Network structure of insomnia and depressive symptoms among shift workers in China

Network Analysis of Health-related Behaviors, Insomnia, and Depression Among Urban Left-behind Adolescents in China

Mental health of urban left-behind adolescents (LBA) is a public issue of growing concern. This study aims to examine the symptom level associations among multiple health-related behaviors, insomnia, and depression in urban LBA. Data on a sample of urban LBA aged 11-19 (N = 3,601) from the Adolescent Mental Health Survey in Shenzhen, China, were used. Health-related behaviors (i.e., Internet use, physical inactivity, social jetlag, smoking, and alcohol consumption), insomnia, and depressive symptoms were assessed using a self-administered questionnaire. Graphical Gaussian Model (GGM) was used to describe key bridging nodes in an undirected network. Directed Acyclic Graph (DAG) was used to construct a directed network and estimate the most likely causal associations among behaviors/symptoms. In the undirected network, Internet use was identified as the key bridging node most strongly associated with insomnia and depression. Two other key bridging nodes include difficulty initiating sleep and appetite change. In the directed network, anhedonia emerged as the most pivotal symptom, which could cause insomnia symptoms and behavioral changes, either directly, or through triggering other depressive symptoms, such as low energy and appetite change. These findings have implications for understanding the occurrence and maintenance process of health-related behaviors, insomnia, and depression in urban LBA. In practice, Internet use should be considered a priority in targeting multiple health behavior interventions. Meanwhile, early screening and treatment for anhedonia are of great significance as well.

Structure of family health and its association with obesity-related eating behavior and depressive symptoms: Insights from network analysis

The health of families is inextricably linked to the health of individuals and communities, providing the foundation for their development. Family health is a multifaceted concept and has been suggested to impact individuals' obesity-related eating behavior and the alleviation of depressive symptoms. However, existing studies have not comprehensively examined the structure of family health and its' potential associations with obesity-related eating behavior and depressive symptoms. The present study employed network analysis to ascertain the most pivotal characteristics within the interdisciplinary and holistic concept of family health. In addition, this study investigated the moderating effect of family health on the association between obesity-related eating behavior and depressive symptoms, and identified the characteristics of family health that were the most strongly linked to the association. A total of 9091 adults participated in this nationally representative study between 10 July and September 15, 2021. The participants completed self-report assessments of family health, obesity-related eating behavior, and depressive symptoms. The results of network analysis indicated that helping each other in seeking health care services when needed (such as making physician's appointments) had the highest node expected influence (1.154) within the network. The results of moderation analysis showed that family health significantly buffered the association between obesity-related eating behavior and depressive symptoms (B = -0.06, 95 % CI = -0.077, -0.042). Further investigation demonstrated that not trusting doctors and other health professionals in the family presented the strongest negative correlation (-0.125) with obesity-related eating behavior, and not having adequate housing in the family showed the strongest negative correlation (-0.069) with depressive symptoms. These findings provide further insight into the critical aspects of family health and its significant correlations with obesity-related eating behavior and depressive symptoms.

Network structure of sleep quality and its bridging association with anhedonia in adolescent major depression disorder

BACKGROUND

Major depressive disorder (MDD) is a leading cause of disease burden in adolescents, with persistently rising prevalence. Anhedonia, core symptom of adolescent MDD, is associated with suicidality and poor clinical outcomes. Impaired sleep quality is proven to be a significant risk factor for adolescent MDD and potentially influence anhedonia symptoms. Understanding the interplay between sleep quality and anhedonia is crucial for early intervention and treatment.

METHODS

This cross-sectional study recruited 200 drug-naïve adolescent MDD patients from Xijing Hospital. Depression, anhedonia and sleep quality were assessed during outpatient visits, using the Hamilton Depression Rating Scale, Snaith-Hamilton Pleasure Scale, and Pittsburgh Sleep Quality Index, respectively. Network analysis was applied to construct sleep quality network and its co-occurrence network with anhedonia. Centrality indices were computed to indicate central symptoms.

RESULTS

Adolescent MDD patients exhibited moderate depression and anhedonia levels, and are heavily accompanied with sleep complaints. The sleep quality network identified "subjective sleep quality" as the most central factor, mainly due to prolonged "sleep latency" and shortened "sleep duration". In the co-occurrence network, "sleep disturbances" had prominent bridging connection with anhedonia, suggesting its critical role in activating anhedonia symptoms.

CONCLUSIONS

Subjective sleep quality was the most central sleep complaints in adolescent MDD, while sleep disturbances were prominently associated with anhedonia. These findings underscore the importance of reducing sleep disturbances to alleviate anhedonia symptoms under clinical settings. Network analysis provides a nuanced understanding of the complex relationship of sleep quality and its association with anhedonia in adolescent MDD.

Family Support Moderates the Relationship Between Pregnancy Stress, Depressive Symptoms, and Insomnia

Objective

Insomnia is a common issue that pregnant women often have to deal with. This study seeks to examine the connections between pregnancy stress, depressive symptoms, family support, and insomnia symptoms.

Methods

Convenience sampling was employed to recruit 1049 valid participants. The primary measurement tools utilized were the Pregnancy Stress Scale, the Family Support Subscale, and the Patient Health Questionnaire-2. Data analysis was conducted using SPSS 24.0 software. Using binary logistic regression to verify the independent effects of pregnancy stress, depression symptoms, and family support on insomnia symptoms. PROCESS macro Model 4 was applied to assess the mediating effect, while PROCESS macro Model 5 was used to evaluate the moderating effect.

Results

The overall prevalence of insomnia symptoms and depressive symptoms among pregnant women was 54% (n=572) and 20% (n=207) in this study. Pregnancy stress, depressive symptoms and family support positively affect insomnia symptoms. The indirect effect of depressive symptoms between pregnancy stress and insomnia symptoms was significant, with the mediator proportion of 45.16%. As moderator, family support weakens the impact of pregnancy stress on insomnia symptoms.

Conclusion

Increased pregnancy stress and increased depressive symptoms could trigger insomnia symptoms. Depressive symptoms mediated the path from between pregnancy stress and insomnia symptoms. Family support weakened the link between pregnancy stress and insomnia symptoms. These findings can assist pregnant women in managing stress more effectively and improving their mental well-being.

Status and risk factors for depression, anxiety, and insomnia symptoms among adolescents in the post-pandemic era

BACKGROUND

Owing to their vulnerability to public health crises, adolescents' mental health status, and related risk factors in the post-pandemic era in China require examination. This study aimed to lay a foundation for subsequent interventions and mental disorder prevention among adolescents.

METHODS

An anonymous online survey was conducted January 8-18, 2023. The survey comprised two parts. The first part collected personal information. The second part included the nine-item Patient Health Questionnaire, seven-item Generalized Anxiety Disorder Scale, and Pittsburgh Sleep Quality Index.

RESULTS

Of 50,666 adolescent participants, 46.8% displayed depressive symptoms, 31.5% showed anxiety symptoms, and 47.9% experienced difficulties initiating sleep within 30 min, while 4.9% manifested depressive, anxiety, and insomnia symptoms simultaneously. Chi-square tests revealed significant variations in the prevalence of these conditions according to age, sex, coronavirus disease-2019 (COVID-19) infection status, family infection status, and increased screen time (P < 0.001). Logistic regression analysis indicated heightened rates of depression, anxiety, and insomnia symptoms among rural adolescents, females, those aged 16-18 years, individuals with a history of COVID-19, those with a long COVID-19 illness, and those with increased screen time (all P < 0.001).

CONCLUSION

The mental health status of adolescents in the post-pandemic era should be taken seriously, particularly that of females, high school students, and adolescents with increased use of electronic screens. Among such efforts, school administrators should strengthen their connection with psychologists, as early identification and intervention in adolescents are important for preventing school crises.

Machine learning and Bayesian network analyses identifies associations with insomnia in a national sample of 31,285 treatment-seeking college students

BACKGROUND

A better understanding of the relationships between insomnia and anxiety, mood, eating, and alcohol-use disorders is needed given its prevalence among young adults. Supervised machine learning provides the ability to evaluate which mental disorder is most associated with heightened insomnia among U.S. college students. Combined with Bayesian network analysis, probable directional relationships between insomnia and interacting symptoms may be illuminated.

METHODS

The current exploratory analyses utilized a national sample of college students across 26 U.S. colleges and universities collected during population-level screening before entering a randomized controlled trial. We used a 4-step statistical approach: (1) at the disorder level, an elastic net regularization model examined the relative importance of the association between insomnia and 7 mental disorders (major depressive disorder, generalized anxiety disorder, social anxiety disorder, panic disorder, post-traumatic stress disorder, anorexia nervosa, and alcohol use disorder); (2) This model was evaluated within a hold-out sample. (3) at the symptom level, a completed partially directed acyclic graph (CPDAG) was computed via a Bayesian hill-climbing algorithm to estimate potential directionality among insomnia and its most associated disorder [based on SHAP (SHapley Additive exPlanations) values)]; (4) the CPDAG was then tested for generalizability by assessing (in)equality within a hold-out sample using structural hamming distance (SHD).

RESULTS

Of 31,285 participants, 20,597 were women (65.8%); mean (standard deviation) age was 22.96 (4.52) years. The elastic net model demonstrated clinical significance in predicting insomnia severity in the training sample [R2 = .44 (.01); RMSE = 5.00 (0.08)], with comparable performance in the hold-out sample (R2 = .33; RMSE = 5.47). SHAP values indicated that the presence of any mental disorder was associated with higher insomnia scores, with major depressive disorder as the most important disorder associated with heightened insomnia (mean |SHAP|= 3.18). The training CPDAG and hold-out CPDAG (SHD = 7) suggested depression symptoms presupposed insomnia with depressed mood, fatigue, and self-esteem as key parent nodes.

CONCLUSION

These findings provide insights into the associations between insomnia and mental disorders among college students and warrant further investigation into the potential direction of causality between insomnia and depression.

TRIAL REGISTRATION

Trial was registered on the National Institute of Health RePORTER website (R01MH115128 || 23/08/2018).

Mediating effects of insomnia and resilience on COVID-19-related post-traumatic stress disorder and quality of life in adolescents

The coronavirus disease-2019 (COVID-19) pandemic has impaired the quality of life (QoL) for many due to its extensive impacts. However, few studies have addressed the specific impact of COVID-19 on the mental health of adolescents, particularly post-traumatic stress disorder (PTSD). This study considered the impact of COVID-19-related PTSD on the QoL of adolescents in China, the mediating effects of insomnia, and the moderating effects of resilience. Participants included 50,666 adolescents aged 12-18 years selected using a comprehensive sampling method. We performed data collection from January 8th to January 18th, 2023, using the Children's Revised Impact of Event Scale, Pittsburgh Sleep Quality Index, Ten-item Connor-Davidson Resilience Scale, and Screening for and Promotion of Health-related QoL in Children and Adolescents Questionnaire for data collection. Male adolescents exhibited significantly lower levels of PTSD and insomnia compared to females and scored significantly higher in psychological resilience and overall QoL. Insomnia played a mediating role between PTSD and QoL. Psychological resilience moderated the impact of COVID-19-related stress on adolescents' QoL through its influence on insomnia. PTSD resulting from the COVID-19 pandemic affects the QoL of adolescents through the presence of insomnia. Psychological resilience plays a moderating role in this process. Cultivating psychological resilience in adolescents can effectively enhance their ability to cope with the impacts of sudden public events.

Inter-relationships of depression and insomnia symptoms with life satisfaction in stroke and stroke-free older adults: Findings from the Health and Retirement Study based on network analysis and propensity score matching

BACKGROUND

Depression and insomnia are common co-occurring psychiatric problems among older adults who have had strokes. Nevertheless, symptom-level relationships between these disorders remain unclear.

OBJECTIVES

In this study, we compared inter-relationships of depression and insomnia symptoms with life satisfaction among older stroke patients and stroke-free peers in the United States.

METHODS

The study included 1026 older adults with a history of stroke and 3074 matched controls. Data were derived from the US Health and Retirement Study. Depression, insomnia and life satisfaction were assessed. Propensity score matching was employed to identify demographically-similar groups of stroke patients and controls. Central and bridge symptoms were assessed using Expected influence (EI) and bridge EI, respectively.

RESULTS

The prevalence of depression in the stroke group (25.0 %) was higher than that of controls (14.3 %, P < 0.001). In stroke group, "Feeling depressed" (CESD1; EI: 5.80), "Feeling sad" (CESD7; EI: 4.67) and "Not enjoying life" (CESD6; EI: 4.51) were the most central symptoms, while "Feeling tired in the morning" (JSS4; BEI: 1.60), "Everything was an effort" (CESD2; BEI: 1.21) and "Waking up during the night" (JSS2; BEI: 0.98) were key bridge symptoms. In controls, the most central symptoms were "Lack of happiness" (CESD4; EI: 6.45), "Feeling depressed" (CESD1; EI: 6.17), and "Feeling sad" (CESD7; EI: 6.12). Furthermore, "Feeling tired in the morning" (JSS4; BEI: 1.93), "Everything was an effort" (CESD2; BEI: 1.30), and "Waking up too early" (JSS3; BEI: 1.12) were key bridge symptoms. Life satisfaction had the most direct associations with "Not enjoying life" (CESD6) and "Feeling lonely" (CESD5) in the two groups, respectively.

CONCLUSION

Older adults with stroke exhibited more severe depression and insomnia symptoms. Interventions targeting central and bridge symptoms may help to mitigate the co-occurrence of these symptoms.

Prevalence, correlates, and mental health outcomes of social jetlag in Chinese school-age adolescents: A large-scale population-based study

BACKGROUND

This cross-sectional study aimed to examine the prevalence and correlates of social jetlag (SJL) in Chinese adolescents, as well as to test the relationships between SJL and mental health problems.

METHODS

A total of 106979 students (Mage = 13.0 ± 1.8 years; Nmale = 58296 [54.5 %]) from Shenzhen, China completed an online survey from May 24th to June 5th, 2022. Information on sociodemographics, lifestyles, sleep characteristics, anxiety symptoms, and depressive symptoms was collected by a self-administered questionnaire. Multivariate and binary logistic regression were adopted for data analysis.

RESULTS

17.8 % of participants experienced SJL ≥ 2 h. To adjust the accumulated sleep debt, sleep-corrected SJL (SJLsc) was calculated and 8.3 % of individuals self-reported SJLsc ≥ 2 h. Both SJL and SJLsc show an increasing trend with age. Risk factors of SJL included females, poor parental marital status, being overweight, physically inactive, smoking, drinking, and having a late chronotype. Moreover, males, having siblings, boarding at school, short sleep duration, experiencing insomnia, and frequent nightmares were significantly associated with an increased risk of SJLsc. After adjusting for all covariates, adolescents with SJLsc ≥ 2 h were more likely to have anxiety symptoms (OR: 1.35, 95 % CI: 1.24-1.48) and depressive symptoms (OR: 1.35, 95 % CI: 1.25-1.46) than those with SJLsc < 1 h.

CONCLUSIONS

SJL is common among Chinese school-age adolescents. This study is valuable for the development of prevention and intervention strategies for SJL in adolescents at the population level. Additionally, the strong links between SJLsc and emotional problems underscore the critical significance of addressing SJL as a key aspect of adolescent well-being.

Machine Learning and Bayesian Network Analyses Identifies Psychiatric Disorders and Symptom Associations with Insomnia in a national sample of 31,285 Treatment-Seeking College Students

Background

A better understanding of the structure of relations among insomnia and anxiety, mood, eating, and alcohol-use disorders is needed, given its prevalence among young adults. Supervised machine learning provides the ability to evaluate the discriminative accuracy of psychiatric disorders associated with insomnia. Combined with Bayesian network analysis, the directionality between symptoms and their associations may be illuminated.

Methods

The current exploratory analyses utilized a national sample of college students across 26 U.S. colleges and universities collected during population-level screening before entering a randomized controlled trial. Firstly, an elastic net regularization model was trained to predict, via repeated 10-fold cross-validation, which psychiatric disorders were associated with insomnia severity. Seven disorders were included: major depressive disorder, generalized anxiety disorder, social anxiety disorder, panic disorder, post-traumatic stress disorder, anorexia nervosa, and alcohol use disorder. Secondly, using a Bayesian network approach, completed partially directed acyclic graphs (CPDAG) built on training and holdout samples were computed via a Bayesian hill-climbing algorithm to determine symptom-level interactions of disorders most associated with insomnia [based on SHAP (SHapley Additive exPlanations) values)] and were evaluated for stability across networks.

Results

Of 31,285 participants, 20,597 were women (65.8%); mean (standard deviation) age was 22.96 (4.52) years. The elastic net model demonstrated clinical significance in predicting insomnia severity in the training sample [R2 = .449 (.016); RMSE = 5.00 [.081]), with comparable performance in accounting for variance explained in the holdout sample [R2 = .33; RMSE = 5.47). SHAP indicated the presence of any psychiatric disorder was associated with higher insomnia severity, with major depressive disorder demonstrated to be the most associated disorder. CPDAGs showed excellent fit in the holdout sample and suggested that depressed mood, fatigue, and self-esteem were the most important depression symptoms that presupposed insomnia.

Conclusion

These findings offer insights into associations between psychiatric disorders and insomnia among college students and encourage future investigation into the potential direction of causality between insomnia and major depressive disorder.

Trial registration

Trial may be found on the National Institute of Health RePORTER website: Project Number: R01MH115128-05.

Network analysis of depressive and anxiety symptoms in older Chinese adults with diabetes mellitus

Background

The move away from investigating mental disorders as whole using sum scores to the analysis of symptom-level interactions using network analysis has provided new insights into comorbidities. The current study explored the dynamic interactions between depressive and anxiety symptoms in older Chinese adults with diabetes mellitus (DM) and identified central and bridge symptoms in the depression-anxiety network to provide potential targets for prevention and intervention for depression and anxiety.

Methods

This study used a cross-sectional design with data from the 2017-2018 wave of the Chinese Longitudinal Healthy Longevity Survey (CLHLS). A regularized partial correlation network for depressive and anxiety symptoms was estimated based on self-reported scales completed by 1685 older adults with DM aged 65 years or older. Depressive and anxiety symptoms were assessed using the 10-item Center for Epidemiologic Studies Depression Scale (CESD-10) and the Seven-Item Generalized Anxiety Disorder Scale (GAD-7), respectively. Expected influence (EI) and bridge expected influence (BEI) indices were calculated for each symptom.

Results

According to cutoff scores indicating the presence of depression and anxiety, the prevalences of depression and anxiety in our sample were 52.9% and 12.8%, respectively. The comorbidity rate of depression and anxiety was 11.5%. The six edges with the strongest regularized partial correlations were between symptoms from the same disorder. "Feeling blue/depressed", "Nervousness or anxiety", "Uncontrollable worry", "Trouble relaxing", and "Worry too much" had the highest EI values. "Nervousness or anxiety" and "Everything was an effort" exhibited the highest BEI values.

Conclusion

Central and bridge symptoms were highlighted in this study. Targeting these symptoms may be effective in preventing the comorbidity of depressive and anxiety symptoms and facilitate interventions in older Chinese adults with DM who are at risk for or currently have depressive and anxiety symptoms.

Problematic internet use and suicide ideation among Chinese adolescents: The indirect effects of insomnia, nightmares, and social jetlag

BACKGROUND

Problematic Internet use (PIU) is related to suicide ideation (SI) in adolescents, but little is known about the potential mechanisms between them. This study aimed to examine the mediation roles of insomnia, nightmares, and social jetlag in the association of PIU with SI in adolescents.

METHODS

A total of 39,731 adolescents (mean age = 13.49 ± 0.76 years, 54.4 % males) from Shenzhen, China, participated in a cross-sectional survey. SI was assessed using the ninth item of the Patient Health Questionnaire-9. PIU was measured by the Revised Chinese Internet Addiction Scale. A self-administered questionnaire was used to assess insomnia symptoms, nightmare frequency, social jetlag, sleep duration, psychological distress, and social-demographical characteristics. Logistic regression and path analyses were performed to examine the associations between PIU, insomnia symptoms, nightmares, social jetlag, and SI.

RESULTS

The prevalence of PIU and SI were 14.9 % and 18.6 %, respectively. PIU, insomnia symptoms, frequent nightmares, and social jetlag were significantly associated with SI. Path analyses showed that the indirect effects of PIU on SI through insomnia symptoms, frequent nightmares, and social jetlag were significant. Conversely, social jetlag significantly mediated the pathway from SI to PIU. The mediation effect sizes of these sleep and circadian problems were slightly larger in females than in males.

LIMITATIONS

Cross-sectional design limited the capacity to infer causal relationships.

CONCLUSIONS

The associations between PIU and SI were mediated by sleep and circadian problems. These findings underscore the importance of assessing and intervening in sleep and circadian problems among adolescents with PIU or SI.

Effects of Neuroticism on Differences in Symptom Structure of Life Satisfaction and Depression-Anxiety among College Students: A Network Analysis

Object: Numerous studies show that depression and anxiety have an adverse effect on life satisfaction among college students. Moreover, neuroticism affects depression, anxiety, and life satisfaction. Comparing the low-neuroticism and high-neuroticism groups, the current study used network analysis to examine the relationship between depression, anxiety, and life satisfaction among college students. Methods: A sample consisted of 1233 college students from China who completed the Big Five Inventory-2 (BFI-2), Self-rating Anxiety Scale (SAS), Self-rating Depression Scale (SDS), and Satisfaction With Life Scale (SWLS).All students were divided into two groups according to levels of neuroticism. Depression-anxiety symptom networks and flow networks were formed. Results: "Insomnia" (SAS19) and "Sleep disturbance" (SDS4) are bridge symptoms of groups with varying neuroticism. In addition, compared to the group with low levels of neuroticism, the group with high levels of neuroticism showed more depression symptoms in bridge symptoms and greater global strength. Many depression-anxiety symptoms are negatively associated with life satisfaction, and "Emptiness" (SDS18) is an important symptom in the high-neuroticism group's flow network. Conclusion: This study contributes to our understanding of the connection between depression, anxiety, neuroticism, and life satisfaction. In addition, the current study identified the essential symptoms to target in depression and anxiety intervention and life satisfaction enhancement among college students.

Symptom association between social anxiety disorder, appearance anxiety, and eating disorders among Chinese University students: A network analysis to conceptualize comorbidity

Background

Incidences of social anxiety disorder (SAD), appearance anxiety, and eating disorders (ED) show an increased prevalence among young people. However, symptoms' associations between these disorders have not been investigated in depth. Network analysis is an approach that can be used to explain the relationship(s) between symptoms of different psychological disorders. Using network analysis, this study aimed to explore the association and potential interacting mechanisms between SAD, appearance anxiety, and ED.

Methods

This study included 96,218 University students from Jilin Province, China. SAD, appearance anxiety and ED were assessed using the Social Anxiety Subscale of the Self-Consciousness Scale (SASS), the Appearance Anxiety Scale Brief Version (AASBV), and the Sick, Control, One, Fat, Food questionnaire (SCOFF), Chinese versions. Network analysis was employed to investigate the symptom associations, while the stability of the network model was analyzed using statistical measures.

Results

The prevalence of ED among the total sample was 38% (95% CI: 38.1-38.8%), while this figure was 31.2% (95% CI: 30.7-31.6%) in males and 43.6% (95% CI: 43.2-44.0%) in females. Additionally, the total score of SAD was significantly higher in females (11.83 ± 5.37) than it in males (10.02 ± 5.46) (P < 0.001). While the total score of appearance anxiety was also different significantly in gender (39.21 ± 9.49 in females vs. 38 ± 9.42 in males) (P < 0.001). Results showed that ED was associated with all three aspects of appearance anxiety, including "appearance concern," "appearance satisfaction," and "wish for good looks." Appearance anxiety and SAD were also associated; specifically, symptoms of "appearance satisfaction" were significantly associated with the symptoms "easily talk to strangers" and "appearance concern", which was also significantly associated with "embarrassed". Compared with males, females showed significantly stronger associations with appearance anxiety symptoms, while ED symptoms were associated with "troubled by being watched" and "appearance concern".

Conclusion

Appearance anxiety was associated with both ED and SAD symptoms. ED may have a potential relationship with SAD, affecting appearance anxiety indirectly. Significant differences were found among males and females in symptom associations between appearance anxiety and SAD. This study therefore clarified that young people should have body-positive interventions and challenge the normative body image discourse, which may help alleviate symptoms of SAD and ED.

Night shifts, insomnia, anxiety, and depression among Chinese nurses during the COVID-19 pandemic remission period: A network approach

Background

The outbreak of the COVID-19 pandemic imposed a heavy workload on nurses with more frequent night shifts, which led to higher levels of insomnia, depression, and anxiety among nurses. The study aimed to describe the symptom-symptom interaction of depression, anxiety, and insomnia among nurses and to evaluate the impact of night shifts on mental distress via a network model.

Methods

We recruited 4,188 nurses from six hospitals in December 2020. We used the Insomnia Severity Index, Patient Health Questionnaire-9, and Generalized Anxiety Disorder Scale-7 to assess insomnia, depression, and anxiety, respectively. We used the gaussian graphical model to estimate the network. Index expected influence and bridge expected influence was adapted to identify the central and bridge symptoms within the network. We assessed the impact of night shifts on mental distress and compared the network structure based on COVID-19 frontline experience.

Results

The prevalence of depression, anxiety, and insomnia was 59, 46, and 55%, respectively. Nurses with night shifts were at a higher risk for the three mental disorders. "Sleep maintenance" was the central symptom. "Fatigue," "Motor," "Restlessness," and "Feeling afraid" were bridge symptoms. Night shifts were strongly associated with sleep onset trouble. COVID-19 frontline experience did not affect the network structure.

Conclusion

"Sleep maintenance," "Fatigue," "Motor," and "Restlessness" were important in maintaining the symptom network of anxiety, depression, and insomnia in nurses. Further interventions should prioritize these symptoms.