Network analysis of depressive and anxiety symptoms in adolescents during the later stage of the COVID-19 pandemic

Comorbidity among symptoms of internet gaming disorder, social withdrawal, and depression in 3430 young people in Hong Kong: A network analysis

BACKGROUND

The present study aimed to examine the comorbidity among symptoms of internet gaming disorder (IGD), social withdrawal, and depression using the network perspective.

METHODS

An online survey recruited 3430 young people in Hong Kong (mean age = 19.4 years, 80.5 % male) via gaming channels in 2019. The participants completed the 9-item IGD Scale, Hikikomori Questionnaire, and Patient Health Questionnaire-9. Network analysis was conducted using R to estimate the central symptoms of IGD and depression in individual networks and identified the bridge symptoms in combined network of IGD, social withdrawal, and depressive symptoms.

RESULTS

All network models showed high stability. 'Withdrawal', 'Loss of control', and 'Tolerance' were the central IGD symptoms, while 'Depressed mood' and 'Self-blame/guilt' were the central depressive symptoms. The bridge symptoms were 'Gaming as escape or mood relief' from IGD cluster, 'Depressed mood' and 'Self-blame/guilt' from depression cluster, and 'Marked social isolation at home' and 'Significant distress due to social isolation' from social withdrawal cluster. The combined network showed no significant differences in network structure and global strength across gender and age groups.

LIMITATIONS

The cross-sectional sample only indicated undirected associations between the symptoms in the three clusters and could not model the intra-individual variation.

CONCLUSIONS

The present study provided the first results on the comorbidity among IGD, social withdrawal, and depression at a symptom level among Chinese young people via network analysis. The bridge symptoms highlight potential targets for interventions of comorbidity among the disorders.

Longitudinal Relationships Between Depressive Symptoms and Generalized Anxiety Symptoms in Adolescents: A Cross-Lagged Network Analysis

The comorbidity of depression and generalized anxiety have raised questions about the existing classification system. Based on the perspective of network analysis, the developmental relationship between psychological symptoms can be explored more clearly. The current study aimed to explore the longitudinal network association of depressive symptoms and generalized anxiety symptoms in non-clinical adolescents. The sample contained 1,947 Chinese adolescents (Mage = 13.93, SD = 1.71; 48.5% girls). Their depression (PHQ-9) and generalized anxiety (GAD-7) symptoms were assessed at baseline (T1) and 6-month follow-up (T2). Data was analyzed using a cross-lagged network analysis. Depressive symptoms and generalized anxiety symptoms were closely related and did not appear to be distinct categories in adolescence. More generalized anxiety symptoms predicted depressive symptoms rather than vice versa. After controlling for gender, and age, "Difficulty relaxing" presented the highest out-expected influence (out-EI) in the network, while "trouble concentrating", and "suicidal ideation" showed the lowest in expected influence (in-EI). Findings suggested that interventions for generalized anxiety symptoms may help reduce depressive symptoms among Chinese adolescents. Specifically, alleviating "difficulty relaxing" may improve overall mental health.

A simulation-based network analysis of intervention targets for adolescent depressive and anxiety symptoms

Although previous research has well explored central and bridge symptoms of mental health problems, little examined whether these symptoms can serve as effective targets for intervention practices. Based on the Ising model, this study constructed a network structure of depressive and anxiety symptoms. The NodeIdentifyR algorithm (NIRA) was used to simulate interventions within this network, examining the effects of alleviating or aggravating specific symptoms on the network's sum scores. In this study, a total of 15,569 participants were recruited from China (50.87 % females, Mage = 13.44; SD = 0.97). The Ising model demonstrated that "sad mood" had the highest expected influence, and "irritability" had the highest bridge expected influence. Alleviating interventions suggested that decreasing the symptom value of "nervousness" resulted in the greatest projected reduction in network symptom activation, which may be a potential target symptom for treatment. Aggravating interventions indicated that elevating the symptom value of "sad mood" had the most projected increase in network activation, which may be a potential target for prevention. Additionally, network structure indices (e.g., central or bridge symptoms) need to be interpreted with more caution as intervention targets, since they may not be exactly the same. These findings enriched the comprehension of the depressive and anxiety network in Chinese adolescents, offering valuable insights for designing effective interventions.

Identification of the Core Characteristics of Vulnerable/Hypersensitive Narcissism and its Association with the Dark Triad in a Large International Sample: A Network Analysis Study

The current paper aimed to investigate the network structure and centrality indexes of hypersensitive narcissism using the hypersensitive Narcissism Scale (HSN). Additionally, we aimed to explore its relationships with dark triad personality aspects. A globally diverse sample of "53,981" participants (47.9% non-United States responders) completed the HSN and Dark Triad Dirty Dozen scale (DTD). We estimated the network structure across genders to determine the core characteristics of hypersensitive narcissism. Additionally, bridge and central nodes (characteristics) were identified. All analyses were performed using R-Studio programming software. The network comparison test indicated significant differences in the network structures between males and females (Network-Invariance: 0.0489, P < 0.01; Global Strength Invariance: 0.101, P < 0.01). In the network of HSN for male participants, characteristics with the highest strength centrality were "Highly affected by criticism" (HSN.2, strength = 1.08) and "Self-absorbed in personal pursuits" (HSN.8, strength = 1.28). For female participants, "Self-absorbed in personal pursuits" (HSN.8, strength = 1.32) and "privately annoyed by others' needs" (HSN.10, strength = 1.21) were the highest central characteristics. The assessment of bridge strength indicated that nodes HSN.2 (Highly sensitive to criticism), scoring 0.42, and DTD.1 (Tendency to manipulate for gain, a component of Machiavellianism), scoring 0.428, showed the highest bridge strength values. The current study identified core characteristics of hypersensitive narcissism and its correlation with dark triad personality, revealing gender-specific patterns and bridging symptoms between the two constructs. These findings showed that focusing on these core characteristics may be advantageous in treating individuals exhibiting elevated levels of narcissism.

Depression, anxiety, and insomnia symptoms among Chinese college students: A network analysis across pandemic stages

BACKGROUND

As the stages of the COVID-19 pandemic evolved, the symptoms of depression, anxiety, and insomnia have increasingly manifested among Chinese college students. The aim of this study is to investigate the relationships between these symptoms through network analysis among Chinese college students during COVID-19.

METHOD

A three-wave cross-sectional survey was conducted at 22 colleges in Guangdong Province, involving 381,152 students during three specific time intervals: T1 (baseline, February 3 to 10, 2020), T2 (19 months after baseline, June 10 to 18, 2021), and T3 (37 months after baseline, March 15 to April 22, 2023). Depression (PHQ-9), anxiety (GAD-7), and insomnia (YSIS) were used separately. We analyzed two key network indices: "Expected influence" and "Bridge expected influence". Network stability was assessed through a case-dropping bootstrap program.

RESULT

The effective sample sizes for the three periods were as follows: T1 - 164,101 (103,645 females, 63.2 %), T2 - 86,767 (52,146 females, 60.1 %), and T3 - 130,284 (76,720 females, 58.9 %). Across these three periods, the key central symptoms were "Fatigue" (PHQ4), "Restlessness" (GAD5), "Uncontrollable worrying" (GAD2), "Worry too much" (GAD3) and "Sleep insufficiency" (YSIS6). Notably, "Fatigue" (PHQ4), "Restlessness" (GAD5) and "Irritability" (GAD6) consistently served as bridge symptoms. In the T1 and T2 period, "Motor" (PHQ8) acted as a bridge symptom but weakened in T3.

CONCLUSION

Throughout the three periods, the mental health issues among Chinese college students displayed characteristics of somatization within the depression-anxiety-insomnia comorbidity network. Over time, anxiety symptoms appeared to become more prominent. Consequently, this study highlights the importance of accurately identifying and promptly intervening in these core symptoms of mental health among college students, as these symptoms may evolve across different stages of a pandemic.

Maternal Depressive Symptoms and Offspring Internalizing Problems: A Cross-Lagged Panel Network Analysis in Late Childhood and Early Adolescence

The present study investigated the relations between maternal depressive symptoms and internalizing problems in offspring during late childhood and early adolescence, examining sex differences using symptom network analysis. A total of 885 Chinese youths in late childhood (n = 497, 38.6% girls; age = 9.58 years, SD = 0.24) and early adolescence (n = 388, 48.5% girls; age = 11.30 years, SD = 0.24) and their mothers (Mage = 37.34 years, SD = 5.42) were recruited. Cross-lagged panel network (CLPN) analysis was used to explore bridge symptoms (i.e., symptoms connecting two or more mental disorders) and identify transmission pathways between maternal depressive symptoms and offspring's internalizing problems at these two developmental stages. The CLPN results revealed that in late childhood, the bridge connections in the network model were boys feeling worried to mothers feeling distractible, and girls feeling worried to mothers feeling powerless. In early adolescence, the bridge connections were boys experiencing depressed mood to mothers feeling powerless, and mothers feeling bad to girls experiencing depressed mood. These findings highlight the network-level relations between maternal depressive symptoms and offspring internalizing problems. They provide insights into the developmental differences and similarities in symptoms during these periods and suggest ways to break the vicious cycle of psychopathology between mothers and their children.

Anxious and depressive symptoms and health-related quality of life in a cohort of people who recently attempted suicide: A network analysis

BACKGROUND

Suicide is an international health concern with immeasurable impact from the perspective of human and social suffering. Prior suicide attempts, anxious and depressive symptoms, and relatively lower health-related quality of life (HRQoL) are among the most replicated risk factors for suicide. Our goal was to visualize the distribution of these features and their interconnections with use of a network analysis approach in individuals who recently attempted suicide.

METHODS

Individuals with a recent suicide attempt were recruited from nine University Hospitals across Spain as part of the SURVIVE cohort study. Anxious and depressive symptoms, and perceived HRQoL were included in the network analysis. Network structures were estimated with the EBICglasso model. Centrality measures and bridge symptoms connecting communities were explored. Subnetworks comparing younger and older individuals, and women and men were analyzed.

RESULTS

A total of 1106 individuals with a recent suicide attempt were included. Depressed mood was the symptom with the greatest influence in the overall network, followed by anxiety symptoms such as feeling nervous, worrying, restless, and having difficulties to relax. Perceived general health was associated with increased suicidal ideation in the whole sample. Older people showed a specific connection between perceived general health and depressed mood.

LIMITATIONS

The cross-sectional design does not allow determination of established causality.

CONCLUSIONS

Depressed mood was the core network's symptom and, therefore, an important target in the management and prevention of suicide. HRQoL had more influence on the network of older populations, in which it should be a primary focus.

Network analysis of pandemic fatigue symptoms in samples from five South American countries

BACKGROUND

Pandemic fatigue generates low motivation or the ability to comply with protective behaviors to mitigate the spread of COVID-19.

AIMS

This study aimed to analyze the symptoms of pandemic fatigue through network analysis in individuals from five South American countries.

METHOD

A total of 1,444 individuals from Argentina, Bolivia, Paraguay, Peru, and Uruguay participated and were evaluated using the Pandemic Fatigue Scale. The networks were estimated using the ggmModSelect estimation method and a polychoric correlation matrix was used. Stability assessment of the five networks was performed using the nonparametric resampling method based on the case bootstrap type. For the estimation of network centrality, a metric based on node strength was used, whereas network comparison was performed using a permutation-based approach.

RESULTS

The results showed that the relationships between pandemic fatigue symptoms were strongest in the demotivation dimension. Variability in the centrality of pandemic fatigue symptoms was observed among participating countries. Finally, symptom networks were invariant and almost identical across participating countries.

CONCLUSIONS

This study is the first to provide information on how pandemic fatigue symptoms were related during the COVID-19 pandemic.

The comorbid network characteristics of anxiety and depressive symptoms among Chinese college freshmen

BACKGROUND

This study aimed to investigate the interplay between anxiety and depressive symptoms in Chinese college freshmen using the causal system perspective (CSP), which differs from the traditional common cause perspective (CCP) by providing an alternative explanation by attributing comorbidity to direct interactions among symptoms.

METHODS

A convenience sample of 2,082 Chinese college freshmen (39.51% male, Mage = 18.61) from a normal university completed the Generalized Anxiety Disorder 7-Item Scale (GAD-7) and the Patient Health Questionnaire (PHQ-9). Network analysis was conducted and evaluated as to centrality, stability, node predictability, and bridging features. Moreover, the moderated network model (MNM) was utilized to detect the moderation effects of gender in the comorbidity network.

RESULTS

The network of anxiety and depressive symptoms exhibited stability, characterized by the core symptoms of "restlessness", "lack of energy", and "excessive worry about control", as well as the bridging symptoms of "fearfulness", "sad mood", and "irritability". Notably, the nodes representing "uncontrollable worry" and "difficulty in relaxation" demonstrated the highest predictive power. Gender did not exert any moderating effects on the anxiety and depressive symptom network.

CONCLUSION

These results reinforce that certain anxiety or depressive symptoms are more central than others, and thus play a more vital role in the comorbid network. These findings highlight underlying potential targeting symptoms to consider in future interventions.

Symptom patterns in the co-occurrence of depressive and generalized anxiety symptoms: A network analysis of a Canadian nationally representative sample

BACKGROUND

This study aimed to investigate the symptom patterns of major depressive disorder (MDD) and generalized anxiety disorder (GAD) in a matched nationally representative sample of the Canadian population. We also tested whether childhood maltreatment (CM) exposures and sex would be linked with different symptom patterns.

METHODS

A total of 3296 participants from the Canadian Community Health Survey-Mental Health with complete information on MDD and GAD symptoms and being matched on the studied sociodemographic characteristics were included in the current study. Network analysis was performed to examine the MDD-GAD symptom network, network stability and centrality indices were also estimated. Finally, network comparison in connectivity patterns was conducted to explore the impact of maltreatment experience and sex differences in the MDD-GAD symptom networks.

RESULTS

The CM group had stronger network connections and showed differences in the network structures from the non-CM group. In the CM group, depressed mood and diminished interest were central symptoms and strongly connected with other symptoms. Additionally, females had stronger connections in the MDD-GAD symptom network than males, and sleep disturbance was a central symptom for females, alongside depressed mood and diminished interest.

LIMITATIONS

The cross-sectional design restricts our capacity to establish longitudinal or causal connections between symptoms.

CONCLUSIONS

Depressed mood was the most central node that was strongly connected with other symptoms in the network. Distinct MDD-GAD symptom networks were discovered in the CM and the female group when compared to their counterparts. Noteworthy, individuals with CM had a stronger correlation between worry and suicidal ideation. Clinical management and intervention efforts should pay close attention to these core symptoms to yield optimal treatment effects, particularly for females and individuals with CM.

Temporal network of experience sampling methodology identifies sleep disturbance as a central symptom in generalized anxiety disorder

BACKGROUND

A temporal network of generalized anxiety disorder (GAD) symptoms could provide valuable understanding of the occurrence and maintenance of GAD. We aim to obtain an exploratory conceptualization of temporal GAD network and identify the central symptom.

METHODS

A sample of participants (n = 115) with elevated GAD-7 scores (Generalized Anxiety Disorder 7-Item Questionnaire [GAD-7] ≥ 10) participated in an online daily diary study in which they reported their GAD symptoms based on DSM-5 diagnostic criteria (eight symptoms in total) for 50 consecutive days. We used a multilevel VAR model to obtain the temporal network.

RESULTS

In temporal network, a lot of lagged relationships exist among GAD symptoms and these lagged relationships are all positive. All symptoms have autocorrelations and there are also some interesting feedback loops in temporal network. Sleep disturbance has the highest Out-strength centrality.

CONCLUSIONS

This study indicates how GAD symptoms interact with each other and strengthen themselves over time, and particularly highlights the relationships between sleep disturbance and other GAD symptoms. Sleep disturbance may play an important role in the dynamic development and maintenance process of GAD. The present study may develop the knowledge of the theoretical model, diagnosis, prevention and intervention of GAD from a temporal symptoms network perspective.

Network analysis of suicide ideation and depression-anxiety symptoms among Chinese adolescents

Background

The co-occurrence of depression and anxiety among adolescents is typically associated with suicide ideation.

Aims

The study aimed to investigate the symptom-level relationship between suicide ideation and the comorbidity of depression and anxiety.

Methods

1501 adolescents aged 12-19 years were assessed using the Patient Health Questionnaire (PHQ-9) and the Generalized Anxiety Disorder Scale, and 716 adolescents who scored ≥5 on both scales were selected as participants. Network analysis was used to identify the network structure of depressive symptoms and anxiety symptoms. Participants were categorised into either the suicide ideation or non-suicide ideation groups based on their scoring on the suicide-related item in PHQ-9. A comparison was made between the depression-anxiety symptom networks of the two groups.

Results

'Restlessness', 'sad mood' and 'trouble relaxing' were the most prominent central symptoms in the depression-anxiety symptom network, and 'restlessness', 'nervousness' and 'reduced movement' were the bridge symptoms in this network. 'Sad mood' was found to be directly related to 'suicide ideation' with the highest variance. The network structure was significantly different in properties between the suicide ideation group and the non-suicide ideation group, with 'restlessness' and 'sad mood' exhibiting significantly higher influence in the network of the suicide ideation group than that in the non-suicide ideation group.

Conclusion

Restlessness and sad mood could be targeted for the intervention of depression-anxiety symptoms among adolescents with suicide ideation.

Associations between anxiety, depression, and personal mastery in community-dwelling older adults: a network-based analysis

BACKGROUND

In China, about 18.70% of the population aged 60 years and older are at risk of low personal mastery as well as anxiety and depression for a variety of reasons. The purpose of this study was to construct a symptom network model of the relationship between anxiety, depression, and personal mastery in community-dwelling older adults and to identify central and bridge symptoms in this network.

METHODS

Depression, anxiety, and personal mastery were measured using the Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder Scale (GAD-7), and Personal Mastery Scale (PMS), respectively. A total of 501 older adults in 16 communities in Changzhou and Zhenjiang, Jiangsu Province, China, were surveyed by using a combination of stratified sampling and convenience sampling methods. The R language was used to construct the network.

RESULTS

(1) The network structure of anxiety-depression-personal mastery was stable, with "Nervousness" (node GAD1, strength = 1.38), "Sad mood" (node PHQ2, strength = 1.22), " Inability to change" (node PMS2, strength = 1.01) and "Involuntarily" (node PMS3, strength = 0.95) as the central symptoms. (2) "Irritability" (node GAD6, bridge strength = 0.743), "Sad mood" (node PHQ2, bridge strength = 0.655), and "Trouble relaxing" (node GAD4, bridge strength = 0.550) were the bridge symptoms connecting anxiety, depressive symptoms, and personal mastery. (3) In the network comparison test (NCT), residence, somatic chronic comorbidity and gender had no significant effect on network structure.

CONCLUSIONS

The construction of the anxiety-depression-personal mastery network structure opens up new possibilities for mechanisms of action and intervention formulation for psychological disorders in community-dwelling older adults. The identification of central symptoms (e.g., nervousness, sad mood, inability to change, involuntarily) and bridge symptoms (e.g., irritability, sad mood, trouble relaxing) in community-dwelling older adults with anxiety, depression, and low sense of mastery can provide a scientific basis for the development of precise interventions.

A network model of depressive and anxiety symptoms: a statistical evaluation

BACKGROUND

Although network analysis studies of psychiatric syndromes have increased in recent years, most have emphasized centrality symptoms and robust edges. Broadening the focus to include bridge symptoms within a systematic review could help to elucidate symptoms having the strongest links in network models of psychiatric syndromes. We conducted this systematic review and statistical evaluation of network analyses on depressive and anxiety symptoms to identify the most central symptoms and bridge symptoms, as well as the most robust edge indices of networks.

METHODS

A systematic literature search was performed in PubMed, PsycINFO, Web of Science, and EMBASE databases from their inception to May 25, 2022. To determine the most influential symptoms and connections, we analyzed centrality and bridge centrality rankings and aggregated the most robust symptom connections into a summary network. After determining the most central symptoms and bridge symptoms across network models, heterogeneity across studies was examined using linear logistic regression.

RESULTS

Thirty-three studies with 78,721 participants were included in this systematic review. Seventeen studies with 23 cross-sectional networks based on the Patient Health Questionnaire (PHQ) and Generalized Anxiety Disorder (GAD-7) assessments of clinical and community samples were examined using centrality scores. Twelve cross-sectional networks based on the PHQ and GAD-7 assessments were examined using bridge centrality scores. We found substantial variability between study samples and network features. 'Sad mood', 'Uncontrollable worry', and 'Worrying too much' were the most central symptoms, while 'Sad mood', 'Restlessness', and 'Motor disturbance' were the most frequent bridge centrality symptoms. In addition, the connection between 'Sleep' and 'Fatigue' was the most frequent edge for the depressive and anxiety symptoms network model.

CONCLUSION

Central symptoms, bridge symptoms and robust edges identified in this systematic review can be viewed as potential intervention targets. We also identified gaps in the literature and future directions for network analysis of comorbid depression and anxiety.

Network analysis of depression and anxiety symptoms and their associations with mobile phone addiction among Chinese medical students during the late stage of the COVID-19 pandemic

Network analysis provides a novel approach to discovering associations between mental disorders at the symptom level. This study aimed to examine the characteristics of the network of depression and anxiety symptoms and their associations with mobile phone addiction (MPA) among Chinese medical students during the late stage of the COVID-19 pandemic. A total of 553 medical students were included. Depression and anxiety symptoms and MPA were measured by the nine-item Patient Health Questionnaire (PHQ-9), the seven-item Generalized Anxiety Disorder Scale (GAD-7), and the Mobile Phone Addiction Index (MPAI), respectively. Central and bridge symptoms were identified with centrality indices and bridge centrality indices. Network stability was examined using the case-dropping procedure. "Uncontrollable worry", "restlessness" and "nervousness" were the central symptoms in the depression and anxiety network. "Restlessness" and "motor" were the most central bridge symptoms linking depression and anxiety. "Concentration", "anhedonia" and "sleep" were most strongly associated with MPA. "Uncontrollable worry", "restlessness", "nervousness," and "motor" may be the symptoms for interventions to target in medical students with comorbid depression and anxiety. From a network perspective, depressive symptoms may be more important than anxiety symptoms in medical students with MPA.

Impact of depressive symptoms on medication adherence in older adults with chronic neurological diseases

BACKGROUND

Nonadherence to medication contributes substantially to worse health outcomes. Especially among older adults with chronic illness, multimorbidity leads to complex medication regimes and high nonadherence rates. In previous research, depressive symptomology has been identified as a major contributor to nonadherence, and some authors hypothesize a link via motivational deficits and low self-efficacy. However, the exact mechanisms linking depressive symptomology and nonadherence are not yet understood. This is in part because the often-employed sum scores cannot do justice to the complexity of depressive symptomology; instead, it is recommended to assess the influence of individual symptoms.

METHODS

Following this symptom-based approach, we performed correlation, network and regression analysis using depressive symptoms as depicted by the items of the revised Beck Depression Inventory II (BDI) to assess their influence with nonadherence in N = 731 older adults with chronic neurological diseases. Nonadherence was measured with the self-report Stendal Adherence to Medication Score (SAMS).

RESULTS

Even when controlling for sociodemographic and health-related covariates, the BDI remained the most influential contributor to nonadherence. Across different methods, Loss of Interest and Difficulty with Concentration were identified as particularly influential for nonadherence, linking nonadherence with other affective or somatic BDI items, respectively. Additionally, Fatigue, Problems with Decision Making, Suicidal Thoughts, and Worthlessness contribute to nonadherence.

CONCLUSION

Using a symptom-driven approach, we aimed to understand which depressive symptoms contribute to higher levels of nonadherence. Our results refine previous hypotheses about motivation and control beliefs by suggesting that it is not merely a lack of beliefs in the efficacy of medication that connects depressive symptoms and nonadherence, but rather an overall lack of interest in improving one's health due to feelings of worthlessness and suicidal tendencies. This lack of interest is further substantiated by already sparse resources caused by changes in concentration and fatigue. In order to improve health outcomes and reduce nonadherence, these associations between depressive symptoms must be further understood and targeted in tailored interventions.

Core and bridge symptoms of demoralization in Chinese female cancer patients: a network analysis

Objective

In this study, we explore the core and bridge symptoms of demoralization in female cancer patients in China, and provide a basis for precise psychological intervention among female cancer patients.

Methods

This study used a cross-sectional survey. Participants were recruited from three third-class hospitals in Jiangsu Province from June 2022 to June 2023 using the convenience sampling method. The severity of each symptom of demoralization was investigated in female cancer patients using the Demoralization Scale (DS). Network analysis was performed using the R language to identify core and bridge symptoms in the network and further explore some characteristic edge connections in the network.

Results

The network structure model of demoralization had strong accuracy and stability. In the network, the symptoms with the highest strength centrality were "Discouragement" (C3, strength=2.19), "No self-worth" (A3, strength=1.21), "Don't want to live" (A5, strength=1.20), "Hopeless" (D4, strength=0.81), and "Vulnerability" (B3, strength=0.74), respectively. The bridge strength analysis identified "Hopeless" (D4, bridge strength=0.92), "Discouragement" (C3, bridge strength=0.85), "No self-worth" (A3, bridge strength=0.75), "Poor spirits" (E2, bridge strength=0.71), and "Vulnerability" (B3, bridge strength=0.69) as the bridge symptoms. The strongest edge connections of all dimensions were "No self-worth" and "Worthless" (A3-E6, edge weighting=0.27), "Poor spirits" and "Loss of emotional control" (E2-D1, edge weighting=0.22), "Discouragement" and "Vulnerability" (C3-B3, edge weighting=0.14), and "Hopeless" and "No meaning of survival" (D4-A4, edge weighting=0.12).

Conclusion

"Discouragement (C3)", "No self-worth (A3)", "Hopeless (D4)", and "Vulnerability (B3)" are both core symptoms and bridge symptoms. These symptoms can not only trigger a patient's demoralization but also stimulate more severe symptom clusters through interactions. The early recognition of and intervention regarding these symptoms could be important for the prevention and treatment of demoralization among female cancer patients.

The Inter-Relationships Between Depressive Symptoms and Suicidality Among Macau Residents After the "Relatively Static Management" COVID-19 Strategy: A Perspective of Network Analysis

Background

Suicidality is a global public health problem which has increased considerably during the coronavirus disease 2019 (COVID-19) pandemic. This study examined the inter-relationships between depressive symptoms and suicidality using network analysis among Macau residents after the "relatively static management" COVID-19 strategy.

Methods

An assessment of suicidal ideation (SI), suicide plan (SP), suicide attempt (SA) and depressive symptoms was conducted with the use of individual binary response items (yes/no) and Patient Health Questionnaire (PHQ-9). In the network analysis, central and bridge symptoms were identified in the network through "Expected Influence" and "Bridge Expected Influence", and specific symptoms that were directly associated with suicidality were identified via the flow function. Network Comparison Tests (NCT) were conducted to examine the gender differences in network characteristics.

Results

The study sample included a total of 1008 Macau residents. The prevalence of depressive symptoms and suicidality were 62.50% (95% CI = 59.4-65.5%) and 8.9% (95% CI = 7.2-10.9%), respectively. A network analysis of the sample identified SI ("Suicidal ideation") as the most central symptom, followed by SP ("Suicide plan") and PHQ4 ("Fatigue"). SI ("Suicidal ideation") and PHQ6 ("Guilt") were bridge nodes connecting depressive symptoms and suicidality. A flow network revealed that the strongest connection was between S ("Suicidality") and PHQ6 ("Guilt"), followed by S ("Suicidality") and PHQ 7 ("Concentration"), and S ("Suicidality") and PHQ3 ("Sleep").

Conclusion

The findings indicated that reduction of specific depressive symptoms and suicidal thoughts may be relevant in decreasing suicidality among adults. Further, suicide assessment and prevention measures should address the central and bridge symptoms identified in this study.

Relationships between psychopathological symptoms, pandemic-related stress, perceived social support, and COVID-19 infection history: a network analysis in Chinese college students

Introduction

Previous coronavirus, 2019 (COVID-19) research has applied network analysis to examine relationships between psychopathological symptoms but rarely extended to potential risk and protective factors or the influence of COVID-19 infection history. This study examined complex inter-relationships between psychopathological symptoms, COVID-19-related stressors, perceived social support, and COVID-19 infection history among Chinese university/college students during the peak of fifth pandemic wave using a network analysis approach.

Methods

A Least Absolute Shrinkage and Selection Operator-regularized partial correlation network using Gaussian graphical model was constructed in 1,395 Chinese university/college students in Hong Kong who completed a survey between 15 March and 3 April, 2022. Depressive, anxiety, and acute/traumatic stress symptoms were measured by Patient Health Questionnaire-9, Generalized Anxiety Disorder-7, and Impact of Event Scale-6, respectively. COVID-19-related stressors and perceived social support were measured. Network differences by COVID-19 infection history (COVID-network vs. no_COVID-network) and network communities were examined.

Results

Our results showed that the most influential nodes were depressed mood, uncontrollable worries, and uncontrollable thoughts about COVID-19. The main bridging symptoms were concentration problems and psychomotor problems. The COVID-network, comprising participants with a history of COVID-19 infection only, was significantly stronger than the no_COVID-network. Perceived social support and stress from conflicts with family/friends formed a unique community with negative cognition and suicidal idea in the COVID-network only.

Conclusion

Our findings indicate that specific interventions targeting interpersonal conflicts and concentration problems as well as facilitating stress buffering effects of social support may represent effective strategies to reduce psychological distress in university/college students during COVID-19 and should be considered for future pandemic preparedness.

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.

Using a longitudinal network structure to subgroup depressive symptoms among adolescents

BACKGROUND

Network modeling has been proposed as an effective approach to examine complex associations among antecedents, mediators and symptoms. This study aimed to investigate whether the severity of depressive symptoms affects the multivariate relationships among symptoms and mediating factors over a 2-year longitudinal follow-up.

METHODS

We recruited a school-based cohort of 1480 primary and secondary school students over four semesters from January 2020 to December 2021. The participants (n = 1145) were assessed at four time points (ages 10-13 years old at baseline). Based on a cut-off score of 5 on the 9-item Patient Health Questionnaire at each time point, the participants were categorized into the non-depressive symptom (NDS) and depressive symptom (DS) groups. We conducted network analysis to investigate the symptom-to-symptom influences in these two groups over time.

RESULTS

The global network metrics did not differ statistically between the NDS and DS groups at four time points. However, network connection strength varied with symptom severity. The edge weights between learning anxiety and social anxiety were prominently in the NDS group over time. The central factors for NDS and DS were oversensitivity and impulsivity (3 out of 4 time points), respectively. Moreover, both node strength and closeness were stable over time in both groups.

CONCLUSIONS

Our study suggests that interrelationships among symptoms and contributing factors are generally stable in adolescents, but a higher severity of depressive symptoms may lead to increased stability in these relationships.

Central symptoms and network associations of depressive symptoms among school-aged students: A network analysis

BACKGROUND

Depression is one of the most prevalent mental health problems occurred among school-aged students. Conceptualizing depressive symptoms as a network of interacting symptoms, this study used network analysis to identify central symptoms and network associations of depressive symptoms. The study also investigated how networks of depressive symptoms differ across school aged periods.

METHODS

A total of 2514 Chinese school-aged students in Grades 4 to 11 were recruited and asked to complete the Child Depression Inventory in this study.

RESULTS

The results showed that self-hatred consistently emerged as a central symptom of depressive symptoms across all school stages. Beyond this, each school stage had its unique central symptoms: loneliness was prominent in both elementary school and junior high school, while fatigue was more specific symptom to senior high school. When comparing the network structures across different school stages, there was a significant difference in network structure between elementary school students and junior high school students. The comparison in global strength showed that the network connectivity of depression network is stronger among elementary school students, with showing closer symptom associations.

CONCLUSIONS

By identifying central symptoms and their distinct associations, particularly the pronounced symptom interconnections among elementary school students, this study emphasize the critical importance of early interventions. Recognizing these stage-specific characteristics is essential for the development of effective prevention and intervention programs for depressive symptoms in school-aged students.

A comparison of psychiatric symptoms between mental health professionals with and without post-infection sequelae of COVID-19

Post-infection sequelae of COVID-19 (PISC) have raised public health concerns. However, it is not clear whether infected mental health professionals (MHPs) with PISC have experienced more psychiatric symptoms than MHPs without PISC do. This study examined differences in the prevalence of self-reported depression, anxiety, insomnia and suicidality as well as the network structures of these symptoms between these two groups. Participants completed questionnaire measures of psychiatric symptoms and demographics. Expected influence was used to measure centrality of symptoms and network comparison tests were adopted to compare differences in the two network models. The sample comprised 2,596 participants without PISC and 2,573 matched participants with PISC. MHPs with PISC had comparatively higher symptom levels related to depression (55.2% vs. 23.5 %), anxiety (32.0% vs. 14.9 %), insomnia (43.3% vs. 17.3 %), and suicidality (9.6% vs. 5.3 %). PHQ4 ("Fatigue"), PHQ6 ("Guilt"), and GAD2 ("Uncontrollable Worrying") were the most central symptoms in the "without PISC" network model. Conversely, GAD3 ("Worry too much"), GAD5 ("Restlessness"), and GAD4 ("Trouble relaxing") were more central in the "with PISC" network model. In sum, MHPs with PISC experienced comparatively more psychiatric symptoms and related disturbances. Network results provide foundations for the expectation that MHPs with PISC may benefit from interventions that address anxiety-related symptoms, while those without PISC may benefit from interventions targeting depression-related symptoms.

Predictors for quality of life in older adults: network analysis on cognitive and neuropsychiatric symptoms

BACKGROUND

Quality of life (QoL) of older adults has become a pivotal concern of the public and health system. Previous studies found that both cognitive decline and neuropsychiatric symptoms (NPS) can affect QoL in older adults. However, it remains unclear how these symptoms are related to each other and impact on QoL. Our aim is to investigate the complex network relationship between cognitive and NPS symptoms in older adults, and to further explore their association with QoL.

METHODS

A cross-sectional study was conducted in a sample of 389 older individuals with complaints of memory decline. The instruments included the Neuropsychiatric Inventory, the Mini Mental State Examination, and the 36-item Short Form Health Survey. Data was analyzed using network analysis and mediation analysis.

RESULTS

We found that attention and agitation were the variables with the highest centrality in cognitive and NPS symptoms, respectively. In an exploratory mediation analysis, agitation was significantly associated with poor attention (β = -0.214, P < 0.001) and reduced QoL (β = -0.137, P = 0.005). The indirect effect of agitation on the QoL through attention was significant (95% confidence interval (CI) [-0.119, -0.035]). Furthermore, attention served as a mediator between agitation and QoL, accounting for 35.09% of the total effect.

CONCLUSIONS

By elucidating the NPS-cognition-QoL relationship, the current study provides insights for developing rehabilitation programs among older adults to ensure their QoL.

Exploring symptom-level associations between anxiety and depression across developmental stages of adolescence: a network analysis approach

BACKGROUND

Anxiety and depression often co-occur during adolescence, but the associations between symptoms of these two disorders in this developmental period are not yet fully understood. Network analysis provides a valuable approach to uncover meaningful associations among symptoms and offers insights for prevention and intervention strategies. This study aimed to investigate symptom-level associations between anxiety and depression using network analysis and to identify core symptoms, bridge symptoms, and differences in network structure across different stages of adolescence.

METHODS

The cross-sectional study was conducted in March 2022 in Shenzhen, China. Participants completed the Generalized Anxiety Disorder Scale-7 and Patient Health Questionnaire Depression Scale, along with demographic questionnaires assessing age and gender. Chinese adolescents aged 10 to 17 who were in Grades 5 or 6 of elementary school, Grades 1 or 2 of middle school, or Grades 1 or 2 of high school, and who could comprehensively understand and read Chinese were recruited as participants. Students in Grade 3 of middle and high schools were excluded due to their upcoming high school or college entrance examinations. Based on age, participants were categorized into early, middle, and late developmental stages of adolescence.

RESULTS

"Loss of control" was among the most central symptoms in the comorbidity network throughout all three developmental stages; "excessive worry" and "anhedonia" emerged as the core symptoms in early adolescence, and "restlessness" as the core symptom in late adolescence. "Anhedonia," "sad mood," and "fatigue" were identified as bridge symptoms between anxiety and depression across all three developmental stages of adolescence. The global strength of the network in middle adolescence was significantly higher compared to the other two stages.

CONCLUSION

These findings highlight the core and bridge symptoms that require special attention and intervention at each stage of adolescence. Moreover, significantly higher network connectivity in middle adolescence suggests this is a critical period for intervention to prevent the development of comorbid mental disorders.

Anxiety and depression played a central role in the COVID-19 mental distress: A network analysis

INTRODUCTION

Psychological, socio-demographics, and clinical factors play an important role in patients with COVID-19, but their relationship is complex. The network approach might be used to disentangle complex interactions in different systems. Using data from a multicentre, cross-sectional, survey among patients with COVID-19 in Spain (July-November 2020), we investigated the network structure of mental disorders symptoms, social support, and psychological resilience, and changes in network structures according to the presence of a pre-existing mental disorder or hospitalization for COVID-19.

METHODS

Subjects completed a survey to evaluate sociodemographic characteristics, COVID-19 infection status, resilience, social support, and symptoms of depression, anxiety disorders, post-traumatic stress disorder, panic attacks, and substance use disorder. 2084 patients with COVID-19 were included in the analysis. Network analysis was conducted to evaluate network and bridge centrality, and the network properties were compared between COVID-19 patients with and without a history of lifetime mental disorder, and between hospitalized and non-hospitalized patients.

LIMITATIONS

Generalization of our findings may be difficult since differences in network connectivity may exist in different populations or samples.

RESULTS

Anxiety and depression showed high centrality in patients with COVID-19 and anxiety showed the highest bridge influence in the network. Resilience and social support showed a low influence on mental disorder symptoms. Global network estimations show no statistically significant changes between patients with and without pre-existing mental disorders or between hospitalized and non-hospitalized patients.

CONCLUSIONS

Anxiety might be a key treatment target in patients with COVID-19 since its treatment might prevent other mental health adverse outcomes.

Centrality depression-anxiety symptoms linked to suicidal ideation among depressed college students--A network approach

The long-term effects of the COVID-19 pandemic have caused severe mental health problems among college students, which can eventually cause suicidal ideation. Therefore, through network analysis, this study aims to explore the new characteristics of the depression-anxiety symptom network that arose during the long-term lockdown of the COVID-19 pandemic and to identify the most influential symptoms linked to suicidal ideation. We used a Patient Health Questionnaire (PHQ-9) score above 10 as the cutoff and screened 622 participants with an inclination toward depressive disorders from 7976 college students, and then divided the sample into suicidal and nonsuicidal groups based on the presence or absence of suicidal ideation. The General Anxiety Disorder scale (GAD-7) was also used. Network analysis was used to identify the network structure of anxiety-depression and which symptoms were directly related to suicidal ideation in the network. The prevalence of depression and anxiety among Chinese college students in the late stage of the COVID-19 pandemic was 7.8% and 17.8%, respectively. The most central symptoms in the nonsuicidal group were "excessive worry," "uncontrollable worry," and "nervousness," and in the suicidal group they were "excessive worry," "motor function," and "irritability." The network of the suicidal group was denser than that of the nonsuicidal group. The most influential symptom directly related to suicidal ideation was "guilt." The most influential central symptom of depression-anxiety comorbidity characteristics of Chinese adolescents showed a tendency to shift from depression-oriented (i.e., sad mood) to anxiety-oriented (i.e., excessive worry) with the continuation of the COVID-19 pandemic. Treatments or interventions focused on these critical symptoms could be useful in preventing college students from suicide risk.

Network of burnout, depression, anxiety, and dropout intention in medical undergraduates

BACKGROUND

Burnout, depression, and anxiety are highly prevalent among medical students, which often leads to their attrition. We aim to assess the inter-relationships of depression, burnout, and anxiety symptoms with dropout intention among Chinese medical undergraduates using the network analysis.

METHOD

A total of 3,648 Chinese medical undergraduates were recruited through snowball sampling. Learning burnout scale, 9-item Patient Health Questionnaire (PHQ-9), and General Anxiety Disorder Scale (GAD-7) was used to assess burnout, depression, and anxiety symptoms, respectively. We used the EBICglasso model to estimate the network. We compared the network based on gender, study phase, and clinical experience.

RESULTS

After removing repeated submissions and incorrect responses to the trap question, 3,536 participants were included in the final analysis. The prevalence of burnout, depression, anxiety, and dropout intention was 38, 62.7, 38.4, and 39% respectively, which is consistent with previous findings. Network analysis suggested that anxiety and depression items clustered together and displayed several strong bridge connections, while burnout items formed another cluster. All the strongest edges were within the respective distress. Cynicism symptoms 'I am fed up with study' and 'I want to study but I feel that studying is boring' were the most central symptoms, while 'fatigue' and 'worthless' were the bridge symptoms within the burnout-depression-anxiety network. Other central symptoms included 'worthless', 'I can handle my courses', 'nervous', and 'uncontrollable worry'. Cynicism symptoms 'I am interested in my major' and 'I feel that the knowledge I have learned is useless' were mostly related to dropout intention. Gender, study phase, and clinical experience didn't affect the global strength of the burnout-depression-anxiety network.

CONCLUSION

Our results indicated the predominance of cynicism symptoms within the burnout-depression-anxiety network and its substantial impact on dropout intention, suggesting that early detection and intervention for cynicism symptoms in Chinese medical students are in urgent need. Other central and bridge symptoms might also serve as potential targets for the prevention and treatment of burnout, depression, and anxiety among medical students. For example, studies suggest cognitive-behavioral therapy could quickly improve 'worthless', which might be beneficial in treating burnout, depression, and anxiety in medical students.

A network analysis of the long-term quality of life and mental distress of COVID-19 survivors 1 year after hospital discharge

Objectives

COVID-19 survivors suffer from persistent mental distress and impaired quality of life (QOL) after recovery from the infection. However, the symptom-symptom interaction between these psychological variables remained unexplored. The present study aimed to determine the symptom network of mental distress (depression, anxiety, sleep disturbance, fatigue, and post-traumatic stress disorder) and their association with QOL among 535 COVID-19 survivors 1 year after hospital discharge.

Methods

9-item Patient Health Questionnaire, 7-item Generalized Anxiety Disorder Scale, Chalder fatigue scale, Impact of Event Scale-Revised, Pittsburgh Sleep Quality Index, and 36-Item Short-Form Health Survey were applied to measure depression, anxiety, fatigue, PTSD, sleep disturbances, and QOL, respectively. Two networks were estimated using Gaussian graphical model. Network 1 consisted of mental symptoms to determine the central and bridge symptoms. Network 2 additionally included QOL to determine which mental symptoms were mostly related to QOL.

Results

60% of the COVID-19 survivors experienced mental distress 1 year after hospital discharge. Uncontrollable and excessive worry, psychomotor symptoms, intrusion, and daytime dysfunction were the most central symptoms. Daytime dysfunction and fatigue (especially mental fatigue and loss of energy) served as the bridge symptoms across the mental distress network and exhibited the most substantial association with QOL.

Conclusion

Our study demonstrated several key symptoms that played a vital role in mental distress and QOL among COVID-19 survivors. Prompt screening and targeted interventions for these symptoms might hold great promise in preventing mental distress and improving QOL in COVID-19 survivors.

Identification and comparison of pandemic-to-symptom networks of South Korea and the United States

Background

The Coronavirus (COVID-19) pandemic resulted in a dramatic increase in the prevalence of anxiety and depression globally. Although the impact on the mental health of young adults was especially strong, its underlying mechanisms remain elusive.

Materials and methods

Using a network approach, the present study investigated the putative pathways between pandemic-related factors and anxiety and depressive symptoms among young adults in South Korea and the U.S. Network analyses were conducted on cross-country data collected during the COVID-19 lockdown period (n = 1,036). Our model included depression symptoms (PHQ-9), generalized anxiety symptoms (GAD-7), and COVID-19-related factors (e.g., COVID-19-related traumatic stress, pandemic concerns, access to medical/mental health services).

Results

The overall structure of pandemic-to-symptom networks of South Korea and the U.S. were found to be similar. In both countries, COVID-related stress and negative future anticipation (an anxiety symptom) were identified as bridging nodes between pandemic-related factors and psychological distress. In addition, worry-related symptoms (e.g., excessive worry, uncontrollable worry) were identified as key contributors in maintaining the overall pandemic-to-symptom network in both countries.

Conclusion

The similar network structures and patterns observed in both countries imply that there may exist a stable relationship between the pandemic and internalizing symptoms above and beyond the sociocultural differences. The current findings provide new insights into the common potential pathway between the pandemic and internalizing symptoms in South Korea and in the U.S. and inform policymakers and mental health professionals of potential intervention targets to alleviate internalizing symptoms.

Longitudinal assessment and determinants of short-term and longer-term psychological distress in a sample of healthcare workers during the COVID-19 pandemic in Quebec, Canada

Introduction

Previous research has demonstrated the negative impact of the COVID-19 pandemic emergency on the wellbeing of healthcare workers. However, few research contributions reported a longitudinal evaluation of psychological distress and examined determinants of its duration and course over time. The present study aims to explore the impact of the pandemic emergency on HCWs mental health by adopting a longitudinal design and assessing mental health as combination of overlapping clinical symptoms (post-traumatic stress disorder, depression and anxiety).

Methods

Data were collected weekly through a mobile application during and after the first wave of COVID-19 in the province of Quebec, Canada, in 2020. Analysis was conducted on a final sample of 382 participants. Participants were grouped into "resilient" (RES) if they did not manifest clinical-level psychological distress during monitoring, "short-term distress" (STD) if distress exceeded the clinical threshold for 1-3 weeks, and longer-term distress (LTD) if it occurred for four or more weeks, even if not consecutively. Descriptive statistics for all variables were computed for each subgroup (RES, STD and LTD), and pairwise comparisons between each group for every descriptive variable were made using chi square statistics for categorical variables and t-test for continuous variables. Predictors of distress groups (STD and LTD vs RES) were assessed running multinomial hierarchical logistic regression models.

Results

In our sample, almost two third (59.4%) HCWs did not manifest moderate or severe distress during the monitoring time. Short-term distress, mostly post-traumatic symptoms that lasted for less than 4 weeks, were the most common distress response, affecting almost one third of participants. Longer psychological distress occurred only in a smaller percentage (12.6%) of cases, as a combination of severe posttraumatic, depressive and anxiety symptoms. Perceived occupational stress was the most significant risk factor; moreover individual, peritraumatic work and family risk and protective factors, were likely to significantly affect the stress response.

Discussion

Results tend to provide a more complex and resiliency-oriented representation of psychological distress compared to previous cross-sectional studies, but are in line with stress response studies. Findings allow us to better describe the profiles of distress response in STD and LTD groups. Participants that manifest short term distress experience acute stress reaction in which the interplay between personal, family and professional life events is associated with the stress response. Conversely, longer term distress response in HCWs presents a more complex mental health condition with an higher level of impairment and support needs compared to participants with short-term distress.

Mapping associations between anxiety and sleep problems among outpatients in high-altitude areas: a network analysis

BACKGROUND

Anxiety and sleep problems are common comorbidities among outpatients living in high-altitude areas. Network analysis is a novel method to investigate the interaction and the association between symptoms across diverse disorders. This study used network analysis to investigate the network structure symptoms of anxiety and sleep problems among outpatients in high-altitude areas, and to explore the differences in symptom associations in various sex, age, educational levels and employment groups.

METHODS

The data was collected from the Sleep Medicine Center of The First People's Hospital of Yunnan Province from November 2017 to January 2021 with consecutive recruitment (N = 11,194). Anxiety and sleep problems were measured by the Chinese version of the seven-item Generalized Anxiety Disorder Scale (GAD-7) and the Pittsburgh Sleep Quality Index (PSQI) respectively. Central symptoms were identified based on centrality indices and bridge symptoms were identified with bridge indices. The difference of network structures in various sex, age, educational levels and employment groups were also explored.

RESULTS

Among all the cases, 6,534 (58.37%; 95% CI: 57.45-59.29%) reported experiencing anxiety (GAD-7 total scores ≥ 5), and 7,718 (68.94%; 95% CI: 68.08-69.80%) reported experiencing sleep problems (PSQI total scores ≥ 10). Based on the results of network analysis, among participants, "Nervousness", "Trouble relaxing", "Uncontrollable worry" were the most critical central symptoms and bridge symptoms within the anxiety and sleep problems network structure. The adjusted network model after controlling for covariates was significantly correlated with the original (r = 0.75, P = 0.46). Additionally, there were significant differences in edge weights in the comparisons between sex, age and educational levels groups (P < 0.001), while the employed and unemployed groups did not show significant differences in edge weights (P > 0.05).

CONCLUSIONS

In the anxiety and sleep problems network model, among outpatients living in high-altitude areas, nervousness, uncontrollable worry, and trouble relaxing were the most central symptoms and bridge symptoms. Moreover, there were significant differences between various sex, age and educational levels. These findings can be used to provide clinical suggestions for psychological interventions and measures targeting to reduce symptoms that exacerbate mental health.

The influence of changes in the Chinese COVID-19 prevention and control policies on mental health of medical staff: A network analysis

BACKGROUND

Shortly after the first outbreak of COVID-19 in Wuhan, the disease spread rapidly around the world. Previous findings reported an increase in mental health problems among Chinese medical staff, but there was a lack of research following changes in COVID-19 prevention and control policies.

METHODS

Medical staff were recruited separately in China from 15 to 16 December 2022 (N = 765, wave 1) and from 5 to 8 January 2023 (N = 690, wave 2). All participants completed the assessments of Generalized Anxiety Disorder-7, the Patient Health Questionnaire-9 and the Euthymia Scale. Network analysis was used to explore the relationships between symptoms both within and across depression, anxiety and euthymia.

RESULTS

Medical staff showed worse anxiety, depression and euthymia at wave 2 than at wave 1. Depression, motor, restlessness and uncontrollable worrying showed high centrality (i.e., strength, expected influence, closeness) at wave 1, but higher at peak. Meanwhile, motor symptoms and restlessness showed the strongest connection between different mental disorders at both wave 1 and wave 2. The network structure was stable over time after the relaxation of the infection policy.

LIMITATIONS

Our participants were not a random sample and the assessments were based on self-reports.

CONCLUSIONS

This study indicated the changes in central and bridging symptoms in medical staff at different stages after lifting of restrictions and the withdrawal of testing requirements, which provided management suggestions for the Chinese government and hospitals, as well as clinical guidance for psychological interventions.

COVID-19 pandemic’s impact on networks of depression and anxiety in naturalistic transdiagnostic sample of outpatients with non-psychotic mental illness

Background

The 2019 coronavirus disease (COVID-19) pandemic has caused an unprecedented disruption of daily lives and a mental health crisis. The present study examined how the depression and anxiety symptom network changed during the COVID-19 pandemic in a naturalistic transdiagnostic sample with non-psychotic mental illness.

Materials and methods

A total of 224 psychiatric outpatients before the pandemic and 167 outpatients during the pandemic were included in the study and were assessed for the Patient Health Questionnaire and the Beck Anxiety Inventory. The network of depression and anxiety symptoms before and during the pandemic were estimated separately and were assessed differences.

Results

The network comparison analysis showed a significant structural difference between the networks before and during the pandemic. Before the pandemic, the most central symptom in the network was feelings of worthlessness, while in the during pandemic network, somatic anxiety emerged as the most central node. Somatic anxiety, which showed the highest strength centrality during the pandemic, showed significantly increased correlation with suicidal ideation during the pandemic.

Limitations

The two cross-sectional network analyses of individuals at one point in time cannot demonstrate causal relationships among measured variables and cannot be assumed to generalize to the intraindividual level.

Conclusion

The findings indicate that the pandemic has brought a significant change in the depression and anxiety network and somatic anxiety may serve as a target for psychiatric intervention in the era of the pandemic.

Differences in Functional Level and Central Symptom of Network Structures in the Patients Seeking Treatment for Panic Disorder Before and During the COVID-19 Pandemic

OBJECTIVE

Mental health problems such as anxiety, panic, and depression have been exacerbated by the coronavirus disease-2019 (COVID-19). This study aimed to compare the symptom severities and overall function before and during the COVID-19 pandemic among patients with panic disorder (PD) seeking treatment compared to healthy controls (HCs).

METHODS

Baseline data were collected from the two groups (patients with PD and HCs) in two separate periods: before COVID-19 (Jan 2016-Dec 2019) and during COVID-19 (Mar 2020-Jul 2022). A total 453 participants (before COVID-19: 246 [139 patients with PD and 107 HCs], during COVID-19: 207 [86 patients with PD and 121 HCs]) was included. Scales for panic and depressive symptoms and overall function were administered. Additionally, network analyses were performed to compare the two groups within the patients with PD.

RESULTS

The results of two-way analysis of variance analyses showed that patients with PD enrolled during COVID-19 showed higher levels of interoceptive fear and lower overall functioning. In addition, a network comparison test revealed that a significantly high strength and expected influence for agoraphobia and avoidance in patients with PD during COVID-19.

CONCLUSION

This study suggested that the overall function could have worsened, and the importance of agoraphobia and avoidance as a central symptom may have increased in patients with PD seeking treatment during COVID-19.

Inter-relationships of depressive and anxiety symptoms with suicidality among adolescents: A network perspective

BACKGROUND

Persons with suicidality including suicidal ideation (SI), suicide plans (SP) and/or suicide attempts (SA) are at higher risk for future suicide than those without suicidality. To reduce the risk of future suicide, it is important to understand symptoms of emotional distress that have the strongest links with SI, SP and SA. This network analysis examined item-level relations of depressive and anxiety symptoms with suicidality among adolescents during the COVID-19 pandemic.

METHODS

Adolescents between 12 and 20 years of age were assessed with the Patient Health Questionnaire (PHQ-9), Generalized Anxiety Disorder Scale (GAD-7), and individual binary reponse (no/yes) items assessing SI, SP, and SA during the pandemic. The structure of depressive symptoms, anxiety symptoms and suicidality was characterized using "Expected Influence" and "Bridge Expected Influence" as centrality indices in the symptom network. Network stability was tested using a case-dropping bootstrap procedure. Node-specific predictive betweenness was computed to examine short paths of anhedonia, other depressive symptoms and anxiety symptoms with suicidality. A Network Comparison Test (NCT) was conducted to examine whether network characteristics differed based on gender.

RESULTS

Prevalence rates of depressive symptoms, anxiety symptoms, and suicidality were 44.60 % (95% confidence interval (CI) = 41.53-47.67 %), 31.12 % (95%CI = 28.26-33.98 %), and 16.95 % (95%CI = 14.63-19.26 %), respectively, in the study sample. The network analysis identified GAD3 ("Worry too much") as the most central symptom, followed by GAD6 ("Irritability") and PHQ6 ("Guilt") in the sample. Additionally, PHQ6 ("Guilt"), GAD6 ("Irritability"), and PHQ2 ("Sad mood") were bridge nodes linking depressive and anxiety symptoms with suicidality. A flow network indicated that the connection between S ("Suicidality") and PHQ6 ("Guilt") reflected the strongest connection, followed by connections of S ("Suicidality") with GAD2 ("Uncontrollable worrying"), and S ("Suicidality") with PHQ2 ("Sad mood"). Finally, PHQ2 ("Sad mood") was the main bridge node linking anhedonia with other depressive and anxiety symptoms and suicidality in the sample.

CONCLUSIONS

Findings highlight the potential importance of reducing specific depressive and anxiety symptoms as possible means of reducing suicidality among adolescents during the pandemic. Central symptoms and key bridge symptoms identified in this study should be targeted in suicide prevention for at-risk adolescents.

Network analysis links adolescent depression with childhood, peer, and family risk environment factors

BACKGROUND

Adolescent mental health is influenced by various adverse environmental conditions. However, it remains unclear how these factors jointly affect adolescent depression. This study aimed to use network analysis to assess the associations between different environmental factors and depressive symptoms in adolescents and to identify key pathways between them.

METHODS

This study included 610 adolescents with depression from inpatient and outpatient units recruited between March 2020 and November 2021. The mean age was 14.86 ± 1.96, with no significant difference between males (n = 155, 15.10 ± 2.19) and females (n = 455, 14.78 ± 1.88). Depressive symptoms were measured using the Children's Depression Inventory, and individual risk environment factors included childhood trauma, social peer and family risk factors. Network features, including network centrality, stability, and bridge centrality, were investigated.

RESULTS

Anhedonia and self-esteem were found to be more central in depressive symptoms. Insult experiences from the social peer and emotional abuse experience from childhood were more central environmental factors. Childhood trauma experiences were more related to adolescent depressive symptoms compared to family and peer factors. Bridge analyses identified emotional abuse, emotional neglect and physical neglect as the main bridges linking environment risk to depressive symptoms.

LIMITATIONS

This was a cross-sectionally designed study, which limited its ability to examine longitudinal dynamic interactions between environmental factors and adolescent depressive symptoms.

CONCLUSIONS

Our findings suggested that childhood trauma experiences might have greater psychological impacts on adolescent depression than family and social peer environments, and should be considered as crucial targets for preventing severe depressive moods.

Psychotic-like experiences as a co-occurring psychopathological indicator of multi-dimensional affective symptoms: Findings from a cross-sectional survey among college students

BACKGROUND

Although connections between psychotic-like experiences (PLEs) and a series of non-psychotic disorders have been widely explored in previous research, it is unclear whether PLEs could act as a co-occurring psychopathological indicator of multi-dimensional affective symptoms.

METHODS

A total of 4761 students took part in an online survey which assessed the frequency of PLEs and three types of affective symptoms over lifetime. Binary logistic regression models were used to examine associations between PLEs and each type of affective symptom. Network analysis was conducted to explore the relationship among three subtypes of PLEs - persecutory ideation (PI), bizarre experiences (BEs) and perceptual abnormalities (PAs), and different types of affective symptoms.

RESULTS

The results showed that compared with the non-PLEs group, the PLEs group suffered significantly higher risk of experiencing three types of affective symptoms, including manic symptoms [adjusted odds ratio (aOR) 11.50, 95 % confidence interval (CI) (4.59-28.81)], depressive symptoms [aOR 7.28, 95 % CI (4.98-10.66)] and anxiety symptoms [aOR 4.47, 95 % CI (3.10-6.43)]. In the network model, bizarre experiences were the most critical central symptom. Both depressive and anxiety symptoms were most strongly associated with persecutory ideation while manic symptoms were most closely related to bizarre experiences.

LIMITATIONS

Cross-sectional data and self-reported symptoms.

CONCLUSIONS

These findings suggest that PLEs are a vital co-occurring indicator of multi-dimensional affective symptoms and show its enormous potential as a target for a host of mental health problems. Further investigation may shed light on the aetiology of the relationship between different subtypes of PLEs and affective symptoms.

Depression and quality of life among Macau residents in the 2022 COVID-19 pandemic wave from the perspective of network analysis

Background

In the summer of 2022, Macau experienced a surge of COVID-19 infections (the 618 COVID-19 wave), which had serious effects on mental health and quality of life (QoL). However, there is scant research on mental health problems and QoL among Macau residents during the 618 COVID-19 wave. This study examined the network structure of depressive symptoms (hereafter depression), and the interconnection between different depressive symptoms and QoL among Macau residents during this period.

Method

A cross-sectional study was conducted between 26th July and 9th September 2022. Depressive symptoms were measured with the 9-item Patient Health Questionnaire (PHQ-9), while the global QoL was measured with the two items of the World Health Organization Quality of Life-brief version (WHOQOL-BREF). Correlates of depression were explored using univariate and multivariate analyses. The association between depression and QoL was investigated using analysis of covariance (ANCOVA). Network analysis was used to evaluate the structure of depression. The centrality index "Expected Influence" (EI) was used to identify the most central symptoms and the flow function was used to identify depressive symptoms that had a direct bearing on QoL.

Results

A total 1,008 participants were included in this study. The overall prevalence of depression was 62.5% (n = 630; 95% CI = 60.00-65.00%). Having depression was significantly associated with younger age (OR = 0.970; p < 0.001), anxiety (OR = 1.515; p < 0.001), fatigue (OR = 1.338; p < 0.001), and economic loss (OR = 1.933; p = 0.026). Participants with depression had lower QoL F (1, 1,008) =5.538, p = 0.019). The most central symptoms included PHQ2 ("Sad Mood") (EI: 1.044), PHQ4 ("Fatigue") (EI: 1.016), and PHQ6 ("Guilt") (EI: 0.975) in the depression network model, while PHQ4 ("Fatigue"), PHQ9 ("Suicide"), and PHQ6 ("Guilt") had strong negative associations with QoL.

Conclusion

Depression was common among Macao residents during the 618 COVID-19 wave. Given the negative impact of depression on QoL, interventions targeting central symptoms identified in the network model (e.g., cognitive behavioral therapy) should be developed and implemented for Macau residents with depression.

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.

Suicide spectrum among young people during the COVID-19 pandemic: A systematic review and meta-analysis

BACKGROUND

There are concerns that suicidal behaviors are arising among adolescents. The COVID-19 pandemic could have worsened the picture, however, studies on this topic reported contrasting results. This work aimed to summarise findings from the worldwide emerging literature on the rates of suicidality among young people during the COVID-19 pandemic.

METHODS

A systematic review and meta-analysis were performed, searching five electronic databases for studies published from January 1, 2020 until July 27, 2022. Studies reporting rates for each of the three considered outcomes (suicide, suicidal behaviors, and suicidal ideation) among young people under 19 years old during the COVID-19 pandemic were included. Random-effects meta-analyses were conducted, and the intra-study risk of bias was assessed. When pre-COVID-19 data were available, incidence rate ratio (IRR) and prevalence ratio (PR) estimates were calculated between the two periods. All the analyses were performed according to the setting explored: general population, emergency department (ED), and psychiatric services. The review protocol was registered on PROSPERO (CRD42022308014).

FINDINGS

Forty-seven observational studies were selected for more than 65 million subjects. The results of the meta-analysis showed a pooled annual incidence rate of suicides of 4.9 cases/100,000 during 2020, accounting for a non-statistically significant increase of 10% compared to 2019 (IRR 1.10, 95% CI: 0.94-1.29). The suicidal behaviors pooled prevalence during the COVID-19 pandemic was higher in the psychiatric setting (25%; 95% CI: 17-36%) than in the general population (3%; 1-13%) and ED (1%; 0-9%). The pooled rate of suicidal ideation was 17% in the general population (11-25%), 36% in psychiatric setting (20-56%) and 2% in ED (0-12%). The heterogeneity level was over 97% for both outcomes in all settings considered. The comparison between before and during COVID-19 periods highlighted a non-statistically significant upward trend in suicidal behaviors among the general population and in ED setting. The only significant increase was found for suicidal ideation in psychiatric setting among studies conducted in 2021 (PR 1.15; 95% CI: 1.04-1.27), not observed exploring 2020 alone.

INTERPRETATION

During the pandemic, suicide spectrum issues seemed to follow the known pattern described in previous studies, with higher rates of suicidal ideation than of suicidal behaviors and suicide events. Governments and other stakeholders should be mindful that youth may have unique risks at the outset of large disasters like the COVID-19 pandemic and proactive steps are necessary to address the needs of youth to mitigate those risks.

FUNDING

The present study was funded by the University of Torino (CHAL_RILO_21_01).

A network analysis of anxiety and depression symptoms among Chinese nurses in the late stage of the COVID-19 pandemic

Background

Nurses are at high risk for depression and anxiety symptoms after the outbreak of the COVID-19 pandemic. We aimed to assess the network structure of anxiety and depression symptoms among Chinese nurses in the late stage of this pandemic.

Method

A total of 6,183 nurses were recruited across China from Oct 2020 to Apr 2021 through snowball sampling. We used Patient Health Questionnaire-9 (PHQ-9) and Generalized Anxiety Disorder scale-7 (GAD-7) to assess depression and anxiety, respectively. We used the Ising model to estimate the network. The index "expected influence" and "bridge expected influence" were applied to determine the central symptoms and bridge symptoms of the anxiety-depression network. We tested the stability and accuracy of the network via the case-dropping procedure and non-parametric bootstrapping procedure.

Result

The network had excellent stability and accuracy. Central symptoms included "restlessness", "trouble relaxing", "sad mood", and "uncontrollable worry". "Restlessness", "nervous", and "suicidal thoughts" served as bridge symptoms.

Conclusion

Restlessness emerged as the strongest central and bridge symptom in the anxiety-depression network of nurses. Intervention on depression and anxiety symptoms in nurses should prioritize this symptom.

Network Analysis of Comorbid Anxiety and Insomnia Among Clinicians with Depressive Symptoms During the Late Stage of the COVID-19 Pandemic: A Cross-Sectional Study

BACKGROUND

A high proportion of clinicians experienced common anxiety, insomnia and depression during the COVID-19 pandemic. This study examined the item-level association of comorbid anxiety and insomnia symptoms among clinicians who suffered from depressive symptoms during the late stage of the COVID-19 pandemic using network analysis (NA).

METHODS

Clinicians with depressive symptoms (with a Patients Health Questionnaire (PHQ-9) total score of 5 and above) were included in this study. Anxiety and insomnia symptoms were measured using the Generalized Anxiety Disorder Scale - 7-item (GAD-7) and Insomnia Severity Index (ISI), respectively. Network analysis was conducted to investigate the network structure, central symptoms, bridge symptoms, and network stability of these disturbances. Expected influence (EI) was used to measure the centrality of index.

RESULTS

Altogether, 1729 clinicians were included in this study. The mean age was 37.1 [standard deviation (SD)=8.04 years], while the mean PHQ-9 total score was 8.42 (SD=3.33), mean GAD-7 total score was 6.45 (SD=3.13) and mean ISI total score was 8.23 (SD=5.26). Of these clinicians, the prevalence of comorbid anxiety symptoms (GAD-7≥5) was 76.8% (95% CI 74.82-78.80%), while the prevalence of comorbid insomnia symptoms (ISI≥8) was 43.8% (95% CI: 41.50-46.18%). NA revealed that nodes ISI7 ("Interference with daytime functioning") (EI=1.18), ISI4 ("Sleep dissatisfaction") (EI=1.08) and ISI5 ("Noticeability of sleep problem by others") (EI=1.07) were the most central (influential) symptoms in the network model of comorbid anxiety and insomnia symptoms in clinicians. Bridge symptoms included nodes PHQ3 ("Sleep") (bridge EI=0.55) and PHQ4 ("Fatigue") (bridge EI=0.49). Gender did not significantly influence the network structure, but "having the experience of caring for COVID-19 patients" significantly influenced the network structure.

CONCLUSION

Central symptoms and key bridge symptoms identified in this NA should be targeted in the treatment and preventive measures for clinicians suffering from comorbid anxiety, insomnia and depressive symptoms during the late stage of the COVID-19 pandemic.