours electronic communication expectations and employee job performance. \u003cem\u003eActa Physiol. Sinica\u003c/em\u003e. \u003cb\u003e54\u003c/b\u003e (8), 964\u0026ndash;978 (2022).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKozel, E., Barnoy, S. \u0026amp; Itzhaki, M. Emotion management of women at risk for premature birth: The association with optimism and social support. \u003cem\u003eAppl. Nurs. research: ANR\u003c/em\u003e. \u003cb\u003e64\u003c/b\u003e, 151568\u0026ndash;151577 (2022).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGottlieb, B. H., Maitland, S. B. \u0026amp; Brown, J. Social support and adjustment among wives of men with prostate cancer. \u003cem\u003eJ. Psychosoc. Oncol.\u003c/em\u003e \u003cb\u003e32\u003c/b\u003e (1), 16\u0026ndash;36 (2014).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAcoba, E. F. Social support and mental health: the mediating role of perceived stress. \u003cem\u003eFront. Psychol.\u003c/em\u003e \u003cb\u003e15\u003c/b\u003e, 1330\u0026ndash;1340 (2024).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBrislin, R. W. Back-translation for cross-cultural research. \u003cem\u003eJ. CrossCultural Psychol.\u003c/em\u003e \u003cb\u003e1\u003c/b\u003e (3), 185\u0026ndash;216 (1970).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBuysse, D. J., Reynolds, C. F., Monk, T. H., Berman, S. R. \u0026amp; Kupfer, D. J. The Pittsburgh Sleep Quality Index: a new instrument for psychiatric practice and research. \u003cem\u003ePsychiatry Res.\u003c/em\u003e \u003cb\u003e28\u003c/b\u003e (2), 193\u0026ndash;213 (1989).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eQuerstret, D. \u0026amp; Cropley, M. Exploring the relationship between work-related rumination, sleep quality, and work-related fatigue. \u003cem\u003eJ. Occup. Health Psychol.\u003c/em\u003e \u003cb\u003e17\u003c/b\u003e (3), 341\u0026ndash;353 (2012).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVan Laethem, M., Beckers, D. G. J., De Bloom, J., Sianoja, M. \u0026amp; Kinnunen, U. Challenge and hindrance demands in relation to self-reported job performance and the role of restoration, sleep quality, and affective rumination. \u003cem\u003eJ. Occup. Organizational Psychol.\u003c/em\u003e \u003cb\u003e92\u003c/b\u003e (2), 225\u0026ndash;254 (2019).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZimet, G. D., Dahlem, N. W., Zimet, S. G. \u0026amp; Farley, G. K. The multidimensional scale of perceived social support. \u003cem\u003eJ. Pers. Assess.\u003c/em\u003e \u003cb\u003e52\u003c/b\u003e (1), 30\u0026ndash;41 (1988).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhou, J. et al. The underlying characteristics of sleep behavior and its relationship to sleep-related cognitions: a latent class analysis of college students in Wuhu city, China. \u003cem\u003ePsychol. health Med.\u003c/em\u003e \u003cb\u003e25\u003c/b\u003e (7), 887\u0026ndash;897 (2020).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePodsakoff, P. M., MacKenzie, S. B. \u0026amp; Podsakoff, N. P. Sources of method bias in social science research and recommendations on how to control it. \u003cem\u003eAnn. Rev. Psychol.\u003c/em\u003e \u003cb\u003e63\u003c/b\u003e, 539\u0026ndash;569 (2012).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePreacher, K. J. \u0026amp; Selig, J. P. Advantages of Monte Carlo Confidence Intervals for Indirect Effects. \u003cem\u003eCommunication Methods Measures\u003c/em\u003e. \u003cb\u003e6\u003c/b\u003e (2), 77\u0026ndash;98 (2012).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlvaro, P. K., Roberts, R. M. \u0026amp; Harris, J. K. A Systematic Review Assessing Bidirectionality between Sleep Disturbances, Anxiety, and Depression. \u003cem\u003eSleep\u003c/em\u003e \u003cb\u003e36\u003c/b\u003e (7), 1059\u0026ndash;1068 (2013).\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":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Medical students, Perceived Stress, Sleep quality, Multilevel model","lastPublishedDoi":"10.21203/rs.3.rs-5415327/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5415327/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eMedical students, the healthcare practitioners in the future, are under greater pressure and prone to physical and mental health problems such as anxiety, depression, and sleep disorders compared with other non-medical specialties.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis study investigated the perceived stress of medical students in China and the relationship between their sleep quality. Based on the Cognitive Appraisal Theory and the Perseverative Cognition Hypothesis, we constructed a cross-sectional structural equation model (SEM) with stress perception as a predictor, sleep quality as an outcome variable, and work rumination and social support as buffer moderators. An online survey of 350 medical students from a medical university were collected, 318 of the participants were defined as study objects.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe results of the study found that medical student\u0026rsquo;s stress perception negatively affects sleep quality; work rumination plays a mediating role in the relationship between stress perception and sleep quality; perceived social support plays a negative cross-level moderating role between stress perception and work rumination, and also plays a positive cross-level moderating role between work rumination and sleep quality.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eThis study provided evidence for the design of stress regulation methods for medical students as well as intervention techniques to improve sleep quality among medical students.\u003c/p\u003e","manuscriptTitle":"The Cross-Level Influence of Medical Students’ Perception of Stress on Sleep Quality—A Moderated Mediation Model","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-12-18 06:42:09","doi":"10.21203/rs.3.rs-5415327/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-06-06T10:11:03+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-27T07:34:37+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"153114097972570291404475074386747110768","date":"2025-05-27T03:32:27+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-12-29T20:57:30+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"187029363950174047911297510308130656311","date":"2024-12-23T17:20:48+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-12-11T03:11:50+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-12-11T03:09:15+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-11-15T19:48:06+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-11-14T06:48:22+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2024-11-08T09:10:00+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"c6ba7978-8392-4dd3-954c-f14e52237041","owner":[],"postedDate":"December 18th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":41457198,"name":"Biological sciences/Psychology"},{"id":41457199,"name":"Health sciences/Health occupations"}],"tags":[],"updatedAt":"2026-04-29T17:54:08+00:00","versionOfRecord":[],"versionCreatedAt":"2024-12-18 06:42:09","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5415327","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5415327","identity":"rs-5415327","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}