Replicability and Generalizability of Posttraumatic Stress Disorder (PTSD) Networks: A Cross-Cultural Multisite Study of PTSD Symptoms in Four Trauma Patient Samples

A Network Analysis of the Association Between Intergroup Contact and Intergroup Relations

PURPOSE

Intergroup contact is an effective strategy to improve intergroup relationships. Although intergroup relationships have been studied extensively, the individual roles of quantity and quality of contact in relationships with cognition, emotion, and intention of behavior toward other ethnic minority groups are not fully understood. This study explores the situation via network analysis among Zhuang and Yao ethnic minorities in Southwest China.

METHODS

We investigated the quantity and quality of intergroup contact and cognition, emotion, and intention of behavior among a sample of 543 Zhuang and 490 Yao ethnic group members. Data were analyzed using the R-package. Network structures were analyzed via the Qgraph package, and the accuracy and stability of the network were measured via the Bootnet package; communities were detected via the Igraph package; bridge analyses were conducted via the Networktools package; and the network difference was compared via the Network Comparison Test package.

RESULTS

The results indicated perceived intimacy is the central node. Quantity of contact constructed a community with "perceived connection," "sense of community," "knowledge about out-group," and "perceived similarity." Meanwhile, quality of contact constructed a community with "intergroup attitude" and a "feeling thermometer." The remainder of the nodes constructed two additional communities. The network global connectivity and structure between the two ethnic groups were highly similar.

CONCLUSION

The study examined the quantity and quality of intergroup contact via network analysis for two ethnic minority groups. It was shown that the two groups' global network structures of intergroup contact and their effects are highly similar. Specifically, quantity and quality of contact produce different effects on intergroup relations. Quantity of contact has proximal effects, including instant cognitive and emotional response without depth cognition, while quality of contact has proximal effects that may change deep-seated cognition and subsequently improve intergroup relations.

Russian Version of the International Trauma Questionnaire: Adaptation and Validation in a Non-Clinical Sample

Purpose. The article presents the results of adaptation and validation of the International Trauma Questionnaire (ITQ) on a Russian sample. The questionnaire measures the symptoms of complex post-traumatic stress disorder (CPTSD), which can develop as a result of exposure to prolonged, repetitive traumatic experiences in the interpersonal sphere. Method. The study was carried out on a non-clinical sample, which included 429 participants who were 18 to 68 years old and who experienced at least one traumatic event in their lives. International Trauma Questionnaire (ITQ), LEC-5 (Life events checklist-5), author’s questionnaire “Emotional abuse”, Symptom Checklist (SCL-90-R) were used in the study. Results. The structure of the questionnaire in the Russian-speaking sample confirmed the two-factor model of complex PTSD, which combines the symptoms of PTSD («Re-experiencing», «Avoidance», «Sense of Threat») and disturbances of Self-organization («Affective Dysregulation», «Negative Self-concept», «Disturbances in Relationships»). Internal consistency of the scale was in the acceptable range. Among those who have experienced at least one traumatic event, 20% met criteria for PTSD (11%) or CPTSD (9%). These data show that respondents with CPTSD have more intense psychopathological symptoms than respondents with PTSD; women show more intense symptoms of CPTSD than men.

Associations between PTSD symptoms and other psychiatric symptoms among college students exposed to childhood sexual abuse: a network analysis

Background: Childhood sexual abuse (CSA) is one of the prevalent forms of trauma experienced during childhood and adolescence. Previous research underscores its associations with depression, anxiety, post-traumatic stress disorder (PTSD), and psychosis. Objective: This study examined symptom connections between depression, anxiety, PTSD, and psychosis while simultaneously investigating whether these connections differed by gender among CSA survivors. Methods: A large-scale, cross-sectional study among 96,218 college students was conducted in China. Participants' CSA was measured by the Childhood Trauma Questionnaire-Short Form (CTQ-SF). Participants' PTSD, psychosis, depression, and anxiety were measured by the Trauma Screening Questionnaire (TSQ), the Psychosis Screener (PS), the nine-item Patient Health Questionnaire (PHQ-9), and the 7-item Generalized Anxiety Disorder Scale (GAD-7), respectively. Network analysis was used to explore the potential associations between these symptoms and to compare the sex differences in the symptoms model. Results: Among participants who suffered from CSA, females were more likely from left-behind households, while males were more likely from households with a high annual income (P < .001, Cohen's W = 0.07). In addition, compared to male victims, female victims were more likely to report depression, anxiety, and PTSD (P < .001, Cohen's d≈0.2), while male victims were more likely to report psychosis (P < .001, Cohen's d = 0.36). Results from network estimation showed that psychosis, depression, anxiety, and PTSD symptoms were positively correlated. Moreover, psychosis had a stronger connection with PTSD symptoms, including hypervigilance, intrusive thoughts, and physiological and emotional reactivity. Conclusions: The current study explores the associations between PTSD symptoms and psychiatric symptoms among college students exposed to CSA using a network analysis approach. These crucial symptoms of PTSD may have potential connections to psychosis. Target intervention and strategy should be developed to improve mental health and quality of life among these CSA victims. Furthermore, longitudinal studies are warranted to advance our understanding of PTSD and psychosis.

Comparing PTSD symptom networks in type I vs. type II trauma survivors

Background: Network analysis has gained increasing attention as a new framework to study complex associations between symptoms of post-traumatic stress disorder (PTSD). A number of studies have been published to investigate symptom networks on different sets of symptoms in different populations, and the findings have been inconsistent. Objective: We aimed to extend previous research by testing whether differences in PTSD symptom networks can be found in survivors of type I (single event; sudden and unexpected, high levels of acute threat) vs. type II (repeated and/or protracted; anticipated) trauma (with regard to their index trauma). Method: Participants were trauma-exposed individuals with elevated levels of PTSD symptomatology, most of whom (94%) were undergoing assessment in preparation for PTSD treatment in several treatment centres in Germany and Switzerland (n = 286 with type I and n = 187 with type II trauma). We estimated Bayesian Gaussian graphical models for each trauma group and explored group differences in the symptom network. Results: First, for both trauma types, our analyses identified the edges that were repeatedly reported in previous network studies. Second, there was decisive evidence that the two networks were generated from different multivariate normal distributions, i.e. the networks differed on a global level. Third, explorative edge-wise comparisons showed moderate or strong evidence for specific 12 edges. Edges which emerged as especially important in distinguishing the networks were between intrusions and flashbacks, highlighting the stronger positive association in the group of type II trauma survivors compared to type I survivors. Flashbacks showed a similar pattern of results in the associations with detachment and sleep problems (type II > type I). Conclusion: Our findings suggest that trauma type contributes to the heterogeneity in the symptom network. Future research on PTSD symptom networks should include this variable in the analyses to reduce heterogeneity.

Co-occurrence of severe PTSD, somatic symptoms and dissociation in a large sample of childhood trauma inpatients: a network analysis

Co-occurrence of mental disorders including severe PTSD, somatic symptoms, and dissociation in the aftermath of trauma is common and sometimes associated with poor treatment outcomes. However, the interrelationships between these conditions at symptom level are not well understood. In the present study, we aimed to explore direct connections between PTSD, somatic symptoms, and dissociation to gain a deeper insight into the pathological processes underlying their comorbidity that can inform future treatment plans. In a sample of 655 adult inpatients with a diagnosis of severe PTSD following childhood abuse (85.6% female; mean age = 47.57), we assessed symptoms of PTSD, somatization, and dissociation. We analyzed the comorbidity structure using a partial correlation network with regularization. Mostly positive associations between symptoms characterized the network structure. Muscle or joint pain was among the most central symptoms. Physiological reactivation was central in the full network and together with concentrations problems acted as bridge between symptoms of PTSD and somatic symptoms. Headaches connected somatic symptoms with others and derealization connected dissociative symptoms with others in the network. Exposure to traumatic events has a severe and detrimental effect on mental and physical health and these consequences worsen each other trans-diagnostically on a symptom level. Strong connections between physiological reactivation and pain with other symptoms could inform treatment target prioritization. We recommend a dynamic, modular approach to treatment that should combine evidence-based interventions for PTSD and comorbid conditions which is informed by symptom prominence, readiness to address these symptoms and preference.

Sexual symptoms in post-traumatic stress disorder following childhood sexual abuse: a network analysis

BACKGROUND

Even though recent research indicates that sexual symptoms are highly prevalent in post-traumatic stress disorder following childhood sexual abuse and cause severe distress, current treatments neither address them nor are they effective in reducing them. This might be due to a lack of understanding of sexual symptoms' specific role in the often complex and comorbid psychopathology of post-traumatic stress disorder following childhood abuse.

METHODS

Post-traumatic, dissociative, depressive, and sexual symptoms were assessed in 445 inpatients with post-traumatic stress disorder following childhood sexual abuse. Comorbidity structure was analyzed using a partial correlation network with regularization.

RESULTS

A total of 360 patients (81%) reported difficulties engaging in sexual activities and 102 patients (23%) reported to suffer from their sexual preferences. Difficulties engaging in sexual activities were linked to depressive and hyperarousal symptoms, whereas sexual preferences causing distress were linked to anger and dissociation. Dissociative amnesia, visual intrusions, and physical reactions to trauma reminders were of central importance for the network. Dissociative amnesia, depressed mood, lack of energy, and difficulties engaging in sexual activities were identified as bridge symptoms. Local clustering analysis indicated the non-redundancy of sexual symptoms.

CONCLUSIONS

Sexual symptoms are highly prevalent in survivors of childhood sexual abuse with post-traumatic stress disorder. Further research is needed regarding the link of difficulties engaging in sexual activities, depression, and post-traumatic stress disorder, as well as regarding the association of dissociation and sexual preferences causing distress. Sexual symptoms require consideration in the treatment of post-traumatic stress disorder following childhood sexual abuse.

Work Addiction and Work Engagement: a Network Approach to Cross-Cultural Data

This study aimed to investigate direct relationships of work addiction symptoms with dimensions of work engagement. We used three samples in which work addiction was measured with the Bergen Work Addiction Scale and work engagement was measured with the Utrecht Work Engagement Scale. One sample comprised responses from working Norwegians (n1 = 776), and two samples comprised responses from working Poles (n2 = 719; n3 = 715). We jointly estimated three networks using the fused graphic lasso method. Additionally, we estimated the stability of each network, node centrality, and node predictability and quantitatively compared all networks. The results showed that absorption and mood modification could constitute a bridge between work addiction and work engagement. It suggests that further investigation of properties of absorption and mood modification might be crucial for answering the question of how engaged workers become addicted to work.

Symptom networks in patients with substance use disorders

BACKGROUND

Reciprocity between symptoms of psychiatric disorders is increasingly recognized to contribute to their chronicity. In substance use disorders (SUD) little is known on reciprocal interactions between symptoms. We applied network analyses to study these interactions.

METHODS

We analyzed 11 DSM-IV / DSM-5 criteria for SUD for the most prevalent substances in addiction care (alcohol, cannabis, cocaine, stimulants, and opioids) in a sample of 10,832 SUD patients in treatment. First, we estimated an overall symptom network. Second, we compared symptom networks between the different substances. Finally, we tested differences in symptom networks between DSM-IV and DSM-5.

RESULTS

In the overall symptom network for SUD patients the most central symptom was: "spending substantial amount of the day obtaining, using, or recovering from substance use". The symptoms "giving up or cutting back on important activities because of use" and "repeated usage causes or contributes to an inability to meet important obligations", were the symptoms that influenced each other the most. Networks differed between substances both in global strength and structure, especially regarding the position of "use despite health or interpersonal problems". Networks based on DSM-5 criteria differed moderately from DSM-IV, mainly because "craving" was more central in the DSM-5 network than "legal problems" in DSM-IV.

CONCLUSIONS

Network analyses can identify core symptoms of SUD that could maintain the disease processes in SUD. Future studies should address whether targeting these core symptoms with precedence, might help to break through the addictive process.

Network analysis of comorbid posttraumatic stress disorder and depression in adolescents across COVID-19 epidemic and Typhoon Lekima

BACKGROUND

Network analytic studies indicate that posttraumatic stress disorder (PTSD) may be comorbid with depression at the symptom level, but it remains unclear whether these findings are replicable and generalizable across trauma types.

OBJECTIVE

This study aim was to examine and compare PTSD-depression comorbidity networks of two types of trauma related to Typhoon Lekima and COVID-19 epidemic.

METHODS

Participants were 1605 and 601 adolescents recruited following Typhoon Lekima and the COVID-19 outbreak, respectively.

RESULTS

COVID-19 and Lekima PTSD-depression networks had considerable similarities, including adequate stability and accuracy, connected symptoms of PTSD and depression, symptoms with high centralities, and bridge symptoms. PTSD-depression comorbid symptoms were more complicated in the COVID-19 network but may show more persistence in the Lekima network. Distinct bridge symptoms contributed to the heterogeneity of PTSD-depression comorbidity characteristics between the two networks. Specifically, restricted affect and felt down and unhappy were two important bridge symptoms with high centrality unique to the COVID-19 network.

CONCLUSIONS

PTSD-depression comorbidity network has considerable replicability across trauma types, but specific symptom-level associations and some bridge symptoms may vary across trauma types. These findings also highlight the importance of negative emotions to comorbid PTSD and depression in adolescents following the COVID-19 outbreak compared with Typhoon Lekima.

Symptom structure of posttraumatic stress disorder after parental bereavement - a network analysis of Chinese parents who have lost their only child

BACKGROUND

The death of a child is a highly traumatic event and often leads to mental health problems, including posttraumatic stress disorder (PTSD). Previous studies have focused on overall PTSD after the loss of an only child; however, little attention has been given to PTSD at the symptom level. This study aims to identify the network structure of PTSD symptoms in bereaved parents who have lost their only child, known as Shidu parents in Chinese society.

METHODS

A cross-sectional study enrolled 385 bereaved individuals who had lost an only child across 10 cities in China from November 2016 to July 2017. PTSD symptoms were measured by the PTSD Checklist for DSM-5 (PCL-5). Network analysis was implemented by using the R packages qgraph and bootnet.

RESULTS

The PTSD network revealed that diminished interest, exaggerated startle, irritability/anger, and nightmares were the most central symptoms. The strongest connections emerged between the symptoms of recurrent thoughts and nightmares, irritability/anger and reckless/self-destructive behavior, and hypervigilance and exaggerated startle.

LIMITATIONS

We utilized cross-sectional data, and it is therefore not possible to infer the evolution of the symptom network over time. In addition, participants were limited to parents who had lost an only child, and the findings of this study must be interpreted with caution.

CONCLUSIONS

The current study provides further clarity regarding how PTSD symptoms relate to each other in bereaved parents who have lost an only child. Symptoms with high centrality and connectedness may be viable targets for intervention in bereaved parents who have lost an only child.

Psychopathological networks: Theory, methods and practice

In recent years, network approaches to psychopathology have sparked much debate and have had a significant impact on how mental disorders are perceived in the field of clinical psychology. However, there are many important challenges in moving from theory to empirical research and clinical practice and vice versa. Therefore, in this article, we bring together different points of view on psychological networks by methodologists and clinicians to give a critical overview on these challenges, and to present an agenda for addressing these challenges. In contrast to previous reviews, we especially focus on methodological issues related to temporal networks. This includes topics such as selecting and assessing the quality of the nodes in the network, distinguishing between- and within-person effects in networks, relating items that are measured at different time scales, and dealing with changes in network structures. These issues are not only important for researchers using network models on empirical data, but also for clinicians, who are increasingly likely to encounter (person-specific) networks in the consulting room.

Relationships between childhood trauma and perceived stress in the general population: a network perspective

BACKGROUND

Experiences of childhood trauma (CT) are associated with increased psychological vulnerability. Past research suggests that CT might alter stress processing with a subsequent negative impact on mental health. However, it is currently unclear how different domains of CT exert effects on specific subjective experiences of stress during adulthood.

METHODS

In the present study, we used network analysis to explore the complex interplay between distinct domains of CT and perceived stress in a large, general-population sample of middle-aged adults (N = 1252). We used a data-driven community-detection algorithm to identify strongly connected subgroups of items within the network. To assess the replicability of the findings, we repeated the analyses in a second sample (N = 862). Combining data from both samples, we evaluated network differences between men (n = 955) and women (n = 1159).

RESULTS

Results indicate specific associations between distinct domains of CT and perceived stress. CT domains reflecting a dimension of deprivation, i.e. experiences of neglect, were associated exclusively to a stress network community representing low perceived self-efficacy. By contrast, CT associated with threat, i.e. experiences of abuse, was specifically related to a stress community reflecting perceived helplessness. Our results replicated with high accordance in the second sample. We found no difference in network structure between men and women, but overall a stronger connected network in women.

CONCLUSIONS

Our findings emphasize the unique role of distinct domains of CT in psychological stress processes in adulthood, implying opportunities for targeted interventions following distinct domains of CT.

Disorder agnostic network structure of psychopathology symptoms in youth

BACKGROUND

Youth mental health disorders are strong predictors of adult mental health disorders. Early identification of mental health disorders in youth is important as it could aid early intervention and prevention. In a disorder agnostic manner, we aimed to identify influential psychopathology symptoms that could impact mental health in youth.

METHODS

This study sampled 6063 participants from the Philadelphia Neurodevelopmental Cohort and comprised of youth of ages 12-21 years. A mixed graphical model was used to estimate the network structure of 115 symptoms corresponding to 16 psychopathology domains. Importance of individual symptoms in the network were assessed using node influence measures such as strength centrality and predictability.

RESULTS

The generated network had stronger associations between symptoms within a psychopathological domain; overall had no negative associations. A conduct disorder symptom eliciting threatening others and a depression symptom - persistent sadness or depressed mood - had the greatest strength centralities (β = 2.85). Fear of traveling in a car and compulsively going in and out a door had the largest predictability (classification accuracy = 0.99). Conduct disorder, depression, and obsessive compulsive disorder symptoms generally had the largest strength centralities. Suicidal thoughts had the largest bridge strength centrality (β = 2.85). Subgroup networks revealed that network structure differed by socioeconomic status (low versus high, p = 0.04) and network connectivity patterns differed by sex (p = 0.01), but not for age or race.

CONCLUSIONS

Psychopathology symptom networks offer insights that could be leveraged for early identification, intervention, and possibly prevention of mental health disorders.

Cross-cultural investigation of COVID-19 related acute stress: A network analysis

The outbreak of the COVID-19 pandemic has confronted humanity with an ongoing biopsychosocial stressor, imposing multifaceted challenges to individuals and societies. Particularly, the pandemic reflects an ongoing, potentially life-threatening danger to self and others, which may instigate acute stress symptoms (ASS). This study utilized a network framework to assess cross-national ASS a short time following the initial COVID-19 outbreak. Three samples of adult participants from China, Israel, and Switzerland completed a self-report assessment of acute stress symptoms. Network analyses were utilized to uncover the phenotype and dynamics of different ASS in these three countries. The ASS network analyses revealed extensive connections in all networks and reflected the structure of ASS. The centrality indexes in all networks were from the hyperarousal cluster. "Feeling jumpy" was the node with the highest strength centrality in the Israeli sample and "physiological reactivity" was the item with the highest centrality in the Swiss sample. In the Chinese sample, the item with the highest centrality was "feeling alert to danger." The findings reveal that despite some variations, the overall clinical picture of ASS in response to the COVID-19 pandemic is universal. These findings highlight the centrality of hyperarousal symptoms, presumably reflecting its significance for clinical interventions.

Network Analysis of Neurobehavioral and Posttraumatic Stress Disorder Symptoms One Year after Traumatic Brain Injury: A Veterans Affairs TBI Model Systems Study

Traumatic brain injury (TBI) is often experienced under stressful circumstances that can lead to both symptoms of posttraumatic stress disorder (PTSD) and neurobehavioral symptoms of brain injury. There is considerable symptom overlap in the behavioral expression of these conditions. Psychometric network analysis is a useful approach to investigate the role of specific symptoms in connecting these two disorders and is thus well-suited to explore their interrelatedness. This study applied network analysis to examine the associations among PTSD and TBI symptoms in a sample of Service Members and Veterans (SM/Vs) with a history of TBI one year after injury. Responses to the Neurobehavioral Symptom Inventory (NSI) and PTSC Checklist-Civilian version (PCL-C) were obtained from participants who completed comprehensive inpatient rehabilitation services at five VA polytrauma rehabilitation centers. Participants (N = 612) were 93.1% male with an average age of 36.98 years at injury. The analysis produced a stable network. Within the NSI symptom groups, the frustration symptom was an important bridge between the affective and cognitive TBI symptoms. The PCL-C nodes formed their own small cluster with hyperarousal yielding connections with the affective, cognitive, and somatic symptom groups. Consistent with this observation, the hyperarousal node had the second strongest bridge centrality in the network. Hyperarousal appears to play a key role in holding together this network of distress and thus represents a prime target for intervention among individuals with elevated symptoms of PTSD and a history of TBI. Network analysis offers an empirical approach to visualizing and quantifying the associations among symptoms. The identification of symptoms that are central to connecting multiple conditions can inform diagnostic precision and treatment selection.

The network structure of core depressive symptom-domains in major depressive disorder following antidepressant treatment: a randomized clinical trial

BACKGROUND

Network analysis (NA) conceptualizes psychiatric disorders as complex dynamic systems of mutually interacting symptoms. Major depressive disorder (MDD) is a heterogeneous clinical condition, and very few studies to date have assessed putative changes in its psychopathological network structure in response to antidepressant (AD) treatment.

METHODS

In this randomized trial with adult depressed outpatients (n = 151), we estimated Gaussian graphical models among nine core MDD symptom-domains before and after 8 weeks of treatment with either escitalopram or desvenlafaxine. Networks were examined with the measures of cross-sectional and longitudinal structure and connectivity, centrality and predictability as well as stability and accuracy.

RESULTS

At baseline, the most connected MDD symptom-domains were fatigue-cognitive disturbance, whereas at week 8 they were depressed mood-suicidality. Overall, the most central MDD symptom-domains at baseline and week 8 were, respectively, fatigue and depressed mood; in contrast, the most peripheral symptom-domain across both timepoints was appetite/weight disturbance. Furthermore, the psychopathological network at week 8 was significantly more interconnected than at baseline, and they were also structurally dissimilar.

CONCLUSION

Our findings highlight the utility of focusing on the dynamic interaction between depressive symptoms to better understand how the treatment with ADs unfolds over time. In addition, depressed mood, fatigue, and cognitive/psychomotor disturbance seem to be central MDD symptoms that may be viable targets for novel, focused therapeutic interventions.

Connecting the dots: A network approach to post‐traumatic stress symptoms in Chinese healthcare workers during the peak of the Coronavirus Disease 2019 outbreak

Healthcare workers are at elevated risk to develop symptoms of post-traumatic stress disorder (PTSD) in response to an outbreak of a highly infectious disease. The current study set-out to model the complex interrelations between PTSD symptoms during the peak of the Coronavirus Disease 2019 outbreak in 291 Chinese healthcare workers and 291 matched control cases that were selected from the general population. For this purpose, we estimated regularized partial correlation networks. Within the network of healthcare workers, we observed a central role for avoidance of reminders of the traumatic event, physiological cue reactivity, anger/irritability, re-experiencing, and startle. We identified three clusters of closely interconnected PTSD symptoms in healthcare workers, consisting of (a) symptoms of re-experiencing and anxious arousal, (b) symptoms of avoidance and amnesia and (c) symptoms of emotional numbing and dysphoric arousal. Respectively, startle, avoidance of reminders and feeling detached emerged as bridging nodes in these communities. Although yielding highly similar network models, the PTSD symptom structure of healthcare workers showed several unique features compared to the matched control sample. This is informative for interventions aimed at targeting PTSD symptoms in healthcare workers in the context of a public health emergency.

Investigating the structure of trait rumination in autistic adults: A network analysis

LAY ABSTRACT

Autistic adults are substantially more likely to develop depression than individuals in the general population, and recent research has indicated that certain differences in thinking styles associated with autism may play a role in this association. Rumination, the act of thinking about the same thing over and over without a functional outcome, is a significant risk factor for depression in both autistic and non-autistic adults. However, little is known about how different kinds of rumination relate to each other and to depressive symptoms in the autistic population specifically. To fill this gap in knowledge, we recruited a large online sample of autistic adults, who completed questionnaire measures of both the tendency to ruminate and symptoms of depression. By examining the interacting network of rumination and depression symptoms, this study was able to identify particular aspects of rumination-such as thinking repetitively about one's guilty feelings or criticizing oneself-that may be particularly important in maintaining these harmful thought patterns in autistic adults. Although further study is needed, it is possible that the symptoms identified as most "influential" in the network may be particularly good targets for future interventions for mood and anxiety disorders in the autistic population.

A network analysis of post-traumatic stress and psychosis symptoms

BACKGROUND

Understanding the interplay between trauma-related psychological mechanisms and psychotic symptoms may improve the effectiveness of interventions for post-traumatic stress reactions in psychosis. Network theory assumes that mental health problems persist not because of a common latent variable, but from dynamic feedback loops between symptoms, thereby addressing the heterogeneous and overlapping nature of traumagenic and psychotic diagnoses. This is a proof-of-concept study examining interactions between post-traumatic stress symptoms, which were hypothesized to reflect trauma-related psychological mechanisms, and auditory hallucinations and delusions.

METHOD

Baseline data from two randomised controlled trials (N = 216) of trauma-focused therapy in people with post-traumatic stress symptoms (87.5% met diagnostic criteria for PTSD) and psychotic disorder were analysed. Reexperiencing, hyperarousal, avoidance, trauma-related beliefs, auditory hallucinations and delusional beliefs were used to estimate a Gaussian graphical model along with expected node influence and predictability (proportion of explained variance).

RESULTS

Trauma-related beliefs had the largest direct influence on the network and, together with hypervigilance, were implicated in the shortest paths from flashbacks to delusions and auditory hallucinations.

CONCLUSIONS

These findings are in contrast to previous research suggesting a central role for re-experiencing, emotional numbing and interpersonal avoidance in psychosis. Trauma-related beliefs were the psychological mechanism most associated with psychotic symptoms, although not all relevant mechanisms were measured. This work demonstrates that investigating multiple putative mediators may clarify which processes are most relevant to trauma-related psychosis. Further research should use network modelling to investigate how the spectrum of traumatic stress reactions play a role in psychotic symptoms.

Measuring Risk Tolerance across Domains: Scale Development and Validation

Risk attitudes are of interest to researchers in many fields as they play a crucial role in our day-to-day decision-making. In this paper we develop a measure of risk attitudes-the Multi-Domain Risk Tolerance (MDRT) scale-that addresses some key shortcomings of popular self-report scales, such as the Domain-Specific Risk-Taking (DOSPERT) scale. We do this by clearly aligning the risk in the items with the particular domain of risk, reducing item ambiguity, and reducing the impact of prior knowledge. We developed the MDRT using an Exploratory Graph Analysis (EGA) and Item Response Theory (IRT) approach with a community sample (N = 921). We examined its construct and convergent validity (N = 493) and construct generalizability (N = 487). We found that the MDRT had excellent internal consistency, dimensionality and latent factor structure. The MDRT also demonstrated significant convergent validity with related scales used in the literature. The MDRT is shown to be a promising alternative measure of risk attitudes.

Identifying the central symptoms of problematic social networking sites use through network analysis

BACKGROUND

Problematic social media use (PSMU) has received growing attention in the last fifteen years. Even though PSMU has been extensively studied, its internal structure is not fully understood. We used network analysis to evaluate which symptoms and associations between symptoms are most central to PSMU - as assessed by the Generalized Problematic Internet Use Scale-2 adapted for PSMU - among undergraduates.

METHOD

Network analysis was applied to a large gender-balanced sample of undergraduates (n = 1344 participants; M = 51.9%; mean age = 22.50 ± 2.20 years).

RESULTS

The most central nodes in the network were the difficulty of controlling one's own use of social media, the tendency to think obsessively about going online, the difficulties in resisting the urge to use social media and the preference for communicating with people online rather than face-to-face. This last element was strongly associated with a general preference for online social interactions and the feeling of being more comfortable online. The network was robust to stability and accuracy tests. The mean levels of symptoms and symptom centrality were not associated.

CONCLUSIONS

Deficient self-regulation and preference for online communication were the most central symptoms of PSMU, suggesting that these symptoms should be prioritized in theoretical models of PSMU and could also serve as important treatment targets for PSMU interventions.

Using network analysis to compare diagnosis-specific and age-specific symptom networks in eating disorders

OBJECTIVE

The network theory of mental disorders conceptualizes eating disorders (EDs) as networks of interacting symptoms. Network analysis studies in EDs mostly have examined transdiagnostic and/or mixed age samples. The aim of our study was to investigate similarities and differences of networks in adolescents and adults with anorexia nervosa (AN) or bulimia nervosa (BN).

METHOD

Participants were 2,535 patients (n = 991 adults with AN, n = 821 adolescents with AN, n = 473 adults with BN, and n = 250 adolescents with BN) who completed the Eating Disorder Inventory-2. Twenty-seven items were selected. Cross-sectional networks were estimated via Joint Graphical Lasso. Core symptoms were identified using strength centrality. Spearman correlations and network comparison tests (NCTs) were used to compare groups.

RESULTS

Across diagnoses and ages, feeling ineffective, desire to be thinner, worries that feelings will get out of control, guilt after overeating as well as doing things perfectly emerged as most central symptoms. There were moderate to high correlations between symptom profiles (0.62-0.97, mean: 0.78) as well as high correlations between network structures (0.83-0.93, mean: 0.87) and network strengths (0.73-0.95, mean: 0.85). Global strength significantly differed in two of the six NCTs, and 2.5-10% of edges differed between networks.

DISCUSSION

Considerable similarities in network structures and strengths across diagnoses and ages speak in favor of the transdiagnostic approach to EDs. Besides drive for thinness, ineffectiveness, emotion regulation difficulties, and perfectionism might be the most consistent factors in ED networks. These symptoms as well as their symptom connections should be especially focused in treatment regardless of age and diagnosis.

A network analysis investigation of the comorbidity between sleep dysfunction and PTSD symptomatology among Filipino domestic workers in Macao (SAR) China

Posttraumatic stress disorder (PTSD) is highly comorbid with sleep dysfunction. This association was previously explained based on cognitive and emotional dysfunction. The current study extends this literature by investigating the symptom level comorbidity of sleep dysfunction and DSM-5 PTSD utilizing a network approach. Participants were trauma-exposed female Filipino domestic workers (N = 1241). Network analysis was applied to 23 items: 18 items from PCL-5 measuring PTSD (Community 1) and 5 items from PSQI assessing sleep dysfunction (Community 2). The results showed that the symptoms within each community had the strongest correlations. Bridge connections were identified between the sleep dysfunction and PTSD symptom communities. Symptoms with the highest bridge strength were concentration difficulties, recklessness, irritability, and sleep disturbance. This is among the first studies investigating the comorbidity between PTSD and sleep dysfunction from the network approach. Future interventions may be developed that emphasize the bridge symptoms to address comorbidity among trauma exposed migrants.

A Network Analysis of the Associations Between Posttraumatic Stress Symptoms and Posttraumatic Growth Among Disaster-Exposed Chinese Young Adults

Posttraumatic stress symptoms (PTSS) and posttraumatic growth (PTG) have been shown to coexist following exposure to a traumatic event, but consensus about what accounts for this association is lacking. Network analysis is a novel analytic method that can explain this linkage. In a sample of 1,809 Chinese college students (66.1% female, age range: 16-35 years) who were directly exposed to a typhoon, we investigated the network structure of PTSS and PTG, along with bridge symptoms and elements, to elucidate how distress and growth coexist. The seven strongest edges found in the model included two between elements in the PTSS cluster, one between elements of PTG, and four between elements of PTSS and PTG. Eight bridge symptoms and elements emerged: intrusive thoughts, emotional cue reactivity, hypervigilance, self-destructive or reckless behavior, nightmares, and physiological cue reactivity among PTSS, and changed priorities and stronger religious faith among PTG elements. These findings reveal connections between PTSS and PTG that explain how these constructs may coexist in individuals exposed to natural disasters. The network perspective provides a novel way to conceptualize the association between PTSS and PTG and contributes to the field's understanding of recovery after traumatic events.

A Network Analysis of Clinical Variables in Chronic Pain: A Study from the Swedish Quality Registry for Pain Rehabilitation (SQRP)

BACKGROUND

Efforts to identify specific variables that impact most on outcomes from interdisciplinary pain rehabilitation are challenged by the complexity of chronic pain. Methods to manage this complexity are needed. The purpose of the study was to determine the network structure entailed in a set of self-reported variables, examine change, and look at potential predictors of outcome, from a network perspective.

METHODS

In this study we apply network analysis to a large sample of people seeking interdisciplinary pain treatment (N = 2,241). Variables analyzed include pain intensity, pain interference, extent of pain, depression, anxiety, insomnia, and psychological variables from cognitive behavioral models of chronic pain.

RESULTS

We found that Acceptance, Pain Interference, and Depression were key, "central," variables in the pretreatment network. Interestingly, there were few changes in the overall network configuration following treatment, specifically with respect to which variables appear most central relative to each other. On the other hand, Catastrophizing, Depression, Anxiety, and Pain Interference each became less central over time. Changes in Life Control, Acceptance, and Anxiety were most strongly related to changes in the remainder of the network as a whole. Finally, no network differences were found between treatment responders and non-responders.

CONCLUSIONS

This study highlights potential future targets for pain treatment. Further application of a network approach to interdisciplinary pain rehabilitation data is recommended. Going forward, it may be better to next do this in a more comprehensive theoretically guided fashion, and ideographically, to detect unique individual differences in potential treatment processes.

A computational network perspective on pediatric anxiety symptoms

BACKGROUND

While taxonomy segregates anxiety symptoms into diagnoses, patients typically present with multiple diagnoses; this poses major challenges, particularly for youth, where mixed presentation is particularly common. Anxiety comorbidity could reflect multivariate, cross-domain interactions insufficiently emphasized in current taxonomy. We utilize network analytic approaches that model these interactions by characterizing pediatric anxiety as involving distinct, inter-connected, symptom domains. Quantifying this network structure could inform views of pediatric anxiety that shape clinical practice and research.

METHODS

Participants were 4964 youths (ages 5-17 years) from seven international sites. Participants completed standard symptom inventory assessing severity along distinct domains that follow pediatric anxiety diagnostic categories. We first applied network analytic tools to quantify the anxiety domain network structure. We then examined whether variation in the network structure related to age (3-year longitudinal assessments) and sex, key moderators of pediatric anxiety expression.

RESULTS

The anxiety network featured a highly inter-connected structure; all domains correlated positively but to varying degrees. Anxiety patients and healthy youth differed in severity but demonstrated a comparable network structure. We noted specific sex differences in the network structure; longitudinal data indicated additional structural changes during childhood. Generalized-anxiety and panic symptoms consistently emerged as central domains.

CONCLUSIONS

Pediatric anxiety manifests along multiple, inter-connected symptom domains. By quantifying cross-domain associations and related moderation effects, the current study might shape views on the diagnosis, treatment, and study of pediatric anxiety.

Unraveling specifics of mental health symptoms in war survivors who fled versus stayed in the area of conflict using network analysis

BACKGROUND

War survivors often report symptoms of post-traumatic stress disorder (PTSD), depression, anxiety, and somatization. Hence, understanding symptom constellations among different populations of war survivors is critical.

METHODS

Using the network approach to psychopathology, we examined symptom centrality for these conditions in war survivors from Balkan countries who had stayed in the area of former conflict compared to those individuals from Balkan countries who had fled to Western European countries (N = 4,167) with the Impact of Events Scale-Revised and the Brief Symptom Inventory. We further compared networks for war survivors who met criteria for PTSD-diagnosis (assessed with the MINI-International Neuropsychiatric Interview) to those without PTSD-diagnosis.

RESULTS

Globally, networks were similar across the groups, whereas specific differences emerged in symptom centrality. More consistencies were found between PTSD and Western country networks, which may be partially explained by a higher prevalence of PTSD in those who had fled to Western European than in those who had stayed in the Balkan countries.

LIMITATIONS

Given the cross-sectional nature of our data, the directionality of edges in our networks remains unclear. Further, higher levels of trauma exposure and symptom severity in Western country participants may have confounded results.

CONCLUSIONS

The PTSD findings are in line with previous research on PTSD symptoms. They further provide novel insights into depressive, anxiety, and somatization symptoms in survivors of war. These findings need to be substantiated and call for future intervention studies that test the effects of targeting central symptoms we identified in our study.

Longitudinal attention-deficit/hyperactivity disorder symptom networks in childhood and adolescence: Key symptoms, stability, and predictive validity

The current study visualized attention-deficit/hyperactivity disorder (ADHD) symptom networks in a longitudinal sample of participants across childhood and adolescence with exploratory examination of age and gender effects. Eight hundred thirty-six children ages 7-13 years were followed annually for 8 years in total. Across parent and teacher report, results suggested "is easily distracted" and "difficulties sustaining attention" as central symptoms across three testing points (i.e., Year 1, Year 3, and Years 5-8 collapsed). "Difficulties following instructions" and "intrudes/interrupts" also emerged as parent-reported central symptoms. Assessment of network structure across the three testing points suggested global robustness of relations among ADHD symptoms from midchildhood into early adolescence. However, relations among symptoms that cause problems in school settings (i.e., being easily distracted) were stronger in teacher-reported than parent-reported networks. When aggregated into a sum score, central symptoms during Year 1 predicted total difficulties related to mental health problems 5 years later just as well as all 18 symptoms. Central symptoms of ADHD may be useful as screeners of future emotional and behavioral difficulties. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Symptom centrality and infrequency of endorsement identify adolescent depression symptoms more strongly associated with life satisfaction

Although depression symptoms are often treated as interchangeable, some symptoms may relate to adolescent life satisfaction more strongly than others. To assess this premise, we first conducted a network analysis on the Mood and Feelings Questionnaire (MFQ) in a large (N = 1,059), cross-sectional sample of community adolescents (age M = 14.72 ± 1.79). The most central symptoms of adolescent depression, as indexed by strength, were self-hatred, loneliness, sadness, and worthlessness while the least frequently endorsed symptoms were self-hatred, anhedonia, feeling like a bad person, and feeling unloved. Moreover, the more central a depression symptom was in the network (i.e., higher strength), the more variance it shared with life satisfaction (r = 0.59, 95% CI: 0.27, 0.76). How frequently a symptom was endorsed was negatively associated with the variance symptoms shared with life satisfaction (r = -0.48, 95% CI: -0.63, -0.21). Cross-validated, prediction focused models found central symptoms were expected to predict more out of fold variance in life satisfaction than peripheral symptoms and frequently endorsed symptoms, but not the least frequently endorsed symptoms. These findings show certain depression symptoms may be more strongly associated with life satisfaction in adolescence and these symptoms can be identified by multiple symptom-level metrics. Limitations include use of cross-sectional data and utilizing a community sample. Better understanding which symptoms of depression share more variance with important outcomes like life satisfaction could help us develop a more fine-grained understanding of adolescent depression.

Internalizing symptoms, well-being, and correlates in adolescence: A multiverse exploration via cross-lagged panel network models

Internalizing symptoms are the most prevalent mental health problem in adolescents, with sharp increases seen, particularly for girls, and evidence that young people today report more problems than previous generations. It is therefore critical to measure and monitor these states on a large scale and consider correlates. We used novel panel network methodology to explore relationships between internalizing symptoms, well-being, and inter/intrapersonal indicators. A multiverse design was used with 32 conditions to consider the stability of results across arbitrary researcher decisions in a large community sample over three years (N = 15,843, aged 11-12 at Time 1). Networks were consistently similar for girls and boys. Stable trait-like effects within anxiety, attentional, and social indicators were found. Within-person networks were densely connected and suggested mental health and inter/intrapersonal correlates related to one another in similar complex ways. The multiverse design suggested the particular operationalization of items can substantially influence conclusions. Nevertheless, indicators such as thinking clearly, unhappiness, dealing with stress, and worry showed more consistent centrality, suggesting these indicators may play particularly important roles in the development of mental health in adolescence.

A Network Analysis of DSM-5 Posttraumatic Stress Disorder Symptoms and Event Centrality

The centrality of a traumatic event to one's autobiographical memory has been associated with posttraumatic stress disorder (PTSD) symptom severity. In the present study, we investigated the associations between specific features of event centrality (EC), as measured using the Centrality of Event Scale, and specific symptoms of PTSD. We computed a cross-sectional graphical lasso network of PTSD symptoms and specific features of EC in a sample of trauma-exposed individuals (n = 451), many of whom met the clinical threshold for a PTSD diagnosis. The graphical lasso revealed intrusive memories, negative trauma-related feelings, and the perception that the traumatic event was central to one's identity to be influential nodes. Viewing the future through the lens of one's trauma exposure was the EC feature most strongly linked to PTSD. Among all PTSD symptoms, blaming oneself or others for the traumatic event showed the strongest link to EC. The network was stable, allowing for reliable interpretations. Future longitudinal research is needed to clarify the associations among EC features and PTSD symptoms over time.

Network Analysis of Posttraumatic Stress and Eating Disorder Symptoms in a Community Sample of Adults Exposed to Childhood Abuse

Posttraumatic stress disorder (PTSD) and eating disorders (EDs) are individually debilitating and highly comorbid conditions. Childhood abuse is a prominent risk factor for PTSD and ED symptoms both individually and as a comorbid syndrome (PTSD-ED). There may be a functional association between comorbid PTSD-ED symptoms whereby disordered eating behaviors are used to avoid trauma-related thoughts and feelings. The current study used a network analytic approach to examine key associations between PTSD and ED symptom subscales (i.e., PCL-5 and EPSI, respectively) in a community sample of 120 adults who endorsed at least one experience of childhood abuse (i.e., physical, sexual, or emotional abuse; witnessing domestic violence). Participants completed an anonymous online survey using Amazon's Mechanical Turk Prime. We used three network analysis indices (i.e., strength centrality, key players, and bridge symptoms) to identify symptoms that may maintain the comorbid PTSD-ED network. The results indicated that reexperiencing symptoms had the highest strength centrality in the PTSD-ED network and bridged the PTSD and ED clusters. For ED, cognitive restraint was a bridge to all PTSD symptoms. Hyperarousal, negative alterations in cognitions and mood (NACM), and purging were key players, indicating they are integral to the network structure. If replicated in prospective studies, these results may indicate that reexperiencing and cognitive restraint are core drivers of PTSD-ED comorbidity, whereas hyperarousal, NACM, and purging may be downstream consequences maintaining the comorbid condition. Concurrent treatments that address PTSD and ED symptoms simultaneously may result in the best outcomes.

The network structure of schizotypy in the general population

Schizotypal personality traits show similarity with schizophrenia at various levels of analysis. It is generally agreed that schizotypal personality is multidimensional; however, it is still debated whether impulsive nonconformity should be incorporated into theories and measurement of schizotypy. In addition, relatively little is known about the network structure of the four-dimensional model of schizotypal personality. To estimate the network structure of schizotypy, we used data from participants recruited from the community (N = 11,807) who completed the short version of the Oxford-Liverpool Inventory of Feelings and Experiences, a widespread self-report instrument that assesses the positive, negative, disorganised and impulsive domains of schizotypy. We performed community detection, then examined differences between communities in terms of centralities and compared the strength of edges within and between communities. We found communities that almost perfectly corresponded to the a priori-defined subscales (93% overlap, normalised mutual information = 0.74). Items in the disorganisation community had higher closeness centrality relative to items in the other communities (Cliff's Δs ranged from 0.55 to 0.83) and weights of edges within the disorganisation community were stronger as compared to the negative schizotypy and impulsive nonconformity communities (Cliff's Δs = 0.33). Our findings imply that the inclusion of impulsive nonconformity items does not dilute the classical three-factor structure of positive, negative and disorganised schizotypy. The high closeness centrality of disorganisation concurs with theories positing that cognitive slippage and associative loosening are core features of the schizophrenic phenotype.

A network analysis of risk factors for suicide in Iraq/Afghanistan-era veterans

Suicidal ideation (SI) is a prevalent issue in the veteran population. A number of factors have been identified as risk factors for suicidal ideation (SI) in veterans, including suicide attempts, depression, posttraumatic stress disorder (PTSD), and drug use. However, clinicians' ability to predict suicide is poor, particularly given the interplay between various factors such as previous suicide attempts. As such, there is a gap in our knowledge of which factors most saliently predict suicide risk and which should be targets for interventions designed to lower SI. Network analysis, a method allowing for an examination of how variables relate within the context of a network of factors, may bridge this gap by simultaneously evaluating the interrelationships between risk factors for suicide in veterans. Current study used network analysis and data from 2268 Iraq/Afghanistan-era military veterans to examine the relationships between suicidal ideation and several factors related to suicide risk, such as past suicide attempts, PTSD symptoms, depression, drug use, trauma exposure. Partial correlation network results showed suicidal ideation to be strongly related to depression, with smaller connections to past suicide attempts and anger. Additionally, past suicide attempts was strongly related to history of childhood trauma and weakly related to problematic drug use and PTSD symptoms. These results offer valuable information for both predicting suicide risk and differentiating targets for interventions lowering suicide risk in veterans.

Network analysis of PTSD in college students across different areas after the COVID-19 epidemic

Background: Various studies have examined the psychological 'typhoon eye' and 'ripple' effects in mental disorders following COVID-19. However, these studies only considered the disorders as entities and assessed severity, and overlooked the differences in specific symptoms of disorders. Objectives: This aim of the study is to assess the psychological typhoon eye and ripple effects at the symptom-level in posttraumatic stress disorder (PTSD), which is considered as a common psychopathology following the COVID-19 epidemic. Method: In total, 1150 undergraduates, including 271 students from the Hubei province (e.g. epidemic centre) and 879 students from other provinces, completed the self-report questionnaire. The networks were estimated and compared using the R packages. Results: Although the PTSD networks of Hubei and non-Hubei undergraduates were similarly connected and shared some symptoms with high centrality (e.g. flashbacks, irritability and anger), there were differences across the networks. Distorted cognition and no positive emotion only exhibited high centrality in the Hubei network. Physiological responses and exaggerated startle only exhibited high centrality in the non-Hubei network. Conclusion: These findings suggested that the psychological typhoon eye and ripple effects may co-exist at the symptom level. Targeted and distinct psychological services for college students in Hubei and non-Hubei provinces should be emphasized following COVID-19.

A review on post-traumatic stress disorder (PTSD): "Symptoms, Therapies and Recent Case Studies"

Post-traumatic stress disorder (PTSD), previously known as battle fatigue syndrome or shell shock, is a severe mental disturbance condition that is normally triggered by the experience of some frightening/scary events or trauma where a person undergoes some serious physical or mental harm or threatened. PTSD is a long-life effect of the continuous occurrence of traumatic conditions which, leading the production of feelings of helplessness, intense fear, and horror in the person. There are various examples of events that can cause PTSD, such as physical, mental, or sexual assault at home or working place by others, unexpected death of a loved one, an accidental event, war, or some kind of natural disaster. Treatment of PTSD includes the removal or reduction of these emotional feelings or symptoms with the aim to improve the daily life functioning of a person. Problems which are needed to be considered in case of PTSD like ongoing trauma, abusive or bad relationships. Various drugs which are used for the treatment of PTSD include selective serotonin reuptake inhibitors (SSRIs) (citalopram, fluvoxamine, fluoxetine, etc.); tricyclic antidepressants (amitriptyline and isocarboxazid); mood stabilizers (Divalproex and lamotrigine); atypical antipsychotics (aripiprazole and quetiapine), etc. In this review, we have covered the different risk factors, case studies related to various treatment options with different age group peoples in PTSD and their effects on them. We have also covered the symptoms and associated disorders which can play a key role in the development of PTSD.

Network Analysis of Psychopathology: Controversies and Challenges

Empirical publications inspired by the network approach to psychopathology have increased exponentially in the twenty-first century. The central idea that an episode of mental disorder arises from causal interactions among its symptomatic elements has especially resonated with those clinical scientists whose disenchantment with traditional categorical and dimensional approaches to mental illness has become all too apparent. As the field has matured, conceptual and statistical concerns about the limitations of network approaches to psychopathology have emerged, inspiring the development of novel methods to address these concerns. Rather than reviewing the vast empirical literature, I focus instead on the issues and controversies regarding this approach and sketch directions where the field might go next.

The importance of transdiagnostic symptom level assessment to understanding prognosis for depressed adults: analysis of data from six randomised control trials

BACKGROUND

Depression is commonly perceived as a single underlying disease with a number of potential treatment options. However, patients with major depression differ dramatically in their symptom presentation and comorbidities, e.g. with anxiety disorders. There are also large variations in treatment outcomes and associations of some anxiety comorbidities with poorer prognoses, but limited understanding as to why, and little information to inform the clinical management of depression. There is a need to improve our understanding of depression, incorporating anxiety comorbidity, and consider the association of a wide range of symptoms with treatment outcomes.

METHOD

Individual patient data from six RCTs of depressed patients (total n = 2858) were used to estimate the differential impact symptoms have on outcomes at three post intervention time points using individual items and sum scores. Symptom networks (graphical Gaussian model) were estimated to explore the functional relations among symptoms of depression and anxiety and compare networks for treatment remitters and those with persistent symptoms to identify potential prognostic indicators.

RESULTS

Item-level prediction performed similarly to sum scores when predicting outcomes at 3 to 4 months and 6 to 8 months, but outperformed sum scores for 9 to 12 months. Pessimism emerged as the most important predictive symptom (relative to all other symptoms), across these time points. In the network structure at study entry, symptoms clustered into physical symptoms, cognitive symptoms, and anxiety symptoms. Sadness, pessimism, and indecision acted as bridges between communities, with sadness and failure/worthlessness being the most central (i.e. interconnected) symptoms. Connectivity of networks at study entry did not differ for future remitters vs. those with persistent symptoms.

CONCLUSION

The relative importance of specific symptoms in association with outcomes and the interactions within the network highlight the value of transdiagnostic assessment and formulation of symptoms to both treatment and prognosis. We discuss the potential for complementary statistical approaches to improve our understanding of psychopathology.

Network analysis of PTSD and depressive symptoms in 158,139 treatment-seeking veterans with PTSD

BACKGROUND

In recent years, a new framework for analyzing and understanding posttraumatic stress disorder (PTSD) was introduced; the network approach. Up until now, network analysis studies of PTSD were largely conducted on small to medium sample sizes (N < 1,000), which might be a possible cause of variability in main findings. Moreover, only a limited number of network studies investigated comorbidity.

METHODS

In this study, we utilized a large sample to conduct a network analysis of 17 symptoms of PTSD (DSM-IV), and compared it to the result of a second network consisting of symptoms of PTSD and depression (based on Patient Health Questionnaire-9 [PHQ-9]). Our sample consisted of 502,036 treatment-seeking veterans, out of which 158,139 had fully completed the assessment of symptoms of PTSD and a subsample of 32,841 with valid PCL and PHQ-9 that was administered within 14 days or less.

RESULTS

Analyses found that in the PTSD network, the most central symptoms were feeling distant or cut off from others, followed by feeling very upset when reminded of the event, and repeated disturbing memories or thoughts of the event. In the combined network, we found that concentration difficulties and anhedonia are two of the five most central symptoms.

CONCLUSION

Our findings replicate the centrality of intrusion symptoms in PTSD symptoms' network. Taking into account the large sample and high stability of the network structure, we believe our study can answer some of the criticism regarding stability of cross-sectional network structures.

Network Structure of Callous-Unemotional Traits and Conduct Disorder Symptoms Among At-Risk Youth: Multi-Informant Reports and Gender Differences

Network analytic techniques examine how items used to measure underlying constructs are related to one another and identify core characteristics. While many studies have examined the covariance of callous-unemotional (CU) traits or features and conduct disorder (CD) symptoms, the inter-item relations of these constructs and the core characteristics of the CU construct are unclear. The present study aimed to examine the network connectivity of, and between, CU features and CD symptoms. We also examined both parent-reports and youth self-reports and gender differences. CU features and CD symptoms were rated by parents (n = 814; 74% mothers; age 23-73, M age = 43.86, SD = 8.13) and their child (n = 608; 57% female; age 7-19, M age = 13.98, SD = 2.36). Network plots depicted greater connectivity (i.e., density and weights) for CU features relative to CD symptoms across both informants. However, youth-reported CU features and CD symptoms were less densely connected than parent-reports. Items commonly comprising the callousness subscale were more central and linked the two constructs together, relative to uncaring items, across informant and gender. Gender related effects indicated lower centrality for male versus female youth, and this finding was particularly evident in youth-reports. Our findings highlight relations between CU features and CD symptoms, and point to the importance of callousness items in conceptualizations of CU features among high-risk youth from both the perspective of the parent and child. We also inform understanding of gender differences in CU features for which the literature is currently limited.

Alternative DSM-5 Model for Personality Disorders Through the Lens of an Empirical Network Model

The Alternative Model for Personality Disorders defined in Diagnostic and Statistical Manual of Mental Disorders-Fifth edition (DSM-5) has recently attracted considerable interest in empirical research, with different hypotheses being proposed to explain the discordant results shown in previous research. Empirical network analysis has begun to be applied for complementing the study of psychopathological phenomena according to a new perspective. This article applies this analysis to personality facets measured in a sample of 626 patients with mental disorders and a 1,034 normative sample, using the Personality Inventory for DSM-5. The results reveal five substructures partially equivalent to domains defined in the DSM-5. Discordant facets (suspiciousness, hostility, rigid perfectionism, attention seeking, and restricted affectivity) play the role of connectors between substructures. Invariance between clinical and community networks was found except for the connection between unusual beliefs and perceptual dysregulation (stronger in the clinical sample). Considering the strength centrality index, anxiousness, emotional lability, and depressivity can be highlighted for their relative importance within both clinical and normative networks.

Disturbed Sleep Connects Symptoms of Posttraumatic Stress Disorder and Somatization: A Network Analysis Approach

Posttraumatic stress disorder (PTSD) and physical health problems, particularly somatic symptom disorder, are highly comorbid. Studies have only examined this co-occurrence at the disorder level rather than assessing the associations between specific symptoms. Using network analysis to identify symptoms that act as bridges between these disorders may allow for the development of interventions to specifically target this comorbidity. We examined the association between somatization and PTSD symptoms via network analysis. This included 349 trauma-exposed individuals recruited through the National Centre for Mental Health PTSD cohort who completed the Clinician-Administered PTSD Scale for DSM-5 and the Patient Health Questionnaire-15. A total of 215 (61.6%) individuals met the DSM-5 diagnostic criteria for PTSD. An exploratory graph analysis identified four clusters of densely connected symptoms within the overall network: PTSD, chronic pain, gastrointestinal issues, and more general somatic complaints. Sleep difficulties played a key role in bridging PTSD and somatic symptoms. Our network analysis demonstrates the distinct nature of PTSD and somatization symptoms, with this association connected by disturbed sleep.

Comparing the network structure of ICD-11 PTSD and complex PTSD in three African countries

BACKGROUND

Symptom network analysis has become an essential tool for researchers and clinicians investigating the structure of mental disorders. Two methods have been used; one relies on partial correlations, and the second relies on zero order correlations with forced-directed algorithm. This combination was used to examine symptom connections for ICD-11 Posttraumatic Stress Disorder (PTSD) and Complex PTSD (CPTSD) as the symptoms for these disorders have been known to be organized in a multi-dimensional and hierarchical fashion. We aimed to examine whether networks of ICD-11 CPTSD symptoms reproduced across samples from three African countries.

METHODS

We produced network models based on data from 2524 participants in Nigeria (n = 1018), Kenya (n = 1006), and Ghana (n = 500). PTSD and CPTSD symptoms were measured using the International Trauma Questionnaire (Cloitre et al., 2018).

RESULTS

The CPTSD network analysis using force-directed method alongside partial correlations based on Gaussian Graphical Models (GGM) revealed the multidimensional-hierarchal structure of CPTSD. The within-cluster symptoms of Disturbances in Self Organization (DSO) and PTSD were strongly correlated with each other in all networks, and the cross-cluster symptoms were lower. The most central symptom was 'feelings of worthlessness', a symptom of Negative Self-Concept that is part of the CPTSD cluster. The networks were very similar across the three countries.

CONCLUSIONS

Findings support the ICD-11 model of PTSD and CPTSD in three African countries.

Posttraumatic stress or posttraumatic growth? Using network analysis to explore the relationships between coping styles and trauma outcomes

Trauma can produce posttraumatic stress disorder (PTSD), but may also foster positive outcomes, such as posttraumatic growth. Individual differences in coping styles may contribute to both positive and negative sequelae of trauma. Using network analytic methods, we investigated the structure of PTSD symptoms, elements of growth, and coping styles in bereaved survivors of a major earthquake in China. Hypervigilance and difficulty concentrating were identified as the most central symptoms in the PTSD network, whereas establishing a new path in life, feeling closer to others, and doing better things with life ranked highest on centrality in the posttraumatic growth network. Direct connections between PTSD symptoms and elements of growth were low in magnitude in our sample. Our final network, which included PTSD symptoms, growth elements, and coping styles, suggests that adaptive and active coping styles, such as positive reframing, are positively related to elements of growth, but not appreciably negatively related to PTSD symptoms. Conversely, maladaptive coping styles are positively related to PTSD symptoms, but are not negatively associated with growth. Future longitudinal studies could shed light on the direction of causality in these relationships and their clinical utility.

A Cross-Country Network Analysis of Adolescent Resilience

PURPOSE

In situations of adversity, young people draw on individual, relational, and contextual (community and cultural) resources to foster their resilience. Recent literature defines resilience as a capacity that is underpinned by a network of interrelated resources. Although empirical studies show evidence of the value of a network approach, little is known regarding how different country contexts influence which resources are most critical within a resource network and how resources interact for adolescent resilience.

METHODS

Network analysis was conducted with data from studies that had used the Child and Youth Resilience Measure. Regularized partial correlation networks of 17 resources were estimated for 14 countries (Botswana, Canada, China, Colombia, Equatorial Guinea, India, Indonesia, Italy, Jordan, New Zealand, the Philippines, Romania, South Africa, and Syrian refugees living in Jordan). The sample size was 18,914 (mean age = 15.70 years, 48.8% female).

RESULTS

We observed mostly positive associations between the resources of interest. The salience and strength of associations between resources varied by country. The most central resource across countries was having supportive caregivers during stressful times because this resource had the most and strongest positive associations with other resources.

CONCLUSIONS

This study gives first empirical evidence from multiple countries that an interplay of social-ecological resources (such as individual skills, peer, caregiver and community support, and educational aspirations and opportunities) matter for adolescent resilience. Across countries, caregiver support appears to be most central for adolescent resilience. Future resilience interventions might apply this network approach to identify important, contextually relevant resources that likely foster additional resources.

A network analysis of posttraumatic stress symptoms among help-seeking refugees in Kenya

We analyzed the network structure of DSM-IV PTSD symptoms among 2792 help-seeking Central and East African refugees in Kenya exposed to multiple, severe traumatic events and on-going stressors. To some extent, our results reproduced structures identified among clinical populations in Europe, including strong links within traditional symptom clusters, such as between avoidance of thoughts and situations, and hypervigilance and startling. However, we found substantial differences in most central symptoms, with detachment and disinterest far less and emotional numbing and concentration problems more central in our analyses. Our networks did not reproduce the common finding of particularly low centrality of amnesia. We further noted substantive similarities in network structure, but also differences, between refugees living in an urban environment and in refugee camps. Concentration problems were most central among mainly Somali refugees at a refugee camp, and associated with amnesia and sense of foreshortened future, while emotional numbing was the most central symptom among majority Congolese refugees in Nairobi. Our findings highlight the importance of contextual and cultural factors for PTSD symptomatology, and are informative for assessment and treatment among help-seeking refugees.

Bayesian Estimation for Gaussian Graphical Models: Structure Learning, Predictability, and Network Comparisons

Gaussian graphical models (GGM; "networks") allow for estimating conditional dependence structures that are encoded by partial correlations. This is accomplished by identifying non-zero relations in the inverse of the covariance matrix. In psychology the default estimation method uses ℓ1-regularization, where the accompanying inferences are restricted to frequentist objectives. Bayesian methods remain relatively uncommon in practice and methodological literatures. To date, they have not yet been used for estimation and inference in the psychological network literature. In this work, I introduce Bayesian methodology that is specifically designed for the most common psychological applications. The graphical structure is determined with posterior probabilities that can be used to assess conditional dependent and independent relations. Additional methods are provided for extending inference to specific aspects within- and between-networks, including partial correlation differences and Bayesian methodology to quantify network predictability. I first demonstrate that the decision rule based on posterior probabilities can be calibrated to the desired level of specificity. The proposed techniques are then demonstrated in several illustrative examples. The methods have been implemented in the R package BGGM.

Problems with Centrality Measures in Psychopathology Symptom Networks: Why Network Psychometrics Cannot Escape Psychometric Theory

Understanding patterns of symptom co-occurrence is one of the most difficult challenges in psychopathology research. Do symptoms co-occur because of a latent factor, or might they directly and causally influence one another? Motivated by such questions, there has been a surge of interest in network analyses that emphasize the putatively direct role symptoms play in influencing each other. In this critical paper, we highlight conceptual and statistical problems with using centrality measures in cross-sectional networks. In particular, common network analyses assume that there are no unmodeled latent variables that confound symptom co-occurrence. The traditions of clinical taxonomy and test development in psychometric theory, however, greatly increase the possibility that latent variables exist in symptom data. In simulations that include latent variables, we demonstrate that closeness and betweenness are vulnerable to spurious covariance among symptoms that connect subgraphs (e.g., diagnoses). We further show that strength is redundant with factor loading in several cases. Finally, if a symptom reflects multiple latent causes, centrality metrics reflect a weighted combination, undermining their interpretability in empirical data. Our results suggest that it is essential for network psychometric approaches to examine the evidence for latent variables prior to analyzing or interpreting patterns at the symptom level. Failing to do so risks identifying spurious relationships or failing to detect causally important effects. Altogether, we argue that centrality measures do not provide solid ground for understanding the structure of psychopathology when latent confounding exists.