A network theory of mental disorders

The role of borderline personality disorder traits in predicting longitudinal variability of major depressive symptoms among a sample of depressed adults

BACKGROUND

Major depressive disorder (MDD) and borderline personality disorder (BPD) often co-occur, with 20 % of adults with MDD meeting criteria for BPD. While MDD is typically diagnosed by symptoms persisting for several weeks, research suggests a dynamic pattern of symptom changes occurring over shorter durations. Given the diagnostic focus on affective states in MDD and BPD, with BPD characterized by instability, we expected heightened instability of MDD symptoms among depressed adults with BPD traits. The current study examined whether BPD symptoms predicted instability in depression symptoms, measured by ecological momentary assessments (EMAs).

METHODS

The sample included 207 adults with MDD (76 % White, 82 % women) recruited from across the United States. At the start of the study, participants completed a battery of mental health screens including BPD severity and neuroticism. Participants completed EMAs tracking their depression symptoms three times a day over a 90-day period.

RESULTS

Using self-report scores assessing borderline personality disorder (BPD) traits along with neuroticism scores and sociodemographic data, Bayesian and frequentist linear regression models consistently indicated that BPD severity was not associated with depression symptom change through time.

LIMITATIONS

Diagnostic sensitivity and specificity may be restricted by use of a self-report screening tool for capturing BPD severity. Additionally, this clinical sample of depressed adults lacks a comparison group to determine whether subclinical depressive symptoms present differently among individuals with BPD only.

CONCLUSIONS

The unexpected findings shed light on the interplay between these disorders, emphasizing the need for further research to understand their association.

A network analysis of positive psychosocial factors and indication of suboptimal HIV care outcomes among Black women living with HIV

Black women living with HIV (BWLWH) face barriers that impact health outcomes. However, positive psychosocial indicators may influence HIV care outcomes. Among this cross-sectional study of 119 BWLWH, a network analysis was utilized to examine relationships between positive psychosocial factors and HIV-related health outcomes. A preliminary polychoric analysis was conducted to examine correlations between the variables, and the network analyzed connections between resilience, self-efficacy, self-esteem, perceived social support, religious coping, post-traumatic growth, and an indicator variable for suboptimal HIV care outcomes (low medication adherence, detectable viral load, and missed HIV-related health visits) and determined the centrality measures within the network. Seven significant associations were found among the factors: self-efficacy and self-esteem, post-traumatic growth and resilience, post-traumatic growth and self-efficacy, post-traumatic growth and religious coping, perceived social support and resilience, self-esteem and resilience, self-esteem and perceived social support (bootstrapped 95% CI did not contain zero). Self-efficacy was the strongest indicator associated with the other factors. Although not statistically significant, the indicator for suboptimal HIV care outcomes was negatively associated with perceived social support and religious coping. Future interventions incorporating self-efficacy may be beneficial to the overall well-being of Black women.

Examining network structure of impulsivity and depression in adolescents and young adults: A two-sample study

BACKGROUND

Depression ranks as one of the top five contributors to ill health in youth, the most formative period in life. Extensive research has highlighted the significant role of impulsivity in understanding depression. However, there has been limited exploration into how each dimension of impulsivity uniquely affect depressive symptoms, especially across crucial developmental stages like adolescence and young adulthood.

METHODS

This study investigates the unique relationships between impulsivity (assessed by the short UPPS-P scale) and depression (assessed by the Patient Health Questionnaire-9) via network analysis. We analysed data from a total of 2296 participants, comprising 858 adolescents aged 14-17 years and 1438 young adults aged 18-25 years, to estimate both a combined network and age-group specific networks. Key features of the networks, including their structure, global connectivity, and bridge nodes, were compared.

RESULTS

The results indicated that age differentially impacts individual depression symptoms, both directly and indirectly, via impulsivity dimensions. The comparison test revealed consistent network structures between the two age groups, with several robust pathways, such as lack of perseverance to concentration difficulties, sensation seeking to suicidal ideation, and negative urgency to feelings of worthlessness. Negative urgency and lack of perseverance were identified as bridge nodes across the two networks.

LIMITATIONS

The study employed a cross-sectional design, which limits the ability to estimate causal or temporal relationships.

CONCLUSIONS

The current findings highlight the significance of tailoring intervention strategies to individual symptom profiles and assessing negative urgency and lack of perseverance as potential early targets for depression among youth.

The impact of antidepressant treatment on the network structure of neurocognition and core emotional depressive symptoms among depressed individuals with a history of suicide attempt: An 8-week clinical study

BACKGROUND

A more in-depth understanding of the relationship between depressive symptoms, neurocognition and suicidal behavior could provide insights into the prognosis and treatment of major depressive disorder (MDD) and suicide. We conducted a network analysis among depressed patients examining associations between history of suicide attempt (HSA), core emotional major depression disorder, and key neurocognitive domains.

METHOD

Depressed patients (n = 120) aged 18-65 years were recruited from a larger randomized clinical trial conducted at the Douglas Institute in Montreal, Canada. They were randomly assigned to receive one of two antidepressant treatments (i.e., escitalopram or desvenlafaxine) for 8 weeks. Core emotional MDD and key neurocognitive domains were assessed pre-post treatment.

RESULTS

At baseline, an association between history of suicide attempt (HSA) and phonemic verbal fluency (PVF) suggested that HSA patients reported lower levels of the latter. After 8 weeks of antidepressant treatment, HSA became conditionally independent from PVF. Similar results were found for both the HAM-D and the QIDS-SR core emotional MDD/neurocognitive networks.

CONCLUSION

Network analysis revealed a pre-treatment relationship between a HSA and decreased phonemic VF among depressed patients, which was no longer present after 8 weeks of antidepressant treatment.

Depression-Anxiety Coupling Strength as a predictor of relapse in major depressive disorder: A CAN-BIND wellness monitoring study report

BACKGROUND

A critical challenge in the study and management of major depressive disorder (MDD) is predicting relapse. We examined the temporal correlation/coupling between depression and anxiety (called Depression-Anxiety Coupling Strength, DACS) as a predictor of relapse in patients with MDD.

METHODS

We followed 97 patients with remitted MDD for an average of 394 days. Patients completed weekly self-ratings of depression and anxiety symptoms using the Quick Inventory of Depressive Symptoms (QIDS-SR) and the Generalized Anxiety Disorder 7-item scale (GAD-7). Using these longitudinal ratings we computed DACS as random slopes in a linear mixed effects model reflecting individual-specific degree of correlation between depression and anxiety across time points. We then tested DACS as an independent variable in a Cox proportional hazards model to predict relapse.

RESULTS

A total of 28 patients (29 %) relapsed during the follow-up period. DACS significantly predicted confirmed relapse (hazard ratio [HR] 1.5, 95 % CI [1.01, 2.22], p = 0.043; Concordance 0.79 [SE 0.04]). This effect was independent of baseline depressive or anxiety symptoms or their average levels over the follow-up period, and was identifiable more than one month before relapse onset.

LIMITATIONS

Small sample size, in a single study. Narrow phenotype and comorbidity profiles.

CONCLUSIONS

DACS may offer opportunities for developing novel strategies for personalized monitoring, early detection, and intervention. Future studies should replicate our findings in larger, diverse patient populations, develop individual patient prediction models, and explore the underlying mechanisms that govern the relationship of DACS and relapse.

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.

Understanding the relationships among adolescents' internet dependence, reward, cognitive control processing, and learning burnout: a network perspective in China

Alterations in the reward and cognitive control systems are commonly observed among adolescents with internet dependence (ID), and this impairment is often accompanied by social dysfunctions, such as academic burnout. However, the intercorrelations among ID, reward, cognitive control processing, and learning burnout remain unclear. We recruited 1074 Chinese adolescents to investigate the complex interrelationships among these variables using network analysis. The resulting network revealed patterns that connected ID to the behavioral inhibition/activation system (BIS/BAS), self-control, and learning burnout; these results exhibited reasonable stability and test-retest consistency. Throughout the network, the node of BAS-drive was the critical influencing factor, and the node of self-control was the protection factor. In addition, several symptoms of learning burnout and ID were positively associated with sensitivity to punishment. As revealed by the network comparison test, the network constructed among internet dependent (ID) group differed from the network constructed among internet nondependent (IND) group not only in the edges between BIS and learning burnout but also in terms of the edges associated with learning burnout. In conclusion, this study provides insights into the complex mechanisms underlying ID among adolescents from the perspective of the network relationships between core influencing factors and negative consequences. It validates the dual-system model of risky behavior among adolescents and offers a foundation for early warning and interventions for ID in this context.

The bridge relationships of PTSD and depression symptoms among snakebite victims: a cross-sectional community-based survey

BACKGROUND

The incidence of comorbid depression and post-traumatic stress disorder (PTSD) symptoms is higher in snakebite victims. However, the present state and contributing factors of depression and PTSD among Chinese snakebite victims remain unclear.

METHODS

A representative sample of 6837 snakebite victims were assessed with the Post-traumatic Stress Disorder Checklist (Civilian Version) and The Center for Epidemiologic Studies Depression Scale. Multivariate analyses, including network analysis, evaluated the contributing factors of PTSD and depression symptoms caused by snake bites, as well as the bridge symptoms of comorbidity networks.

RESULTS

Among 6,837 snakebite victims, 79.5% reported PTSD symptoms and 81.4% reported depression symptoms. Comorbidity of PTSD and depression symptoms was found in 75.1%. Key factors included the presence sequelae after snakebite (ORPTSD = 2.31, ORDepression = 1.89), time to medical facilities (6-8 h: ORPTSD = 3.17, ORDepression = 2.46), and marital status (divorced/widowed: ORPTSD = 1.78, ORDepression = 1.76). Symptoms I1 ("Repeated disturbing memories") and D1 ("Bothered by things that don't usually bother me") bridged PTSD and depression networks.

CONCLUSION

The primary psychological challenges for snakebite victims in China are PTSD and depression symptoms, which is concerning. Standardized diagnosis and treatments, timely medical care, and stable marital relationships can reduce risks. Additional psychological support and management of negative memories, especially for those with severe bridge symptoms, can be beneficial. Further research should concentrate on understanding victims' psychological states and developing effective interventions.

Clarifying the relationship between insecure attachment and problematic social media use across platforms: a network analysis

BACKGROUND

Despite evidence suggesting that insecure attachment is a significant risk factor for Problematic Social Media Use (PSMU), there remains a lack of comprehensive studies exploring this relationship, and a unified understanding of its role has yet to be established.

METHODS

We employed network analysis to construct an integrated model for examining the complex interrelations between negative emotions, trait and state attachment, motives, and PSMU across three platforms (i.e., WeChat, Sina Weibo, and TikTok), as well as for identifying potential mediating variables between attachment and PSMU. Data were collected from 685 young adults via online self-reported questionnaires.

RESULTS

We found that negative emotions are positively correlated with insecure trait and state attachment but have a negligible direct relationship with PSMU. The conformity motive and state attachment security emerged as important central nodes when measured by strength, closeness, and betweenness. Moreover, attachment states and motives were found to be clustered. Such strong interrelationships were also evident between insecure attachment and PSMU, while trait attachment anxiety and avoidance were observed to be related to PSMU across various platforms.

CONCLUSIONS

Our findings promote a deeper understanding of the relationship between insecure attachment and PSMU from a cross-platform perspective and offer novel insights into the mechanisms underlying their co-occurrence, which may guide the development of effective interventions for healthier social media engagement.

The structure of motivation: Assessing readiness to change dimensions and their predictive value with the network validation of the Italian version of the Anorexia Nervosa Stages of Change Questionnarie

OBJECTIVE

Motivation to change is an important predictor for treatment outcomes in individuals with anorexia nervosa (AN), however, the existence and clinical relevance of distinct motivational dimensions are understudied. This study aimed to structurally validate the AN Stage of Change Questionnaire (ANSOCQ) in the Italian adult AN population to identify separate motivational dimensions and their association with clinical variables and outcomes.

METHOD

Inpatients and outpatients with AN (N = 300) completed the ANSOCQ and measures assessing eating and depressive psychopathology. Unique Variable Analysis and Exploratory Graph Analysis were employed to identify dimensions in the network structure of ANSOCQ. Cross-sectional associations with clinical variables were assessed in the whole sample. Predictive value on weight and psychopathology was assessed in inpatients.

RESULTS

Two dimensions were identified, one comprising items relative to weight gain, and the second items regarding attitudes towards eating, body, and emotional problems. Feelings associated with eating resulted as most central in the network. Higher scores in the first dimension and ANSOCQ total predicted weight gain during hospitalisation. No significant predictors emerged for changes in eating psychopathology.

DISCUSSION

These findings confirm the robust psychometric properties of ANSOCQ and provide support for the use of its subdimensions in clinical practice.

A symptom level perspective on irritability, PTSD, and depression in children and adults

BACKGROUND

Although irritability is a prominent clinical manifestation among traumatized populations, its relationships with other psychopathology are rarely studied. Adopting a symptom-level perspective, this study aimed to explore how symptoms of irritability, posttraumatic stress disorder (PTSD), and depression are associated.

METHOD

The Brief Irritability Test, the PTSD Checklist for DSM-5, and the Patient Health Questionnaire-9 were used to measure irritability, PTSD, and depression, respectively, in a large sample of trauma-exposed children and adolescents (n = 5454), trauma-exposed adults (n = 4718), and children and adolescents with probable PTSD (n = 556). Exploratory graph analysis (EGA) and network analysis were conducted to examine potential communities and significant relations.

RESULTS

Although irritability, PTSD, and depression were highly correlated at the disorder level, EGA results indicated that, at the symptom level, they formed highly stable and dense communities, respectively. Relations across disorders mainly emerged at symptoms related to negative cognition, dysphoria, and suicidal thoughts. Especially, strong transdiagnostic relations across all samples were "negative belief" and "suicidal thoughts", "numbing" and "suicidal thoughts", "startle" and "moving slowly or restless", "bothering" and "moving slowly or restless". Furthermore, irritability symptoms seem more central than PTSD and depression symptoms, with "snap" being the most central node across all networks, especially in the child and adolescent sample.

CONCLUSION

Irritability, PTSD, and depression are relatively independent constructs when analyzed at the symptom level. Irritability symptoms emerged as core symptoms in trauma-exposed populations. Our findings highlight the importance of independent assessment of irritability in the diagnosis and treatment of PTSD.

Investigating the network ties between affect, attachment, and psychopathology

OBJECTIVES

Recent years have seen an increased interest regarding theoretical and empirical associations of adult attachment security and primary affective traits concerning psychiatric disorders. In this study, network analysis technique is applied to dissect the links between both psychodynamic personality constructs and an array of psychopathological symptoms.

METHODS

A total sample of 921 (69.9 % female) participants from the general population was investigated. A regularized cross-sectional partial correlation network between attachment (Experiences in Close Relationships-Revised [ECR-RD8]), primary affective traits (Brief Affective Neuroscience Personality Scales [BANPS-GL]) and psychopathological symptoms (ICD-10-Symptom-Rating Questionnaire [ISR]) was estimated via the EBICglasso algorithm. Node centrality, predictability and bridge centrality were analyzed. To evaluate the stability of the network and evaluate the significance of differences, we employed bootstrap techniques.

RESULTS

The network was found to be stable, allowing reliable interpretations. We observed SADNESS, as well as depressive, PTSD and anxiety symptoms as the most influential nodes within the investigated network. Attachment AV and SADNESS were observed as nodes with the highest bridge centrality.

CONCLUSIONS

The results provide a data-driven in-depth look into the complex dynamics between psychopathological symptoms, attachment security and basic affective traits. Results underscore the critical interconnections between affect, attachment, and psychopathology, advocating for a psychodynamically informed systems approach in psychological research that considers the affective dimensions underlying human mental health.

An exploration of blood-based biomarkers of negative symptoms of psychosis in men

Negative symptoms in the context of psychosis are still poorly understood and diagnosed, which impairs the treatment efficacy of current therapies and patient's integration in society. In this study, we aimed to test hypothesis-based and exploratory associations of negative symptom domains, as defined by the Brief Negative Symptom Scale (BNSS), with hormonal and hematological variables, and, complementarily, with standard psychological/cognitive and psychopathological measures. Fifty-one male patients diagnosed with a psychotic disorder underwent a structured interview and blood collection. Standard Spearmen bivariate correlations were used for data analysis. We obtained evidence of hypothesis-based associations between specific negative symptoms and oxytocin, thyroid stimulating hormone levels and neutrophil-to-lymphocyte ratio; as well as novel and hypothesis-free associations with erythrocyte and lymphocyte count, mean corpuscular volume and red cell distribution width. Complementarily, we also obtained some validation of previous associations of negative symptoms with illness resolution, cognitive symptom severity and social performance, and a novel association with anger contagion. We hope our results can generate new hypotheses in psychosis research. Our work suggests further avenues in research on erythrocytic, inflammatory, thyroid and oxytocin-related markers and abnormalities in psychosis, especially in regards to specific negative symptoms, towards more precise and comprehensive etiological, diagnostic and therapeutic models.

Using network analysis to identify factors influencing the heath-related quality of life of parents caring for an autistic child

BACKGROUND

Raising an autistic child is associated with increased parenting stress relative to raising typically developing children. Increased parenting stress is associated with lower parent wellbeing, which in turn can negatively impact child wellbeing.

AIMS

The current study sought to quantify parenting stress and parent health-related quality of life (HRQOL) in the autism context, and further understand the relationship between them by employing a relatively novel statistical method, Network Analysis.

METHODS AND PROCEDURES

This cross-sectional study involved 476 parents of an autistic child. Parents completed an online survey requesting information on parent and child characteristics, parent's perceptions of their autistic child's symptoms and problem behaviours, and assessed their parenting stress and HRQOL.

OUTCOMES AND RESULTS

Relative to normative data, parent HRQOL was significantly lower in terms of physical health and mental wellbeing. The structure extracted by the Network Analysis indicated that child age and externalising behaviours were the main contributors to parenting stress, and that externalising behaviours, ASD core behavioural symptoms, and parenting stress predicted HRQOL.

CONCLUSIONS AND IMPLICATIONS

Parental responses to child-related factors likely determine parent HRQOL. Findings are discussed in relation to the transactional model, emphasising the importance of both parent and child wellbeing.

Individual outcomes after tailored versus generic self-management strategies for persistent fatigue in youth with a fatigue syndrome or rheumatic condition: A multiple single-case study

OBJECTIVE

To examine individual outcomes after tailored lifestyle (PROfeel) or generic dietary advice as self-management intervention for persistent fatigue in adolescents and young adults with a chronic condition, to compare participants who did and did not benefit and to explore changes to factors in the biopsychosocial model of fatigue after PROfeel.

METHOD

A multiple single-case AB-phase design was embedded in a randomized crossover trial (N = 45). Intensive longitudinal data (ILD) on outcomes 'fatigue severity', 'self-efficacy' and 'quality of life' (QoL) were collected through weekly smartphone measurement for 20 weeks. ILD on biopsychosocial factors were collected through experience sampling methodology for 28 days pre-post first intervention. Baseline characteristics were compared with t-tests and chi-square tests. Permutation distancing tests were used to assess change over time in all ILD.

RESULTS

Regarding weekly measurements, nineteen participants (42.22%) showed small to large positive outcomes (drange = .05 to 2.59), mostly after PROfeel. Eleven participants (24.44%) showed small to moderate negative outcomes (drange = -.02 to -2.46), mostly after dietary advice. Fatigue severity improved most, followed by self-efficacy. Participants who benefitted showed higher QoL levels and lower fatigue and pain levels compared with others at baseline (all p < .02). When positive outcomes were observed after PROfeel, typically ≥1 biopsychosocial factor had been targeted successfully.

CONCLUSION

Self-management advice has more potential when tailored to individual characteristics, including the biopsychosocial model of fatigue. PROfeel appears particularly useful as fatigue intervention for individuals with relatively less severe symptoms.

Developing a transdiagnostic Ecological Momentary Assessment protocol for psychopathology

OBJECTIVES

The network approach to psychopathology posits that mental disorders emerge from dynamic interactions among psychopathology-relevant variables. Ecological Momentary Assessment (EMA) is frequently used to assess these variables in daily life. Considering the transdiagnostic nature of the network approach to psychopathology, this study describes the development of a transdiagnostic EMA protocol for psychopathology.

METHODS

First, 96 clinicians completed an online survey, providing three EMA constructs for up to three disorders they specialize in, and three EMA constructs relevant across disorders (transdiagnostic constructs). Second, 12 focus groups were conducted with clinical experts for specific types of diagnoses (e.g., mood disorders, anxiety disorders). Finally, a selection of items was reached by consensus. Two raters independently coded the online survey responses with an inter-rater agreement of 87.3%.

RESULTS

Jaccard indices showed up to 52.6% overlap in EMA items across types of diagnoses. The most frequently reported transdiagnostic constructs were mood, sleep quality, and stress. A final set of EMA items is created based on items' frequency and informativeness, ensuring completeness across diagnoses and minimizing burden.

CONCLUSIONS

The described procedure resulted in a feasible EMA protocol to examine psychopathology transdiagnostically. Feasibility was helped by the overlap in mentioned symptoms across disorders. Such overlap raises questions about the validity of DSM categories.

Examination of PTSD symptom networks over the course of cognitive processing therapy

OBJECTIVES

Cognitive processing therapy (CPT) is an evidence-based psychotherapy for posttraumatic stress disorder (PTSD); however, little is known about how interrelationships between PTSD symptoms change over the course of treatment. The current study examined baseline, midtreatment, and posttreatment PTSD symptom networks during CPT for PTSD.

METHOD

Adults with PTSD (n = 107) received 12 sessions of CPT as part of a randomized trial. Self-reported PTSD symptoms were assessed at pretreatment, midtreatment, and posttreatment, and network analysis was used to examine the interrelationships between symptoms at these three timepoints. Linear regression was conducted to examine whether any baseline symptoms or midpoint symptoms predicted overall treatment change.

RESULTS

In the baseline PTSD network, feelings of detachment and feeling upset at reminders of the trauma were central to the symptom network. These symptoms were no longer central at midtreatment, possibly suggesting that CPT quickly reduces the importance of these symptoms. These findings were consistent with regression results that, after accounting for multiple comparisons, high baseline scores of feeling upset at trauma reminders predicted later treatment change. At the conclusion of treatment, strong negative emotions were the most central symptom and may be most important in maintaining or lowering other PTSD symptoms at the conclusion of treatment.

CONCLUSIONS

Though replication is necessary, these findings offer insights into identifying which symptoms may be most predictive of treatment outcomes and the course by which CPT reduces PTSD symptoms. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

The network structures of mental and behavioral problems among children and adolescents in China using propensity score matching: A comparison between one-child and multi-child families based on a nationwide survey

BACKGROUND

Exploring networks of mental and behavioral problems in children and adolescents may identify differences between one-child and multi-child families. This study compared the network structures of mental and behavioral problems in children and adolescents in one-child families versus multi-child families based on a nationwide survey.

METHODS

Propensity score matching (PSM) was used to match children and adolescents from one-child families with those from multi-child families. Mental and behavioral problems were assessed using the Achenbach's Child Behavior Checklist (CBCL) with eight syndromal subscales. In the network analysis, strength centrality index was used to estimate central symptoms, and case-dropping bootstrap method was used to assess network stability.

RESULTS

The study included 39,648 children and adolescents (19,824 from one-child families and 19,824 from multi-child families). Children and adolescents from multi-child families exhibited different network structure and higher global strength compared to those from one-child families. In one-child families, the most central symptoms were "Social problems", "Anxious/depressed" and "Withdrawn/depressed", while in multi-child families, the most central symptoms were "Social problems", "Rule-breaking behavior" and "Anxious/depressed".

CONCLUSION

Differences in mental and behavioral problems among children and adolescents between one-child and multi-child families were found. To address these problems, interventions targeting "Social problems" and "Anxious/depressed" symptoms should be developed for children and adolescents in both one-child and multi-child families, while other interventions targeting "Withdrawn/depressed" and "Rule-breaking behavior" symptoms could be useful for those in one-child and multi-child families, respectively.

Role of interoceptive fear and maladaptive attention and behaviors in the escalation of psychopathology-a network analysis

The complex interplay of fear, attention, and behavior toward bodily sensations with psychopathological symptoms and how they mutually influence and potentially reinforce one another remains to be fully elucidated. In this study, we used a network analytical approach to unravel these complex interactions. Specifically, we aimed to identify central symptoms and etiologically relevant factors that might be associated with anxiety and depressive core symptoms. To this end, the following clusters were assessed in 791 adults: interoceptive fear, interoceptive attention, maladaptive behaviors related to bodily sensations, and core symptoms of anxiety and depression. This network was modeled using a Gaussian Graphical Model. Central variables (nodes) were identified using centrality indices and bridge analysis. Self-examination and attention to bodily sensations emerged as central nodes. Moreover, time spent paying attention to bodily sensations, fear of anxiety-related sensations, and self-examination were identified as central bridge nodes, that is, central nodes connecting psychopathologically relevant symptom clusters. The present study indicates that fear of bodily sensations, the amount of attention and time spent focusing on somatic sensations, and self-examination are central factors. The findings suggest potential targets for future longitudinal studies on the impact of these factors for the escalation of anxiety and depressive symptoms.

The comorbidity mechanism of problematic internet use and depression among Chinese college students: A cross-lagged panel network analysis

Problematic internet use (PIU) and depression usually co-occur and are common among college students. According to network theory, it may be attributed to the interplay of symptoms that connect these two mental health problems. However, most studies have failed to examine complex and subtle connections at the symptom level and have not clarified how PIU and depression symptoms are intercorrelated, which symptoms serve as the source of comorbidity (i.e., the central symptoms), and whether such a comorbidity mechanism would change with higher grades. To explore these questions, this study examined four contemporaneous networks and three cross-lagged panel networks, visualizing the symptoms as nodes and the connections between symptoms as edges. A total of 2,420 college students (Mage = 18.35, SD = 0.84; 67.98 % girls) completed four annual surveys. Overall, the results of contemporaneous networks and cross-lagged panel networks indicated that (a) PIU and depression symptoms are intercorrelated; (b) the core symptoms responsible for comorbidity mostly belonged to PIU, and (c) the comorbidity mechanism would change with time. These findings explain the dynamic relation between PIU and depression and identify possible primary symptoms that comorbidity programs can mitigate at different stages of the college years.

Network structure of adolescent social, emotional, and behavioral difficulties and their differential relationships with suicidality

BACKGROUND

Social, emotional, and behavioral difficulties (SEBDs) tend to develop during adolescence. Their presence and especially co-occurrence induce numerous disrupting consequences, including suicidality. A recently developed network analysis is suitable to investigate the symptom-level structure of comorbid psychopathology. Rather than pairwise comorbidity networks, the current study investigated a comprehensive network of SEBDs at the symptom level and explored the differential relationships between symptoms of SEBDs and suicidality.

METHODS

Recruited from four public schools in China, a sample of adolescents (N = 6974, mean age = 15.84, 50.1% boys) were assessed with the Strengths and Difficulties Questionnaire (SDQ) and one suicidality-related item. The cross-sectional network structure of the SEBD symptoms was investigated. The differential associations between individual symptoms of SEBDs and suicidality were also explored with a relative importance analysis.

RESULTS

The results showed that constantly fidgeting, worry a lot, unhappy, down-hearted, tearful, and easily scared emerged as the most central symptoms in the network of SEBDs. Worry a lot, constantly fidgeting, lose my temper, and being bullied served as bridge symptoms, connecting various domains of SEBDs. In addition, the centrality of symptoms was positively associated with the variance shared with suicidality, with worry a lot and unhappy, down-hearted, and tearful explaining a large portion of the variance of suicidality.

CONCLUSIONS

Taken together, the results were indicative of close connections among emotional, hyperactivity-inattention, peer, and conduct aspects of adolescent mental health difficulties, as well as the central role of emotional difficulties in the SEBDs network.

Exploring Temporal Relationships Between Anxiety, Mood and Mental Imagery in Patients With Bipolar Disorder: A Network Analysis

INTRODUCTION

Bipolar disorder is a severe mental health problem with limited treatment success. There is a call for improving interventions, requiring an increased understanding of factors driving mood instability. One promising avenue is to study temporal associations between factors that appear relevant according to the emotional amplifier model of Holmes are changes in mood, anxiety and mental imagery.

METHODS

The current study used data from a recent RCT for a secondary analysis which applied a network analysis approach to explore temporal associations between weekly measurements of mania, depression, anxiety and mental imagery measured during 32 weeks in two randomised groups (N = 55) receiving either imagery-focused cognitive therapy (ImCT) or group psychoeducation (PE).

RESULTS

Both negative intrusive mental imagery and anxiety appeared central in the network analyses, driving changes in both mania and depression, but only in the PE group. In the ImCT group, only anxiety was driving changes in mania and depression.

CONCLUSION

Although exploratory, findings suggest that prior increases in anxiety and negative intrusive mental imagery might be associated with subsequent increases in depression and mania symptoms in patients with bipolar disorder. Anxiety might in turn increase negative intrusive imagery and associated negative emotions. Although more research is needed, results are in line with the emotional amplifier model and stress that future interventions with a focus on anxiety and imagery might help to improve psychosocial therapies for patients with bipolar disorder. In addition, this study suggests that a network approach is a helpful and feasible way to study mood instability, anxiety and mental imagery to increase our understanding of mechanisms underpinning mood instability.

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.

Bridging personality dimensions and eating symptoms: A transdiagnostic network approach

OBJECTIVE

Eating disorders (ED) have recently been studied from a network approach, conceptualising them as a complex system of interconnected variables, while highlighting the role of non-ED symptoms and personality dimensions. This study aims to explore the connections between personality and ED symptoms, identify central nodes, and compare the EDs network to a healthy control network.

METHODS

We employed network analysis to examine the personality-ED symptom connections in 329 individuals with an ED diagnosis and 192 healthy controls. We estimated a regularised partial correlation network and the indices of centrality and bridge centrality to identify the most influential nodes for each group. Network differences between groups were also examined.

RESULTS

Low Self-Directedness and high Harm avoidance emerged as central bridge nodes, displaying the strongest relationship with ED symptoms. Both networks differed in their global connectivity and structure, although no differences were found in bridge centrality and centrality indices.

CONCLUSIONS

These findings shed light on the role of personality dimensions, such as Self-Directedness and Harm Avoidance in the maintenance of ED psychopathology, supporting the transdiagnostic conceptualisation of ED. This study advances a deeper understanding of the complex interplay between personality dimensions and ED symptoms, offering potential directions for clinical interventions.

Gender Difference in the Onset of Adolescent Depressive Symptoms: A Cross-Lagged Panel Network Analysis

Depressive symptoms are prevalent in adolescents, especially girls, underscoring the need for early detection and targeted interventions. Identifying initial symptoms and their temporal associations is vital for such interventions. This study used cross-lagged panel network (CLPN) analysis to examine the central depressive symptoms and their interconnections within a national cohort derived from the China Family Panel Study (CFPS). The participants included 2524 adolescents (45.8% girls), with depressive symptoms assessed using the Epidemiological Studies Depression Scale (CES-D-8) in 2016 (Mage = 12.30) and 2018 (Mage = 14.25). The CLPN model showed that "loneliness" and "not getting going (fatigue)" at T1 were the strongest predictors of subsequent depressive symptoms at T2, after controlling for demographic variables and depressive symptoms at T1. Conversely, depressed mood and anhedonia at T2 were most likely to be influenced by other symptoms at T1. Gender-stratified analyses identified "loneliness" as the initial symptom in girls and "fatigue" for boys. Additionally, girls exhibited stronger reciprocal associations among depressive symptoms than boys. The findings suggest that addressing interpersonal loneliness is crucial for adolescent girls, whereas somatic fatigue should be a focus for adolescent boys, highlighting the need for gender-specific approaches in early intervention strategies. This research provides insights into the distinct gendered networks of depressive symptomatology in adolescents, informing tailored prevention and intervention efforts.

Topological properties of psychopathological networks of healthy and disordered individuals across mental disorders

The identification of psychopathological markers has been the focus of several scientific fields. The results were inconsistent due to lack of a clear nosology. Network analysis, focusing on the interactions between symptoms, provided important insights into the nosology of mental disorders. These interactions originate several topological properties that could constitute markers of psychopathology. One of these properties is network connectivity, which has been explored in recent years. However, the results have been inconsistent, and the topological properties of psychopathological networks remain largely unexplored and unknown. We compared several topological properties (i.e., connectivity, average path length, assortativity, average degree, modularity, global clustering) of psychopathological networks of healthy and disordered participants across depression (N = 2830), generalized anxiety (N = 13,463), social anxiety (N = 12,814), and obsessive-compulsive disorder (N = 16,426). Networks were estimated using Bayesian Gaussian Graphical Models. The Janson-Shannon measure of divergence was used to identify differences between the network properties. Network connectivity distinguished healthy and disordered participants' networks in all disorders. However, in depression and generalized anxiety, network connectivity was higher in healthy participants. The presence and number of motifs also distinguished the networks of healthy and disordered participants. Other topological properties (i.e., modularity, clustering, average path length and average degree) seem to be disorder-specific. The psychopathological significance of network connectivity must be clarified. Some topological properties of psychopathological networks are promising markers of psychopathology and may contribute to clarifying the nosology of mental disorders.

Unveiling the Interplay Between Depressive Symptoms' Alleviation and Quality of Life Improvement in Major Depressive Disorder: A Network Analysis Based on Longitudinal Data

Background

Understanding the dynamic relationship between depressive symptoms and quality of life (QOL) is essential in improving long-term outcomes for patients with Major Depressive Disorder (MDD). While previous studies often relied on cross-sectional data, there is a pressing need for stronger evidence based on longitudinal data to better inform the development of effective clinical interventions. By focusing on key depressive symptoms, such interventions have the potential to ultimately enhance QOL in individuals with MDD.

Methods

This multi-center prospective study, conducted between 2016 and 2020, enrolled outpatients and inpatients diagnosed with MDD across twelve psychiatric hospitals in China. Longitudinal data on Patient Health Questionnaire - 9 (PHQ-9) and Quality of Life Enjoyment and Satisfaction Questionnaire-Short Form (Q-LES-Q-SF) was analyzed using an Extended Bayesian Information Criterion (EBIC) graphical least absolute shrinkage and selection operator (gLASSO) network model to explore the connections between depressive symptom changes and QOL changes. Flow network was applied to investigate relationships between individual symptom changes and overall QOL score change, as well as daily functional independence.

Results

This study included 818 participants with complete data after 8-week antidepressant treatment. Apart from the overlapping items from PHQ-9 and Q-LES-Q-SF, the three edges between "mood" (delta-QLES2) and "anhedonia" (delta-DEP1), between "physical health" (delta-QLES1) and "sleep problems" (delta-DEP3), and between "physical health" (delta-QLES1) and "sad mood" (delta-DEP2) were the most strong bridges between the cluster of depressive symptoms alleviation and the cluster of QOL change. "Anhedonia" (delta-DEP1), "sad mood" (delta-DEP2) and "loss of energy" (delta-DEP4) had the highest bridge strength between the alleviations of depressive symptoms and the total score change of Q-LES-Q-SF. Anhedonia had the greatest connection with participants' satisfaction with function in daily life.

Conclusion

This study highlighted the potential for developing highly effective interventions by targeting on central symptoms, thereby to ultimately improve QOL for patients with MDD.

Childhood trauma, resilience, psychopathology and social functioning in schizophrenia: A network analysis

The affective pathway to psychosis implicates affective symptoms and neuroticism as mediating steps between childhood trauma and symptoms of schizophrenia. Prior research seldom examined the interplay between childhood trauma, resilience, personality, social functioning and symptoms in schizophrenia patients. This study recruited 290 schizophrenia patients, and constructed a regularized partial correlation network of childhood trauma, resilience, big-five personality traits, symptoms and social functioning. We further applied flow diagram and shortest path analysis to clarify how different childhood trauma types would contribute to and reach different symptoms. In the network, emotional and physical abuse showed the highest expected influence, and resilience showed the highest strength. In flow diagrams, all nodes together contributed two-thirds of variance of social functioning (which had highest predictability). Among childhood trauma types, emotional abuse contributed most to positive symptoms; physical neglect contributed most to negative, depressive and disorganized symptoms. Childhood abuse reached positive symptoms via neuroticism and depressive symptoms, yet it reached negative symptoms via physical neglect and social functioning. Childhood neglect reached positive symptoms via resilience, conscientiousness, neuroticism and depressive symptoms, yet it reached negative symptoms via social functioning. Our findings support that different childhood trauma types contribute to different symptoms, and interacts with resilience, personality and social functioning.

A latent profile analysis and network analysis of anxiety and depression symptoms in Chinese widowed elderly

BACKGROUND

Widowhood, as a traumatic event in the aging process, may lead to adverse psychological consequences such as anxiety and depression. However, the heterogeneity of anxiety and depression comorbidity patterns in widowed elderly and the interrelationships between symptoms have not been adequately studied.

METHOD

10,239 elderly aged 65 years and older were screened from the Chinese Longitudinal Healthy Longevity Survey (CLHLS 2017-2018), to assess depression and anxiety using the Center for Epidemiologic Studies Depression Scale (CESD) and the 7-item Generalized Anxiety Disorder Questionnaire (GAD). The subgroups of widowed elderly with similar patterns of symptoms were identified by latent profile analysis (LPA). The structure of anxiety-depressive comorbidity network was characterized using "bridge expected influence" as centrality indices. Network stability was tested using a case drop bootstrap program. A network comparison test (NCT) was performed to examine the differences in network characteristics across LPA subgroups.

RESULT

LPA identified dichotomous profiles: low comorbid (n = 4457) and high comorbid (n = 692). NCT revealed a significant difference in the global strength between networks (S = 0.631, p < 0.001). GAD1 (Nervousness or anxiety) is the common bridging symptom for both networks, while the bridging symptom for the high comorbidity network also includes GAD3 (Generalized worry).

LIMITATIONS

Cross-sectional methods are unable to verify causal relationships, and further randomized controlled trials are warranted.

CONCLUSION

Anxiety-depressive pattern in Chinese widowed elderly can be categorized into a low comorbid or a high comorbid group. GAD3 (Generalized worry) can be used as the core intervention target during intervention.

Symptom network connectivity and interaction among people with HIV in China: secondary analysis based on a cross-sectional survey

BACKGROUND

The symptom burden in people with HIV (PWH) is considerable. Nonetheless, the identification of a central symptom, or bridge symptom, among the myriad symptoms experienced by PWH remains unclear. This study seeks to establish networks of symptom experiences within different clusters and investigate the relationships and interconnectedness between these symptoms in PWH.

METHODS

A multicenter, cross-sectional descriptive design was carried out in China over two periods: November 2021 to January 2022 and April 2022 to May 2022. A total of 711 PWH completed online questionnaires, providing information on demographics and the 27-item Self-Report Symptom Scale. The symptom network was analyzed using Network/Graph theory, allowing for the exploration of connections between physical, cognitive, and psychological symptoms. This analysis was based on data from a subset of 493 individuals out of the total 711 PWH.

RESULTS

A total of 493 PWH who exhibited symptoms out of a total of 711 PWH were analyzed. The average number of symptoms reported was 5.367. The most prevalent symptom was sleep disturbance (37.98%). In the node centrality analysis, a cognitive symptom, 'becoming confusing', emerged as the most central symptom with significant values for node centrality (strength = 1.437, betweenness = 140.000, closeness = 0.003). Fever was identified as the bridge symptom with the highest bridge strength (0.547), bridge closeness (0.053), lower bridge betweenness (23.000), and bridge expectedinfluence (0.285). Overall, our network displayed good accuracy and stability.

CONCLUSION

Early identification and assessment of the central or bridge symptoms should be emphasized in clinical practice. According to the findings from network analysis, healthcare providers should proactively explore intervention strategies or bundle care to alleviate the burden of symptoms and enable anticipatory care.

Dynamic patterns of COVID stress syndrome among university students during an outbreak: a time-series network analysis

OBJECTIVE

Assessing the progression of COVID stress syndrome (CSS) and understanding how cognitive and emotional factors play a role in the dynamic system is critical for prevention and intervention during the COVID-19 pandemic. We investigated the dynamic relationship between self-reported COVID stress syndrome, cognitive factors, and emotional factors through time-series network analysis.

METHODS AND MEASURES

Participants were 188 university students involved in an experience sampling method study that lasted 14 days, three times a day, during the COVID-19 pandemic period following a shift in pandemic prevention and control policy.

RESULTS

CSS symptoms are usually present simultaneously, and xenophobia is the most central node of the network. There is a complex mutual predictive relationship between CSS symptoms, in which traumatic stress symptoms are crucial in developing and maintaining the CSS symptom network. Negative affect was associated with CSS symptoms at the same time, and subjective health cognition was a significant predictor of CSS symptoms the next time.

CONCLUSIONS

Traumatic stress symptoms are essential nodes in the CSS symptom network, and negative emotions and subjective health influence the occurrence and development of CSS symptoms.

More similar than different: Characterizing special interests in autistic boys and girls based on caregiver report

Almost all autistic youths have special interests (SIs), which are focused, intense areas of passion and interest in a particular topic. Emerging research suggests that there are gender differences in SIs among autistic youth; however, commonly used measures that assess for the presence of SIs may not fully capture the granular nature of those differences between autistic boys and girls. Characterizing these differences is important for autism identification in girls, as SIs in autistic girls may often be overlooked by caregivers, teachers, and clinicians due to their more "typical" and more socially oriented content areas compared to autistic boys. This study therefore aimed to more fully characterize gender differences in SIs using a newly developed caregiver-report measure of SIs (the Special Interests Survey; SIS). Caregivers of 1921 autistic youth completed the SIS. Analyses revealed many similarities between boys and girls; there were no gender differences in mean age SI onset, caregivers' perceptions of uniqueness or interferences of endorsed SIs, or duration of previous SIs. There were gender differences in endorsement of less than half (39%) of the SI categories measured, and there were minor differences in the number of endorsed current and past SIs. Categories with significant gender differences fell along typical gender lines (e.g., more boys interested in math and construction, more girls interested in animals and arts/crafts). This study extends the growing literature on SIs and gender differences in autism and has important implications for supporting autistic youth and their families.

Unraveling the core and bridge menopausal symptoms of perimenopausal women: a network analysis

OBJECTIVE

Perimenopause is the period from the early menopausal transition to 12 months after the final menstrual period. The clustering of menopausal symptoms poses a challenge for perimenopausal management. Core symptoms are targets for interventions that can alleviate other related symptoms. Bridge symptoms are connectors that link related symptom clusters and can improve the effectiveness of interventions. This study aims to construct a network structure of menopausal symptoms and to identify core and bridge symptoms as a reference for future management.

METHODS

Two hundred forty-two Chinese perimenopausal women were included in the survey. The structure and associations of the menopausal symptoms assessed by the Greene Climacteric Scale were analyzed using a network analysis. We generated the network structure graph using R software and checked its accuracy and stability.

RESULTS

In the menopausal transition, the most prevalent symptoms were feeling tired or lacking in energy, excitability, and irritability. Sexual dysfunction was common among early postmenopausal women. Irritability (S = 7.16, C = 0.0167, B = 8) was a core symptom of the network. The depressive symptom cluster was a core symptom cluster, most of which have high centrality indices. Excitability (B = 6) was a bridge symptom connecting the anxiety and depressive symptom clusters.

CONCLUSIONS

Our study has highlighted the crucial significance of irritability and excitability in perimenopausal management. Overcoming the challenges of perimenopausal management requires the public to ameliorate the prejudice and stigma associated with emotional symptoms.

Impacts of risk thresholds and age on clinical high risk for psychosis: a comparative network analysis

One of the main goals for supporting people with a psychotic disorder is early detection and intervention, and the detection of Clinical High Risk (CHR) is a major challenge in this respect. This study sought to compare core symptoms of CHR for psychosis networks based on two CHR self-assessment tools, across different risk thresholds and age groups. This cross-sectional online investigation analyzed 936 individuals for CHR, in France and the UK, with the Prodromal Questionnaire-16 (PQ-16) and the Perceptual and Cognitive Aberrations (PCA). Twelve different symptom networks were constructed, assessing relationships, compactness, centrality, predictability, and comparisons between them, based on different thresholds and age groups. In the above-threshold PQ-16 network, the most central symptom was "Voices or whispers"; in the PCA network, the most central symptom was "Non-relevant thoughts distract or bother". They presented low overall predictability. No significant difference was found between them. This study makes three key contributions. First, this cross-network analyses highlight the relative importance of some central symptoms. Secondly, comparisons between networks demonstrate the unity of the CHR construct across scales, thresholds, and ages, affirming its phenotypic homogeneity, an essential issue for patient care pathways. Thirdly, the low average network predictability suggests the existence of unconsidered symptoms within these CHR networks. These results shed light on the organization of CHR symptoms using routine clinical questionnaires, offering insights for preventive targets in a logic of precision semiology.

A Transdiagnostic Network Analysis of Childhood Trauma and Psychopathology

BACKGROUND AND HYPOTHESIS

Psychiatric comorbidities suggest that symptoms overlap across different diagnoses; the transdiagnostic network approach is valuable for studying psychopathology. Childhood trauma is a common transdiagnostic risk factor for psychiatric disorders, but the complex relationship between childhood trauma and psychopathology has seldom been investigated using a large cross-sectional transdiagnostic sample.

STUDY DESIGN

This study recruited 869 patients with different diagnoses, including 418 schizophrenia, 215 bipolar disorder, and 236 major depressive disorder. Participants completed psychiatric interviews and self-report questionnaires. We constructed dimension- and item-level Least Absolute Shrinkage and Selection Operator-based (LASSO) networks to explore the relationship between childhood trauma, psychopathology, and duration of illness. Moreover, we constructed directed acyclic graphs (DAGs) to tentatively clarify the potential directions of associations among these variables. Network Comparison Tests (NCTs) were conducted for different diagnostic groups and gender-stratified groups.

STUDY RESULTS

The transdiagnostic LASSO networks showed that different types of childhood trauma exerted distinct impacts on various psychopathological dimensions. Emotional abuse was linked to depressive symptoms, physical abuse to excited symptoms, sexual abuse to positive and disorganized symptoms, emotional neglect to depressive symptoms and motivation and pleasure (MAP) deficits factor of negative symptoms, and physical neglect to MAP factor. The DAG findings generally concurred with the LASSO network. The NCT showed comparable networks.

CONCLUSIONS

Our findings suggest that childhood trauma is significantly associated with the development of psychopathology across different diagnostic groups. The affective pathway model suggests that early identification and tailored interventions would be needed for people with a history of childhood trauma.

Robust Inference of Dynamic Covariance Using Wishart Processes and Sequential Monte Carlo

Several disciplines, such as econometrics, neuroscience, and computational psychology, study the dynamic interactions between variables over time. A Bayesian nonparametric model known as the Wishart process has been shown to be effective in this situation, but its inference remains highly challenging. In this work, we introduce a Sequential Monte Carlo (SMC) sampler for the Wishart process, and show how it compares to conventional inference approaches, namely MCMC and variational inference. Using simulations, we show that SMC sampling results in the most robust estimates and out-of-sample predictions of dynamic covariance. SMC especially outperforms the alternative approaches when using composite covariance functions with correlated parameters. We further demonstrate the practical applicability of our proposed approach on a dataset of clinical depression (n=1), and show how using an accurate representation of the posterior distribution can be used to test for dynamics in covariance.

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.

Children's oppositional defiant disorder symptoms and neural synchrony in mother-child interactions: An fNIRS study

Interpersonal neural synchrony (INS) between mothers and children responds to the temporal similarity of brain signals in joint behavior between dyadic partners and is considered an important neural indicator of the formation of adaptive social interaction bonds. Parent-child interactions are particularly important for the development and maintenance of oppositional defiant disorder (ODD) in children, but the underlying neurocognitive mechanisms are unknown. Therefore, in the current study we measured INS between mothers and children in interactions by using simultaneous functional Near-infrared Spectroscopy (fNIRS), and explored its association with ODD symptoms in children. Seventy-two mother-child dyads were recruited to participate in the study, including 35 children with ODD and 37 healthy children to be used as a control. Each mother-child dyad was measured for neural activity in frontal, parietal, and temporal lobe regions while completing free-play as well as positive, and negative topic discussion tasks. We used Phase-locked value to calculate the synchrony strength and then used the K-means algorithm and k-space based alignment tests to confirm the specific patterns of parent-child synchrony in different brain areas. The results showed that, in free-play (right MFG and bilateral SFG), positive (left TPJ and bilateral SFGdor), and negative (bilateral SFGmed, right ANG, and left MFG) topic discussions, the mother-child pairs showed different patterns of INS. These specific INS patterns were significantly lower in the ODD group compared to the control group and were negatively associated with ODD symptoms in children. Network analyses showed that these INS patterns were connected to different nodes in the ODD symptom network. Our findings suggest that ODD mother-child dyads exhibit lower neural synchrony across a wide range of parent-child interactions. Neural synchrony in the context of interpersonal interactions provides new insights into understanding the neural mechanisms of ODD and can be used as an indicator of neural and socio-environmental factors in the network of psychological disorder symptoms.

Network analysis to prioritize issues for intervention to improve the health-related quality of life of people with HIV in Spain

OBJECTIVES

The objective is to assess the interconnectedness of a network of health-related quality of life (HRQoL) variables among people with HIV (PHIV) to identify key areas for which clinical interventions could improve HRQoL for this population.

METHODS

Between 2021 and 2023, we carried out a cross-sectional study within the Spanish CoRIS cohort. We conducted a weighted and undirected network analysis, which examines complex patterns of relationships and interconnections between variables, to assess a network of eight HRQoL dimensions from the validated Clinic Screening Tool for HIV (CST-HIV): anticipated stigma, psychological distress, sexuality, social support, material deprivation, sleep and fatigue, cognitive problems and physical symptoms.

RESULTS

A total of 347 participants, predominantly male (93.1%), currently working (79.0%), self-reported homosexual (72.6%) and college-educated (53.9%), were included in the study. Psychological distress showed the highest centrality in the network, indicating its strong connections with sleep and fatigue, cognitive problems and social support within the HRQoL network.

CONCLUSIONS

Psychological distress, sleep and fatigue, cognitive issues and social support were identified as key factors in an HRQoL network, indicating that interventions focused on these areas could significantly enhance overall well-being.

Cross-Lagged Panel Networks of Sleep Inertia Across Its Distinct Change Patterns Among Intern Nurses with Shift Work in China

Purpose

Although experimental psychopathology using PET, EEG, and fMRI is at the forefront of understanding the underlying mechanisms of sleep inertia, many questions concerning causality remain unanswerable due to ethical constraints and the use of small and heterogeneous samples in experimental methods. There is a pressing need for a novel perspective in a large and relatively homogeneous population to fully capture and elucidate longitudinal processes and dynamic causality that culminate in episodes of sleep inertia over time. Therefore, this study aimed to reveal the causal relationships between symptoms of sleep inertia across its distinct patterns.

Patients and Methods

A total of 1636 intern nurses participated in the first survey (94.1% validity rate), then 1277 intern nurses were followed up (82.9% tracing rate). Symptoms of sleep inertia were self-reported using the Sleep Inertia Questionnaire. The cross-lagged panel network models were used to examine unique longitudinal relationships between symptoms of sleep inertia across distinct trajectories.

Results

Four distinct trajectories of sleep inertia were established. Additionally, we found differences in those symptoms with the highest influence on other symptoms at the subsequent point across the networks of four trajectories, particularly, "Difficulty in concentrating" in the persistent-high group and "Feeling tense" in the deteriorating groups.

Conclusion

The current study highlights changes in sleep inertia based on the long-term course over time. Notably, symptoms of "Difficulty in concentrating" and "Feeling tense" are imperative to address these specific symptoms within subpopulations.

The association between online learning, perceived parental relationship, anxiety, and depression symptoms among secondary school students: insight from symptom network and cross-lagged panel network approach

INTRODUCTION

Anxiety and depression often co-occur in adolescents, with factors from family and school playing a significant role in the comorbidity. However, network analysis has not examined and clarified the detailed bridge and central symptoms of this comorbidity caused by online learning and perceived parental relationships across different COVID-19 times.

METHODS

Over four months, 2,356 secondary school students completed the Patient Health Questionnaire-9 and Generalized Anxiety Disorder Scale-7. Participants were divided into harmonious and disharmonious groups based on their answers to a question about parental conflicts.

RESULTS

The results indicated that adolescents perceiving more parental conflicts showed a denser comorbidity network after four months of online learning. Significant bridge symptoms decreased from three to two across two waves in the harmonious group, while in the disharmonious group, they increased from two to three. The number of central symptoms increased from one in wave 1 to three in wave 2 for the harmonious group, while four in wave 1 decreased to two in wave 2 for the disharmonious group. Furthermore, the CLPN analysis revealed that the strongest positive cross-lagged edge intensity between symptoms was anhedonia-energy in the harmonious group, with anhedonia being the most trigger symptom. In contrast, for the disharmonious group, guilt-suicide and trouble relaxing-excessive worry were the strongest cross-lagged edge, and trouble relaxing was the most trigger symptom.

CONCLUSION

These findings may have implications for interventions designed to promote adolescent mental health in the context of online learning and parental conflicts.

Nurse burnout: deep connections and solutions revealed by network analysis

BACKGROUND

Burnout is very important to nurses' physical and mental health and career development. Current approaches to assessing nurse burnout tend to use a total score modeling paradigm to explore the impact of external factors on burnout. The purpose of this study is to delve into the item-level relationship between nurse burnout and its influencing factors at both the social and psychological levels using a network analysis approach.

METHODS

This study was conducted in June 2023 and 1,005 nurses from 4 hospitals out of 8 tertiary care hospitals in Harbin were selected to participate in this study using whole cluster sampling method. Measurements included a general demographic questionnaire, Trait coping styles questionnaire, Organizational commitment questionnaire, Work-family conflict scale, Transformational leadership questionnaire, and Maslach Burnout Inventory-General Survey.

RESULTS

Our results suggest that "C1 Time-Based work interference with family" showed the strongest centrality and bridging in the overall network. This finding underscores its centrality to burnout. Other strongest bridge symptoms included "E2 Reduced personal accomplishment" and "A1 Positive coping styles" indicating their strongest connections to other clusters.

CONCLUSIONS

Nurse administrators should be encouraged to pay more attention to nurses' work situations and family distress, and to help nurses in a flexible way.

Modelling the longitudinal dynamics of paranoia in psychosis: A temporal network analysis over 20 years

BACKGROUND

Paranoia is a key feature of psychosis that can be highly debilitating. Theories of paranoia mostly interface with short-scale or cross-sectional data models, leaving the longitudinal course of paranoia underspecified.

METHODS

We develop an empirical characterisation of two aspects of paranoia - persecutory and referential delusions - in individuals with psychosis over 20 years. We examine delusional dynamics by applying a Graphical Vector Autoregression Model to data collected from the Chicago Follow-up Study (n = 135 with a range of psychosis-spectrum diagnoses). We adjusted for age, sex, IQ, and antipsychotic use.

RESULTS

We found that referential and persecutory delusions are central themes, supported by other primary delusions, and are strongly autoregressive - the presence of referential and persecutory delusions is predictive of their future occurrence. In a second analysis we demonstrate that social factors influence the severity of referential, but not persecutory, delusions.

IMPLICATIONS

We suggest that persecutory delusions represent central, resistant states in the cognitive landscape, whereas referential beliefs are more flexible, offering an important window of opportunity for intervention. Our data models can be collated with prior biological, computational, and social work to contribute toward a more complete theory of paranoia and provide more time-dependent evidence for optimal treatment targets.

Perfectionism, self-esteem, and affective symptoms in anorexia nervosa subtypes: A network analysis of French inpatients

OBJECTIVE

Previous studies have highlighted the relevance of perfectionism, self-esteem, and anxio-depressive symptoms in anorexia nervosa (AN). However, the relationships between these factors and cardinal eating disorders (ED) symptoms remain unclear, particularly in AN subtypes. This study aimed to examine their interconnections using network analysis.

METHOD

The sample included n = 338 inpatients with AN who completed the Eating Disorder Examination Questionnaire, Frost Multidimensional Perfectionism Scale, Rosenberg Self-Esteem Scale, and Hospital Anxiety and Depression Scale. Using network analysis, we estimated three networks: full sample, AN-restrictive (AN-R) and AN-binge/purging (AN-BP) subtypes. We estimated central and bridge symptoms using expected influence and conducted an exploratory network comparison test to compare AN subtypes.

RESULTS

Overvaluation of Weight and Shape, Concern over Mistakes, and Personal Standards were consistently central in all networks. The most central bridge symptoms across all networks were Concern over Mistakes and Self-Esteem. Concern over Mistakes bridged perfectionism and ED symptoms, while Self-Esteem was highly connected to all symptom clusters. Anxiety was significantly more central in the AN-R network compared to the AN-BP network.

CONCLUSIONS

The present study contributes to a growing body of network studies suggesting that nodes related to perfectionism are just as central as cardinal ED symptoms, indicating the relevance of perfectionism in ED pathology. The high bridge centrality of self-esteem suggests that it may be an important link between perfectionism, mood, and ED symptoms. Future research should investigate the efficacy of targeting multiple psychological factors in the treatment of AN, as well as their potential transdiagnostic relevance.

Genetic network structure of 13 psychiatric disorders in the general population

Psychiatric disorders frequently co-occur and share common symptoms and genetic backgrounds. Previous research has used genome-wide association studies to identify the interrelationships among psychiatric disorders and identify clusters of disorders; however, these methods have limitations in terms of their ability to examine the relationships among disorders as a network structure and their generalizability to the general population. In this study, we explored the network structure of the polygenic risk score (PRS) for 13 psychiatric disorders in a general population (276,249 participants of European ancestry from the UK Biobank) and identified communities and the centrality of the network. In this network, the nodes represented a PRS for each psychiatric disorder and the edges represented the connections between nodes. The psychiatric disorders comprised four robust communities. The first community included attention-deficit hyperactivity disorder, autism spectrum disorder, major depressive disorder, and anxiety disorder. The second community consisted of bipolar I and II disorders, schizophrenia, and anorexia nervosa. The third group included Tourette's syndrome and obsessive-compulsive disorder. Cannabis use disorder, alcohol use disorder, and post-traumatic stress disorder make up the fourth community. The PRS of schizophrenia had the highest values for the three metrics (strength, betweenness, and closeness) in the network. Our findings provide a comprehensive genetic network of psychiatric disorders and biological evidence for the classification of psychiatric disorders.

Relationships between trauma types and psychotic symptoms: A network analysis of patients with psychotic disorders in a large, multi-country study in East Africa

BACKGROUND

The link between trauma exposure and psychotic disorders is well-established. Further, specific types of trauma may be associated with specific psychotic symptoms. Network analysis is an approach that can advance our understanding of the associations across trauma types and psychotic symptoms.

METHODS

We conducted a network analysis with data from 16,628 adult participants (mean age [standard deviation] = 36.3 years [11.5]; 55.8% males) with psychotic disorders in East Africa recruited between 2018 and 2023. We used the Life Events Checklist and the Mini International Neuropsychiatric Interview to determine whether specific trauma types experienced over the life course and specific psychotic symptoms were connected. We used an Ising model to estimate the network connections and bridge centrality statistics to identify nodes that may influence trauma types and psychotic symptoms.

RESULTS

The trauma type "exposure to a war zone" had the highest bridge strength, betweenness, and closeness. The psychotic symptom "odd or unusual beliefs" had the second highest bridge strength. Exposure to a war zone was directly connected to visual hallucinations, odd or unusual beliefs, passivity phenomena, and disorganized speech. Odd or unusual beliefs were directly connected to transportation accidents, physical assault, war, and witnessing sudden accidental death.

CONCLUSION

Specific trauma types and psychotic symptoms may interact bidirectionally. Screening for psychotic symptoms in patients with war-related trauma and evaluating lifetime trauma in patients with odd or unusual beliefs in clinical care may be considered points of intervention to limit stimulating additional psychotic symptoms and trauma exposure. This work reaffirms the importance of trauma-informed care for patients with psychotic disorders.

Associations Between Internet-Specific Parenting, General Parenting, and Adolescents' Online Behaviors: A Cross-Lagged Panel Network Analysis

Parents play a crucial role in adolescents' Internet use. Both general parenting (i.e., autonomy-supportive and controlling parenting) and Internet-specific parenting (i.e., restrictive mediation, active mediation, and parental encouragement) are related to adolescents' online behaviors. However, existing studies have focused either on an Internet-specific parenting or general parenting strategy and have neglected their interaction, failing to capture the intricate nature of the parenting context of youth's online behaviors. Few studies have examined parental encouragement or acknowledged the bidirectional influence of parenting on adolescents' online behaviors. To address this gap, this study employed a cross-lagged panel network model to examine the associations among restrictive and active mediation, parental encouragement, and autonomy-supportive and controlling parenting, as well as the interplay of all five parenting strategies with adolescents' online behaviors. A total of 564 Chinese students (51.1% male; mean age = 14.54, SD = 0.7) completed the survey at two time points. The results indicate that in most cases, previous online behaviors are significant and strong predictors of subsequent parenting strategies and not vice versa, corroborating the child effect. The parent and reciprocal effects were observed in the problematic smartphone-use domain, suggesting that the effects may differ for distinct behavioral domains. The effects of parental mediation extend beyond parental encouragement, implying that risk-prevention-related parenting is an effective means of guiding adolescents' online behaviors. Autonomy-relevant general parenting is closely related to active mediation and parental encouragement, while restrictive general parenting is closely related to restrictive mediation, suggesting a consistency between Internet-specific and general parenting strategies.

Stress from early life to adulthood: Is there a protective role of cognitive control?

Early life events can have long-lasting effects that may impact the quality of life into adulthood. The link between childhood adversities and adult mental and physical health is well documented, however, the underlying mechanisms remain poorly understood. Executive functions are assumed to be a key factor in successfully dealing with cognitive-emotional challenges thereby contributing to stress resilience and mental health across the lifespan. Here, we examined whether cognitive control moderates the link between early life adversity and depression. Data was available from a sample of 424 participants aged 20-70 years (Clinicaltrials.gov: NCT05155397). They performed in the Stroop task and behavior as well as frontal theta power were recorded. Negative childhood experiences were assessed with the Childhood Trauma Questionnaire (CTQ), chronic stress was measured with the Trier Inventory for Chronic Stress (TICS) and depression symptoms with Beck's Depression Inventory (BDI). The CTQ predicted symptoms of chronic stress and depression. Regression models pointed to the TICS as a crucial mediator in the relationship between CTQ and BDI. However, parameters of cognitive control demonstrated a rather weak effect as moderators. These results indicate that chronic stress is an important mediator linking childhood trauma to depression but suggest only a limited role for cognitive control.

Network analysis of social anxiety and problematic mobile phone use in Chinese adolescents: A longitudinal study

Social anxiety is a common comorbid factor of problematic mobile phone use, but the relationship between them from the inside structure has been underexplored. This two-wave longitudinal study aims to identify the central symptoms of problematic mobile phone use and social anxiety, respectively, as well as the bridge symptoms between the two disorders. Furthermore, this study examined the time and gender differences. A total of 3,294 Chinese adolescents were recruited during two waves (T1: January 2023; T2: August 2023), and completed the questionnaires of social anxiety and problematic mobile phone use. Through network analysis, the results showed that 1) the central symptom of problematic mobile phone use was "loss of control" both at T1 and T2, 2) the central symptom of social anxiety was "fear of negative evaluation" both at T1 and T2, and 3) the bridge symptom between social anxiety and problematic mobile phone use was "withdrawal" both at T1 and T2. Moreover, the network comparison test indicated that the nodes of social anxiety were more strongly associated with "craving", "loss of control", and "negative life consequences" of problematic mobile phone use at T2 than at T1. The nodes of social anxiety were more strongly associated with "negative life consequences" of problematic mobile phone use for boys than for girls, while the "fear of negative evaluation" was more strongly associated with "loss of control" for girls than for boys. These findings provide new scientific basis for interventions targeting adolescents who are susceptible to social anxiety and problematic mobile phone use.