Mental disorders as networks of problems: a review of recent insights

Pixels and perception: Mapping the association between digital media and psychotic-like experiences in adolescents

INTRODUCTION

Psychotic-like experiences (PLEs) during adolescence can lead to psychotic disorders. Digital media usage has been suggested to link to PLEs, but research is limited on how different types of screen exposure may differentially relate to PLEs over time. This study aimed to examine longitudinal associations between screen usage patterns and PLEs in adolescents.

METHODS

Participants comprised 11,876 adolescents assessed annually from ages 9-12 years as part of the Adolescent Brain Cognitive Development study (ABCD). Screen usage (TV, video games, online video, social media, texting, video chat) and PLEs were assessed via self-report. Longitudinal network analysis models were estimated to examine connections between screen usage types and PLEs across three time points.

RESULTS

Two clusters were formed, including digital media for socializing (e.g., social media/texting/video chat) and digital media for entertainment (e.g., online video/video games/TV). Texting and online video(s) had the highest centrality at each time point, suggesting importance in the network. PLE symptoms of hallucinations and concentration difficulties exhibited higher centrality than other symptoms. Online video and TV were influential bridges between screen usage and PLEs. Network structure significantly differed between ages 9-10 and 10-12 years, but global strength was unchanged over time.

DISCUSSION

Results highlight the importance of understanding the associations between specific screen usage types and PLE symptoms. Texting and online video usage appear most influential in the development of adolescent PLEs over time. Findings can inform targeted interventions to promote healthy screen habits and reduce PLEs in at-risk youth.

Characteristics of symptoms and development of psychological status in late Chinese adolescence

BACKGROUND

Many late adolescents experience a state of psychological sub-health, requiring early recognition and intervention. This study aims to assess the psychological state of late Chinese adolescents and uncover developmental trend of mental health through network analysis.

METHOD

We analyzed data from 9072 Chinese high school adolescents in Shandong Province surveyed in 2020-2021, and divided them into the normal, the suspected, and the abnormal groups based on Symptom Checklist 90 (SCL-90) scores. Network analysis was employed to identify the core symptoms and bridge symptoms across different states.

RESULTS

Anxiety and depression were the most central symptoms, without gender differences. Core symptoms, network structure, and network invulnerability varied across different psychological states. The abnormal group exhibited the highest value of natural connectivity, followed by the suspected and normal groups. This pattern extended to bridge networks. While not meeting diagnostic criteria, the suspected group demonstrated abnormalities in network edge invariance and global strength invariance.

LIMITATIONS

The cross-sectional design cannot establish causality, and biases in self-report measurements cannot be ignored.

CONCLUSION

Compared to traditional scale indicators, network structural characteristics may be a more sensitive assessment indicator.

The cross-sectional and longitudinal interconnectedness of physical, psychological and role functioning following physical trauma: A network analysis

OBJECTIVE

Surviving physical trauma can have a large impact on one's daily life. Patients are at increased risk for poor physical health, psychological complaints, and problems in role functioning - which is often experienced simultaneously. The present study explores the interconnectedness of physical, psychological, and role functioning during the first two years post-injury, both cross-sectionally and longitudinally from a network perspective.

METHODS

3785 trauma patients (Mage = 64.2 years, SDage = 18.9 years, 50.5% female) completed questionnaires on physical, psychological, and role functioning across six measurement occasions during the first two years post-injury. The Injury Severity Score (ISS) was retrieved from the local trauma registry. Mixed graphical network models and cross-lagged network models were estimated to examine which items of recovery played a central role and were mostly related to other items in cross-sectional and longitudinal networks respectively.

RESULTS

The cross-sectional networks showed especially strong interconnections between impairments of physical and role functioning and also within post-traumatic stress symptoms. The longitudinal networks extended these results by showing that pain, impaired mobility, limitations in self-care, anxiety/depressive symptoms, and several post-traumatic stress symptoms were strong predictors for impairments in functioning at later stages of recovery.

CONCLUSION

Our findings showed that impairments in physical, psychological, and role functioning experienced by trauma patients are largely intertwined across the two years following injury. Monitoring physical impairments and psychological complaints early in recovery might help to more promptly provide the best fitting aftercare for trauma patients, which can improve recovery on the long-term.

The association of impulsivity with depression and anxiety symptoms: A transdiagnostic network analysis and replication

BACKGROUND

Impulsivity increases the risk for depression and anxiety. However, the granular pathways among them remain unknown. A network approach that moves from disorder-level analysis to symptom-level analysis can provide further understanding of psychopathological mechanisms. In this study, we examined the network structure of impulsivity and separate and comorbid symptoms of depression and anxiety.

METHODS

Regularized partial-correlation networks were estimated using cross-sectional data from 1047 Chinese participants aged 18-26 years (main dataset, mean age = 21.45 ± 2.01 years) and 325 Chinese participants aged 18-36 years (an independent replication dataset, mean age = 21.49 ± 3.73 years), including impulsivity-depression, impulsivity-anxiety, and impulsivity-depression-anxiety networks. The datasets were collected from 1 June 2023 to 4 August 2023 and from 27 April 2022 to 16 May 2022, respectively. Impulsivity, depression, and anxiety were assessed using Barratt Impulsiveness Scale Version 11, Patient Health Questionnaire-9, and Generalized Anxiety Disorder-7, respectively. Bridge centrality was analyzed, and a network comparison test (NCT) was conducted to investigate the differences between the main dataset and replication dataset.

RESULTS

The motor impulsivity dimension was revealed to be closely connected with individual symptoms of depression and anxiety regardless of whether they were in separate disorder forms or comorbid forms. In all the networks, motor impulsivity was the most important bridge node. The NCT showed comparable network connectivity and network structure between the main and replication datasets.

LIMITATIONS

The use of cross-sectional data limited the inferences about the direction of causality between variables.

CONCLUSIONS

These findings elucidate the psychopathological mechanisms underlying how impulsivity functions within depression, anxiety, and comorbidity and support that motor impulsivity is an important risk factor across different mental disorders and is responsible for comorbidity. The implications of these findings are discussed.

Psychopathology of cognitive disengagement syndrome (CDS): a network analysis based on CBCL scales in 72,106 Chinese school students

Cognitive Disengagement Syndrome (CDS) is a cluster of behavioral problems that severely affect an individual's functioning. Currently, there is no consensus on the main clinical features of CDS, and further exploration in large samples is needed. Using a cluster-stratified random sampling method, 72,106 children and adolescents were recruited from five provinces in mainland China for this study. Using both the traditional two-factor scoring method and the CBCL DSM-oriented scales, we assessed individual behavioral problems from psychopathological and DSM-oriented perspectives. Network analysis was employed to explore the relationship between CDS and behavioral problems. The various networks were compared by gender and age subgroups. Among 72,106 participants (mean age, 11.49 years; minimum age, 5 years; maximum age, 16 years), there were 36,449 males (50.5%) and 35,657 females (49.5%). From a psychopathological perspective, the motor symptoms node was associated with the sad node and the withdrawn node, while the cognitive symptoms node was linked to the nervous node and the self-conscious node. In terms of gender, males had stronger associations of the motor symptoms node with the sad node and the withdrawn node than females (P = 0.043), and weaker associations of the cognitive symptoms node with the nervous node than females (P = 0.027). In terms of growth stage, the adolescent group had stronger associations of the cognitive symptoms node with the nervous node and the self-conscious node than the child group (P = 0.016, 0.001). From DSM perspective, motor symptoms node were associated with sad node, and cognitive symptoms node were related to can't concentrate node, nervous node, and worthless node. With increasing age, there was an upward trend in the strength of the cognitive and motor symptoms node. CDS is closely linked to psychological and behavioral issues, especially internalizing problems, with differences observed by gender and growth stage. The connection between CDS and the affective, anxiety, and ADH symptoms is particularly pronounced.

Monozygotic twins discordant for depression: An extended network comparison of depressive symptoms, cognitive functions and daily activities

Monozygotic twins share the same genotype; however, they can be phenotypically discordant on various traits. Studying discordant monozygotic twins allows the investigation of differences in associations between symptoms and psychopathological risk factors, controlled for shared genetic liability. The network approach to psychopathology suggests that depressive symptoms, along with risk and protective factors (e.g., cognition, daily activities), form a complex system of mutually interacting components. We compared monozygotic twins discordant for lifetime depression on their respective extended networks of depressive symptoms, cognitive functions and daily activities (intellectual, physical, social), and evaluated if these networks differ in their associations between variables and in the role of each variable within the network. Regularized partial correlations investigated the networks' composition in 147 monozygotic twin pairs discordant for depression from the Danish Twin Registry. Affected twins had stronger overall associations within their network of depressive symptoms, cognitive functions and daily activities than their unaffected co-twins, while the importance of the network components' associations did not differ between the co-twins. In affected twins, decreased frequency in experiencing happiness had the strongest association with remaining variables (i.e., the most influence in activating other network elements). Also, variables from different groups were significantly associated (e.g., loneliness with delayed memory, pessimism with low social activities, verbal learning with intellectual activities). In unaffected twins, both mood symptoms and cognitive functions were important, but between-groups associations were quasi-absent. These results suggest that external events affecting the ability to feel happiness likely trigger the psychopathological process (depression network activation), independently from the genetic predisposition to depression.

Module control of network analysis in psychopathology

The network approach to characterizing psychopathology departs from traditional latent categorical and dimensional approaches. Causal interplay among symptoms contributed to dynamic psychopathology system. Therefore, analyzing the symptom clusters is critical for understanding mental disorders. Furthermore, despite extensive research studying the topological features of symptom networks, the control relationships between symptoms remain largely unclear. Here, we present a novel systematizing concept, module control, to analyze the control principle of the symptom network at a module level. We introduce Module Control Network (MCN) to identify key modules that regulate the network's behavior. By applying our approach to a multivariate psychological dataset, we discover that non-emotional modules, such as sleep-related and stress-related modules, are the primary controlling modules in the symptom network. Our findings indicate that module control can expose central symptom cluster governing psychopathology network, offering novel insights into the underlying mechanisms of mental disorders and individualized approach to psychological interventions.

The relationship between psychological distress and cognitive failure among breast cancer survivors: a network analysis

Background

Psychological distress is highly prevalent and has a severe impact on the quality of life among breast cancer survivors. This type of distress is associated with cognitive failure. However, previous studies have focused solely on the total scale scores of these two concepts while ignoring the unique relationship between specific components. In the present study, we utilized network analysis to explore the relationship between psychological distress and cognitive failure in breast cancer survivors.

Methods

The network analysis approach was adopted to estimate the regularized partial correlation network in a cross-sectional sample of 409 breast cancer survivors. All participants were assessed using the Depression Anxiety Stress Scale and the Cognitive Failure Questionnaire. The Gaussian Graphical Model was employed to estimate the network, centrality indices, and edge weights, providing a description of the characteristics of the network.

Results

The results indicated that anxiety-stress and depression-stress were the strongest edges in the community of psychological distress. Distractibility-memory was the strongest edge in the community of cognitive failure. Distractibility and memory were the most central nodes, with the highest expected influence in the network. Depression and motor coordination acted as important bridge nodes with the highest bridge expected influence.

Conclusion

Distractibility and memory in cognitive failure played important roles in activating and maintaining the relationship network. Motor coordination was identified as the crucial pathway for the impact of cognitive failure on psychological distress. Interventions targeting these specific issues might be more effective in improving cognitive failure and reducing psychological distress among breast cancer survivors.

Network analysis of trait aggression among community youths and juvenile offenders

OBJECTIVE

The mainstream view in trait aggression research has regarded the structure as representing the latent cause of the cognitions, emotions, and behaviors that supposedly reflect its nature. Under network perspective, trait aggression is not a latent cause of its features but a dynamic system of interacting elements. The current study uses network theory to explain the structure of relationships between trait aggression features in juvenile offenders and their peers.

METHODS

Network analysis was applied to investigate the dynamic system of trait aggression operationalized by the Buss-Perry Aggression Questionnaire in a sample of community youths (Mage = 17.46, N = 715) and juvenile offenders (Mage = 18.36, N = 834).

RESULTS

The facet level networks showed that anger is a particularly effective mechanism for activating all other traits. In addition, anger was more strongly associated with physical aggression and the overall network strength was greater in juvenile delinquency networks than in their peers. The item level networks revealed that A4 and A6 exhibited the highest predictability and strength centrality in both samples. Also, the Bayesian network indicated that these two items were positioned at the highest level in the model. There are similarities and differences between juvenile delinquents and community adolescents in trait aggression.

CONCLUSION

Trait aggression was primarily activated by difficulty controlling one's temper and feeling like a powder keg.

A Note on Ising Network Analysis with Missing Data

The Ising model has become a popular psychometric model for analyzing item response data. The statistical inference of the Ising model is typically carried out via a pseudo-likelihood, as the standard likelihood approach suffers from a high computational cost when there are many variables (i.e., items). Unfortunately, the presence of missing values can hinder the use of pseudo-likelihood, and a listwise deletion approach for missing data treatment may introduce a substantial bias into the estimation and sometimes yield misleading interpretations. This paper proposes a conditional Bayesian framework for Ising network analysis with missing data, which integrates a pseudo-likelihood approach with iterative data imputation. An asymptotic theory is established for the method. Furthermore, a computationally efficient Pólya-Gamma data augmentation procedure is proposed to streamline the sampling of model parameters. The method's performance is shown through simulations and a real-world application to data on major depressive and generalized anxiety disorders from the National Epidemiological Survey on Alcohol and Related Conditions (NESARC).

Exploring the interplay between core and mood symptoms in schizophrenia: A network analysis

BACKGROUND

Schizophrenia is a complex neuropsychiatric disorder characterized by positive symptoms, negative symptoms, cognitive deficits, and co-occurring mood symptoms. Network analysis offers a novel approach to investigate the intricate relationships between these symptom dimensions, potentially informing personalized treatment strategies.

METHODS

A cross-sectional study was conducted from November 2019 to October 2021, involving 1285 inpatients with schizophrenia in Liaoning Province, China. Symptom severity was assessed using the Positive and Negative Syndrome Scale (PANSS), Hamilton Depression Rating Scale (HAMD-17), Hamilton Anxiety Rating Scale (HAMA-14), and Montreal Cognitive Assessment (MoCA). Network analysis was conducted to investigate the network structure, central symptoms, and bridge symptoms.

RESULTS

The network analysis uncovered profound interconnectivity between core symptoms and the anxiety-depression community. Central symptoms, such as psychic anxiety, poor rapport, delusions, and attention, were identified as potential therapeutic targets. Bridge symptoms, including insomnia, depressed mood, anxiety-somatic, conceptual disorganization, and stereotyped thinking, emerged as key nodes facilitating interactions between symptom communities. The stability and reliability of the networks were confirmed through bootstrapping procedures.

DISCUSSION

The findings highlight the complex interplay between schizophrenia symptoms, emphasizing the importance of targeting affective symptoms and cognitive impairment in treatment. The identification of central and bridge symptoms suggests potential pathways for personalized interventions aimed at disrupting self-reinforcing symptom cycles. The study underscores the need for a transdiagnostic, personalized approach to schizophrenia treatment.

Exploring mental health dynamics during eating disorder treatment: A psychometric network study with panel data

To explore mental health associations during eating disorder (ED) treatment. Based on the dual-continua model of mental health, general and ED-specific psychopathology, as well as emotional, psychological, and social well-being were considered as mental health domains.

Network analyses with panel data were applied to explore within- (temporal and contemporaneous networks) and between-person effects in a sample of 1250 female ED patients during 12 months of outpatient treatment. The associations between the domains and their centrality were examined. Autoregressive and cross-lagged effects were also estimated.

ED psychopathology was the most central domain in the temporal network. ED psychopathology changes predicted further ED psychopathology changes and small changes in the other domains. Weak bi-directional associations were found between changes in the well-being domains and general psychopathology. In contrast to the temporal network, ED psychopathology was the least central and psychological well-being the most central domain in the contemporaneous and between-subjects networks. This suggests a central role of psychological well-being for experiencing mental health within time points.

ED psychopathology may change relatively independent from other mental health domains. Well-being domains may be considered as more stable aspects of mental health.

Exploring the Association of Age with Depressive Symptomatology in Childhood and Adolescence: A Network Study

OBJECTIVE

This study aimed to explore the association of age with individual depression and anxiety symptoms and their connectivity (i.e., number/strength of connections with other symptoms) in girls and boys.

METHOD

Our study comprised cross-sectional data from 31,960 Dutch girls and 32,162 Dutch boys aged 8 to 18 and considered 11 depression symptoms and 14 anxiety symptoms measured by the Revised Child Anxiety and Depression Scale. Network estimations were used to examine whether age was associated with individual symptoms and, in a separate step, with the connectivity of depression symptoms with other depression symptoms and with the connectivity of depression symptoms with anxiety symptoms.

RESULTS

Age was, in general, positively associated with depression symptoms in girls, but not in boys, and with the connectivity of depression symptoms with other depression symptoms in both sexes. These findings were the most profound for energy-related symptoms in girls. Age was, in general, negatively associated with anxiety symptoms and not or negatively associated with the connectivity of depression symptoms with anxiety symptoms in girls and boys, respectively. Substantial differences across symptoms were found.

CONCLUSIONS

This study shows that it is important to focus on individual symptoms, for age is mainly associated with energy-related depression symptoms and their connectivity in girls. Future etiologic studies may examine the role of energy-related depression symptoms in the development of depressive symptomatology in girls as these symptoms seem potential targets for the prevention of depression in the female population.

Putting the Vicious Cycle to the Test: Evidence for the Cognitive Behavioral Model of Persistent Somatic Symptoms From an Online Study

OBJECTIVE

In clinical practice, persistent somatic symptoms are regularly explained using a cognitive-behavioral model (CBM). In the CBM, predisposing, perpetuating, and precipitating factors are assumed to interact and to cause the onset and endurance of somatic symptoms. However, these models are rarely investigated in their entirety.

METHODS

We conducted an online survey during the COVID-19 pandemic. A total of 2114 participants from the general German population completed questionnaires that measured different factors of the CBM. We used state negative affectivity and neuroticism as predisposing factors, fear of a COVID-19 infection as the precipitating factor, and somatic symptoms, misinterpretation of bodily symptoms, attention allocation to bodily symptoms, and health anxiety as perpetuating factors. Moreover, we added safety and avoidance behavior as end points to the model. We conducted a psychological network analysis to exploratively study the relationships between the model's different factors and tested the assumptions of the CBM by evaluating a structural equation model (SEM) that incorporated all factors of the model.

RESULTS

Network analyses revealed clustering in our data: Health anxiety and different cognitive factors are closely related, whereas somatic symptoms and state negative affectivity are strongly associated. Our SEM showed adequate fit.

CONCLUSIONS

Our findings from an exploratory and a confirmatory approach give empirical support for the CBM, suggesting it as a suitable model to explain bodily symptoms in the general population and to possibly guide clinical practice. The network model additionally indicates the necessity to apply an individualized CBM for patients, depending on a preponderance of either persistent somatic symptoms or health concerns.

Exploring the Co-Occurrence of Depressive Symptoms and Aggression among Chinese Adolescents: Patterns and Stability

Depressive symptoms and aggression frequently occur together, and this co-occurrence may result in more severe developmental problems. However, it is unclear if there are distinct patterns of co-occurrence. This study investigated the co-occurrence patterns of depressive symptoms and aggression, and examined their stability and demographic characteristics. A total of 1010 Chinese adolescents (50.6% girls; mean age at T1 = 12.54 years, SD = 0.42) participated in annual surveys over three years (2019-2021). Three different patterns of co-occurrence were found except for the normal group: depression-dominant co-occurrence (13.6%), aggression-dominant co-occurrence (3.2%), and moderate co-occurrence (6.0%) (T1). In these co-occurrence patterns, adolescents classified as aggression-dominant co-occurrence exhibited the most instability and frequent changes, while adolescents classified as depression-dominant co-occurrence exhibited the most stability. Boys or younger adolescents were more likely to exhibit the aggression-dominant co-occurrence, while girls or older adolescents were more likely to exhibit the depression-dominant co-occurrence. The findings indicate that the co-occurrence patterns observed are distinct and are dominated by aggression or depression, which implies the need for targeted intervention practices.

Social activities and depressive symptoms among migrant middle-aged and older adults in China: a network analysis

Background

This study investigated the central symptom within the depression network and examined the relationship between social activities and depressive symptoms among migrant middle-aged and older adults in China.

Methods

We analyzed data from 1,926 migrants aged 45 and older, derived from the 2018 China Health and Retirement Longitudinal Study (CHARLS). Using network analysis, we identified the central depressive symptom and assessed the association between various social activities and depressive symptoms.

Results

Network analysis revealed that depressed mood was the most central symptom. Regarding mitigation of depressive symptoms, informal social activities predominantly influenced positive emotions and somatic symptoms. Formal activities were mainly revealed through positive emotions. Solitary activities were manifested primarily through positive emotions and somatic symptoms. In addition, informal and solitary activities showed a stronger correlation with the alleviation of depressive symptoms compared to formal activities.

Conclusion

The findings underscore the importance of addressing depressed mood in treating depression among migrant middle-aged and older adults. Recognizing the differential impacts of various social activities can aid in the development of customized prevention and intervention strategies aimed at enhancing the mental well-being of this demographic in China.

Are There Differences Among Evidence-Based Psychotherapies for Treating Different DSM-5 PTSD Symptom Clusters? A Systematic Review and Meta-analysis of Controlled Clinical Trials

ABSTRACT

Posttraumatic stress disorder (PTSD) is a heterogeneous disease defined by four Diagnostic and Statistical Manual of Mental Disorders, 5th Edition (DSM-5) symptom clusters: reexperiencing, avoidance, negative alterations in cognitions and mood, and hyperarousal. There are effective evidence-based psychotherapies (EBPs) for PTSD. However, given the variety of PTSD clinical presentations, we conducted the first meta-analysis investigating whether DSM-5 PTSD symptom clusters show different responses to EBPs. We systematically reviewed the literature for controlled clinical trials in five databases, performed a meta-analysis, and evaluated the methodological quality of the studies. We screened 633 studies and included seven. Three showed high risk, two showed some concerns, and one showed a low risk of bias. The symptom clusters do not seem to respond differently to EBPs (SMD cluster B: -0.40; 95% confidence interval [CI], -0.87 to 0.08; cluster C: -0.49; 95% CI, -0.90 to -0.08; cluster D: -0.44; 95% CI, -0.94 to 0.05; cluster E: -0.54; 95% CI, -1.07 to -0.0), even when analyzed by the therapeutic focuses. The findings dovetail nicely with the network theory of PTSD symptom, as although it is a heterogeneous disorder, the EBPs seem to promote a kind of cascade of symptom improvement.

Maternal antenatal mental health and its associations with perinatal outcomes and the use of healthcare services in children from the NINFEA birth cohort study

To investigate the associations between maternal mental health disorders before and during pregnancy and perinatal outcomes and child healthcare utilization between 6 and 18 months of age. Among the 6814 mother-child pairs from the Italian Internet-based NINFEA birth cohort, maternal depression, anxiety, and sleep disorders diagnosed by a physician before and during pregnancy were assessed through self-reported questionnaires completed during pregnancy and 6 months after delivery. Perinatal outcomes (preterm birth, birth weight, small for gestational age, congenital anomalies, and neonatal intensive care unit (NICU)) and children's healthcare utilization (emergency department (ED) visits, hospitalizations, and outpatient visits) were reported by mothers at 6 and 18 months postpartum. We used regression models adjusted for maternal age, education, parity, country of birth, region of delivery, and household income. Maternal mental health disorders were not associated with perinatal outcomes, except for depression, which increased the risk of offspring admission to NICU, and anxiety disorders during pregnancy, which were associated with preterm birth and lower birth weight. Children born to mothers with depression/anxiety disorders before pregnancy, compared to children of mothers without these disorders, had an increased odds of a visit to ED for any reason (odds ratio (ORadj) = 1.26, 95% confidence interval (CI): 1.02-1.54), of an ED visit resulting in hospitalization (ORadj = 1.75, 95%CI: 1.27-2.42), and of planned hospital admissions (ORadj = 1.55, 95%CI: 1.01-2.40). These associations with healthcare utilization were similar for mental disorders also during pregnancy. The association pattern of maternal sleep disorders with perinatal outcomes and child healthcare utilization resembled that of maternal depression and/or anxiety disorders with these outcomes.   Conclusion: Antenatal maternal mental health is a potential risk factor for child-health outcomes and healthcare use. Early maternal mental health interventions may help to promote child health and reduce healthcare costs. What is Known: • Poor maternal mental health affects pregnancy outcomes and child health, and children of mothers with mental health conditions tend to have increased healtcare utilization. • Parents with poor mental health often face challenges in caring for their children and have less parenting self-efficacy, which could potentially lead to frequent medical consultations for minor health issues. What is New: • Maternal pre-pregnancy mental disorders were not associated with preterm birth, low birth weight, SGA, and congenital anomalies, except for depression, which increased the risk of offspring admission to NICU. Anxiety disorders during pregnancy were associated with lower birth weight and an increased odds of preterm birth. • Maternal depression and/or anxiety and sleep disorders, both before and during pregnancy, were associated with an increase in children's healthcare utilization between 6 and 18 months of life.

Mild differences in the role of somatic symptoms in depression networks in pregnancy and postpartum: A comparison with women outside peripartum

Depression is one of the most prevalent mental ailments in pregnancy. Many authors have discussed the appropriateness of somatic symptoms for depression assessment in pregnancy and postpartum. However, no study has examined the role of somatic symptoms in networks of pregnant and postpartum women compared to women outside peripartum. Here, we show that somatic symptoms are essential to depression assessment during pregnancy and postpartum. We compared networks of the nine PHQ-9 items across pregnant women (n = 894, Mage = 29.29), women in postpartum (n = 586, Mage = 29.83) and women outside peripartum (n = 1029, Mage = 24.87). While three of the five somatic symptoms in PHQ-9 were more present in pregnant women than in those outside the peripartum, the three networks were highly similar regarding the position of the somatic symptoms and their relation to the emotional-cognitive symptoms. Most depression symptoms in pregnant women were predicted by other depression symptoms to a lesser extent than in postpartum and outside peripartum. Other external variables are therefore needed to explain these sensations in pregnancy. In addition to the incidence of somatic symptoms, practitioners should ask pregnant women about their attributions of these.

Symptom networks in glioma patients: understanding the multidimensionality of symptoms and quality of life

PURPOSE

To comprehend the complex relationship between symptoms and health-related quality of life (HRQoL) in patients with diffuse glioma, we applied symptom network analysis to identify patterns of associations between depression, cognition, brain tumor-related symptoms, and HRQoL. Additionally, we aimed to compare global strength between symptom networks to understand if symptoms are more tightly connected in different subgroups of patients.

METHODS

We included 256 patients and stratified the sample based on disease status (preoperative vs. postoperative), tumor grade (grade II vs. III/IV), and fatigue status (non-fatigued vs. fatigued). For each subgroup of patients, we constructed a symptom network. In these six networks, each node represented a validated subscale of a questionnaire and an edge represented a partial correlation between two nodes. We statistically compared global strength between networks.

RESULTS

Across the six networks, nodes were highly correlated: fatigue severity, depression, and social functioning in particular. We found no differences in GS between the networks based on disease characteristics. However, global strength was lower in the non-fatigued network compared to the fatigued network (5.51 vs. 7.49, p < 0.001).

CONCLUSIONS

Symptoms and HRQoL are highly interrelated in patients with glioma. Interestingly, nodes in the network of fatigued patients were more tightly connected compared to non-fatigued patients.

IMPLICATIONS FOR CANCER SURVIVORS

We introduce symptom networks as a method to understand the multidimensionality of symptoms in glioma. We find a clear association between multiple symptoms and HRQoL, which underlines the need for integrative symptom management targeting fatigue in particular.

Family Environmental Risk and Perceived Stress in Adolescent Depressive Symptoms: A Network Analysis

This study, grounded in the Process-Person-Context-Time framework, investigates the complex interplay of family environmental factors and their influence on adolescent depressive symptoms, focusing on the role of 'perceived stress'. Using network analysis, we examined data from 735 junior high students (52.1% female adolescents) from three provinces in China (Jiangsu, Shandong, and Henan), with an average age of 13.81 ± 0.92 years, ranging from 12 to 16 years, exploring the relationships between depressive symptoms, perceived stress, and seven family risk factors. The analysis identified three distinct communities. The incorporation of perceived stress led to its integration into a community that included depressive symptoms, parental restrictive monitoring, and family economic strain. Perceived stress emerged as the strongest predictor of depressive symptoms, surpassing parental restrictive monitoring. Furthermore, it overtook depressive symptoms as the node with the strongest bridging connection within its community. These findings underscore the importance of interventions targeting both family conditions and the internal processing of these stressors by adolescents, especially in challenging family environments, to mitigate the risk of depression and promote resilience.

Identifying symptom clusters and temporal interconnections in patients with lung tumors after CT-guided microwave ablation: A network analysis

PURPOSE

To explore symptom clusters and interrelationships using a network analysis approach among symptoms in patients with lung tumors who underwent computed tomography (CT)-guided microwave ablation (MWA).

METHODS

A longitudinal study was conducted, and 196 lung tumor patients undergoing MWA were recruited and were measured at 24 h, 48 h, and 72 h after MWA. The Chinese version of the MD Anderson Symptom Inventory and the Revised Lung Cancer Module were used to evaluate symptoms. Network analyses were performed to explore the symptom clusters and interrelationships among symptoms.

RESULTS

Four stable symptom communities were identified within the networks. Distress, weight loss, and chest tightness were the central symptoms. Distress, and weight loss were also the most key bridge symptoms, followed by cough. Three symptom networks were temporally stable in terms of symptom centrality, global connectivity, and network structure.

CONCLUSION

Our findings identified the central symptoms, bridge symptoms, and the stability of symptom networks of patients with lung tumors after MWA. These network results will have important implications for future targeted symptom management intervention development. Future research should focus on developing precise interventions for targeting central symptoms and bridge symptoms to promote patients' health.

How do men and women differ in their depressive symptomatology? A gendered network analysis of depressive symptoms in a French population-based cohort

BACKGROUND

The experience of depressive manifestations and the presentation of symptoms in clinical settings may differ in men and women. Despite the extensive literature, it remains unclear how depressive manifestations interact at symptom levels in men and women. First, we aimed to describe and compare depressive networks by sex. Second, we examined symptom connections to Clinical depression and Functional Limitations as a proxy of self-recognition of a depressive episode.

METHODS

We estimated networks from the 20 CES-D items in men and women from a large population-based French cohort. We computed centrality measures and ran comparisons. Then, we re-estimated two networks in men and women separately, adding, on the one hand, Clinical Depression and, on the other hand, Limitations due to a depressive episode.

RESULTS

Over 200,000 participants were included in this study. Women were twice as likely to have a previous diagnosis of depression. Sex-ratio was less pronounced (1,7:1) for Limitations due to depression. Centrality measures revealed similar symptom patterns. However, network structures differed between men and women. We found some symptom connections to Clinical depression and Limitations to be non-invariant according to sex.

LIMITATIONS

Cross-sectional data does not capture the direction of the connections between symptoms and an eventual diagnosis. We lacked data about the diagnosis's context and could not account for other factors influencing depressive symptomatology.

CONCLUSIONS

Network structures differed, suggesting gender-specific mechanisms in activating symptoms and depressive states. Addressing central symptoms evoking depressed moods with tailored interventions may serve to tackle depressive states in men and women.

Mastery is central: an examination of complex interrelationships between physical health, stress and adaptive cognition, and social connection with depression and anxiety symptoms

Background

Research has established the link between physical health, stress and cognition, and social connection with depression and anxiety. Nevertheless, an understanding of the comorbidity of depression and anxiety symptoms and their complex interrelationships with relevant factors remains still limited. This study investigated the complex pattern of interplay between depression and anxiety symptoms and pertinent physical, cognitive, and social factors and potential gender differences.

Methods

Using a sample of 600 middle-aged men and women, depression and anxiety as well as physical health, perceived stress and mastery, and social connection were assessed. The network structure of depression and anxiety symptoms and risk and resilience factors were characterized by examining interrelationships and the centrality indices of Strength and Bridge Strength. Gender differences were examined using the Network Comparison Test.

Results

Perceived stress and mastery were central bridge factors influencing comorbid depression and anxiety symptoms, and perceived stress, anhedonia, and mastery exhibited strong inter-connections to each other. The connections of physical health-anhedonia and sleep disturbance-irritability were stronger in men than in women, while social connection with family was linked to interpersonal problems only in women.

Conclusions

The results underscore that prevention and interventions targeting reducing perceptions of stress and promoting mastery would prevent onset or recurrence of depression and anxiety symptoms among middle-aged men and women. Engaging in behavioral activities to maintain physical health and ensuring adequate sleep could be particularly beneficial for men in reducing overall symptom severity.

Dopaminergic Modulation and Computational ADMET Insights for the Antidepressant-like Effect of N-(3-(Phenylselanyl)prop-2-yn-1-yl)benzamide

The compound N-(3-(phenylselanyl)prop-2-yn-1-yl)benzamide (SePB), which combines a selenium atom and a benzamide nucleus in an organic structure, has demonstrated a fast antidepressant-like effect in mice. This action is influenced by the serotonergic system and represents a promising development in the search for novel antidepressant drugs to treat major depressive disorder (MDD), which often resists conventional treatments. This study aimed to further explore the mechanism underlying the antidepressant-like effect of SePB by investigating the involvement of the dopaminergic and noradrenergic systems in the tail suspension test (TST) in mice and evaluating its pharmacokinetic profile in silico. Preadministration of the dopaminergic antagonists haloperidol (0.05 mg/kg, intraperitoneally (i.p.)), a nonselective antagonist of dopamine (DA) receptors, SCH23390 (0.01 mg/kg, subcutaneously (s.c.)), a D1 receptor antagonist, and sulpiride (50 mg/kg, i.p.), a D2/3 receptor antagonist, before SePB (10 mg/kg, intragastrically (i.g.)) prevented the anti-immobility effect of SePB in the TST, demonstrating that these receptors are involved in the antidepressant-like effect of SePB. Administration of the noradrenergic antagonists prazosin (1 mg/kg, i.p.), an α1-adrenergic antagonist, yohimbine (1 mg/kg, i.p.), an α2-adrenergic antagonist, and propranolol (2 mg/kg, i.p.), a β-adrenergic antagonist, did not block the antidepressant-like effect of SePB on TST, indicating that noradrenergic receptors are not involved in this effect. Additionally, the coadministration of SePB and bupropion (a noradrenaline/dopamine reuptake inhibitor) at subeffective doses (0.1 and 3 mg/kg, respectively) produced antidepressant-like effects. SePB also demonstrated good oral bioavailability and low toxicity in computational absorption, distribution, metabolism, excretion, and toxicity (ADMET) analyses. These findings suggest that SePB has potential as a new antidepressant drug candidate with a particular focus on the dopaminergic system.

The "central" importance of loneliness in mental health: A network psychometric study

Loneliness is linked to negative mental health outcomes like depression and social anxiety. However, it is unclear how loneliness and these conditions are connected. This study aims to address two questions: (a) Are there pathways connecting loneliness to these conditions? (b) What symptoms play a role in these pathways? Using network analyses, the study examined a representative sample of 962 adults from the UK (mean age = 46, females = 492). The network analysis revealed four dimensions: depression, social anxiety and two dimensions for loneliness (isolation and social connectedness). Two distinct pathways were identified for the transmission of symptoms between loneliness, social anxiety and depression. The depression-isolation pathway involved a node representing the perceived loss of social connections. The social anxiety-social connectedness pathway was characterised by intimate interaction contexts. These findings suggest that loneliness is associated with different symptom pathways, potentially contributing to comorbidity between loneliness, social anxiety and depression.

Investigating change in network structure of eating disorder symptoms after delivery of a smartphone app-based intervention

BACKGROUND

Eating disorder (ED) research has embraced a network perspective of psychopathology, which proposes that psychiatric disorders can be conceptualized as a complex system of interacting symptoms. However, existing intervention studies using the network perspective have failed to find that symptom reductions coincide with reductions in strength of associations among these symptoms. We propose that this may reflect failure of alignment between network theory and study design and analysis. We offer hypotheses for specific symptom associations expected to be disrupted by an app-based intervention, and test sensitivity of a range of statistical metrics for identifying this intervention-induced disruption.

METHODS

Data were analyzed from individuals with recurrent binge eating who participated in a randomized controlled trial of a cognitive-behavioral smartphone application. Participants were categorized into one of three groups: waitlist (n = 155), intervention responder (n = 49), and intervention non-responder (n = 77). Several statistical tests (bivariate associations, network-derived strength statistics, network invariance tests) were compared in ability to identify change in network structure.

RESULTS

Hypothesized disruption to specific symptom associations was observed through change in bivariate correlations from baseline to post-intervention among the responder group but were not evident from symptom and whole-of-network based network analysis statistics. Effects were masked when the intervention group was assessed together, ignoring heterogeneity in treatment responsiveness.

CONCLUSION

Findings are consistent with our contention that study design and analytic approach influence the ability to test network theory predictions with fidelity. We conclude by offering key recommendations for future network theory-driven interventional studies.

Comparing psychological versus pharmacological treatment in emotional disorders: A network analysis

Transdiagnostic group cognitive behavioural therapy (TD-GCBT) is more effective in improving symptoms and severity of emotional disorders (EDs) than treatment as usual (TAU; usually pharmacological treatment). However, there is little research that has examined the effects of these treatments on specific symptoms. This study used Network Intervention Analysis (NIA) to investigate the direct and differential effects of TD-GCBT + TAU and TAU on specific symptoms of anxiety and depression. Data are from a multicentre randomised clinical trial (N = 1061) comparing TD-GCBT + TAU versus TAU alone for EDs. The networks included items from the PHQ-9 (depression) and GAD-7 (anxiety) questionnaire and mixed graphical models were estimated at pre-treatment, post-treatment and 3-, 6- and 12-month follow-up. Results revealed that TD-GCBT + TAU was associated with direct effects, mainly on several anxiety symptoms and depressed mood after treatment. New direct effects on other depressive symptoms emerged during the follow-up period promoted by TD-GCBT compared to TAU. Our results suggest that the improvement of anxiety symptoms after treatment might precipitate a wave of changes that favour a decrease in depressive symptomatology. NIA is a methodology that can provide fine-grained insight into the likely pathways through which treatments exert their effects.

Cross-Informant Compatibility of Depression Symptoms in Children: A Network Approach

Utilizing multiple informants to assess children's depressive symptoms increases diagnostic accuracy, reliability, and validity of inferences. However, previous studies have found low to moderate agreement among informants. We applied network statistics to gain insight into children and their mothers' differential perceptions of depressive symptoms. The sample included children and mother dyads (n = 185) who applied to psychotherapy services at an outpatient university clinic. Mothers filled out the Child Behavior Checklist, which includes a depression subscale, and children filled out the Children's Depression Inventory. We computed association networks for thirteen depressive symptoms separately for children and mothers using the graphical LASSO. Sadness had the highest strength centrality in the networks of both children and mothers, but the pattern of connectivity and centrality of other symptoms differed. We discussed our findings within the framework of network theory.

Centrality statistics of symptom networks of schizophrenia: a systematic review

The network theory of psychological disorders posits that systems of symptoms cause, or are associated with, the expression of other symptoms. Substantial literature on symptom networks has been published to date, although no systematic review has been conducted exclusively on symptom networks of schizophrenia, schizoaffective disorder, and schizophreniform (people diagnosed with schizophrenia; PDS). This study aims to compare statistics of the symptom network publications on PDS in the last 21 years and identify congruences and discrepancies in the literature. More specifically, we will focus on centrality statistics. Thirty-two studies met the inclusion criteria. The results suggest that cognition, and social, and occupational functioning are central to the network of symptoms. Positive symptoms, particularly delusions were central among participants in many studies that did not include cognitive assessment. Nodes representing cognition were most central in those studies that did. Nodes representing negative symptoms were not as central as items measuring positive symptoms. Some studies that included measures of mood and affect found items or subscales measuring depression were central nodes in the networks. Cognition, and social, and occupational functioning appear to be core symptoms of schizophrenia as they are more central in the networks, compared to variables assessing positive symptoms. This seems consistent despite heterogeneity in the design of the studies.

Network Analysis Revealed the Role of Helplessness as a Central Feature Among Late-Life Depressive Symptoms in Patients With Mild Cognitive Impairment and Early Stage Dementia

OBJECTIVE

It has been reported that depressive symptoms in older adults are different from those in younger adults, especially when accompanied by cognitive decline. However, few studies have investigated the network structure of depressive symptoms in this population.

METHODS

The participants consisted of 627 older adults (>60 yr) who were diagnosed with mild cognitive impairment (MCI) or early stage dementia. Among them, 36.7% were male and the mean age was 76.20±7.71 years. The Korean form of Geriatric Depression Scale (KGDS) was used to evaluate their depressive symptoms and network analyses were performed using bootnet R-package to identify the central features among depressive symptoms.

RESULTS

Of all the KGDS items, we found that KGDS 2 (often feel helpless) had the highest node strength followed by KGDS 21 (in good spirits), KGDS 14 (not confident at all), and KGDS 15 (cheerful and happy). In terms of node betweenness, KGDS 2 also showed the highest value. The edge weights of edges connected to node KGDS 2 were strongest in KGDS 3 (restless and fidgety) and KGDS 28 (easily get tired).

CONCLUSION

In this study, we presented which symptoms are central among the elderly with MCI and early stage dementia. This result not only increases the understanding of depressive symptoms in this group but would also help determine target symptoms in the treatment program.

Network analysis used to investigate the interplay among somatic and psychological symptoms in patients with cancer and cancer survivors: a scoping review

PURPOSE

Patients with cancer often experience multiple somatic and psychological symptoms. Somatic and psychological symptoms are thought to be connected and may reinforce each other. Network analysis allows examination of the interconnectedness of individual symptoms. The aim of this scoping review was to examine the current state of knowledge about the associations between somatic and psychological symptoms in patients with cancer and cancer survivors, based on network analysis.

METHODS

This scoping review followed the five-stage framework of Arksey and O'Malley. The literature search was conducted in May, 2023 in PubMed, APA PsycINFO, Embase Cochrane central, and CINAHL databases.

RESULTS

Thirty-two studies were included, with eleven using longitudinal data. Seventeen studies reported on the strength of the associations: somatic and psychological symptoms were associated, although associations among somatic as well as among psychological symptoms were stronger. Other findings were the association between somatic and psychological symptoms was stronger in patients experiencing more severe symptoms; associations between symptoms over time remained rather stable; and different symptoms were central in the networks, with fatigue being among the most central in half of the studies.

IMPLICATIONS FOR CANCER SURVIVORS

Although the associations among somatic symptoms and among psychological symptoms were stronger, somatic and psychological symptoms were associated, especially in patients experiencing more severe symptoms. Fatigue was among the most central symptoms, bridging the somatic and psychological domain. These findings as well as future research based on network analysis may help to untangle the complex interplay of somatic and psychological symptoms in patients with cancer.

A network analysis of ICD-11 Complex PTSD, emotional processing, and dissociative experiences in the context of psychological trauma at different developmental stages

Objective

Traumatic experiences are a significant risk factor for psychological disturbances, including disorders such as complex posttraumatic stress disorder, emotion-processing problems, and trauma-related dissociative experiences. The present investigation examined the coexistence of these symptoms using a network analysis model.

Method

This study included a sample of 406 people referred to comprehensive health centers in Tehran from September to December 2023 with psychopathological syndromes. Variables were assessed using The International Trauma Questionnaire, International Measurement of Exposure to Traumatic Event checklist, Baker Emotional Processing Questionnaire, and Dissociative Experiences. A regularized partial correlation network and Glasso algorithm, in combination with Extended Bayesian information criteria, were applied to estimate the network structure.

Results

Signs of unprocessed emotions and disturbance in self-organization symptoms were the most important symptoms in the symptom network, forming strong connections with other nodes. Thereby, these two symptoms can be regarded as the most important clinical manifestations in the symptom network following traumatic experiences. Three distinct symptom communities were identified: the community of traumatic experiences (childhood, adolescence, adulthood), the community of dissociative experiences (amnesia, depersonalization/derealization, and absorption), and the community of emotional processing (suppression, unpleasant emotional experience, Signs of unprocessed emotions, avoidance, and emotional control, posttraumatic stress disorder symptoms and disturbance in self-organization symptoms). The strongest edges observed were between childhood trauma-adolescence trauma (0.473) in the community of traumatic experiences, between amnesia and depersonalization/derealization (0.644) in the community of dissociative experiences, and between disturbance in self-organization symptoms and unprocessed emotions (0.324) in the community of emotional processing, indicating the recurrent occurrence of these symptoms.

Conclusion

In this study, disturbance in self-organization symptoms was identified as the central psychopathologic symptom in individuals experiencing traumas at different developmental stages. It seems that adolescent trauma and not childhood trauma plays a more decisive role in the symptoms that a person manifests after traumatic experiences. Also, posttraumatic stress disorder symptoms and disturbance in self-organization symptoms were recognized in the cluster of emotional processing symptoms and can have substantial roles in prioritizing therapeutic measures.

Understanding the Risk of Sexual Reoffending in Adult Men: A Network-Based Model

The predominant approach to understand dynamic risk factors of sexual reoffending has been referred to as the Propensities Model (Thornton, 2016). According to this model, dynamic risk factors can be conceptualized as latent constructs whose change alters the risk of sexual reoffending. Despite its strengths and contributions to research, this model does not offer answers to the question of how dynamic risk factors contribute to the risk of sexual reoffending, or of how sustained change in risk might take place. In this paper we introduce the Network-Based Model of Risk of Sexual Reoffending (NBM-RSR), which addresses several limitations and constraints of the Propensities Model and offers empirically testable propositions regarding the nature and development of the risk of sexual reoffending. The NBM-RSR considers risk of sexual reoffending to involve a self-sustaining network of causally connected dynamic risk factors. Consistent with this, an increased risk of sexual reoffending is characterized through a network that contains more and stronger interconnected dynamic risk factors with a higher strength. Sustained change in risk of sexual reoffending occurs when activity in the network exceeds a critical point resulting in a new self-sustaining network. Propositions based on the NBM-RSR are introduced and translated into testable hypotheses. These propositions revolve around (a) risk of sexual reoffending resulting from the construction of a network of causally connected dynamic risk factors, (b) network stability, sudden changes, and critical transitions, and (c) dynamic risk factors' relative influence on risk of sexual reoffending.

Identifying the core residual symptom in patients with major depressive disorder using network analysis and illustrating its association with prognosis: A study based on the national cohorts in China

OBJECTIVE

To identify the core residual symptom of MDD and assess its relationship with patients' long-term outcomes.

METHOD

All patients were administered antidepressants during the acute phase and treated continuously. The 521 patients remitted at month 6 of a multicenter prospective project were included. Remission was defined as a Quick Inventory of Depressive Symptoms-Self-Report total score of ≤5. Functional impairments were measured with the Sheehan Disability Scale, quality of life with the Quality of Life Enjoyment and Satisfaction Questionnaire - short form, and family burden with the Family Burden Scale of Disease. Visits were scheduled at baseline, weeks 2, 8, 12, and month 6.

RESULTS

Difficulty with concentration/decision making was the core residual symptom of MDD, determined with the centrality measure of network analysis. It was positively associated with functional impairments and family burden (r = 0.35, P < 0.01 and r = 0.31, P < 0.01, respectively) and negatively associated with life satisfaction (r = -0.29, P < 0.01). The exhibition of this residual symptom was associated with a family history of psychiatric disorders (OR = 2.610 [1.242-5.485]).

CONCLUSIONS

The core residual symptom of MDD, difficulty with concentration/decision making, is associated with poorer social functioning, heavier family burden, and lower life satisfaction. Early detection and intervention of this symptom may be beneficial.

CLINICAL TRIALS REGISTRATION NUMBER

(Chinese Clinical Trials.gov identifier) ChiCTR-OOC-17012566 and ChiCTR-INR-17012574.

Recommendations for a Better Understanding of Sex and Gender in the Neuroscience of Mental Health

There are prominent sex/gender differences in the prevalence, expression, and life span course of mental health and neurodiverse conditions. However, the underlying sex- and gender-related mechanisms and their interactions are still not fully understood. This lack of knowledge has harmful consequences for those with mental health problems. Therefore, we set up a cocreation session in a 1-week workshop with a multidisciplinary team of 25 researchers, clinicians, and policy makers to identify the main barriers in sex and gender research in the neuroscience of mental health. Based on this work, here we provide recommendations for methodologies, translational research, and stakeholder involvement. These include guidelines for recording, reporting, analysis beyond binary groups, and open science. Improved understanding of sex- and gender-related mechanisms in neuroscience may benefit public health because this is an important step toward precision medicine and may function as an archetype for studying diversity.

Identification of central symptoms of children depression and development of two short version of Children's Depression Inventory: Based on network analysis and machine learning

BACKGROUND

Using network analysis to study the central symptoms is important for understanding the mechanism of depression symptoms and selecting items for the short version depression screening scale. This study aimed to identify the central symptoms of depression and develop the short and effective depression screening tools for Chinese rural children.

METHODS

Firstly, the 2458 individuals (Mage = 10.74; SDage = 1.64; 51.2 % were female) were recruited from the rural children's mental health database. Children's Depression Inventory (CDI) was used to assess depression symptoms. Then, network analysis was used to identify the central symptoms of depression. The accuracy, stability, and gender invariance of the depression symptoms network were tested. Finally, a short version of CDI with central symptoms (CDI-SC) and a new CDI-10 (CDI-10-N) were developed by network analysis and feature selection techniques to optimize the existing CDI-10. Their performances in screening depression symptoms were validated by the cutoff threshold and machine learning.

RESULTS

The central symptoms of Chinese rural children's depression were sadness, self-hatred, loneliness and self-deprecation. This result was accurate and stable and depression symptoms network has gender invariance. The AUC values of CDI-10-N and CDI-SC are over 0.9. The CDI-10-N has a higher AUC than CDI-10. The optimal cutoff thresholds for CDI-10-N and CDI-SC are 6 and 1. The performance of machine learning on AUC generally outperforms those of cutoff threshold.

CONCLUSIONS

The central symptoms identified in this study should be highlighted in screening depression symptoms, and CDI-10-N and CDI-SC are effective tools for screening depression symptoms in Chinese rural children.

Hurting myself to cope: Using network analysis to understand the association between perceived stigma and non-suicidal self-injury functions among men who have sex with men in China

Prior studies have demonstrated that perceived stigma is robustly associated with risky and life-threatening behaviors, including non-suicidal self-injury (NSSI), among men who have sex with men (MSM). However, studies regarding the relationship between perceived stigma and NSSI are limited. The present study aimed to investigate the network structure of perceived stigma and NSSI functions, along with bridge nodes, to elucidate how they co-exist. A sample of 2610 Chinese MSM (mean age = 23.99, age range: 18-68 years) was recruited from an online survey platform. All participants completed a web-based survey with measures of perceived stigma and NSSI functions. Results indicated that 'negative attitudes towards homosexuality' and 'disappointment in gay son' were identified as the most central nodes in the perceived stigma network, whereas 'seeking attention' and 'influencing others to change' ranked highest on centrality in the NSSI network. Two bridge connections were exhibited within the combined perceived stigma and NSSI network model: 'unwelcoming in public' and 'avoiding unpleasant tasks' from perceived stigma and NSSI communities, respectively. This is among the first studies investigating the co-occurrence between perceived stigma and NSSI from the network approach. Our findings provide an empirically-based perspective on the importance of family- and community-based interventions, with potential clinical implications for reducing NSSI among sexual and gender minority groups.

Dynamic Individual Risk Networks: Personalized Network Modelling Based on Experience Sampling Data

Following a network perspective, risk of sexual reoffending can be understood as a construct that emerges from the interactions between risk factors. If these interrelationships are validly mapped out, this leads to an increased understanding of the risk and thus may contribute to more effective and/or more efficient interventions. This paper reports on personalized network modeling mapping the interrelationships of dynamic risk factors for an individual convicted of sexual offenses, using experience sampling (ESM) based on Stable-2007 items. The longitudinal character of ESM enables both the assessment of interrelations between risk factors within a timeframe and the relationships between risk factors over time. Networks are calculated and compared to the clinical assessment of interrelationships between the risk factors.

Dynamic time warp analysis of individual symptom trajectories in individuals with bipolar disorder

BACKGROUND

Manic and depressive mood states in bipolar disorder (BD) may emerge from the non-linear relations between constantly changing mood symptoms exhibited as a complex dynamic system. Dynamic Time Warp (DTW) is an algorithm that may capture symptom interactions from panel data with sparse observations over time.

METHODS

The Young Mania Rating Scale and Quick Inventory of Depressive Symptomatology were repeatedly assessed in 141 individuals with BD, with on average 5.5 assessments per subject every 3-6 months. Dynamic Time Warp calculated the distance between each of the 27 × 27 pairs of standardized symptom scores. The changing profile of standardized symptom scores of BD participants was analyzed in individual subjects, yielding symptom dimensions in aggregated group-level analyses. Using an asymmetric time-window, symptom changes that preceded other symptom changes (i.e., Granger causality) yielded a directed network.

RESULTS

The mean age of the BD participants was 40.1 (SD 13.5) years old, and 60% were female participants. Idiographic symptom networks were highly variable between subjects. Yet, nomothetic analyses showed five symptom dimensions: core (hypo)mania (6 items), dysphoric mania (5 items), lethargy (7 items), somatic/suicidality (6 items), and sleep (3 items). Symptoms of the "Lethargy" dimension showed the highest out-strength, and its changes preceded those of "somatic/suicidality," while changes in "core (hypo)mania" preceded those of "dysphoric mania."

CONCLUSION

Dynamic Time Warp may help to capture meaningful BD symptom interactions from panel data with sparse observations. It may increase insight into the temporal dynamics of symptoms, as those with high out-strength (rather than high in-strength) could be promising targets for intervention.

A network perspective on real-life threat, anxiety, and avoidance

BACKGROUND

Anxiety, approach, and avoidance motivation crucially influence mental and physical health, especially when environments are stressful. The interplay between anxiety and behavioral motivation is modulated by multiple individual factors. This proof-of-concept study applies graph-theoretical network analysis to explore complex associations between self-reported trait anxiety, approach and avoidance motivation, situational anxiety, stress symptoms, perceived threat, perceived positive consequences of approach, and self-reported avoidance behavior in real-life threat situations.

METHODS

A total of 436 participants who were matched on age and gender (218 psychotherapy patients, 218 online-recruited nonpatients) completed an online survey assessing these factors in response to the COVID-19 pandemic.

RESULTS AND DISCUSSION

The resulting cross-sectional psychological network revealed a complex pattern with multiple positive (e.g., between trait anxiety, avoidance motivation, and avoidance behavior) and negative associations (e.g., between approach and avoidance motivation). The patient and online subsample networks did not differ significantly, however, descriptive differences may inform future research.

Suicidal behaviour in adolescents: A network analysis

OBJECTIVE

Suicidal behaviour has not yet been analysed from a network approach in adolescent samples. It is imperative to incorporate new psychological models to understand suicidal behaviour from a different perspective. The main objective of this work was twofold: (a) to examine suicidal behaviour through network analysis and (b) to estimate the psychological network between suicidal behaviour and protective and risk factors in school-age adolescents.

METHOD

Participants were 443 students (M=14.3 years; SD=0.53; 51.2% female) selected incidentally from different schools. Different instruments were administered to assess suicidal behaviour, emotional and behavioural difficulties, prosocial behaviour, subjective well-being, emotional intelligence, self-esteem, depressive symptomatology, empathy, positive and negative affect, and emotional regulation.

RESULTS

The resulting network of suicidal behaviour was strongly interconnected. The most central node in terms of strength and expected influence was "Consider taking your own life". In the estimated psychological network of suicidal behaviour and risk and protective factors, the nodes with the highest strength were depressive symptomatology, positive affect, and empathic concern. The most influential nodes were those related to emotional intelligence abilities. Suicidal behaviour was positively connected to depression symptoms and negative affect, and negatively connected to self-esteem and positive affect. The results of the stability analysis indicated that the networks were accurately estimated.

CONCLUSIONS

Suicidal behaviour can be conceptualized as a dynamic, complex system of cognitive, emotional, and affective characteristics. The new psychopathological and psychometric models allow us to analyse and understand human behaviour and mental health problems from a new perspective, suggesting new forms of conceptualization, evaluation, intervention, and prevention.

The longitudinal structure of negative symptoms in treatment resistant schizophrenia

BACKGROUND AND HYPOTHESIS

The negative symptoms of schizophrenia are strong prognostic factors but remain poorly understood and treated. Five negative symptom domains are frequently clustered into the motivation and pleasure (MAP) and emotional expression (EE) 'dimensions', but whether this structure remains stable and behaves as a single entity or not remains unclear.

STUDY DESIGN

We examined a cohort of 153 patients taking clozapine for treatment-resistant schizophrenia in a regional mental health clinic. Patients were assessed longitudinally over a mean period of 45 months using validated scales for positive, negative and mood symptoms. Network analyses were performed to identify symptom 'communities' and their stability over time. The influence of common causes of secondary negative symptoms as well as centrality measures were also examined.

STUDY RESULTS

Across patients at baseline, two distinct communities matching the clinical domains of MAP and EE were found. These communities remained highly stable and independent over time. The communities remained stabled when considering psychosis, depression, and sedation severity, and these causes of secondary negative symptoms were clustered into the MAP community. Centrality measures also remained stable over time, with similar centrality measures across symptoms.

CONCLUSIONS

Our results suggest that MAP and EE are independent dimensions that remain highly stable over time in chronic schizophrenia patients treated with clozapine. Common causes of secondary negative symptoms mapped onto the MAP dimension. Our results emphasise the need for clinical trials to address either MAP or EE, and that treating causes of secondary negative symptoms may improve MAP.

Eating disorders symptoms and depressive symptoms in Chinese Tibetan University students: a network analysis

BACKGROUND

Depression is being increasingly acknowledged as a global public health concern, and following this trend, attention towards eating disorders (EDs) has surged within China's national consciousness. EDs symptoms frequently coexist with various mental health conditions, including depression. However, research focusing on EDs symptoms and depressive symptoms among Tibetan students in China remains scant. This study employs network analysis to estimate the relational network between EDs and depressive symptoms.

METHODS

Tibetan (n = 2,582) and Han (n = 1,743) students from two universities in the Xizang Autonomous Region, China, completed the Eating Attitude Test-26 (EAT-26) and the Patient Health Questionnaire-9 (PHQ-9). We estimated the network structure of EDs symptoms and depressive symptoms, identified central and bridge symptoms, and examined whether network characteristics differed by gender and ethnic.

RESULTS

The core symptoms identified within this study were Calorie_awareness, Desire_to_thin and Fatigue. Conversely, bridge symptoms included Appetite, Suicide, Anhedonia, Guilty, Body_fat_awareness, and Food_preoccupation. The study also revealed no significant gender differences within the network model. However, disparities among ethnic groups were observed within the network structure.

CONCLUSIONS

Our study examined the correlation between EDs symptoms and depressive symptoms in Tibetan college students. Focusing on the individual's quest for the perfect body shape and some Tibetan students' appetite problems - potentially stemming from transitioning to a new university environment, adapting to the school canteen's diet, or being away from their hometown - could aid in the prevention and management of EDs and depression symptoms. It could reduce the incidence of complications by helping students maintain good physical and mental health. Concurrently, our research provides insights into the relatively higher levels of depression triggered by the unique plateau environment.

Revealing the psychopathological pathway linking trauma to post-traumatic stress disorder: longitudinal network approach

The present study investigated the psychopathological processes of post-traumatic stress disorder (PTSD) following the network approach to psychopathology. The directed acyclic graph model was employed to analyse a large longitudinal data-set of Chinese children and adolescents exposed to a destructive earthquake. It was found that intrusion symptoms were first activated by trauma exposure, and subsequently activated other PTSD symptoms. The data are consistent with the idea that symptoms may form a self-sustaining dynamic network by interacting with each other to promote or maintain the chronicity of PTSD. The findings advance the current understanding about the psychopathological processes of PTSD, and inform further research and clinical practices on post-traumatic psychopathology.

The Predictive Role of Tolerance and Health Problems in Problem Gambling: A Cross-Sectional and Cross-Lagged Network Analyses

The existing symptomatic networks of problem gambling are all based on cross-sectional data. Thus, there is a need to explore longitudinal symptom networks of problem gambling. Moreover, the replicability of cross-sectional symptom networks can be limited; therefore, further research should assess the convergence between cross-sectional networks of problem gambling symptoms. The present study aimed (i) to examine cross-sectional networks of problem gambling symptoms and evaluate their replicability and (ii) to examine a longitudinal cross-lagged network of problem gambling symptoms. The study included a representative sample of young adult gamblers (born between 1984 and 2000) from the first two waves of the Budapest Longitudinal Study (original sample: N = 2777; final sample: N = 335). The Problem Gambling Severity Index was used to assess symptoms of problem gambling. Cross-sectional symptom networks showed differences in the centrality of nodes. Correlations between the two cross-sectional networks were low in the presence vs. absence of edges, rank order of edge weights, and centrality estimates. However, network invariance tests indicated non-significant differences between them. The cross-lagged network revealed that the symptoms of tolerance and health problems could predict the subsequent presence of multiple problem gambling symptoms. Overall, limited evidence demonstrated the replicability of cross-sectional symptom networks of problem gambling. Future research needs to explore the utility of cross-sectional networks of problem gambling and assess more precisely causal relationships between problem gambling symptoms by distinguishing within- and between-subject effects.

Sexual abuse and psychotic phenomena: a directed acyclic graph analysis of affective symptoms using English national psychiatric survey data

BACKGROUND

Sexual abuse and bullying are associated with poor mental health in adulthood. We previously established a clear relationship between bullying and symptoms of psychosis. Similarly, we would expect sexual abuse to be linked to the emergence of psychotic symptoms, through effects on negative affect.

METHOD

We analysed English data from the Adult Psychiatric Morbidity Surveys, carried out in 2007 (N = 5954) and 2014 (N = 5946), based on representative national samples living in private households. We used probabilistic graphical models represented by directed acyclic graphs (DAGs). We obtained measures of persecutory ideation and auditory hallucinosis from the Psychosis Screening Questionnaire, and identified affective symptoms using the Clinical Interview Schedule. We included cannabis consumption and sex as they may determine the relationship between symptoms. We constrained incoming edges to sexual abuse and bullying to respect temporality.

RESULTS

In the DAG analyses, contrary to our expectations, paranoia appeared early in the cascade of relationships, close to the abuse variables, and generally lying upstream of affective symptoms. Paranoia was consistently directly antecedent to hallucinations, but also indirectly so, via non-psychotic symptoms. Hallucinosis was also the endpoint of pathways involving non-psychotic symptoms.

CONCLUSIONS

Via worry, sexual abuse and bullying appear to drive a range of affective symptoms, and in some people, these may encourage the emergence of hallucinations. The link between adverse experiences and paranoia is much more direct. These findings have implications for managing distressing outcomes. In particular, worry may be a salient target for intervention in psychosis.

Relationship of sleep-quality and social-anxiety in patients with breast cancer: a network analysis

BACKGROUND

There is a complex relationship between social anxiety and sleep quality. However, network analysis studies of associations between social anxiety and sleep quality are lacking, particularly among patients with breast cancer. The current study aimed to extend this research to a sample of patients with breast cancer and to examine symptom-level associations between social anxiety and sleep quality using network analysis.

METHODS

Network analysis was conducted to explore their associations and identify bridge items of social anxiety and sleep quality.

RESULTS

The network structure revealed 9 important edges between social anxiety and sleep quality. "Subjective sleep quality" had the highest EI value in the network. "Working difficulty under watching" and "Sleep disorders" had the highest BEI values in their own communities.

CONCLUSION

There are complex pathological correlation pathways between social anxiety and sleep quality in breast cancer patients. "Subjective sleep quality", "Working difficulty under watching" and "Sleep disorders" have the potential to be intervention targets for sleep disorder-social anxiety comorbidity. Medical staff can take corresponding interventions according to the the centrality indices and bridge centrality indicators identified in this study, which is likely to effectively reduce the comorbidity of sleep disorders and social anxiety.

Validity of the Capacity to Work Index: Development of an Instrument to Measure Work Capacity in Relation to Depression and Anxiety in the General Working Population

PURPOSE

To develop an index to assess capacity to work in relation to common mental disorders (CMDs) in the general working population and field test its psychometric properties.

METHODS

Content analysis of three qualitative studies on people (n = 49) with their own experiences of working with CMD guided the items selected for the index. Face and content validity and test-retest reliability were performed. The index was field tested in two versions with 26 and 17 items, respectively, among health care professionals regarding internal reliability, component structure and concurrent validity.

RESULTS

The final version of the Capacity to Work Index (C2WI; 17 items) was normally distributed in the field test with high internal reliability (Cronbach's alpha, 0.84). Missing responses were randomly distributed and nonspecific. Principal component analysis showed one clear component with negatively framed items. Concurrent validity showed high correlation with the WHO-5 Well-Being Scale (Pearson's r, 0.68), but lower correlation for the general health question (r, - 0.44), one item of the Work Ability Index (r, - 0.33), and the Stress of Conscience constructs (r, 0.44).

CONCLUSION

The C2WI showed promising psychometric qualities. Low and negative correlation with the item from Work Ability Index suggests that the C2WI measures additional dimensions, but further testing in larger and more diverse samples is required.

Associations between sleep habits, quality, chronotype and depression in a large cross-sectional sample of Swedish adolescents

OBJECTIVE

To investigate behavioral sleep habits, self-perceived quality of sleep, and chronotype, and to examine their association with clinically relevant levels of depression in Swedish adolescents.

METHOD

Questionnaire data were obtained from a representative sample of Swedish adolescents (n = 8449; 50.8% girls; aged 12-16). Depression was defined as >13 BDI-II scores. Logistic regression modelling estimated the effects of sleep duration, sleep quality, and chronotype on depression, adjusted for socio-demographic factors.

RESULTS

On weekdays, approximately 46% of adolescents slept less than the recommended length of eight hours per night (depressed: 68%, non-depressed: 40%). On weekends, however, only 17% slept shorter than recommended. Short weekday sleep duration was more common among girls than boys (53% vs. 38%) and girls reported worse sleep quality. The regression model showed that depression was predicted by weekday sleep duration (OR = 0.773, p < .0001), sleep quality (OR = 0.327, p < .0001), and late chronotype (OR = 1.126, p = .0017), but not by weekend sleep duration. A 30-minute increase in weekday sleep duration was associated with about 10% lower odds of depression.

CONCLUSIONS

A substantial proportion of Swedish adolescents do not seem to meet the sleep recommendations of eight hours per night. Short sleep duration on weekdays, poor sleep quality, and late chronotype were associated with increased risk of depression. Interventions promoting longer weekday sleep duration (e.g., later school start times) seem relevant in this context, but further research is needed to investigate the directionality and underlying mechanisms of these associations.