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

An Examination of Idiographic Networks of Posttraumatic Stress Disorder Symptoms

Although the application of network theory to posttraumatic stress disorder (PTSD) has yielded promising insights, the lack of equivalence between inter- and intraindividual variation limits the generalizability of these findings to any one individual with PTSD. Instead, a better understanding of how PTSD symptoms occur and vary over time within an individual requires exploring the idiographic network structure of PTSD. To do so, the present study used an intensive repeated-measures design to estimate intraindividual networks of PTSD symptoms on a person-by-person basis. Participants were 20 individuals who met criteria for PTSD and completed daily surveys assessing PTSD symptoms; surveys were completed four times per day for approximately 30 days. Employing a recently validated method provided by Fisher, Reeves, Lawyer, Medaglia, and Rubel (2017), we used these data to estimate a contemporaneous and temporal network of PTSD symptoms for individuals on a person-by-person basis. We then calculated centrality metrics to determine the relative importance of each symptom in each idiographic network. Across all contemporaneous networks, negative trauma-related cognitions and emotions were most commonly the most central symptoms. Further, across all temporal networks, (a) negative trauma-related emotions were the most common driver of variation in other symptoms over time and (b) distressing trauma-related dreams and sleep disturbance were the most common downstream consequences of variation in other PTSD symptoms over time. We also reviewed data from two randomly selected participants to illustrate how this approach could be used to identify maintenance factors of PTSD for each individual and guide individual treatment planning.

The replicability and generalizability of internalizing symptom networks across five samples

The popularity of network analysis in psychopathology research has increased exponentially in recent years. Yet, little research has examined the replicability of cross-sectional psychopathology network models, and those that have used single items for symptoms rather than multiitem scales. The present study therefore examined the replicability and generalizability of regularized partial correlation networks of internalizing symptoms within and across 5 samples (total N = 2,573) using the Inventory for Depression and Anxiety Symptoms, a factor analytically derived measure of individual internalizing symptoms. As different metrics may yield different conclusions about the replicability of network parameters, we examined both global and specific metrics of similarity between networks. Correlations within and between nonclinical samples suggested considerable global similarities in network structure (rss = .53-.87) and centrality strength (rss = .37-.86), but weaker similarities in network structure (rss = .36-.66) and centrality (rss = .04-.54) between clinical and nonclinical samples. Global strength (i.e., connectivity) did not significantly differ across all 5 networks and few edges (0-5.5%) significantly differed between networks. Specific metrics of similarity indicated that, on average, approximately 80% of edges were consistently estimated within and between all 5 samples. The most central symptom (i.e., dysphoria) was consistent within and across samples, but there were few other matches in centrality rank-order. In sum, there were considerable similarities in network structure, the presence and sign of individual edges, and the most central symptom within and across internalizing symptom networks estimated from nonclinical samples, but global metrics suggested network structure and symptom centrality had weak to moderate generalizability from nonclinical to clinical samples. (PsycINFO Database Record (c) 2020 APA, all rights reserved).

Pretreatment Posttraumatic Stress Disorder Symptom Network Metrics Predict the Strength of the Association Between Node Change and Network Change During Treatment

Network analysis has been increasingly applied in an effort to understand complex interactions among symptoms in posttraumatic stress disorder (PTSD). Although methods that initially focused on identifying central symptoms in cross-sectional networks have been extended to longitudinal data that can reveal the relative roles of acute symptoms in the emergence of the PTSD syndrome, the association between network metrics and symptom change during treatment have yet to be explored in PTSD. To address this gap, we estimated pretreatment PTSD symptom networks in a sample of patients from a multisite clinical trial for women with full or subthreshold PTSD and substance use. We tested the hypothesis that node metrics calculated in the pretreatment network would be predictive of the strength of the association between a symptom's change and the change in the severity of all other symptoms through the course of treatment. A symptom node's strength and predictability in the pretreatment network were each strongly correlated with the association between that symptom's change and overall change across the symptom network, r(15) = .79, p < .001 and r(15) = .75, p < .001, respectively, whereas a symptom's mean severity at pretreatment was not, r(15) = .27, p = .292. These findings suggest that a node's centrality prior to treatment engagement is a predictor of its association with overall symptom change throughout the treatment process.

Network Analysis of Posttraumatic Stress Experiences of Adults Seeking Psychological Treatment for Childhood Sexual Abuse

Network analysis proposes that mental disorders may best be construed as causal systems embodied in networks of functionally interconnected symptoms. We employed network analysis to test how adult survivors of childhood sexual abuse (CSA) experienced symptoms of posttraumatic stress, using alternative conceptualizations of posttraumatic stress disorder (PTSD). Given the characteristics of the sample (i.e., the nature of and time since trauma), we hypothesized that (a) symptoms related to arousal would not be prominent in the networks and (b) symptoms related to negative alternations in cognition and mood (NACM) would be core components in the network. Danish adults seeking psychological treatment for CSA (n = 473) completed the Harvard Trauma Questionnaire and Trauma Symptom Checklist. Three alternative models (DSM-5, DSM-5 with dissociation, and ICD-11 complex PTSD [CPTSD]) were estimated using regularized partial correlation models. In the DSM-5 network, strong associations emerged for experiences of NACM (blame and guilt) and intrusions (thoughts and flashbacks). The addition of "depersonalization" and "derealization" to the DSM-5 model produced a strong association, but these experiences were largely unrelated to other PTSD clusters. In the CPTSD network, interpersonal problems and negative self-concept were central to the survivors' experiences. For this highly-specific survivor group who experienced traumatic CSA many years ago, experiences related to NACM appeared to be more central to the posttrauma experience than those of arousal. If replicated, these findings could help inform treatment plans for specific groups of survivors. Methodological implications as to the usefulness of network models in the psychopathological research literature are discussed.

A Network Approach to Studying the Associations Between Posttraumatic Stress Disorder Symptoms and Dissociative Experiences

In recent years, there has been a growing recognition of a dissociative subtype of posttraumatic stress disorder (D-PTSD), characterized by experiences of depersonalization (DP) and derealization (DR), among individuals with PTSD. Little is known, however, about how experiences of DP and/or DR are associated with the experience of other PTSD symptoms. The central aim of the present paper was to explore the associations among DP, DR, and other PTSD symptoms by means of a network analysis of cross-sectional data for 557 participants whose overall self-reported PTSD symptom severity warranted a probable PTSD diagnosis. Three notable findings emerged: (a) a strong association between DP and DR, (b) the identification of DP as the most central symptom in the network, and (c) the discovery that clusters of symptoms in the network were roughly consistent with DSM-5 PTSD criteria. We discuss these findings in light of some considerations, including the nature of our sample and the limits of interpreting cross-sectional network models.

The network approach to posttraumatic stress disorder: a systematic review

Background: The empirical literature of network analysis studies of posttraumatic stress symptoms (PTSS) has grown rapidly over the last years. Objective: We aimed to assess the characteristics of these studies, and if possible, the most and least central symptoms and the strongest edges in the networks of PTSS. Method: The present systematic review, conducted in PsycInfo, Medline, and Web of Science, synthesizes findings from 20 cross-sectional PTSS network studies that were accepted for publication between January 2010 and November 2018 (PROSPERO ID: CRD42018112825). Results: Results indicated that the network studies investigated a broad range of samples and that most studies used similar analytic approaches including stability analysis. Only strength centrality was generally adequately stable. Amnesia was consistently reported to have lowest strength, while there was substantial heterogeneity regarding which nodes had highest strength centrality. The strongest edge weights were typically within each DSM-IV/DSM-5 PTSD symptom cluster. Conclusions: Hypothesis-driven studies are needed to determine whether the heterogeneity in networks resulted from differences in samples or whether they are the product of underlying methodological reasons.

Relation between PTSD symptom clusters and positive memory characteristics: A network perspective

Positive memory characteristics relate to posttraumatic stress disorder (PTSD) severity. We utilized a network approach to examine relations between PTSD clusters (intrusions, avoidance, negative alterations in cognitions and mood [NACM], alterations in arousal and reactivity [AAR]) and positive memory characteristics (count, accessibility, valence, vividness, coherence, time perspective, sensory details). We identified differential relations between PTSD clusters and positive memory characteristics, and central/bridging symptoms. Participants were an Amazon Mechanical Turk-recruited sample of 206 individuals (M_age = 35.36; 61.20% females). We estimated a regularized Gaussian Graphic Model comprising four nodes representing the PTSD clusters and six nodes representing positive memory characteristics. Regarding cross-community relations, AAR (highest node strength) was negatively associated with positive memory count, valence, coherence, and accessibility; avoidance was positively and negatively associated with positive memory vividness and count respectively. The NACM-AAR and intrusion-avoidance edges were significantly stronger than most edges. From the PTSD community, AAR and avoidance had the highest bridge strength and bridge expected influence respectively; from the positive memory community, coherence and vividness had the highest bridge strength and bridge expected influence respectively. Results indicate the potential pivotal role of AAR, avoidance, coherence, and vividness in the PTSD-positive memory relation, which renders them assessment/treatment targets pending further investigation.

The network structure of posttraumatic stress disorder among Filipina migrant domestic workers: comorbidity with depression

BACKGROUND

Labour migrants are exposed to potentially traumatic events throughout the migration cycle, making them susceptible to developing mental disorders. Posttraumatic stress disorder (PTSD) is often comorbid with depression. Comorbidity worsens the course of illness, prognosis, treatment response, and increases suicidal risk. Using network analysis, this study examined the structure of PTSD and depression in a sample of migrant domestic workers, an especially vulnerable community of labour migrants. This study sought to derive the central or most important symptoms, strongest edges or relationships among symptoms, and bridge symptoms between PTSD and depression.

METHODS

Data were obtained from 1,375 Filipina domestic workers in Macao SAR, China. Data from a subsample of 1,258 trauma-exposed participants were analysed using R software.

RESULTS

Most of the strongest edges were within the same disorder and, for PTSD, within the same symptom cluster. Highest node centrality were PCL-5's 'avoid thoughts', 'lose interest', 'negative emotions', and 'not concentrate', and PHQ-9's 'sleep difficulties'. The bridge symptoms were PHQ-9's 'sleep difficulties,' 'psychomotor agitation/retardation,' and 'fatigue,' PCL-5's 'not concentrate', and PHQ-9's 'worthlessness' and 'anhedonia'.

LIMITATIONS

Results may not generalize to Filipino migrant workers in other occupations and to male migrant workers. Potentially relevant symptoms like somatic symptoms and fear of somatic and mental symptoms were not included.

CONCLUSIONS

Central and bridge symptoms are the most important nodes in the network. Developing interventions targeting these symptoms, particularly depression symptoms, is a promising alternative to PTSD treatment given substantial barriers to specialist care for this population.

Development of an international data repository and research resource: the Prospective studies of Acute Child Trauma and Recovery (PACT/R) Data Archive

Background: Studies that identify children after acute trauma and prospectively track risk/protective factors and trauma responses over time are resource-intensive; small sample sizes often limit power and generalizability. The Prospective studies of Acute Child Trauma and Recovery (PACT/R) Data Archive was created to facilitate more robust integrative cross-study data analyses. Objectives: To (a) describe creation of this research resource, including harmonization of key variables; (b) describe key study- and participant-level variables; and (c) examine retention to follow-up across studies. Methods: For the first 30 studies in the Archive, we described study-level (design factors, retention rates) and participant-level (demographic, event, traumatic stress) variables. We used Chi square or ANOVA to examine study- and participant-level variables potentially associated with retention. Results: These 30 prospective studies (N per study = 50 to 568; overall N = 5499) conducted by 15 research teams in 5 countries enrolled children exposed to injury (46%), disaster (24%), violence (13%), traffic accidents (10%), or other acute events. Participants were school-age or adolescent (97%), 60% were male, and approximately half were of minority ethnicity. Using harmonized data from 22 measures, 24% reported significant traumatic stress ≥1 month post-event. Other commonly assessed outcomes included depression (19 studies), internalizing/externalizing symptoms (19), and parent mental health (19). Studies involved 2 to 5 research assessments; 80% of participants were retained for ≥2 assessments. At the study level, greater retention was associated with more planned assessments. At the participant level, adolescents, minority youth, and those of lower socioeconomic status had lower retention rates. Conclusion: This project demonstrates the feasibility and value of bringing together traumatic stress research data and making it available for re-use. As an ongoing research resource, the Archive can promote 'FAIR' data practices and facilitate integrated analyses to advance understanding of child traumatic stress.

Estimating and Examining the Replicability of Belief System Networks

Belief system structure can be investigated by estimating belief systems as networks of interacting political attitudes, but we do not know if these estimates are replicable. In a sample of 31 countries from the World Values Survey (N = 52,826), I find that countries’ belief system networks are relatively replicable in terms of connectivity, proportion of positive edges, some centrality measures (e.g., expected influence), and the estimates of individual edges. Betweenness, closeness, and strength centrality estimates are more unstable. Belief system networks estimated with smaller samples or in countries with more unstable political systems tend to be less replicable than networks estimated with larger samples in stable political systems. Although these analyses are restricted to the items available in the World Values Survey, they show that belief system networks can be replicable, but that this replicability is related to features of the study design and the political system.

A Network Analysis of Peritraumatic Distress Reactions and Their Relation to Posttraumatic Stress Symptoms in People Exposed to Community Fires

Objective: Research indicates that people who experience more intense peritraumatic reactions are at higher risk of subsequently developing PTSD. The study used network analysis to: 1) explore the network structure of peritraumatic distress reactions; 2) identify clusters of peritraumatic distress reactions; and 3) assess whether central items in the peritraumatic network have stronger network associations with subsequent posttraumatic stress symptoms (PTS). Method: A convenience sample of adults living in communities affected by large-scale community fires in Israel (November 2016) were recruited. Participants completed the 13-item peritraumatic distress inventory (PDI) within one month of the fires (n = 372), and the PTSD checklist for DSM-5 (PCL-5) four months after the fires (n = 199). Network analyses and exploratory graph analysis were conducted. Results: The PDI items were positively connected to each other in a network structure, which divided into two clusters: emotional reactions; and physical/somatic reactions along with guilt and shame. Loss of emotional control was the most central peritraumatic distress symptom. Highly central peritraumatic distress symptoms were not strongly associated with subsequent PTS; rather, physical reactions were most associated with PTS levels four months after the fires. Conclusions: Future studies should investigate targeting peritraumatic physical reactions as an early secondary prevention strategy for PTSD.

A Network Analysis of Post-traumatic Stress Disorder Symptoms and Correlates During the COVID-19 Pandemic

Background and Objective: The coronavirus disease 2019 (COVID-19) outbreak has been suggested as a collective trauma, which presents a continuing crisis. However, the specific post-traumatic implication of this crisis has not been adequately studied yet. The current study was aimed to ascertain the most central symptom and the strong connections between symptoms of post-traumatic stress disorder (PTSD). At the same time, exploring the relationship between covariates and the network of PTSD symptoms, by taking sex, anxiety, depression, suicidal ideation, quality of life, and social support as covariates, may help us to know the arise and maintenance of PTSD symptoms and give specified suggestions to people under the shadow of COVID-19. Method: The Post-traumatic Stress Disorder Checklist for Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5), was used to assess the PTSD symptoms extent of 338 healthy participants over the past month. Networks were analyzed using state-of-the-art regularized partial correlation models. In addition, the centrality of the symptoms and the robustness of the results were analyzed. Results: The network analysis revealed that the especially strong connections emerged between avoidance of thoughts and avoidance of reminders, hypervigilance and exaggerated startle response, intrusive thoughts and nightmares, flashbacks and emotional cue reactivity, and detachment and restricted affect. The most central symptoms were self-destructive/reckless behavior. Incorporation of covariates into the network revealed the strong connections path between self-destructive/reckless behavior and loss of interest and depression. Conclusion: Self-destructive/reckless behavior was the most central symptom in the network of PTSD symptoms related to the COVID-19 pandemic, which as an important target of interfere may have great benefits.

New findings questioning the construct validity of complex posttraumatic stress disorder (cPTSD): let's take a closer look

This commentary provides a broader context for interpreting evidence from Latent Class and Latent Profile analyses on complex posttraumatic stress disorder (CPTSD) that was provided in a recent contribution to the European Journal of Psychotraumatology. These data analytic strategies are not alone sufficient to test the construct validity of CPTSD. They base their conclusion on the empirical finding of substantial variation in latent models obtained with different analytic procedures and interpretations of the fit of different latent models, as well as interesting additional evidence of dispersion when individual patients' symptom counts and symptom severity scores on PTSD and CPTSD are examined. However, the results of their analyses actually do provide support for one feature of construct validity, demonstrating discriminant validity by showing a consistent differentiation between PTSD and CPTSD (with expectable variation in both PTSD and CPTSD severity level by persons). Even in a sample of patients diagnosed with PTSD, there may be a Disorders of Self Organization (DSO) sub-group with low PTSD symptom severity. More detailed examination of which DSO symptoms and sub-domains characterize the DSO sub-group and the CPTSD sub-group is needed in order to clarify the nature of the DSO/CPTSD construct. Other analyses needed to fully test construct validity also are described.

Symptomatology following loss and trauma: Latent class and network analyses of prolonged grief disorder, posttraumatic stress disorder, and depression in a treatment-seeking trauma-exposed sample

BACKGROUND

Although bereavement is likely a common stressor among patients referred to a psychotrauma clinic, no study has yet examined the co-occurrence and relationships between symptoms of prolonged grief disorder (PGD), posttraumatic stress disorder (PTSD), and major depressive disorder symptoms in this population.

METHOD

In a sample of patients seeking treatment following psychological trauma (n = 458), we used latent class analysis to identify classes of patients sharing the same profile of PGD, PTSD, and depression symptoms. We then used network analysis to investigate the relationships among these symptoms and with loss-related variables.

RESULTS

Most participants (65%) were members of a class that exhibited elevated endorsement of PGD symptoms. PGD, PTSD, and depression symptoms hung together as highly overlapping but distinguishable communities of symptoms. Symptoms related to social isolation and diminished sense of self bridged these communities. Violent loss was associated with more difficulty accepting the loss. The loss of close kin was most strongly associated with difficulty moving on in life.

CONCLUSIONS

PGD symptoms are common in trauma-exposed bereaved adults and closely associated with symptoms of PTSD and depression, illustrating the importance of assessing bereavement and PGD symptoms in those seeking treatment following trauma.

Dysfunctional posttraumatic cognitions, posttraumatic stress and depression in children and adolescents exposed to trauma: a network analysis

BACKGROUND

The latest version of the International Classification of Diseases (ICD-11) proposes a posttraumatic stress disorder (PTSD) diagnosis reduced to its core symptoms within the symptom clusters re-experiencing, avoidance and hyperarousal. Since children and adolescents often show a variety of internalizing and externalizing symptoms in the aftermath of traumatic events, the question arises whether such a conceptualization of the PTSD diagnosis is supported in children and adolescents. Furthermore, although dysfunctional posttraumatic cognitions (PTCs) appear to play an important role in the development and persistence of PTSD in children and adolescents, their function within diagnostic frameworks requires clarification.

METHODS

We compiled a large international data set of 2,313 children and adolescents aged 6 to 18 years exposed to trauma and calculated a network model including dysfunctional PTCs, PTSD core symptoms and depression symptoms. Central items and relations between constructs were investigated.

RESULTS

The PTSD re-experiencing symptoms strong or overwhelming emotions and strong physical sensations and the depression symptom difficulty concentrating emerged as most central. Items from the same construct were more strongly connected with each other than with items from the other constructs. Dysfunctional PTCs were not more strongly connected to core PTSD symptoms than to depression symptoms.

CONCLUSIONS

Our findings provide support that a PTSD diagnosis reduced to its core symptoms could help to disentangle PTSD, depression and dysfunctional PTCs. Using longitudinal data and complementing between-subject with within-subject analyses might provide further insight into the relationship between dysfunctional PTCs, PTSD and depression.

The Network Structure of Adolescent Well-Being Traits: Results From a Large-Scale Chinese Sample

Background: The mental health and well-being of adolescents are becoming increasingly important globally. Understanding the relationship between different aspects of well-being is crucial for effective interventions of the well-being of adolescents. The present study aims to analyze the network structure of adolescent well-being and identify the central well-being traits.

Methods: We used a network model to analyze the network structure of a psychometrically sound measurement of adolescent well-being – the engagement, perseverance, optimism, connectedness, and happiness (EPOCH) scale. The dataset comes from a representative sample of Chinese adolescents (17, 854 participants from rural and urban areas from Southern, Northern, and the middle part of China).

Results: The 20 items of EPOCH formed a highly interconnected network. The item H4 (“I am a cheerful person.”), item E2 (“I get completely absorbed in what I am doing”), and item O4 (“I believe that things will work out, no matter how diffcult they seem”) were the traits with the highest centrality in the network.

Conclusions: Cheerfulness, engagement in current activity, and optimism for the future are most central to the psychological well-being of Chinese adolescents. Future studies should further test the dynamics between these central traits and other well-being traits to find effective interventions of well-being of adolescents.

Changes in the network structure of posttraumatic stress disorder symptoms at different time points among youth survivors: A network analysis

BACKGROUND

Despite considerable studies focused on the symptoms of posttraumatic stress disorder (PTSD), little is understood about how symptoms of PTSD change over time. The study aimed to use a network analysis approach to understand the nature of the association between PTSD symptoms at different time points among children and adolescents who experience an earthquake.

METHODS

A longitudinal study enrolled 1623 youth survivors who completed 3 assessments with the Children's Revised Impact of Event Scale at 2 weeks, 3 months and 6 months after the Lushan earthquake. The epicentre was Baoxing Country that located in the Ya'an city (Sichuan Province in China). A network analysis approach was used to investigate how symptom networks change at different time points.

RESULTS

A total of 1623 youth survivors (768 male and 855 female) completed three assessments. Different centrality symptoms existed at different time points. Flashback and upset by reminders were centrality symptoms at 2 weeks, 3 months and 6 months. The overall network connectivity was significantly stronger at 3 months than at 2 weeks (5.663 vs. 5.140, s = 0.523, p = 0.000), and significantly stronger at 6 months than at 2 weeks (6.094 vs. 5.663, s = 0.432, p = 0.020).

LIMITATIONS

Participants from a specific region might limit the generalizability of our results. A self-report questionnaire was used to assess PTSD symptoms.

CONCLUSIONS

Re-experience cluster (flashback and upset by reminders) and their interactions might play a key role in PTSD symptom evolution. Over time, the global connectivity becomes stronger, suggesting that youth survivors are more vulnerable in the chronic phases.

Network Approach to Items and Domains From the Toronto Alexithymia Scale

The aim of this study is to explore network structures of the Toronto Alexithymia Scale in a large sample of 1925 French-speaking Belgian university students and compare results with previous studies from different samples and tools to identify potential targets for clinical intervention. We estimated network models for the 20 items of the Toronto Alexithymia Scale and for its three domains difficulty identifying feelings, difficulty describing feelings, and externally oriented thinking. We explored item connectivity through node predictability (shared variance with other network components). We performed an exploratory graph analysis to explore the dimensionality of our data set and compare results with the original three-factor model; because a different model was proposed, we estimated an additional network structure on the new structure. Items from the Toronto Alexithymia Scale connect both within and between domains. The three-domain network identifies difficulty describing feelings as the most connected domain. The exploratory graph analysis reported that three items from externally oriented thinking form a new domain, distraction. In the new four-domain network, difficulty describing feelings remains the most interconnected domain; however, two negative connections are found. Our findings support the relative importance of identifying and describing feelings as a meaningful target for intervention.

A decennial review of psychotraumatology: what did we learn and where are we going?

On 6 December 2019 we start the 10th year of the European Journal of Psychotraumatogy (EJPT), a full Open Access journal on psychotrauma. This editorial is part of a special issue/collection celebrating the 10 years anniversary of the journal where we will acknowledge some of our most impactful articles of the past decade (also discussed below and marked with * in the reference list). In this editorial the editors present a decennial review of the field addressing a range of topics that are core to both the journal and to psychotraumatology as a discipline. These include neurobiological developments (genomics, neuroimaging and neuroendocrine research), forms of trauma exposure and impact across the lifespan, mass trauma and early interventions, work-related trauma, trauma in refugee populations, and the potential consequences of trauma such as PTSD or Complex PTSD, but also resilience. We address innovations in psychological, medication (enhanced) and technology-assisted treatments, mediators and moderators like social support and finally how new research methods help us to gain insights in symptom structures or to better predict symptom development or treatment success. We aimed to answer three questions 1. Where did we stand in 2010? 2. What did we learn in the past 10 years? 3. What are our knowledge gaps? We conclude with a number of recommendations concerning top priorities for the future direction of the field of psychotraumatology and correspondingly the journal.

The Differential Role of Central and Bridge Symptoms in Deactivating Psychopathological Networks

The network model of psychopathology suggests that central and bridge symptoms represent promising treatment targets because they may accelerate the deactivation of the network of interactions between the symptoms of mental disorders. However, the evidence confirming this hypothesis is scarce. This study re-analyzed a convenience sample of 51 cross-sectional psychopathological networks published in previous studies addressing diverse mental disorders or clinically relevant problems. In order to address the hypothesis that central and bridge symptoms are valuable treatment targets, this study simulated five distinct attack conditions on the psychopathological networks by deactivating symptoms based on two characteristics of central symptoms (degree and strength), two characteristics of bridge symptoms (overlap and bridgeness), and at random. The differential impact of the characteristics of these symptoms was assessed in terms of the magnitude and the extent of the attack required to achieve a maximum impact on the number of components, average path length, and connectivity. Only moderate evidence was obtained to sustain the hypothesis that central and bridge symptoms constitute preferential treatment targets. The results suggest that the degree, strength, and bridgeness attack conditions are more effective than the random attack condition only in increasing the number of components of the psychopathological networks. The degree attack condition seemed to perform better than the strength, bridgeness, and overlap attack conditions. Overlapping symptoms evidenced limited impact on the psychopathological networks. The need to address the basic mechanisms underlying the structure and dynamics of psychopathological networks through the expansion of the current methodological framework and its consolidation in more robust theories is stressed.

The symptom representation of posttraumatic stress disorder in a sample of unaccompanied and accompanied refugee minors in Germany: a network analysis

Background: Given the unprecedented number of traumatized refugee minors in Europe and the increased prevalence of mental disorders such as PTSD in this vulnerable population, new methodologies that help us to better understand their symptomatology are crucial. Network analysis might help clinicians to both understand which symptoms might trigger other symptoms, and to identify relevant targets for treatment. However, to date only two studies have applied the network analysis approach to an (adult) refugee population and only three studies examined this approach in children and adolescents. Objective: The aim of this study is to explore the network structure and centrality of DSM-5 PTSD symptoms in a cross-sectional sample of severely traumatized refugee minors. Method: A total of N = 419 (M age = 16.3; 90.7% male) unaccompanied (79.9%) and accompanied (20.1%) refugee minors were recruited in five studies in southern Germany. PTSD symptoms were assessed using the Child and Adolescent Trauma Screen (CATS). The network was estimated using state-of-the-art regularized partial correlation models using the R-package qgraph. Results: The most central symptoms were nightmares, physiological and psychological reactivity, and concentration problems. The strongest connections between symptoms were established for psychological and physiological reactivity, irritability/anger and self-destructive/reckless behaviour, intrusions and nightmares, nightmares and sleep disturbance, and between concentrations problems and sleep disturbance. Conclusion: This study furnishes information relevant to research and the clinical management of PTSD in refugee minors, and also in terms of comparisons with trauma-exposed children and adolescents without a migration background. Re-experiencing symptoms seem to be central in the refugee minor PTSD profile and thus merit special consideration in the diagnostic and treatment evaluation process. Investigating the PTSD network longitudinally and complementing between-subject analyses with within-subject ones might provide further insight into the symptomatology of refugee minors and how to treat them successfully.

Identifying key targets for interventions to improve psychological wellbeing: replicable results from four UK cohorts

BACKGROUND

An increasing importance is being placed on mental health and wellbeing at individual and population levels. While there are several interventions that have been proposed to improve wellbeing, more evidence is needed to understand which aspects of wellbeing are most influential. This study aimed to identify key items that signal improvement of mental health and wellbeing.

METHODS

Using network analysis, we identified the most central items in the graph network estimated from the well-established Warwick-Edinburgh Mental Well-being Scale (WEMWBS). Results were compared across four major UK cohorts comprising a total of 47,578 individuals: the Neuroscience in Psychiatry Network, the Scottish Schools Adolescent Lifestyle and Substance Use Survey, the Northern Ireland Health Survey, and the National Child Development Study.

RESULTS

Regardless of gender, the three items most central in the network were related to positive self-perception and mood: 'I have been feeling good about myself'; 'I have been feeling confident'; and 'I have been feeling cheerful'. Results were consistent across all four cohorts.

CONCLUSIONS

Positive self-perception and positive mood are central to psychological wellbeing. Psychotherapeutic and public mental health interventions might best promote psychological wellbeing by prioritising the improvement of self-esteem, self-confidence and cheerfulness. However, empirical testing of interventions using these key targets is needed.

Psychometric Network Analysis of the Hungarian WAIS

The positive manifold-the finding that cognitive ability measures demonstrate positive correlations with one another-has led to models of intelligence that include a general cognitive ability or general intelligence (g). This view has been reinforced using factor analysis and reflective, higher-order latent variable models. However, a new theory of intelligence, Process Overlap Theory (POT), posits that g is not a psychological attribute but an index of cognitive abilities that results from an interconnected network of cognitive processes. These competing theories of intelligence are compared using two different statistical modeling techniques: (a) latent variable modeling and (b) psychometric network analysis. Network models display partial correlations between pairs of observed variables that demonstrate direct relationships among observations. Secondary data analysis was conducted using the Hungarian Wechsler Adult Intelligence Scale Fourth Edition (H-WAIS-IV). The underlying structure of the H-WAIS-IV was first assessed using confirmatory factor analysis assuming a reflective, higher-order model and then reanalyzed using psychometric network analysis. The compatibility (or lack thereof) of these theoretical accounts of intelligence with the data are discussed.

Frequency and network analysis of depressive symptoms in patients with cancer compared to the general population

BACKGROUND

The use of sum scores of depressive symptoms has been increasingly criticized and may be particularly problematic in oncological settings. Frameworks analyzing individual symptoms and their interrelationships such as network analysis represent an emerging alternative.

METHODS

We aimed to assess frequencies and interrelationships of 9 DSM-5 symptom criteria of major depression reported in the PHQ-9 questionnaire by 4020 patients with cancer and 4020 controls from the general population. We estimated unregularized Gaussian graphical models for both samples and compared network structures as well as predictability and centrality of individual symptoms.

RESULTS

Depressive symptoms were more frequent, but less strongly intercorrelated in patients with cancer than in the general population. The overall network structure differed significantly between samples (correlation of adjacency matrices: rho=0.73, largest between-group difference in any edge weight: 0.20, p < 0.0001). Post-hoc tests showed significant differences in interrelationships for four symptom pairs. The mean variance of symptoms explained by all other symptoms in the same network was lower among cancer patients than in the general population (29% vs. 43%).

LIMITATIONS

Cross-sectional data do not allow for temporal or causal inferences about the directions of associations and results from population-based samples may not apply to clinical psychiatric populations.

CONCLUSIONS

In patients with cancer, both somatic and cognitive/affective depression symptoms are less likely to be explained by other depressive symptoms than in the general population. Rather than assuming a consistent depression construct, future research should study individual depressive symptom patterns and their potential causes in patients with cancer.

Using network analysis to identify central eating disorder symptoms among men

OBJECTIVE

The network theory of psychopathology has been described as an "innovative framework" that may "transform" clinical psychological science. Several network studies have identified central eating disorder (ED) symptoms, yet studies have been comprised primarily of women. Using two large samples, we constructed ED symptom networks among men to identify central symptoms.

METHOD

Participants were recruited from three universities and using Amazon's Mechanical Turk. Participants completed the Eating Disorder Examination-Questionnaire (EDE-Q), Male Body Attitudes Scale, and Drive for Muscularity Scale. ED symptom networks were jointly estimated among men with (n = 248) and without core ED symptoms (n = 902). Core ED symptoms were defined by (a) scoring above a suggested male EDE-Q clinical cutoff and (b) reporting symptoms consistent with probable ED diagnoses. Expected influence and predictability (proportion of each node's variance explained by other nodes in the network) were calculated for each node.

RESULTS

Shape overvaluation, desiring weight loss, fear of losing control over eating, feeling guilty for missing weight training, and using supplements had the greatest expected influence and predictability. Network structures did not significantly differ between participants with versus without core ED symptoms.

DISCUSSION

The centricity of body dissatisfaction items in the networks supports some components of cognitive behavioral theories of EDs. However, the findings also suggest the importance of muscularity- and leanness-oriented concerns, which have been traditionally neglected from leading ED theories that tend to focus on thinness pursuits as a main driver of body dissatisfaction.

In search of disorders: internalizing symptom networks in a large clinical sample

BACKGROUND

The co-occurrence of internalizing disorders is a common form of psychiatric comorbidity, raising questions about the boundaries between these diagnostic categories. We employ network psychometrics in order to: (a) determine whether internalizing symptoms cluster in a manner reflecting DSM diagnostic criteria, (b) gauge how distinct these diagnostic clusters are and (c) examine whether this network structure changes from childhood to early and then late adolescence.

METHOD

Symptom-level data were obtained for service users in publicly funded mental health services in England between 2011 and 2015 (N = 37,162). A symptom network (i.e. Gaussian graphical model) was estimated, and a community detection algorithm was used to explore the clustering of symptoms.

RESULTS

The estimated network was densely connected and characterized by a multitude of weak associations between symptoms. Six communities of symptoms were identified; however, they were weakly demarcated. Two of these communities corresponded to social phobia and panic disorder, and four did not clearly correspond with DSM diagnostic categories. The network structure was largely consistent by sex and across three age groups (8-11, 12-14 and 15-18 years). Symptom connectivity in the two older age groups was significantly greater compared to the youngest group and there were differences in centrality across the age groups, highlighting the age-specific relevance of certain symptoms.

CONCLUSIONS

These findings clearly demonstrate the interconnected nature of internalizing symptoms, challenging the view that such pathology takes the form of distinct disorders.

Does mindfulness change the mind? A novel psychonectome perspective based on Network Analysis

If the brain is a complex network of functionally specialized areas, it might be expected that mental representations could also behave in a similar way. We propose the concept of ‘psychonectome’ to formalize the idea of psychological constructs forming a dynamic network of mutually dependent elements. As a proof-of-concept of the psychonectome, networks analysis (NA) was used to explore structural changes in the network of constructs resulting from a psychological intervention. NA was applied to explore the effects of an 8-week Mindfulness-Based Stress Reduction (MBSR) program in healthy participants (N = 182). Psychological functioning was measured by questionnaires assessing five key domains related to MBSR: mindfulness, compassion, psychological well-being, psychological distress and emotional-cognitive control. A total of 25 variables, covering the five constructs, were considered as nodes in the NA. Participants significantly improved in most of the psychological questionnaires. More interesting from a network perspective, there were also significant changes in the topological relationships among the elements. Expected influence and strength centrality indexes revealed that mindfulness and well-being measures were the most central nodes in the networks. The nodes with highest topological change after the MBSR were attentional control, compassion measures, depression and thought suppression. Also, cognitive appraisal, an adaptive emotion regulation strategy, was associated to rumination before the MBSR program but became related to mindfulness and well-being measures after the program. Community analysis revealed a strong topological association between mindfulness, compassion, and emotional regulation, which supports the key role of compassion in mindfulness training. These results highlight the importance of exploring psychological changes from a network perspective and support the conceptual advantage of considering the interconnectedness of psychological constructs in terms of a ‘psychonectome’ as it may reveal ways of functioning that cannot be analyzed through conventional analytic methods.

Testing Cold and Hot Cognitive Control as Moderators of a Network of Comorbid Psychopathology Symptoms in Adolescence

Comorbidity is pervasive across psychopathological symptoms, diagnoses, and domains. Network analysis is a method for investigating symptom-level associations that underlie comorbidity, particularly through bridge symptoms connecting diagnostic syndromes. We applied network analyses of comorbidity to data from a population-based sample of adolescents (n = 849). We implemented a method for assessing nonparametric moderation of psychopathology networks to evaluate differences in network structure across levels of intelligence and emotional control. Symptoms generally clustered by clinical diagnoses, but specific between-cluster bridge connections emerged. Internalizing symptoms demonstrated unique connections with aggression symptoms of interpersonal irritability, whereas externalizing symptoms showed more diffuse interconnections. Aggression symptoms identified as bridge nodes in the cross-sectional network were enriched for longitudinal associations with internalizing symptoms. Cross-domain connections did not significantly vary across intelligence but were weaker at lower emotional control. Our findings highlight transdiagnostic symptom relationships that may underlie co-occurrence of clinical diagnoses or higher-order factors of psychopathology.

The Study of Psychopathology from the Network Analysis Perspective: A Systematic Review

BACKGROUND

Network analysis (NA) is an analytical tool that allows one to explore the map of connections and eventual dynamic influences among symptoms and other elements of mental disorders. In recent years, the use of NA in psychopathology has rapidly grown, which calls for a systematic and critical analysis of its clinical utility.

METHODS

Following PRISMA guidelines, a systematic review of published empirical studies applying NA in psychopathology, between 2010 and 2017, was conducted. We included the literature published in PubMed and PsycINFO using as keywords any combination of "network analysis" with the terms "anxiety," "affective disorders," "depression," "schizophrenia," "psychosis," "personality disorders," "substance abuse" and "psychopathology."

RESULTS

The review showed that NA has been applied in a plethora of mental disorders in adults (i.e., 13 studies on anxiety disorders; 19 on mood disorders; 7 on psychosis; 1 on substance abuse; 1 on borderline personality disorder; 18 on the association of symptoms between disorders), and 6 on childhood and adolescence.

CONCLUSIONS

A critical examination of the results of each study suggests that NA helps to identify, in an innovative way, important aspects of psychopathology like the centrality of the symptoms in a given disorder as well as the mutual dynamics among symptoms. Yet, despite these promising results, the clinical utility of NA is still uncertain as there are important limitations on the analytic procedures (e.g., reliability of indices), the type of data included (e.g., typically restricted to secondary analysis of already published data), and ultimately, the psychometric and clinical validity of the results.

Exploring multicultural classroom dynamics: A network analysis

Students' relationships with peers and teachers strongly influence their motivation to engage in learning activities. Ethnic minority students, however, are often victimized in schools, and their educational achievement lags behind that of their majority group counterparts. The aim of the present study was to explore teachers' multicultural approach within their classrooms as a possible factor of influence over students' peer relationships and motivation. We utilized the novel methodology of estimating psychological networks in order to map out the interactions between these constructs within multicultural classrooms. Results indicate that a multicultural approach is directly connected to student motivation for both ethnic majority and minority students. Social integration within peer groups, however, seems to be a possible mediator of this relationship for the ethnic minority students. Due to the hypothesis generating nature of the psychological network approach, a more thorough investigation of this generated mediation hypothesis is called for.

The temporal dynamics of symptoms during exposure therapies of PTSD: a network approach

Background: Analysis of dynamic (temporal) networks allows an identification of important targets of treatment. Objective: This study examined the dynamic network of symptoms in patients diagnosed with post-traumatic stress disorder (PTSD) during exposure therapy. Method: Patients (n = 65) were randomized to either standard prolonged exposure, which includes imaginal exposure to the traumatic memory, or modified prolonged exposure, where imagery re-scripting of the memory replaced imaginal exposure, in a 10-week residential program. They completed a measure of DSM-IV PTSD symptoms weekly. The multilevel vector autoregressive (mlVAR) model was used to analyse the data, producing a temporal (dynamic), contemporaneous, and between-person network. Results: Physiological reactivity to reminders in a given week was positively related to distress reactivity and to flashbacks the subsequent week. Hypervigilance one week was positively related to startle response and external avoidance the subsequent week. In addition, sleep problems were positively predicted by previous week internal avoidance and negatively predicted by previous week flashbacks. Hypervigilance and physiological reactivation had the highest out-strength, indicating that they were the most predictive of other symptoms. Conclusions: The present within-person results make a preliminaryrect basis for the recommendation to monitor and facilitate change in physiological reactivation and hypervigilance in the treatment of PTSD. Future studies should examine the replicability of our temporal PTSD network and also include causal variables beyond symptoms.

The replicability of ICD-11 complex post-traumatic stress disorder symptom networks in adults

BACKGROUND

The ICD-11 includes a new disorder, complex post-traumatic stress disorder (CPTSD). A network approach to CPTSD will enable investigation of the structure of the disorder at the symptom level, which may inform the development of treatments that target specific symptoms to accelerate clinical outcomes.AimsWe aimed to test whether similar networks of ICD-11 CPTSD replicate across culturally different samples and to investigate possible differences, using a network analysis.

METHOD

We investigated the network models of four nationally representative, community-based cross-sectional samples drawn from Germany, Israel, the UK, and the USA (total N = 6417). CPTSD symptoms were assessed with the International Trauma Questionnaire in all samples. Only those participants who reported significant functional impairment by CPTSD symptoms were included (N = 1591 included in analysis; mean age 43.55 years, s.d. 15.10, range 14-99, 67.7% women). Regularised partial correlation networks were estimated for each sample and the resulting networks were compared.

RESULTS

Despite differences in traumatic experiences, symptom severity and symptom profiles, the networks were very similar across the four countries. The symptoms within dimensions were strongly associated with each other in all networks, except for the two symptom indicators assessing aspects of affective dysregulation. The most central symptoms were 'feelings of worthlessness' and 'exaggerated startle response'.

CONCLUSIONS

The structure of CPTSD symptoms appears very similar across countries. Addressing symptoms with the strongest associations in the network, such as negative self-worth and startle reactivity, will likely result in rapid treatment response.Declaration of interestA.M. and M.C. were members of the World Health Organization (WHO) ICD-11 Working Group on the Classification of Disorders Specifically Associated with Stress, reporting to the WHO International Advisory Group for the Revision of ICD-10 Mental and Behavioural Disorders. The views expressed in this article are those of the authors and do not represent the official policies or positions of the International Advisory Group or the WHO.

The network structure of schizotypal personality traits in a population-based sample

Outcomes for people with schizophrenia-spectrum disorders (SSDs) are generally poor, making it important to understand risk states and illness transition. The network approach, which conceptualizes psychopathology as a network of causally interacting symptoms, may hold promise in this regard. Here, we present a network analysis of schizotypal personality traits (i.e., schizophrenia-like cognitive, perceptual, affective, interpersonal, and behavioral anomalies that may index one's vulnerability for a SSD) using an international sample. We analyzed data from 9505 participants between the ages of 14-70 who completed the Schizotypal Personality Questionnaire-Brief on TestMyBrain.org. In line with other research, we find that the network of schizotypal traits is densely connected, characterized by three communities of items-interpersonal (I), disorganized (D), cognitive-perceptual (CP)-with I and D features exhibiting the greatest centrality (z-scored M strength: I = 0.56, D = 0.29, CP = -0.84; expected influence: I = 0.54, D = 0.33, CP = -0.84) and predictability (M I = 0.37, D = 0.43, CP = 0.23). Importantly, within our sample, we found the estimated network to be replicable (Network Comparison Test: network structure difference: M = 0.304, p = .420; global strength difference: S = 0.904, p = .530), and estimates of node centrality to be stable (correlation-stability coefficient = 0.75). Further, we find network differences between certain groups differing in levels of SSD risk as a function of age (network structure: difference M = 0.562, p < .001; global strength difference: S = 3.483, p = .012) and ethnic minority status (global strength difference: S = 11.488, p = .004). Together, these findings demonstrate the utility of using network approaches to understand SSD risk states as well as the replicability of network findings on schizotypal personality traits and related SSD risk concepts.

Network structure of the Wisconsin Schizotypy Scales-Short Forms: Examining psychometric network filtering approaches

Schizotypy is a multidimensional construct that provides a useful framework for understanding the etiology, development, and risk for schizophrenia-spectrum disorders. Past research has applied traditional methods, such as factor analysis, to uncovering common dimensions of schizotypy. In the present study, we aimed to advance the construct of schizotypy, measured by the Wisconsin Schizotypy Scales-Short Forms (WSS-SF), beyond this general scope by applying two different psychometric network filtering approaches-the state-of-the-art approach (lasso), which has been employed in previous studies, and an alternative approach (information-filtering networks; IFNs). First, we applied both filtering approaches to two large, independent samples of WSS-SF data (ns = 5,831 and 2,171) and assessed each approach's representation of the WSS-SF's schizotypy construct. Both filtering approaches produced results similar to those from traditional methods, with the IFN approach producing results more consistent with previous theoretical interpretations of schizotypy. Then we evaluated how well both filtering approaches reproduced the global and local network characteristics of the two samples. We found that the IFN approach produced more consistent results for both global and local network characteristics. Finally, we sought to evaluate the predictability of the network centrality measures for each filtering approach, by determining the core, intermediate, and peripheral items on the WSS-SF and using them to predict interview reports of schizophrenia-spectrum symptoms. We found some similarities and differences in their effectiveness, with the IFN approach's network structure providing better overall predictive distinctions. We discuss the implications of our findings for schizotypy and for psychometric network analysis more generally.

Item and domain network structures of the Resilience Scale for Adults in 675 university students

AIMS

The Resilience Scale for Adults (RSA) is a questionnaire that measures protective factors of mental health. The aim of this paper is to perform a network analysis of the RSA in a dataset composed of 675 French-speaking Belgian university students, to identify potential targets for intervention to improve protective factors in individuals.

METHODS

We estimated a network structure for the 33-item questionnaire and for the six domains of resilience: perception of self, planned future, social competence, structured style, family cohesion and social competence. Node predictability (shared variance with surrounding nodes in the network) was used to assess the connectivity of items. An exploratory graph analysis (EGA) was performed to detect communities in the network: the number of communities detected being different than the original number of factors proposed in the scale, we estimated a new network with the resulting structure and verified the validity of the new construct which was proposed. We provide the anonymised dataset and code in external online materials (10.17632/64db36w8kf.2) to ensure complete reproducibility of the results.

RESULTS

The network composed of items from the RSA is overall positively connected with strongest connections arising among items from the same domain. The domain network reports several connections, both positive and negative. The EGA reported the existence of four communities that we propose as an additional network structure. Node predictability estimates show that connectedness varies among the items and domains of the RSA.

CONCLUSIONS

Network analysis is a useful tool to explore resilience and identify targets for clinical intervention. In this study, the four domains acting as components of the additional four-domain network structure may be potential targets to improve an individual's resilience. Further studies may endeavour to replicate our findings in different samples.

Annual Research Review: Pediatric posttraumatic stress disorder from a neurodevelopmental network perspective

BACKGROUND

Experiencing traumatic stress is common and may lead to posttraumatic stress disorder (PTSD) in a number of children and adolescents. Research using advanced imaging techniques is beginning to elucidate some of the neurobiological correlates of the traumatic stress response in youth.

METHODS

This paper summarizes the emerging network perspective of PTSD symptoms and reviews brain imaging research emphasizing structural and functional connectivity studies that employ magnetic resonance imaging techniques in pediatric samples.

RESULTS

Differences in structural connections and distributed functional networks such as the salience, default mode, and central executive networks are associated with traumatic and severe early life stress. The role of development has been relatively underappreciated in extant studies though there is evidence that critical brain regions as well as the structural and functional networks implicated undergo significant change in childhood and these typical developmental differences may be affected by traumatic stress.

CONCLUSIONS

Future research will benefit from adopting a truly developmental approach that considers children's growth as a meaningful effect (rather than simply a covariate) interacting with traumatic stress to predict disruptions in the anatomical, functional, and connective aspects of brain systems thought to underlie the network of PTSD symptoms. Linking symptom networks with neurodevelopmental network models may be a promising avenue for future work.

Further evidence that psychopathology networks have limited replicability and utility: Response to Borsboom et al. (2017) and Steinley et al. (2017)

In our target article, we tested the replicability of 4 popular psychopathology network estimation methods that aim to reveal causal relationships among symptoms of mental illness. We started with the focal data set from the 2 foundational psychopathology network papers (i.e., the National Comorbidity Survey-Replication) and identified the National Survey of Mental Health and Wellbeing as a close methodological match for comparison. We compared the psychopathology networks estimated in each data set-as well as in 10 sets of random split-halves within each data set-with the goal of quantifying the replicability of the network parameters as they are interpreted in the extant psychopathology network literature. We concluded that current psychopathology network methods have limited replicability both within and between samples and thus have limited utility. Here we respond to the 2 commentaries on our target article, concluding that the findings of Steinley, Hoffman, Brusco, and Sher (2017)-along with other recent developments in the literature-provide further conclusive evidence that psychopathology networks have poor replicability and utility. (PsycINFO Database Record

Network analysis of Contingencies of Self-Worth Scale in 680 university students

This study investigates the Contingencies of Self-Worth Scale (CSWS) in a sample of 680 university students from a network perspective. We estimated regularized partial correlations among seven CSWS domains: family support, competition, appearance, God's love, academic competence, virtue and other's approval. Competition - academic competence and competition - appearance represent the strongest connections in the network. Mean node predictability (shared variance with surrounding nodes) is 0.25. Appearance and academic competence were the most central (i.e., interconnected) domains in the network. Future studies should explore the network structure of self-worth in other healthy adult samples, and also in people with psychopathology. We provide the anonymized dataset as well as the full code in the supplementary materials to ensure complete reproducibility of the results.

Sex differences in global and local connectivity of adolescent posttraumatic stress disorder symptoms

BACKGROUND

Sex differences in youth's posttraumatic stress disorder (PTSD) symptomatology have not been well studied.

METHODS

Based on a recently burgeoning theory of psychopathology networks, this study conducted sex comparisons of global and local connectivity of PTSD symptoms in a sample of 868 disaster-exposed adolescents (57.0% girls; a mean age of 13.4 ± 0.8 years) with significant PTSD symptomatology evaluated by the UCLA PTSD Reaction Index for DSM-IV.

RESULTS

The results revealed that global connectivity was stronger in girls' network than in boys', and individual symptoms' connectivity and its rankings differed by sex. Intrusive recollections, flashbacks, avoiding activities/people, and detachment were the most strongly connected symptoms in girls, whereas flashbacks, physiological cue reactivity, diminished interest, and foreshortened future were the most strongly connected symptoms in boys. Several symptoms were identified as featuring large connectivity differences across sex.

CONCLUSIONS

These findings provide novel insights into sex differential risk and features of youth's PTSD symptomatology. Sex differences reflected in the co-occurrence of PTSD symptoms may merit more consideration in research and clinical practice.

What Is Central to Political Belief System Networks?

A central challenge for identifying core components of a belief system is examining the position of components within the structure of the entire belief system. We test whether operational (i.e., positions on issues) or symbolic (i.e., affective attachments to political groups and labels) components are most central by modeling a political belief system as a network of interconnected attitudes and beliefs. Across seven waves of representative panel data from New Zealand, we find that symbolic components are more central than operational components (ds range = 0.78-0.97). Symbolic components were also closer than operational components in the network to self-reported voting (d = −2.43), proenvironmental actions (ds = −1.71 and −1.63), and religious behaviors (d = −0.74). These findings are consistent with perspectives that emphasize the importance of symbolic politics in tying belief systems together and motivating behavior, and further the link between political belief system research and network science.

Psychology's Replication Crisis and Clinical Psychological Science

Despite psychological scientists' increasing interest in replicability, open science, research transparency, and the improvement of methods and practices, the clinical psychology community has been slow to engage. This has been shifting more recently, and with this review, we hope to facilitate this emerging dialogue. We begin by examining some potential areas of weakness in clinical psychology in terms of methods, practices, and evidentiary base. We then discuss a select overview of solutions, tools, and current concerns of the reform movement from a clinical psychological science perspective. We examine areas of clinical science expertise (e.g., implementation science) that should be leveraged to inform open science and reform efforts. Finally, we reiterate the call to clinical psychologists to increase their efforts toward reform that can further improve the credibility of clinical psychological science.

Between vulnerability and resilience: A network analysis of fluctuations in cognitive risk and protective factors following remission from depression

Research exploring how cognitive risk- and protective factors relate following remission from internalizing disorders suggests a central role for resilience. However, it remains unclear what constitutes resilience in this context. Furthermore, previous studies have typically relied on cross-sectional data which do not allow to map the temporal dynamics of such relations. Using a seven-day experience sampling period in 85 remitted depressed patients, we examined the interplay between five transdiagnostic vulnerability- and protective factors in daily life. We present a temporal, contemporaneous, and a between-subjects network, providing an in-depth analysis of how these factors relate to daily life fluctuations in residual symptomatology. Furthermore, we test the role of positive affect as a main resilience factor. Resilience uniquely predicted all other factors over time (temporal network). Higher levels of resilience were related to less momentary use of rumination, more deployment of positive appraisal, and lower occurrence of residual symptoms (contemporaneous network). Participants scoring high on resilience mostly engaged in positive appraisal (between-subjects network). Similar structures were obtained when substituting self-reported resilience by positive affect. This highlights the importance of resilience, and in particular, positive affectivity, to cope with stressors following remission. This may be fostered by facilitating the use of positive appraisal.

The centrality of health behaviours: A network analytic approach

OBJECTIVES

Since behavioural risk factors are the foremost causes of disability and premature mortality, developing new perspectives for understanding them is of utmost importance. This paper describes an innovative approach that conceptualizes health-related behaviours as nodes in a weighted network.

DESIGN & METHODS

Using self-reported data from a representative sample (n = 374), a network of 37 health behaviours was analysed, with the aim of identifying 'central' nodes, that is, behaviours that are likely to co-occur with others and potentially influence them.

RESULTS

In line with conservation of resources theory, the analysis indicated that behaviours related to basic physiological needs (nutrition and sleep) were most central. Behaviour centrality also varied across subpopulations: Periodic medical examinations, eating meals regularly, and sleep hygiene were more central among high- compared to low-socio-economic status participants; behaviours related to supportive social relationships and sun protection were more central among women compared to men.

CONCLUSION

By emphasizing behavioural connectivity, the approach applied herein has identified core health behaviours with potentially high impact on healthy lifestyle behaviours. Statement of Contribution What is already known on this subject? Many health behaviours are related to each other. Engagement in one health behaviour can affect engagement in other behaviours. What does this study add? Health behaviour can be viewed and analysed as a network. Sleep and nutrition behaviours are the most central behaviours in the network. Centrality varies as a function of socio-economic status and gender.

Posttraumatic Stress Disorder Symptom Network Analysis in U.S. Military Veterans: Examining the Impact of Combat Exposure

Recent work inspired by graph theory has begun to conceptualize mental disorders as networks of interacting symptoms. Posttraumatic stress disorder (PTSD) symptom networks have been investigated in clinical samples meeting full diagnostic criteria, including military veterans, natural disaster survivors, civilian survivors of war, and child sexual abuse survivors. Despite reliable associations across reported networks, more work is needed to compare central symptoms across trauma types. Additionally, individuals without a diagnosis who still experience symptoms, also referred to as subthreshold cases, have not been explored with network analysis in veterans. A sample of 1,050 Iraq/Afghanistan-era U.S. military veterans (851 males, mean age = 36.3, SD = 9.53) meeting current full-criteria PTSD (n = 912) and subthreshold PTSD (n = 138) were assessed with the Structured Clinical Interview for DSM-IV Disorders (SCID). Combat Exposure Scale (CES) scores were used to group the sample meeting full-criteria into high (n = 639) and low (n = 273) combat exposure subgroups. Networks were estimated using regularized partial correlation models in the R-package qgraph, and robustness tests were performed with bootnet. Frequently co-occurring symptom pairs (strong network connections) emerged between two avoidance symptoms, hypervigilance and startle response, loss of interest and detachment, as well as, detachment and restricted affect. These associations replicate findings reported across PTSD trauma types. A symptom network analysis of PTSD in a veteran population found significantly greater overall connectivity in the full-criteria PTSD group as compared to the subthreshold PTSD group. Additionally, novel findings indicate that the association between intrusive thoughts and irritability is a feature of the symptom network of veterans with high levels of combat exposure. Mean node predictability is high for PTSD symptom networks, averaging 51.5% shared variance. With the tools described here and by others, researchers can help refine diagnostic criteria for PTSD, develop more accurate measures for assessing PTSD, and eventually inform therapies that target symptoms with strong network connections to interrupt interconnected symptom complexes and promote functional recovery.

A network analysis of female sexual function: comparing symptom networks in women with decreased, increased, and stable sexual desire

Problems related to low sexual desire in women are common clinical complaints, and the aetiology is poorly understood. We investigated predictors of change in levels of sexual desire using a novel network approach, which assumes that mental disorders arise from direct interactions between symptoms. Using population-based data from 1,449 Finnish women, we compared between-subject networks of women whose sexual desire decreased, increased, or remained stable over time. Networks were estimated and analyzed at T1 (2006) and replicated at T2 (2013) using R. Domains included were, among others, sexual functions, sexual distress, anxiety, depression, body dissatisfaction, and relationship status. Overall, networks were fairly similar across groups. Sexual arousal, satisfaction, and relationship status were the most central variables, implying that they might play prominent roles in female sexual function; sexual distress mediated between general distress and sexual function; and sexual desire and arousal showed different patterns of relationships, suggesting that they represent unique sexual function aspects. Potential group-differences suggested that sex-related pain and body dissatisfaction might play roles in precipitating decreases of sexual desire. The general network structure and similarities between groups replicated well; however, the potential group-differences did not replicate. Our study sets the stage for future clinical and longitudinal network modelling of female sexual function.

The Network Structure of Schizotypal Personality Traits

Elucidating schizotypal traits is important if we are to understand the various manifestations of psychosis spectrum liability and to reliably identify individuals at high risk for psychosis. The present study examined the network structures of (1) 9 schizotypal personality domains and (2) 74 individual schizotypal items, and (3) explored whether networks differed across gender and culture (North America vs China). The study was conducted in a sample of 27001 participants from 12 countries and 21 sites (M age = 22.12; SD = 6.28; 37.5% males). The Schizotypal Personality Questionnaire (SPQ) was used to assess 74 self-report items aggregated in 9 domains. We used network models to estimate conditional dependence relations among variables. In the domain-level network, schizotypal traits were strongly interconnected. Predictability (explained variance of each node) ranged from 31% (odd/magical beliefs) to 55% (constricted affect), with a mean of 43.7%. In the item-level network, variables showed relations both within and across domains, although within-domain associations were generally stronger. The average predictability of SPQ items was 27.8%. The network structures of men and women were similar (r = .74), node centrality was similar across networks (r = .90), as was connectivity (195.59 and 199.70, respectively). North American and Chinese participants networks showed lower similarity in terms of structure (r = 0.44), node centrality (r = 0.56), and connectivity (180.35 and 153.97, respectively). In sum, the present article points to the value of conceptualizing schizotypal personality as a complex system of interacting cognitive, emotional, and affective characteristics.