Problematic pornography use and novel patterns of escalating use: A cross-sectional network analysis with two independent samples

Modern internet pornography allows users to harness sexual novelty in numerous ways, which can be used to overcome desensitisation through increasing volume of use (quantitative tolerance), progressing to more stimulating genres (qualitative escalation), skipping between stimuli (tab-jumping), delaying orgasm ('edging'), and engaging in pornographic binges. However, existing research has not yet evaluated how these potentially reciprocal consumption patterns relate to problematic pornography use (PPU). To this end, we recruited two independent samples of male pornography users (N1 = 1,356, Mage = 36.86, SD = 11.26; N2 = 944, Mage = 38.69, SD = 12.26) and examined the relationships between these behavioural dimensions and self-reported difficulties in controlling one's pornography use. Data were analysed through the network analysis approach (using Gaussian graphical models). As hypothesised, i) quantitative tolerance was centrally placed within the overall network, and ii) acted as a statistical bridge node between other patterns of pornography use (e.g., pornographic binges), and all measured facets of PPU. Our results are consistent with other emerging literature suggesting that tolerance, pornographic binges, tab-jumping, and edging behaviours as relevant features ofPPU, and that upscaling overall usage may connect broader patterns of use with problematic engagement. Clinical and theoretical implications, as well as future research directions, are discussed.

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.

The network structures of depressive and insomnia symptoms among cancer patients using propensity score matching: Findings from the Health and Retirement Study (HRS)

OBJECTIVE

Both depression and insomnia are found to be more prevalent in cancer patients compared to the general population. This study compared the network structures of depression and insomnia among cancer patients versus cancer-free participants (controls hereafter).

METHOD

The 8-item Center for Epidemiological Studies Depression Scale (CESD-8) and the 4-item Jenkins Sleep Scale (JSS-4) were used to measure depressive and insomnia symptoms, respectively. Propensity score matching (PSM) was used to construct the control group using data from the Health and Retirement Study (HRS). In total, a sample consisting of 2216 cancer patients and 2216 controls was constructed. Central (influential) and bridge symptoms were estimated using the expected influence (EI) and bridge expected influence (bridge EI), respectively. Network stability was assessed using the case-dropping bootstrap method.

RESULT

The prevalence of depression (CESD-8 total score ≥ 4) in cancer patients was significantly higher compared to the control group (28.56 % vs. 24.73 %; P = 0.004). Cancer patients also had more severe depressive symptoms relative to controls, but there was no significant group difference for insomnia symptoms. The network structures of depressive and insomnia symptoms were comparable between cancer patients and controls. "Felt sadness" (EI: 6.866 in cancer patients; EI: 5.861 in controls), "Felt unhappy" (EI: 6.371 in cancer patients; EI: 5.720 in controls) and "Felt depressed" (EI: 6.003 in cancer patients; EI: 5.880 in controls) emerged as the key central symptoms, and "Felt tired in morning" (bridge EI: 1.870 in cancer patients; EI: 1.266 in controls) and "Everything was an effort" (bridge EI: 1.046 in cancer patients; EI: 0.921 in controls) were the key bridge symptoms across both groups.

CONCLUSION

Although cancer patients had more frequent and severe depressive symptoms compared to controls, no significant difference was observed in the network structure or strength of the depressive and insomnia symptoms. Consequently, psychosocial interventions for treating depression and insomnia in the general population could be equally applicable for cancer patients who experience depression and insomnia.

Dissociative Experiences, Borderline Personality Disorder Features, and Childhood Trauma: Generating Hypotheses from Data-Driven Network Analysis in an International Sample

Dissociation is a multifaceted phenomenon that occurs in various mental disorders, including borderline personality disorder (BPD), but also in non-clinical populations. Severity of childhood trauma (abuse, neglect) plays an important role in the development of dissociation and BPD. However, the complex interplay of different dissociative symptoms, BPD features, and self-reported childhood trauma experiences is not yet fully understood. Graph-theoretical network analysis can help to better understand such multivariate interrelations. Objective: This study aimed to investigate associations between self-reported dissociation, BPD features, and childhood trauma experiences using a graph-theoretical approach. Data was collected online via international mental health platforms and research sites. N = 921 individuals (77.4% female) were included; 40% reported pathological levels of dissociation. Variables were assessed with established psychometric scales (Dissociative Experiences Scale; Personality Assessment Inventory Borderline Features Scale; Childhood Trauma Questionnaire) and analyzed within a partial correlation network. Positive bivariate correlations between all variables were found. When accounting for their mutual influence on each other, dissociation was predominantly connected to BPD features with effect sizes between rp = .028 and rp = .126, while still showing a slight unique relationship with physical neglect (rp = .044). Findings suggest close associations between dissociative experiences and BPD features. While childhood trauma plays an important role in the development of dissociation and BPD, its recall may not fully explain their current co-occurrence. Prospective studies are needed to shed more light on causal pathways to better understand which factors contribute to dissociation and its link to BPD (features).

Psychometric Evaluation of the Affective Reactivity Index Among Children and Adolescents in China: A Multi-Method Assessment Approach

The Affective Reactivity Index (ARI) is one of the most studied scales for assessing youth irritability, but little is known about its measurement performance in community populations. This study applied item response theory (IRT), network analysis, and classical test theory (CTT) to examine the psychometric properties of the ARI in a sample of n = 395 community-based children (Mage = 13.44, SD = 2.51) and n = 403 parents. In this sample, the ARI demonstrated good reliability, as well as convergent and concurrent validity. The one-factor structure was supported by both confirmatory factor analysis (CFA) and network analysis. IRT analysis revealed that the ARI effectively distinguished between various levels of irritability within the community population. Network analysis identified "Loses temper easily,""Gets angry frequently," and "Often loses temper" are central aspects of irritability. The findings support the ARI as a brief, reliable, and valid instrument to assess irritability in community children and adolescents.

Understanding heterogeneity, comorbidity, and variability in depression: Idiographic models and depression outcomes

This study uses time-intensive, item-level assessment to examine individual depressive and co-occurring symptom dynamics. Participants experiencing moderate-severe depression (N = 31) completed ecological momentary assessment (EMA) four times per day for 20 days (total observations = 2480). We estimated idiographic networks using MDD, anxiety, and ED items. ED items were most frequently included in individual networks relative to depression and anxiety items. We built ridge and logistic regression ensembles to explore how idiographic network centrality metrics performed at predicting between-subject depression outcomes (PHQ-9 change score and clinical deterioration, respectively) at 6-months follow-up. For predicting PHQ-9 change score, R2 ranged between 0.13 and 0.28. Models predicting clinical deterioration ranged from no better than chance to 80 % accuracy. This pilot study shows how co-occurring anxiety and ED symptoms may contribute to the maintenance of depressive symptoms. Future work should assess the predictive utility of psychological networks to develop understanding of how idiographic models may inform clinical decisions.

Evaluation of symptom network density as a predictor of treatment outcome of inpatient psychotherapy

OBJECTIVE

The network approach implies that the persistence of a mental disorder is rooted in a dense causal interconnection of symptoms. This study attempts to replicate and generalize previous findings in support of the assumption that higher density predicts poorer outcomes. The study examines the predictive value of network density at admission for recovery after inpatient treatment.

METHOD

N = 1375 adult patients with various forms of mental illness were classified as recovered (28%) versus not recovered (72%) after inpatient treatment. Recovery was defined as clinically significant improvement in impairment from admission to discharge. Networks of transdiagnostic symptoms at the time of admission were estimated. Network density, measured by global strength d, was compared between the recovered and not recovered groups using a permutation test.

RESULTS

Global strength at the time of admission tended to be higher in the No-Recovery group (d = 10.83) than the Recovery group (d = 7.53) but the association was not significant (p = .12). Similar results were found after controlling for group size and symptom severity.

CONCLUSION

The predictive value of network density for treatment outcomes remains unclear. There might be structural differences between the groups that the current measure of network density does not adequately represent.

Unravelling inter-relations within and between psychodynamic constructs and psychopathology using network analysis

Psychodynamic constructs and psychopathology are closely inter-related, but more detailed insight is needed. We investigated these complex inter-relations using network analysis. A Gaussian graphical model in a sample of N = 2232 psychotherapeutic inpatients was estimated. Self-administered questionnaires to assess interpersonal relations (Inventory of Interpersonal Problems-32), psychodynamic conflicts (Operationalized Psychodynamic Diagnosis-Conflict Questionnaire), personality functioning (Operationalized Psychodynamic Diagnosis-Structure Questionnaire-Short Form, Inventory of Personality Organization-Short Form), and psychopathology (Brief Symptom Inventory) were utilized. We investigated the network structure, identified the most inter-related psychodynamic constructs and the psychodynamic constructs with the strongest inter-relations to psychopathology, and explored the clustering of all included constructs. Active and passive conflict processing modes were negatively inter-related in most conflicts. Passive conflict processing modes were more strongly related to psychopathology than active ones in all conflicts, apart from the care versus autarky conflict. Identity diffusion shared the strongest inter-relations within psychodynamic constructs. The psychodynamic constructs that were most strongly related to psychopathology were impairments in self-perception and the passive self-worth conflict. Psychopathology and psychodynamic constructs formed distinct clusters. Our results emphasize the relevance of personality functioning within psychodynamic constructs and in relation to psychopathology.

Interaction between anxiety symptoms and decreased meaning in life: One possible pathway linking childhood trauma and depression- evidence from the network analysis

BACKGROUND

Robust evidence suggests that individuals exposed to childhood trauma are more vulnerable to suffering from later depression. However, the pathway connecting the experience of childhood trauma and depression remains unclear.

PARTICIPANTS AND SETTINGS

A total of 3663 participants from six colleges in China completed the Childhood Trauma Questionnaire-Short Form, Patient Health Questionnaire-9, Generalized Anxiety Disorder Scale-7, and Multidimensional Existential Meaning Scale. Among all participants, 3115 (Mage = 19.20, SDage = 1.38, males = 1384) participants met the selective standard of suffering from childhood trauma and were divided into the traumatized depressed group (the DT group) (n = 1432, Mage = 19.26, males = 700) and traumatized non-depressed group (the UDT group) (n = 1683, Mage = 19.15, males = 684).

METHODS

In the present study, we examined the comorbidity of anxiety and the facets of meaning in the life network model. We then calculated the bridge symptoms and compared the networks of the DT group and the UDT group.

RESULTS

The results of the t-test showed that the DT group scored significantly higher on all symptoms of anxiety and significantly lower on all dimensions of meaning in life compared to the UDT group. Meanwhile, the strongest bridge exists between "Mattering" and "Restlessness" in the symptom network of the DT group, while there is no bridge in the symptom network of the UDT group. The result of NCT indicates that the global strength and the EI value of "Mattering" are significantly higher in the symptom network of the DT group than in the UDT group.

CONCLUSION

Intervention targeting improving the self-esteem of individuals suffering from childhood trauma may help to alleviate their depression and anxiety symptoms.

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

BACKGROUND

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

METHODS

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

RESULTS

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

LIMITATIONS

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

CONCLUSIONS

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

Exploring the complex interrelation between depressive symptoms, risk, and protective factors: A comprehensive network approach

BACKGROUND

Depressive symptoms seem to be interrelated in a complex and self-reinforcing way. To gain a better understanding of this complexity, the inclusion of theoretically relevant constructs (such as risk and protective factors) offers a comprehensive view into the complex mechanisms underlying depression.

METHODS

Cross-sectional data from individuals diagnosed with a major depressive disorder (N = 986) and healthy controls (N = 1049) were analyzed. Participants self-reported their depressive symptoms, as well as several risk factors and protective factors. Regularized partial correlation networks were estimated for each group and compared using a network comparison test.

RESULTS

Symptoms of depression were more strongly connected in the network of depressed patients than in healthy controls. Among the risk factors, perceived stress, the experience of negative life events, emotional neglect, and emotional abuse were the most centrally embedded in both networks. However, the centrality of risk factors did not significantly differ between the two groups. Among the protective factors, social support, personal competence, and acceptance were the most central in both networks, where the latter was significantly more strongly associated with the symptom of self-hate in depressed patients.

CONCLUSION

The network analysis revealed that key symptoms of depression were more strongly connected for depressed patients than for healthy controls, and that risk and protective factors play an important role, particularly perceived stress in both groups and an accepting attitude for depressed patients. However, the purpose of this study is hypothesis generating and assisting in the potential selection of non-symptom nodes for future research.

Sleep Health Analysis Through Sleep Symptoms in 35,808 Individuals Across Age and Sex Differences: Comparative Symptom Network Study

BACKGROUND

Sleep health is a multidimensional construct that includes objective and subjective parameters and is influenced by individual sleep-related behaviors and sleep disorders. Symptom network analysis allows modeling of the interactions between variables, enabling both the visualization of relationships between different factors and the identification of the strength of those relationships. Given the known influence of sex and age on sleep health, network analysis can help explore sets of mutually interacting symptoms relative to these demographic variables.

OBJECTIVE

This study aimed to study the centrality of symptoms and compare age and sex differences regarding sleep health using a symptom network approach in a large French population that feels concerned about their sleep.

METHODS

Data were extracted from a questionnaire provided by the Réseau Morphée health network. A network analysis was conducted on 39 clinical variables related to sleep disorders and sleep health. After network estimation, statistical analyses consisted of calculating inferences of centrality, robustness (ie, testifying to a sufficient effect size), predictability, and network comparison. Sleep clinical variable centralities within the networks were analyzed by both sex and age using 4 age groups (18-30, 31-45, 46-55, and >55 years), and local symptom-by-symptom correlations determined.

RESULTS

Data of 35,808 participants were obtained. The mean age was 42.7 (SD 15.7) years, and 24,964 (69.7%) were women. Overall, there were no significant differences in the structure of the symptom networks between sexes or age groups. The most central symptoms across all groups were nonrestorative sleep and excessive daytime sleepiness. In the youngest group, additional central symptoms were chronic circadian misalignment and chronic sleep deprivation (related to sleep behaviors), particularly among women. In the oldest group, leg sensory discomfort and breath abnormality complaint were among the top 4 central symptoms. Symptoms of sleep disorders thus became more central with age than sleep behaviors. The high predictability of central nodes in one of the networks underlined its importance in influencing other nodes.

CONCLUSIONS

The absence of structural difference between networks is an important finding, given the known differences in sleep between sexes and across age groups. These similarities suggest comparable interactions between clinical sleep variables across sexes and age groups and highlight the implication of common sleep and wake neural circuits and circadian rhythms in understanding sleep health. More precisely, nonrestorative sleep and excessive daytime sleepiness are central symptoms in all groups. The behavioral component is particularly central in young people and women. Sleep-related respiratory and motor symptoms are prominent in older people. These results underscore the importance of comprehensive sleep promotion and screening strategies tailored to sex and age to impact sleep health.

Network structure of complex interactions of premenstrual syndrome and influencing factors in young adult women

BACKGROUND

In the transition phase from adolescence to adulthood, premenstrual syndrome (PMS) occurs more commonly, with a variety of symptoms. The occurrence of PMS may be the result of a combination of demographic, physiological, psychological and sociological factors. This study aimed to identify the central symptoms of PMS, and explored the complex influencing factors especially the one-to-one inter-relationships factors with specific symptoms.

METHOD

This is a cross-sectional study conducted in mainland China. 3458 young adult women were assessed. Using the Premenstrual Syndrome Scale (PSS) to assess the PMS, and PSS score was over 6 divided into PMS group, and vice versa. Influencing factors were assessed by a set of self-reported questionnaire. Network analysis was used to examined the interplay of PMS, whilst also considering the influencing factors of PMS.

RESULTS

In summary, 1479 participants were in PMS group. Anxiety had the highest strength centrality (1.12/1.09), shown higher centrality in the both network. Swelling of the hands or feet also shown higher strength centrality (0.89) in PMS group. PMS is associated with a higher history of dysmenorrhea, and neurotic personality. Neurotic personality - depressed mood/nervousness (0.27/0.23), history of dysmenorrhea - abdominal distension (0.21), had significantly higher weight than other edges in PMS group.

CONCLUSION

Anxiety was the most central symptom in the network, and was closely associated with other symptoms like depressed mood, which provided additional evidence for the centrality of emotional features in PMS. Moreover, the influencing factors of PMS combined demographic, physiological, psychological, and sociological factors. According to the central symptoms and factors affecting the specific PMS symptoms in young adult women, targeted intervention is helpful to prevent and alleviate PMS.

LIMITATION

Cross-sectional design cannot infer the directionality of the associations between variables. All data is self-reported with recall bias and the edge weights across the constructs of influencing factors and PMS were fairly small.

Exploring networks of complex developmental trauma symptomatology among children and adolescents involved in child welfare

Background

Clinical presentations of child and adolescent psychopathology can vary systematically for boys and girls. While network analysis is increasingly being applied to explore psychopathology in adults, there is a dearth of network studies considering differences in symptoms for boys and girls, particularly in developmental trauma-related symptomatology.

Methods

This study involves rural children (n = 375, 39.47% girls) and adolescents (n = 291, 51.20% girls) involved with child protection services in Ontario, Canada. Caregivers completed the Assessment Checklist for Children or Adolescents within the first 6 months of care. Psychometric network analyses were conducted using subscales for boys and girls. Differences were examined via network comparison permutation tests, moderated network models, and independent t-tests.

Results

Attachment-related interpersonal difficulties were the most central nodes in the child and adolescent networks for both boys and girls. Emotional dysregulation also had high strength centrality for adolescents. While network comparison tests found the overall network structures and global network strength to be invariant between boys and girls for children and adolescents, moderated network models and independent t-tests revealed several differences with regards to the expression of specific symptoms. Among children, girls exhibited more indiscriminate and pseudomature interpersonal behaviors, whereas boys expressed significantly more non-reciprocal interpersonal behaviors and self-injury. Adolescent girls exhibited more behavioral dysregulation and suicide discourse in the moderated network model; t-tests also indicated higher levels of emotional dysregulation, negative self-image, and other items considered clinically important complex trauma symptoms (e.g., distrust of adults, confused belonging).

Discussion

This study supports evidence of differences in the expression of complex trauma symptomatology for boys and girls. Additionally, girls exhibit more symptoms, in general. Consistent with the transdiagnostic conceptualization of the consequences of developmental trauma, findings demonstrate the primacy of attachment-specific difficulties and emotion dysregulation.

Interpersonal relationships and suicidal ideation among Chinese youths: A network analysis

BACKGROUND

Suicidal ideation is a noteworthy health problem that requires further study in the field of interpersonal relationships. The main scope of relationships include family, teachers, peers, and the Internet. However, few studies have considered the effects of interpersonal interactions. Based on the Interpersonal Theory of Suicide, this study explores the relation between different interpersonal relationships and suicidal ideation.

METHODS

A network analysis approach was used to test the relationships. Cross-sectional data (N = 1694; 52.1 % boys; Mage = 11.86 years, SD = 1.59) were collected from primary and secondary students in October-November 2022. Participants completed a survey including demographic part and questionnaires: Positive and Negative Suicide Ideation Inventory (PANSI), Interpersonal Needs Questionnaire (INQ), Family Adaptability and Cohesion Evaluation Scale (FACES II), Inventory of Parent and Peer Attachment (IPPA), Student-Teacher Relationship Scale (STRS) and Facebook Intensity Scale (FIS).

RESULTS

All variables showed a significant correlation in this inferred network. Family, teacher-student, and peer relationships are protective against suicidal ideation. The closeness of the teacher-student relationship showed the highest strength centrality. However, online interpersonal relationship is a risk factor for suicide. Thwarted belongingness and perceived burdensomeness are proximal factors of suicidal ideation that influenced all interpersonal relationships.

LIMITATIONS

The network analysis as a data-driven and exploratory method may be limited to provide exact cause and effect relationship.

CONCLUSIONS

This study shows that teacher-student connections may be more important than other relationships of young people. Improper peer and online interpersonal relationship could be risky for suicide. Further studies are needed to examine the role of these relationships elaborately.

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.

Eating disorder symptom dimensions and protective factors: A structural network analysis study

Eating Disorders (EDs) and related symptoms pose a substantial public health concern due to their widespread prevalence among both genders and associated negative outcomes, underscoring the need for effective preventive interventions. In this context, deepening our understanding of the interplay between ED symptoms and related protective factors appears crucial. Therefore, this study employed a structural network analysis approach considering both ED symptom dimensions (i.e., drive for thinness, bulimic symptoms, and body dissatisfaction) and related protective factors (i.e., body and functionality appreciation, intuitive eating, and self-esteem) to shed light on how these factors are interrelated. A community sample of 1391 individuals (34.4% men; Mage = 26.4 years) completed a socio-demographic schedule and self-report questionnaires. The network showed that the nodes with the highest positive expected influence were body and functionality appreciation, while those with the highest negative expected influence were eating for physical rather than emotional reasons and unconditional permission to eat (i.e., two components of intuitive eating). Crucially, the most relevant bridges between the conceptual communities "ED symptom dimensions" and "Protective factors" were the negative relations between (a) eating for physical rather than emotional reasons and bulimic symptoms, (b) unconditional permission to eat and drive for thinness, and (c) body appreciation and body dissatisfaction. Finally, age, gender, and body mass index did not moderate any edge in the network. The practical implications of these findings are discussed, especially in terms of preventive interventions for ED symptoms.

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.

Prevalence and network structure of depression, insomnia and suicidality among mental health professionals who recovered from COVID-19: a national survey in China

Psychiatric syndromes are common following recovery from Coronavirus Disease 2019 (COVID-19) infection. This study investigated the prevalence and the network structure of depression, insomnia, and suicidality among mental health professionals (MHPs) who recovered from COVID-19. Depression and insomnia were assessed with the Patient Health Questionnaire (PHQ-9) and Insomnia Severity Index questionnaire (ISI7) respectively. Suicidality items comprising suicidal ideation, suicidal plan and suicidal attempt were evaluated with binary response (no/yes) items. Network analyses with Ising model were conducted to identify the central symptoms of the network and their links to suicidality. A total of 9858 COVID-19 survivors were enrolled in a survey of MHPs. The prevalence of depression and insomnia were 47.10% (95% confidence interval (CI) = 46.09-48.06%) and 36.2% (95%CI = 35.35-37.21%), respectively, while the overall prevalence of suicidality was 7.8% (95%CI = 7.31-8.37%). The key central nodes included "Distress caused by the sleep difficulties" (ISI7) (EI = 1.34), "Interference with daytime functioning" (ISI5) (EI = 1.08), and "Sleep dissatisfaction" (ISI4) (EI = 0.74). "Fatigue" (PHQ4) (Bridge EI = 1.98), "Distress caused by sleep difficulties" (ISI7) (Bridge EI = 1.71), and "Motor Disturbances" (PHQ8) (Bridge EI = 1.67) were important bridge symptoms. The flow network indicated that the edge between the nodes of "Suicidality" (SU) and "Guilt" (PHQ6) showed the strongest connection (Edge Weight= 1.17, followed by "Suicidality" (SU) - "Sad mood" (PHQ2) (Edge Weight = 0.68)). The network analysis results suggest that insomnia symptoms play a critical role in the activation of the insomnia-depression-suicidality network model of COVID-19 survivors, while suicidality is more susceptible to the influence of depressive symptoms. These findings may have implications for developing prevention and intervention strategies for mental health conditions following recovery from COVID-19.

Sex differences in entrapment in a multinational sample: a network analysis perspective

Background

The concept of entrapment has been highlighted as a transdiagnostic element that manifests itself in disorders such as depression, anxiety, and suicidal ideation. Although research has been conducted in different contexts independently, a comprehensive multi-country study to assess gender differences in entrapment through network analysis has not yet been carried out. The objective of this study was to evaluate the entrapment network in men and women at the multinational level.

Methods

A sample of 2,949 participants, ranging in age from 18 to 73 years from six countries (Germany, Iran, Spain, Slovakia, El Salvador, and Peru), was considered. They completed the entrapment scale. A network analysis was performed for both men and women to identify the connectivity between indicators and the formation of clusters and domains, in addition to the centrality assessment in both sex groups.

Results

The study findings revealed the presence of a third domain focused on external interpersonal entrapment in the network of men and women. However, in relation to the interconnectivity between domains, variations were evidenced in both networks, as well as in centrality, it was reported that men present a greater generalized entrapment in various aspects of life, while women tend to experience a more focused entrapment in expressions of intense emotional charge.

Conclusion

The multinational study identified variations in the structure of entrapment between genders, with three domains (internal, external, and external-interpersonal) and differences in the interaction of indicators and groupings, as well as discrepancies in centrality.

The dynamic relationships between well-being, behavioral restrictions, and health behaviors during the COVID-19 pandemic: A large-scale intensive longitudinal network study

The behavioral restrictions disrupting daily life during the COVID-19 pandemic have profoundly impacted well-being, and health behaviors have been advocated to prevent decline. To understand how processes related to fluctuation in well-being unfold within individuals, analyses on the within-person level are required. In this preregistered intensive longitudinal study, 1,709 individuals from the Norwegian adult population provided data daily over 40 consecutive days during the pandemic. The responses were modeled in a multilevel vector autoregressive model to estimate within-person networks, across and within-day, and a between-person network. All three networks revealed productivity, relatedness, and optimism as positively associated. Social distancing was contemporaneously negatively associated with productivity and relatedness. Among behavioral factors, being physically active predicted lower relatedness across days but displayed positive associations with relatedness, productivity, and optimism contemporaneously. Alcohol consumption predicted lower productivity across and within-day, although revealing a positive association with optimism within-day. Being social online and feeling related to others displayed a temporal negative bidirectional relationship. In contrast, being social online was positively associated with optimism, productivity, and relatedness contemporaneously. Our study emphasizes the dynamic nature of well-being and its complex associations with behavioral factors during the pandemic. The study shed light on opposing associations of behavioral factors at the within- and between-person level.

A Network Approach to Understanding the Role of Executive Functioning and Alpha Oscillations in Inattention and Hyperactivity-Impulsivity Symptoms of ADHD

OBJECTIVE

ADHD is a prevalent neurodevelopmental disorder characterized by symptoms of inattention and hyperactivity-impulsivity. Impairments in executive functioning (EF) are central to models of ADHD, while alpha-band spectral power event-related decreases (ERD) have emerged as a putative electroencephalography (EEG) biomarker of EF in ADHD. Little is known about the roles of EF and alpha ERD and their interactions with symptoms of ADHD.

METHOD

We estimated network models of ADHD symptoms and integrated alpha ERD measures into the symptom network.

RESULTS

EF emerges as a bridge network node connecting alpha ERD and the hyperactivity/impulsivity and inattention symptoms. We found that EF most closely relates to a subset of symptoms, namely the motoric symptoms, "seat" (difficulty staying seated), and "runs" (running or climbing excessively).

CONCLUSIONS

EF functions as a bridge node connecting alpha ERD and the ADHD symptom network. Motoric-type symptoms and EF deficits may constitute important nodes in the interplay between behavior/symptoms, cognition, and neurophysiological markers of ADHD.

The Impact of Music Therapy in a Pediatric Oncology Setting: An Italian Observational Network Study

BACKGROUND

Music Therapy (MT) is a non-pharmacological, art-based intervention that employs music experiences within a therapeutic alliance to attend to clients' physical, emotional, cognitive, and social requirements. This is the first study aiming at investigating the impact of MT on the psychological facets of children suffering from cancer.

METHODS

The study, combining the AQR and m-YPAS assessment tools, evaluated behavioral, sound-musical, and interactive parameters in pediatric oncology patients undergoing MT sessions during hospitalization. Fifty patients admitted to the Paediatric Oncology and Haematology Unit at Policlinico S. Orsola Hospital in Bologna, Italy, were enrolled, irrespective of their treatment regimen. Data collection occurred on the first day of the MT session between 3 p.m. and 5 p.m., with observations conducted by independent observers. In addition to traditional statistical analysis, network analysis was used to explore the combined interactions of all parameters, effectively discerning the distinctive roles played by each one during therapy sessions and their influence on all others.

RESULTS

Network analysis highlighted distinct patterns of interactions among parameters during the various sessions, emphasizing the role of positive emotions and a calm setting, the child's ability to take the initiative in sessions, their sense of agency, and the parent's role in guiding them. Significant differences were recorded at each time point between all variables considered.

CONCLUSIONS

The results of this innovative study may pave the way for future multicenter studies aimed at further exploring the role of MT in children undergoing both curative and palliative treatments for cancer.

Ukrainian-Russian bilingualism in the war-affected migrant and refugee communities in Austria and Germany: a survey-based study on language attitudes

Introduction

This paper provides an initial exploration of Ukrainian-Russian bilingualism in the context of the war-affected migration from Ukraine to Austria and Germany. While extensive research exists on various aspects of Ukrainian- Russian bilingualism in relation to Ukraine itself, thus far no studies have been conducted on this bilingualism in the diasporic context, i.e., as a language of the first and subsequential generations with a migrant background in Austria and Germany.

Methods

To address this research gap, our paper examines the language attitudes of two respondent groups with a Ukrainian background in the two countries: migrants and refugees who left Ukraine after 2014 and those who left after Russia's invasion in February 2022. In the framework of a sociolinguistic survey, we describe their current attitudes regarding the use of Ukrainian and Russian, among others, in relation to the actual and intended use of the language(s) in the multilingual context of migration. The survey eliciting information on demographic information, language proficiency, language attitudes and language use was conducted on 406 Ukrainians in two host countries (Austria: n = 103; Germany: n = 306). First, we compared self-rated proficiency in Ukrainian and Russian as well as attitudes and use of these languages. Second, we applied a network modelling analysis to determine the nature of relationships between these variables.

Results and discussion

The results indicated that proficiency in Ukrainian and in Russian were the strongest nodes in the model affecting language use and language attitudes toward the respective languages. Our data analysis focused on the pragmatic and symbolic value of Russian and Ukrainian playing a crucial role in the language vitality in multilingual settings. The paper discusses the imbalanced correlation of the symbolic and pragmatic value of Ukrainian and Russian in the diasporic Ukrainian communities. While Ukrainian has gained a higher symbolic status, Russian maintains a better pragmatic one, despite its negative symbolic status. However, we anticipate that the increasing symbolic value of Ukrainian and the diminishing value of Russian will lead to an increase in the use of Ukrainian also in Russian-dominant bilingual groups of Ukrainian migrants and refugees, even as an insider-code in hermetic minority groups.

A network analysis of exhaustion disorder symptoms throughout treatment

BACKGROUND

Stress-induced Exhaustion Disorder (ED) is associated with work absenteeism and adverse health outcomes. Currently, little is known regarding how the symptoms of ED are interrelated and whether the patterns of symptoms influence treatment outcomes. To this end, the current study applied network analyses on ED patients participating in a multimodal intervention.

METHODS

The first aim of the study was to explore the internal relationships between exhaustion symptoms and identify symptoms that were more closely related than others. A second aim was to examine whether the baseline symptom network of non-responders to treatment was more closely connected than the baseline symptom networks of responders, by comparing the sum of all absolute partial correlations in the respective groups' symptom network. This comparison was made based on the hypothesis that a more closely connected symptom network before treatment could indicate poorer treatment outcomes. Network models were constructed based on self-rated ED symptoms in a large sample of patients (n = 915) participating in a 24-week multimodal treatment program with a 12-month follow-up.

RESULTS

The internal relations between self-rated exhaustion symptoms were stable over time despite markedly decreased symptom levels throughout participation in treatment. Symptoms of limited mental stamina and negative emotional reactions to demands were consistently found to be the most closely related to other ED symptoms. Meanwhile, sleep quality and irritability were weakly related to other exhaustion symptoms. The symptom network for the full sample became significantly more closely connected from baseline to the end of treatment and 12-month follow-up. The symptom network of non-responders to treatment was not found to be more closely connected than the symptom network of responders at baseline.

CONCLUSIONS

The results of the current study suggest symptoms of limited mental stamina and negative emotional reactions to demands are central ED symptoms throughout treatment, while symptoms of irritability and sleep quality seem to have a weak relation to other symptoms of ED. The implications of these findings are discussed in relation to the conceptualization, assessment, and treatment of ED.

TRIAL REGISTRATION

The clinical trial was registered on Clinicaltrials.gov 2017-12-02 (Identifier: NCT03360136).

Behavioral Precursors of Nicotine Product Use Trajectories Among Youth

INTRODUCTION

Preventing nicotine use among youth is a public health priority. Nicotine use emerges from complex relationships between numerous factors. This project used network analysis to model behavioral precursors of nicotine use (knowledge, attitudes, perceptions, intentions) among youth who had never used nicotine and determine which predicted future trajectories of use across multiple nicotine products.

METHODS

Data were from the Population Assessment of Tobacco and Health study (2013-2018; analyzed 2023-2024), youth ages 12-17, who reported never using nicotine at Wave 1. Network structure was determined for behavioral precursors at Wave 1 and central network nodes were identified (N=5,087). Central nodes were then tested as predictors of trajectories of use across multiple nicotine products during Waves 1-4 (N=3,851).

RESULTS

Central nodes of the Wave 1 network were harm perception, expectancy that tobacco would calm anger/reduce stress, and intention to try. Those with lower intent to try at Wave 1 had lower odds of being in an Experimentation or Use class versus a Nonuse class during Waves 1-4 (p<0.0001). Those with more accurate harm perception had lower odds of being in an Experimentation versus Nonuse class (p=0.004). Those with positive expectancies had higher odds of being in an Experimentation versus Nonuse or Use class (p=0.04, 0.02).

CONCLUSIONS

Findings suggest a network model of behavioral precursors of nicotine use that can be tested, including central nodes that predicted trajectories of use across multiple nicotine products, and therefore may be priority intervention targets.

Understanding Work Ability in Employees with Pain and Stress-Related Ill-Health: An Explorative Network Analysis of Individual Characteristics and Psychosocial Work Environment

PURPOSE

There is a wide range of individual and work environment factors that influence work ability among workers with pain and stress-related ill-health. The multiple interactions and overlap between these factors are insufficiently understood, and a network approach could mitigate limitations of previous research. This pilot study aimed to explore interactions between individual characteristics and psychosocial work environment and potential links to long-term work ability.

METHODS

Prospective data from a prevention project was used. Individuals (N = 147) with pain and/or stress-related ill-health (95% women) at public sector workplaces filled out baseline questionnaires about a collection of individual and work environment factors, which were used for constructing undirected networks. The model was run in three subsamples of workplaces. Finally, a separate model was established with work ability at 6-month follow-up as outcome variable. A shortest pathway analysis was calculated to identify mediators of work ability.

RESULTS

Symptom catastrophizing and perceived stress were the most influential factors in all network models. Symptom catastrophizing and pain-disability risk were found to mediate the relation between perceived stress and long-term work ability. Further, demand-control-support factors were interrelated, and patterns of interaction differed between different types of workplaces.

CONCLUSION

The findings support the importance of individual factors, specifically symptom catastrophizing in an individual's coping with pain or stress-problems and its influence on long-term work ability. Catastrophizing might play a role in stress-related disorders which should be further investigated. Individual and work environment factors interact and vary across context, which needs to be taken into consideration to prevent pain and stress-related ill-health at work.

Multiple paths to rumination within a network analytical framework

Theories of rumination have proposed different psychological factors to place one at risk for repetitive negative thinking. A comprehensive empirical test that captures the most relevant contributors to rumination is lacking. Building on influential self-regulatory and metacognitive frameworks, we modeled how key constructs in this context relate to ruminative thinking. 498 participants completed online questionnaires including indicators of rumination, metacognition, promotion goal orientation, effortful control, and depression. We estimated regularized partial correlation networks to investigate unique associations between the different constructs and followed these analyses up with directed acyclic graphs to identify potential pathways towards rumination. Results demonstrated that: (1) both self-regulatory and metacognitive factors were directly linked to rumination, amongst these were (2) positive beliefs, negative beliefs about uncontrollability and harm, cognitive self-consciousness, depression, effortful control, perfectionism, and (lack of) cognitive confidence, and (3) we identified multiple directed pathways, suggesting three direct contributors to rumination while controlling for the influence of all other variables: diminished effortful control, positive beliefs, and cognitive self-consciousness. This study is the first to comprehensively assess metacognitive and self-regulatory frameworks of rumination in a data-driven manner. Our findings suggest that there are multiple pathways towards rumination, which should be incorporated in clinical case conceptualization of rumination and related disorders.

Simulation-Based Performance Evaluation of Missing Data Handling in Network Analysis

Network analysis has gained popularity as an approach to investigate psychological constructs. However, there are currently no guidelines for applied researchers when encountering missing values. In this simulation study, we compared the performance of a two-step EM algorithm with separated steps for missing handling and regularization, a combined direct EM algorithm, and pairwise deletion. We investigated conditions with varying network sizes, numbers of observations, missing data mechanisms, and percentages of missing values. These approaches are evaluated with regard to recovering population networks in terms of loss in the precision matrix, edge set identification and network statistics. The simulation showed adequate performance only in conditions with large samples (n ≥ 500 ) or small networks (p = 10). Comparing the missing data approaches, the direct EM appears to be more sensitive and superior in nearly all chosen conditions. The two-step EM yields better results when the ratio of n/p is very large - being less sensitive but more specific. Pairwise deletion failed to converge across numerous conditions and yielded inferior results overall. Overall, direct EM is recommended in most cases, as it is able to mitigate the impact of missing data quite well, while modifications to two-step EM could improve its performance.

Comparison of network structures between autistic and non-autistic adults, and autism subgroups: A focus on demographic, psychological, and lifestyle factors

LAY ABSTRACT

There are large differences in the level of demographic, psychological, and lifestyle characteristics between autistic and non-autistic adults but also among autistic people. Our goal was to test whether these differences correspond to differences in underlying relationships between these characteristics-also referred to as network structure-to determine which characteristics (and relationships between them) are important. We tested differences in network structure in (1) autistic and non-autistic adults and (2) two previously identified subgroups of autistic adults. We showed that comparing networks of autistic and non-autistic adults provides subtle differences, whereas networks of the autism subgroups were similar. There were also no sex differences in the networks of the autism subgroups. Thus, the previously observed differences in the level of characteristics did not correspond to differences across subgroups in how these characteristics relate to one another (i.e. network structure). Consequently, a focus on differences in characteristics is not sufficient to determine which characteristics (and relationships between them) are of importance. Hence, network analysis provides a valuable tool beyond looking at (sub)group level differences. These results could provide hints for clinical practice, to eventually determine whether psychological distress, cognitive failures, and reduced quality of life in autistic adults can be addressed by tailored support. However, it is important that these results are first replicated before we move toward intervention or support.

Mapping prodromal symptoms in patients with bipolar disorder: A network perspective

Bipolar disorder (BD) is a major mental disorder that significantly impairs behavior and social functioning. This study assessed the network structure of prodromal symptoms in patients with BD prior to their index mood episode. Semi-structured interviews were conducted with the Bipolar Prodrome Symptom Scale-Retrospective (BPSS-R) to examine patients' prodromal symptoms. Network analysis was conducted to elucidate inter-relations between prodromal symptoms. A total of 120 eligible patients participated in this study. Network analysis indicated that the observed model was stable. The edge Mania3-Depression9 ('Racing thoughts' - 'Thinking about suicide', edge weight = 14.919) showed the strongest positive connection in the model, followed by the edge Mania1-depression1 ('Extremely energetic/active' - 'Depressed mood', edge weight = 14.643). The only negative correlation in the model was for Mania7-depression2 ('Overly self-confident' - 'Tiredness or lack of energy', edge weight = -1.068). Nodes Mania3 ('Racing thoughts'), Depression9 ('Thinking about suicide'), Mania1 ('Extremely energetic/active'), and Depression1 ('Depressed mood') were the most central symptoms. Both depressive and manic or hypomanic symptoms appeared in the prodromal phase. Symptoms reflecting 'Racing thoughts', 'Thinking about suicide', 'Extremely energetic/active', and 'Depressed mood' should be thoroughly assessed and targeted as crucial prodromal symptoms in interventions to reduce the risk of BD episodes.

Emotional wellbeing in teachers

Wellbeing is determined by happiness and both positive and negative affects. These constructs are, in turn, related to emotional intelligence and play an important role in individual behaviour. This study examined the relationship between happiness, emotional intelligence, and positive and negative affects in a sample of 344 (121 men 35.17 % and 223 women 64.83 %) trainee teachers, with an average age of 22.36 years. Happiness and affects yielded lower values, which may be related to the age of the participants. All variables under study were found to be correlated, which suggests that they are measuring the same construct: subjective wellbeing. Network analysis indicated that the self-regulation of emotions was the axial factor in the relationship. Finally, it was found that only the factor of emotional intelligence that measures the self-regulation of emotion and affects (both positive and negative) can be used to predict happiness. The present investigation reveals that more research is needed that takes more variables into consideration to describe the effect of these variables on personal wellbeing. The study offers empirical support to models that argue for a relationship between happiness, emotional intelligence, and affects, and emphasises the need to work on future teachers during their training to address their psychological wellbeing.

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.

Modeling lexical abilities of heritage language and L2 speakers of Hebrew and English in Israel and the United States: a network approach

Introduction

This paper examines the productive vocabulary skills of five groups of English-Hebrew bilinguals in Israel and the United States. The juxtaposition of these five groups allows us to simultaneously compare performance across dominance profiles, acquisition contexts (L2 learned in school, HL maintained at home, immigration and immersion), and countries (Israel and the USA).

Methods

A total of 185 participants took part in study: Hebrew-dominant heritage English speakers, Hebrew-dominant L2-English speakers, English-dominant heritage Hebrew speakers, and English-dominant L2-Hebrew speakers in the US and in Israel. They were all administered the MINT assessment in both languages, as well as background questionnaires. We then employ network modeling based on a secondary data analysis of background questionnaires to consider how each group's lexical proficiency ties in to reported input factors.

Results and discussion

The MINT results indicate clear language dominance in all the groups except Hebrew-dominant heritage English speakers, who show balanced proficiency in both their languages. The network models indicate key distinctions between the groups as a function of linguistic context, and we assess our findings in the context of recent work on quantifying the bilingual experience.

A longitudinal network analysis of suicide risk factors among service members and veterans sampled for suicidal ideation or attempt

BACKGROUND

Suicidal thoughts and behaviors are elevated among active-duty service members (ADSM) and veterans compared to the general population. Hence, it is a priority to examine maintenance factors underlying suicidal ideation among ADSM and veterans to develop effective, targeted interventions. In particular, interpersonal risk factors, hopelessness, and overarousal have been robustly connected to suicidal ideation and intent.

METHODS

To identify the suicidal ideation risk factors that are most relevant, we employed network analysis to examine between-subjects (cross-sectional), contemporaneous (within seconds), and temporal (across four hours) group-level networks of suicidal ideation and related risk factors in a sample of ADSM and veterans (participant n = 92, observations n = 10 650). Participants completed ecological momentary assessment (EMA) surveys four times a day for 30 days, where they answered questions related to suicidal ideation, interpersonal risk factors, hopelessness, and overarousal.

RESULTS

The between-subjects and contemporaneous networks identified agitation, not feeling close to others, and ineffectiveness as the most central symptoms. The temporal network revealed that feeling ineffective was most likely to influence other symptoms in the network over time.

CONCLUSION

Our findings suggest that ineffectiveness, low belongingness, and agitation are important drivers of moment-to-moment and longitudinal relations between risk factors for suicidal ideation in ADSM and veterans. Targeting these symptoms may disrupt suicidal ideation.

Psychometric network analysis of the Patient Health Questionnaire-4 (PHQ-4) in Paraguayan general population

BACKGROUND

Depression and anxiety are two of the most prevalent and disabling mental disorders worldwide, both in the general population and in outpatient clinical settings.

OBJECTIVE

This study aimed to analyze the psychometric properties of the Patient Health Questionnaire-4 (PHQ-4) based on network analysis metrics.

METHODS

A total of 911 Paraguayans (23.71% women and 76.29% men; mean age 31.25 years, SD = 10.63), selected by non-probabilistic convenience sampling, participated in the study. Network analysis was used to evaluate the internal structure, reliability, and measurement invariance between men and women.

RESULTS

The results revealed that the PHQ-4 is a unidimensional measure through Exploratory Graph Analysis (EGA). Reliability, through structural consistency, identified that 100% of the time, only a single dimension was obtained, and all items remained stable, as they were always replicated within the empirical dimension. The unidimensional structure has shown evidence of configural invariance; therefore, the network structure functioned equally among the different sex groups.

CONCLUSION

The PHQ-4 presented optimal preliminary evidence of validity based on its internal structure, reliability, and invariance between sexes. Therefore, it may be useful as an accurate and brief measure of anxiety and depressive symptoms in the Paraguayan context.

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

BACKGROUND

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

METHODS

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

RESULTS

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

LIMITATIONS

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

CONCLUSIONS

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

Mapping network connection and direction among symptoms of depression and anxiety in patients with chronic gastritis

Regarding neurophysiological and developmental findings, anxiety and depression are usual comorbidities of gastritis patients. However, research related to anxiety and depression among chronic gastritis patients was conducted on the disease level while ignoring symptoms. Hence, we rendered the network approach to reveal the symptoms of anxiety and depression among chronic gastritis patients. Three hundred and sixty-nine chronic gastritis patients (female = 139, Mage = 55.87 years) were asked to complete the Self-Rating Anxiety Scale and Self-Rating Depression Scale. Three symptom networks and one directed acyclic graph (DAG) network were formed. First, in the anxiety network of chronic gastritis patients, dizziness was the most influential symptom. In the depression network of chronic gastritis patients, depressed affect and psychomotor retardation were the influential symptoms. Second, panic, easy fatiguability, weakness, palpitation, depressed affect, tachycardia, fatigue, and psychomotor agitation bridged the anxiety-depression network of chronic gastritis patients. Third, DAG networks showed that anxiousness and hopelessness could trigger other symptoms in the anxiety-depression networks of chronic gastritis patients. The current study provided insightful information on patients with chronic gastritis by examining the structures of symptoms.

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.

What time-varying network models based on functional analysis tell us about the course of a patient's problem

Background: Relations among psychological variables are assumed to be complex and to vary over time. Personalized networks can model multivariate complex interactions. The development of time-varying networks allows to model the variation of parameters over time. Objectives: We aimed to determine the value of time-varying networks for clinical practice. Methods: We applied time-varying mixed graphical models (TV-MGM) and time-varying vector autoregressive models (TV-VAR) to intensive longitudinal data of nine participants with depressive symptoms (n = 6) or anxiety (n = 3). Results: Most of the participants showed temporal changes in network topology within the assessment period of 30 days. Time-varying networks of participants with small, medium, and large time variability in edge parameters clearly show the different temporal evolvements of dynamic interactions between variables. The case example indicates clinical utility but also limitations to the application of time-varying networks in clinical practice. Conclusion: Time-varying network models provide a data-driven and exploratory approach that could complement current diagnostic standards by reflecting interacting, often mutually reinforcing processes of mental health problems and by accounting for variation over time. They can be used to generate hypotheses for further confirmatory and clinical testing.

Psychological flexibility and cognitive-affective processes in young adults' daily lives

Psychological flexibility plays a crucial role in how young adults adapt to their evolving cognitive and emotional landscapes. Our study investigated a core aspect of psychological flexibility in young adults: adaptive variability and maladaptive rigidity in the capacity for behavior change. We examined the interplay of these elements with cognitive-affective processes within a dynamic network, uncovering their manifestation in everyday life. Through an Ecological Momentary Assessment design, we collected intensive longitudinal data over 3 weeks from 114 young adults ages 19 to 32. Using a dynamic network approach, we assessed the temporal dynamics and individual variability in flexibility in relation to cognitive-affective processes in this sample. Rigidity exhibited the strongest directed association with other variables in the temporal network as well as highest strength centrality, demonstrating particularly strong associations to other variables in the contemporaneous network. In conclusion, the results of this study suggest that rigidity in young adults is associated with negative affect and cognitions at the same time point and the immediate future.

Relationship between depression and burnout among nurses in Intensive Care units at the late stage of COVID-19: a network analysis

BACKGROUND

Mental health problems are critical and common in medical staff working in Intensive Care Units (ICU) even at the late stage of COVID-19, particularly for nurses. There is little research to explore the inner relationships between common syndromes, such as depression and burnout. Network analysis (NA) was a novel approach to quantified the correlations between mental variables from the perspective of mathematics. This study was to investigate the interactions between burnout and depression symptoms through NA among ICU nurses.

METHOD

A cross-sectional study with a total of 616 Chinese nurses in ICU were carried out by convenience sampling from December 19, 2022 to January19, 2023 via online survey. Burnout symptoms were measured by Maslach Burnout Inventory-General Survey (MBI-GS) (Chinese version), and depressive symptoms were assessed by the 9-item Patient Health Questionnaire (PHQ-9). NA was applied to build interactions between burnout and depression symptoms. We identified central and bridge symptoms by R package qgraph in the network model. R package bootnet was used to examined the stability of network structure.

RESULTS

The prevalence of burnout and depressive symptoms were 48.2% and 64.1%, respectively. Within depression-burnout network, PHQ4(Fatigue)-MBI2(Used up) and PHQ4(Fatigue)-MBI5(Breakdown) showed stronger associations. MBI2(Used up) had the strongest expected influence central symptoms, followed by MBI4(Stressed) and MBI7 (Less enthusiastic). For bridge symptoms. PHQ4(Fatigue), MBI5(Breakdown) and MBI2(Used up) weighed highest. Both correlation stability coefficients of central and bridge symptoms in the network structure were 0.68, showing a high excellent level of stability.

CONCLUSION

The symptom of PHQ4(Fatigue) was the bridge to connect the emotion exhaustion and depression. Targeting this symptom will be effective to detect mental disorders and relieve mental syndromes of ICU nurses at the late stage of COVID-19 pandemic.

Unveiling the relationship between social anxiety, loneliness, motivations, and problematic smartphone use: A network approach

BACKGROUND

Previous studies suggested social anxiety as an essential risk factor for problematic smartphone use, but the complex interactions and the most influential components affecting this relationship remain unclear. This study capitalizes on network analysis to identify the central factors and possible mediating paths among social anxiety, loneliness, five types of motivation, and problematic smartphone use.

MATERIAL AND METHODS

Employing 549 emerging adults, we obtained a stable network of the above variables. The central components and the stability of this network were also identified.

RESULTS

Within this network, the edge linking withdrawal behavior and use of application (APP) exhibits the most robust edge intensity. The central components include social comfort, use of APP, withdrawal behavior, and companionship while the bridge central nodes include social anxiety and escapism motivation. The direct link between social anxiety and PSU revealed only fragile edges with both withdrawal behavior and use of APP. Considering the possible mediating pathways, three pathways were observed in our network. Loneliness and escapism mediated the relationship between social anxiety and social comfort. Moreover, another mediating way was from social anxiety, loneliness, social interaction motivation, and escapism motivation to social comfort.

DISCUSSION

Based on the above identification of related components and pathways, future researchers could intervene against problematic smartphone usage in this socially anxious population.

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 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.

Dynamic symptom associations in posttraumatic stress disorder: a network approach

Background and objective: The current study aimed to investigate the within-day symptom dynamics in PTSD patients, specifically focusing on symptoms that most predict changes in other symptoms. The study included a baseline diagnostic assessment, followed by an assessment using the experience sampling method (ESM) via a smartphone.Method: Participants answered questions related to their PTSD symptoms four times per day for 15 consecutive days (compliance rate 75%). The clinical sample consisted of 48 treatment-seeking individuals: 44 with PTSD as a primary diagnosis, and four patients with subsyndromal PTSD, all of whom had not yet begun trauma-focused treatment. The ESM assessment included the 20 items from the PTSD Checklist for DSM-5, five items from the International Trauma Questionnaire (ITQ) assessing disturbances in relationships and functional impairment, and two items from the Clinician-Administered PTSD Scale for DSM-5 assessing symptoms of depersonalization and derealization.Results: Temporal networks (prospective associations between symptoms) showed that changes in hypervigilance predicted changes in the greatest number of symptoms at the next time point. Furthermore, hypervigilance showed temporal connections with at least one additional symptom from each of the DSM-5 PTSD symptom clusters.Conclusions: Results show that the contemporaneous network (representing the relationship between given symptoms within the same assessment occasion) and the temporal network (representing prospective associations between symptoms) differ and that it is important to estimate both. Some findings from earlier research are replicated, but heterogeneity across studies remains. Future studies should include potential moderators.

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.

Fear of disease in patients with epilepsy - a network analysis

Background

Disease-related fear among patients with epilepsy has significantly impacted their quality of life. The Disease-Related Fear Scale (D-RFS), comprising three dimensions, serves as a relatively well-established tool for assessing fear in these patients. However, certain problems potentially exist within the D-RFS's attribution of items, and its internal structure is still unclear. To establish an appropriate dimensional structure and gain deeper comprehension of its internal structure-particularly its core variables-is vital for developing more effective interventions aimed at alleviating disease-related fear among patients with epilepsy.

Methods

This study employed a cross-sectional survey involving 609 patients with epilepsy. All participants underwent assessment using the Chinese version of the D-RFS. We used exploratory network analysis to discover a new structure and network analysis to investigate the interrelationships among fear symptom domains. In addition to the regularized partial correlation network, we also estimated the node and bridge centrality index to identify the importance of each item within the network. Finally, it was applied to analyze the differences in network analysis outcomes among epilepsy patients with different seizure frequencies.

Results

The research findings indicate that nodes within the network of disease-related fear symptoms are interconnected, and there are no isolated nodes. Nodes within groups 3 and 4 present the strongest centrality. Additionally, a tight interconnection exists among fear symptoms within each group. Moreover, the frequency of epileptic episodes does not significantly impact the network structure.

Conclusion

In this study, a new 5-dimension structure was constructed for D-RFS, and the fear of disease in patients with epilepsy has been conceptualized through a network perspective. The goal is to identify potential targets for relevant interventions and gain insights for future research.

eHealth tools use and mental health: a cross-sectional network analysis in a representative sample

eHealth tools usage is vital for health care systems and increased significantly after the COVID-19 pandemic, which aggravated mental health issues. This cross-sectional study explored whether sociodemographic characteristics and mental health indices (stress and symptoms of anxiety and depression) were linked to the behavioral intention to use eHealth tools and eHealth tools usage in a representative sample from Poland using a network approach. Measurements were conducted in March 2023 among 1000 participants with a mean age of 42.98 (18-87) years, with 51.50% women. The measures included the behavioral intention to use eHealth tools (BI) based on the UTUAT2; eHealth tool use frequency (use behavior) including ePrescription, eSick leave, eReferral, electronic medical documentation (EMD), Internet Patient Account (IKP), telephone consultation, video consultation, mobile health applications, and private and public health care use; and the PSS-4, GAD-2, and PHQ-2. Furthermore, sociodemographic factors (sex, age, children, relationship status, education, and employment) were included in the research model. Network analysis revealed that mental health indices were weakly related to eHealth tools use. Higher stress was positively linked with mobile health application use but negatively linked to video consultation use. Use of various eHealth tools was intercorrelated. Sociodemographic factors were differentially related to the use of the eight specific eHealth tools. Although mental health indices did not have strong associations in the eHealth tools use network, attention should be given to anxiety levels as the factor with the high expected influence.

Network Analysis on Family Resilience, Fear of Progression, and Quality of Life in Chinese Patients with Pulmonary Hypertension

BACKGROUND

The long-term quality of life of Chinese patients with pulmonary hypertension has been seriously compromised. Interventions to enhance patient quality of life of are urgently required.

OBJECTIVE

To investigate the relationship between quality of life and its influencing factors in patients through network analysis.

METHOD

247 patients with pulmonary hypertension in 3 hospitals in Jinan, Shandong Province, self-reported their immediate family resilience, fear of progression, and quality of life via questionnaires. A mixed graphical model was constructed to investigate the relationship among multidimensional structures of variables.

RESULTS

A total of 247 patients (173 female and 74 male) were included (age 18-34, n=115; age 35-49, n=99; age 50-64, n=23; age > 65 years, n=10). "Family communication and problem solving" was at the center of the network, with serving as a bridge node. Within communities, the strongest edge was "Family communication and problem solving-maintaining a positive outlook." Across communities, the strongest edge between family resilience and quality of life was "Family communication and problem solving-environmental domain quality of life," and the strongest edge across the fear of progression and quality of life was "physiological health fear-psychological domain quality of life."

CONCLUSIONS

Family resilience and fear of progression may affect the quality of life in patients with pulmonary hypertension. Developing a program with "family communication and problem solving" as a primary target may reduce patient fear of progression, enhance family resilience, and improve patient quality of life.