Using natural language processing to facilitate the harmonisation of mental health questionnaires: a validation study using real-world data.

BACKGROUND: Pooling data from different sources will advance mental health research by providing larger sample sizes and allowing cross-study comparisons; however, the heterogeneity in how variables are measured across studies poses a challenge to this process. METHODS: This study explored the potential of using natural language processing (NLP) to harmonise different mental health questionnaires by matching individual questions based on their semantic content. Using the Sentence-BERT model, we calculated the semantic similarity (cosine index) between 741 pairs of questions from five questionnaires. Drawing on data from a representative UK sample of adults (N = 2,058), we calculated a Spearman rank correlation for each of the same pairs of items, and then estimated the correlation between the cosine values and Spearman coefficients. We also used network analysis to explore the model's ability to uncover structures within the data and metadata. RESULTS: We found a moderate overall correlation (r = .48, p < .001) between the two indices. In a holdout sample, the cosine scores predicted the real-world correlations with a small degree of error (MAE = 0.05, MedAE = 0.04, RMSE = 0.064) suggesting the utility of NLP in identifying similar items for cross-study data pooling. Our NLP model could detect more complex patterns in our data, however it required manual rules to decide which edges to include in the network. CONCLUSIONS: This research shows that it is possible to quantify the semantic similarity between pairs of questionnaire items from their meta-data, and these similarity indices correlate with how participants would answer the same two items. This highlights the potential of NLP to facilitate cross-study data pooling in mental health research. Nevertheless, researchers are cautioned to verify the psychometric equivalence of matched items.

Socioeconomic and sex inequalities in parent-reported adolescent mental ill-health: time trends in four British birth cohorts.

BACKGROUND: Studies using symptom-based screeners have suggested that mental ill-health has increased in adolescents in recent decades, however, few studies have tested the equivalence of their instruments, which is critical for inferring changes in prevalence. In addition, little research has explored whether socioeconomic position (SEP) and sex inequalities in adolescent mental health have changed over time. METHODS: Using structural equation modelling, we explored SEP and sex differences in harmonised parent reports of emotional and behavioural problems, using data from four UK birth cohorts: the 1958 National Child Development Study (NCDS'58; n = 10,868), the 1970 British Cohort Study (BCS'70; n = 8,242), the 1991-92 Avon Longitudinal Study of Parents and Children (ALSPAC'91; n = 5,389), and the 2000-01 Millennium Cohort Study (MCS'01; n = 9,338). RESULTS: Compared with the two earliest cohorts, members of MCS'01 had higher latent mean scores on emotional problems (both sexes), and lower scores on behavioural problems (females only). The associations between four indicators of SEP and emotional problems were strongest in MCS'01, with housing tenure having the strongest association. All four SEP indicators were associated with behavioural problems in each cohort, with housing tenure again more strongly associated with problems in the MCS'01. Mediation analyses suggested that the increase in emotional problems occurred despite broadly improving socioeconomic conditions. CONCLUSIONS: Our findings suggest that parent reports of adolescent emotional problems, but not behavioural problems, have risen in recent generations and this trend is not solely due to reporting styles. A failure to address widening social inequalities may result in further increases in mental ill-health amongst disadvantaged young people.

War exposure, posttraumatic stress disorder, and complex posttraumatic stress disorder among parents living in Ukraine during the Russian war.

BACKGROUND: High rates of posttraumatic stress disorder (PTSD) have been documented in war-affected populations. The prevalence of Complex PTSD (CPTSD) has never been assessed in an active war zone. Here, we provide initial data on war-related experiences, and prevalence rates of ICD-11 PTSD and CPTSD in a large sample of adults in Ukraine during the Russian war. We also examined how war-related stressors, PTSD, and CPTSD were associated with age, sex, and living location in Ukraine. METHOD: Self-report data were gathered from a nationwide sample of 2004 adult parents of children under 18 from the general population of Ukraine approximately 6 months after Russia's invasion. RESULTS: All participants were exposed to at least one war-related stressor, and the mean number of exposures was 9.07 (range = 1-26). Additionally, 25.9% (95% CI = 23.9%, 27.8%) met diagnostic requirements for PTSD and 14.6% (95% CI = 12.9%, 16.0%) met requirements for CPTSD. There was evidence of a strong dose-response relationship between war-related stressors and meeting criteria for PTSD and CPTSD. Participants who had the highest exposure to war-related stressors were significantly more likely to meet the requirements for PTSD (OR = 4.20; 95% CI = 2.96-5.95) and CPTSD (OR = 8.12; 95% CI = 5.11-12.91) compared to the least exposed. CONCLUSIONS: Humanitarian responses to the mental health needs of the Ukrainian population will need to take account of posttraumatic stress reactions. Education in diagnosing and treating PTSD/CPTSD, especially in the situation of a significant lack of human resources and continuing displacement of the population, is necessary.

Associations among psychosis, mood, anxiety, and posttraumatic stress symptoms: A network analysis.

The associations among psychotic experiences (i.e., hallucinations and delusions), trauma exposure, and posttraumatic stress symptoms are complex and multidirectional. Using network analysis to understand how psychotic experiences and symptoms of posttraumatic stress disorder (PTSD) relate to one another may identify new interventional targets to treat comorbidity and its underlying pathological processes. This study aimed to use network analysis to examine the associations among psychotic experiences; negative symptoms of psychosis; and symptoms of PTSD, anxiety, and depression. In this population-based cohort study, 4,472 participants (36.7% male) were assessed for psychotic experiences, negative symptoms of psychosis, PTSD, anxiety, and depression at age 23 (M = 23.86 years, SD = 0.520) or 24 years (M = 24.03, SD = 0.848). Associations among symptoms were assessed via network analysis. Exploratory graph analysis identified three clusters of densely connected symptoms within the overall network: psychotic experiences; PTSD symptoms; and depressive and anxiety symptoms and negative symptoms of psychosis. Psychotic experiences had the strongest associations with other symptoms in the network, and symptoms of anxiety played a key role in bridging psychotic experiences, symptoms of PTSD, and depressive symptoms. Consistent with the stress reactivity and affective models for psychotic experiences, the results suggest that symptoms of anxiety and emotional distress (e.g., hyperarousal, panic) may have a key role in the development and maintenance of psychotic experiences and symptoms of PTSD. Targeting these symptoms may ameliorate symptom burden transdiagnostically.

Investigating the latent structure of the International Trauma Questionnaire to assess ICD-11 posttraumatic stress disorder (PTSD) and complex PTSD in an adult civilian sample during the Ukraine war.

The symptom structure of ICD-11 posttraumatic stress disorder (PTSD) and complex PTSD (CPTSD) and the validity of the International Trauma Questionnaire (ITQ) are yet to be tested among civilians in an active war zone. The present investigation examined the factor structure of the ITQ, the internal consistency of observed scores, and their associations with demographic characteristics and war-related experiences using a nationwide sample of 2,004 adults from the general population of Ukraine approximately 6 months after the full-scale Russian invasion in 2022. Overall, rates of endorsement across all symptom clusters were high. The mean total number of war-related stressors reported was 9.07 (SD = 4.35, range: 1-26). Internal reliability was good for all six ITQ subscales, Cronbach's αs = .73-.88, and the correlated six-factor model was found to provide the best representation of the latent structure of the ITQ in the present sample based on fit indices. There was evidence of a dose-response relationship, with increasing scores on all symptom clusters associated with higher total reported war-related stressors.

Change in child mental health during the Ukraine war: evidence from a large sample of parents.

The ongoing war in Ukraine is expected to negatively impact the mental health of the country's population. This study aims to provide a preliminary estimate of the degree of change in the mental health problems of Ukrainian children following Russia's invasion in February 2022, and to identify the sociodemographic and war-related risk factors associated with these changes. A nationwide, opportunistic sample of 1238 parents reported on a single randomly chosen child within their household as part of The Mental Health of Parents and Children in Ukraine Study. Data were collected between July 15th and September 5th, 2022. Participants completed modified versions of the Pediatric Symptom Checklist (PSC-17) which was adapted to capture change in the frequency of symptoms since the beginning of the war. Parents reported increases across all 17 indicators of internalizing, externalizing, and attention problems of the PSC-17. Increased problems were most pronounced within the internalizing domain, with 35% of parents reporting that their child worried more since the beginning of the war. A number of individual, parental, and war-related factors were associated with increases across the three domains. Exposure to war trauma, pre-existing mental health problems, and child age were among the strongest predictors of change. This survey provides preliminary evidence that the Russian war on Ukraine has led to an increase in common mental health problems among children in the general population. Further research is required to determine the extent and sequela of this increase, and to develop intervention strategies for those most in need.

Refining Anger: Summarizing the Self-Report Measurement of Anger.

The current paper presents a five-factor measurement model of anger summarizing scores on public-domain self-report measures of anger. Exploratory and confirmatory factor analyses of self-report measures of anger (UK, n = 500; USA, n = 625) suggest five replicable latent anger factors: anger-arousal, anger-rumination, frustration-discomfort, anger-regulation, and socially constituted anger. Findings suggested a 5-factor interpretation provided the best fit of the data. We also report evidence of measurement invariance for this 5-factor model of anger across gender, age, and ethnicity. The findings suggest a useful and parsimonious account of anger, summarizing over 50 years of research around the self-report measurement of anger.

Pre-pandemic mental health and disruptions to healthcare, economic and housing outcomes during the COVID-19 pandemic: evidence from 12 UK longitudinal studies.

BACKGROUND: The COVID-19 pandemic has disrupted lives and livelihoods, and people already experiencing mental ill health may have been especially vulnerable. AIMS: Quantify mental health inequalities in disruptions to healthcare, economic activity and housing. METHOD: We examined data from 59 482 participants in 12 UK longitudinal studies with data collected before and during the COVID-19 pandemic. Within each study, we estimated the association between psychological distress assessed pre-pandemic and disruptions since the start of the pandemic to healthcare (medication access, procedures or appointments), economic activity (employment, income or working hours) and housing (change of address or household composition). Estimates were pooled across studies. RESULTS: Across the analysed data-sets, 28% to 77% of participants experienced at least one disruption, with 2.3-33.2% experiencing disruptions in two or more domains. We found 1 s.d. higher pre-pandemic psychological distress was associated with (a) increased odds of any healthcare disruptions (odds ratio (OR) 1.30, 95% CI 1.20-1.40), with fully adjusted odds ratios ranging from 1.24 (95% CI 1.09-1.41) for disruption to procedures to 1.33 (95% CI 1.20-1.49) for disruptions to prescriptions or medication access; (b) loss of employment (odds ratio 1.13, 95% CI 1.06-1.21) and income (OR 1.12, 95% CI 1.06 -1.19), and reductions in working hours/furlough (odds ratio 1.05, 95% CI 1.00-1.09) and (c) increased likelihood of experiencing a disruption in at least two domains (OR 1.25, 95% CI 1.18-1.32) or in one domain (OR 1.11, 95% CI 1.07-1.16), relative to no disruption. There were no associations with housing disruptions (OR 1.00, 95% CI 0.97-1.03). CONCLUSIONS: People experiencing psychological distress pre-pandemic were more likely to experience healthcare and economic disruptions, and clusters of disruptions across multiple domains during the pandemic. Failing to address these disruptions risks further widening mental health inequalities.

Psychological distress from early adulthood to early old age: evidence from the 1946, 1958 and 1970 British birth cohorts.

BACKGROUND: Existing evidence on profiles of psychological distress across adulthood uses cross-sectional or longitudinal studies with short observation periods. The objective of this research was to study the profile of psychological distress within the same individuals from early adulthood to early old age across three British birth cohorts. METHODS: We used data from three British birth cohorts: born in 1946 (n = 3093), 1958 (n = 13 250) and 1970 (n = 12 019). The profile of psychological distress - expressed both as probability of being a clinical case or a count of symptoms based on comparable items within and across cohorts - was modelled using the multilevel regression framework. RESULTS: In both 1958 and 1970 cohorts, there was an initial drop in the probability of being a case between ages 23-26 and 33-34. Subsequently, the predicted probability of being a case increased from 12.5% at age 36 to 19.5% at age 53 in the 1946 cohort; from 8.0% at age 33 to 13.7% at age 42 in the 1958 cohort and from 15.7% at age 34 to 19.7% at age 42 in the 1970 cohort. In the 1946 cohort, there was a drop in the probability of caseness between ages 60-64 and 69 (19.5% v. 15.2%). Consistent results were obtained with the continuous version of the outcome. CONCLUSIONS: Across three post-war British birth cohorts midlife appears to be a particularly vulnerable phase for experiencing psychological distress. Understanding the reasons for this will be important for the prevention and management of mental health problems.

Measuring positive memories of home and family during childhood: The development and initial validation of the 'Memories of Home and Family Scale'.

There is a burgeoning evidence base highlighting the positive influence of benevolent childhood experiences (BCEs), even in the context of adversity. However, few measures are available to assess BCEs. The current study sought to develop and validate a measure which assesses positive recollections of experiences and emotions at home and with family during childhood called the 'Memories of Home and Family Scale'(MHFS). Confirmatory factor analysis (CFA) was employed to test the latent structure of the preliminary MHFS item scores in a sample of university students from the United Kingdom (N = 624). Following selection of the best-fitting model and final items for inclusion in the scale, total and subscale scores were correlated with a range of mental health outcomes. CFA results indicated that the latent structure of the MHFS items was best represented by a correlated six-factor first-order model. The final MHFS demonstrated high levels of internal reliability and convergent validity.

On top or underneath: where does the general factor of psychopathology fit within a dimensional model of psychopathology?

BACKGROUND: Dimensional models of psychopathology are increasingly common and there is evidence for the existence of a general dimension of psychopathology ('p'). The existing literature presents two ways to model p: as a bifactor or as a higher-order dimension. Bifactor models typically fit sample data better than higher-order models, and are often selected as better fitting alternatives but there are reasons to be cautious of such an approach to model selection. In this study the bifactor and higher-order models of p were compared in relation to associations with established risk variables for mental illness. METHODS: A trauma exposed community sample from the United Kingdom (N = 1051) completed self-report measures of 49 symptoms of psychopathology. RESULTS: A higher-order model with four first-order dimensions (Fear, Distress, Externalising and Thought Disorder) and a higher-order p dimension provided satisfactory model fit, and a bifactor representation provided superior model fit. Bifactor p and higher-order p were highly correlated (r = 0.97) indicating that both parametrisations produce near equivalent general dimensions of psychopathology. Latent variable models including predictor variables showed that the risk variables explained more variance in higher-order p than bifactor p. The higher-order model produced more interpretable associations for the first-order/specific dimensions compared to the bifactor model. CONCLUSIONS: The higher-order representation of p, as described in the Hierarchical Taxonomy of Psychopathology, appears to be a more appropriate way to conceptualise the general dimension of psychopathology than the bifactor approach. The research and clinical implications of these discrepant ways of modelling p are discussed.

The individual, place, and wellbeing - a network analysis.

BACKGROUND: Previous research has examined individual-level and place characteristics as correlates of subjective wellbeing, with many studies concluding that individual factors (e.g. health, finances) are more strongly related to wellbeing. However, this 'dualistic' approach has been challenged, with some arguing that it is impossible to disentangle the effects of the two domains, and that wellbeing should be considered as part of a network of mutually reinforcing relationships between individual, community and place characteristics. We used network analysis to explore these complex associations. METHODS: Data were from a large sample of adults from a socioeconomically disadvantaged region of the United Kingdom (N = 4319). Wellbeing was assessed using the 7-item version of the Warwick-Edinburgh Mental Wellbeing Scale (SWEMWBS). Mixed graphical networks were estimated including wellbeing, place and individual-characteristic variables as nodes. RESULTS: We found a densely connected network in which wellbeing was associated, both directly and indirectly, with all of the individual, community and place characteristics assessed. Wellbeing was most strongly connected with individual characteristics, in particular financial difficulty and subjective physical health. However, controlling for all other variables in the network model, wellbeing was positively associated with local greenspace usage, civic agency, and neighbourhood cohesion, and negatively associated with housing disrepair. Greater specificity in these associations was observed when the wellbeing construct was broken down into its constituent parts. CONCLUSIONS: These findings highlight the complex relationships that exist between individual, community and place characteristics in the context of subjective wellbeing, and that all domains need to be considered when developing population-level strategies to improve wellbeing. Further consideration needs to be given to how this might happen in practice, for example through a combination of consistent use of community engagement methodologies alongside Health in All Policy (HiAP) approaches.

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.

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.

Developmental stability of general and specific factors of psychopathology from early childhood to adolescence: dynamic mutualism or p-differentiation?

BACKGROUND: Recent research indicates that the best-fitting structural model of psychopathology includes a general factor capturing comorbidity (p) and several more specific, orthogonal factors. Little is known about the stability of these factors, although two opposing developmental processes have been proposed: dynamic mutualism suggests that symptom-level interaction and reinforcement may lead to a strengthening of comorbidity (p) over time, whereas p-differentiation suggests a general vulnerability to psychopathology that gives way to increasingly distinct patterns of symptoms over time. In order to test both processes, we examine two forms of developmental stability from ages 2 to 14 years: strength (i.e., consistency in the amount of variance explained by general and specific factors) and phenotypic stability (i.e., homotypic and heterotypic continuity). METHODS: Data are from the NICHD Study of Early Child Care and Youth Development. Psychopathology symptoms were assessed nine times between ages 2 and 14 years (n = 1,253) using the Child Behavior Checklist completed by mothers. Confirmatory bifactor modeling was used to test structural models of psychopathology at each age. Consistency in strength was examined by calculating the Explained Common Variance (ECV) and phenotypic stability was investigated with cross-lagged modeling of the general and specific factors. RESULTS: Bifactor models fit the data well across this developmental period. ECV values were reasonably consistent across development, with the general factor accounting for the majority of shared variance (61%-71%). Evidence of both homotypic and heterotypic continuity emerged, with most heterotypic continuity involving the general factor, as it both predicted and was predicted by specific factors. CONCLUSIONS: A bifactor model effectively captures psychopathological comorbidity from early childhood through adolescence. The longitudinal associations between the general and specific factors provide evidence for both the hypothesized processes (dynamic mutualism and p-differentiation) occurring through development.

Co-occurring internalizing and externalizing psychopathology in childhood and adolescence: a network approach.

The network approach suggests that psychopathology arises from complex associations between symptoms and may offer insight into the mechanisms that underpin psychiatric comorbidities. The transition from childhood to adolescence is a key period in the development of psychopathology, yet has rarely been considered from a network perspective. As such, the present study examined the network structure of internalizing and externalizing psychopathology from middle childhood through adolescence using data from the Avon Longitudinal Study of Parents and Children (ALSPAC; n = 4405). Eight DSM-IV disorders were assessed using maternal reports when children were aged 7.5, 10.5 and 14 years. Weighted, undirected networks were estimated and the relative importance of each node was assessed using three common measures of node centrality; strength, betweenness, and closeness. A consistent network structure emerged at all three time points; nodes clustered together in two regions of space broadly reflecting the internalizing and externalizing spectra. Permutation tests supported structural invariance across this developmental period. These spectra were bridged by numerous disorder-level interactions, the most consistent of which was between depression and oppositional defiant disorder (ODD). Furthermore, inspection of the centrality indices indicated that generalised anxiety disorder and ODD were the most central disorders in the networks. These findings demonstrate that symptom/disorder-level interplay and reciprocal influence are plausible mechanisms for the association between internalizing and externalizing psychopathology in childhood/adolescence.

Internalizing and externalizing disorders in childhood and adolescence: A latent transition analysis using ALSPAC data.

BACKGROUND: Research examining the association between internalizing and externalizing dimensions of psychopathology has relied heavily on variable-centered analytical techniques. Person-centered methodologies complement the variable-centered approach, and may help explain the medium-to-large correlations that exist between higher order dimensions of psychopathology. What little person-centered research exists has been cross-sectional and utilized adult samples. The present study sought to take a person-centered approach to the modeling of psychiatric comorbidity during a key developmental phase; middle childhood through adolescence. METHODS: Analysis was conducted on data from the Avon Longitudinal Study of Parents and Children (ALSPAC, N=9282). Latent transition analysis (LTA) was conducted using eight DSM-IV disorders assessed at ages 7.5 and 14years as measured indicators. RESULTS: At both time points, a four class solution provided the best fit, with classes labeled as (i) normative, (ii) primarily internalizing, (iii) primarily externalizing, and (iv) high-risk/multimorbid. There was considerable individual-level stability across time, with approximately 80% of children remaining in the same class at both time points. Those in the internalizing class at baseline were more likely to transition to a less severe class (i.e., the normative class). CONCLUSIONS: Person-centered methodologies demonstrate that the association between internalizing and externalizing is accounted for by a sub-population at high risk for experiencing psychiatric comorbidity, and 'cross-class' disorders which link the internalizing and externalizing spectra.

Homotypic and heterotypic psychopathological continuity: a child cohort study.

BACKGROUND: Heterotypic psychopathological continuity (i.e. one disorder predicting another at a later time point) contradicts the conventional view that psychiatric disorders are discrete, static entities. Studying this phenomenon may help to tease out the complex mechanisms that underpin psychiatric comorbidity. To date, no studies have explicitly compared heterotypic effects within and across higher order dimensions of psychopathology. METHODS: Patterns of homotypic and heterotypic psychopathological continuity were examined using cohort data from the Avon Longitudinal Study of Parents and Children (ALSPAC, N = 4815). Eight common psychiatric disorders were assessed at age 7.5 and again at age 14 years using the maternal report version of the Development and Well-Being Assessment (DAWBA). Cross-lagged models were used to compare patterns of homotypic and heterotypic continuity within and across three higher order dimensions of psychopathology; internalizing-fear, internalizing-distress, and externalizing. RESULTS: Homotypic continuity was universal. Considerable heterotypic continuity was observed even after controlling for homotypic continuity and the presence of all disorders at baseline. Heterotypic continuity was more common within higher order dimensions, but a number of significant cross-dimension effects were observed, with ADHD acting as a strong predictor of subsequent internalizing disorders. CONCLUSIONS: Heterotypic continuity may reflect elements of shared aetiology, or local-level interactions between disorders.

Variation in post-traumatic response: the role of trauma type in predicting ICD-11 PTSD and CPTSD symptoms.

PURPOSE: The World Health Organization's 11th revision to the International Classification of Diseases manual (ICD-11) will differentiate between two stress-related disorders: PTSD and Complex PTSD (CPTSD). ICD-11 proposals suggest that trauma exposure which is prolonged and/or repeated, or consists of multiple forms, that also occurs under circumstances where escape from the trauma is difficult or impossible (e.g., childhood abuse) will confer greater risk for CPTSD as compared to PTSD. The primary objective of the current study was to provide an empirical assessment of this proposal. METHODS: A stratified, random probability sample of a Danish birth cohort (aged 24) was interviewed by the Danish National Centre for Social Research (N = 2980) in 2008-2009. Data from this interview were used to generate an ICD-11 symptom-based classification of PTSD and CPTSD. RESULTS: The majority of the sample (87.1%) experienced at least one of eight traumatic events spanning childhood and early adulthood. There was some indication that being female increased the risk for both PTSD and CPTSD classification. Multinomial logistic regression results found that childhood sexual abuse (OR = 4.98) and unemployment status (OR = 4.20) significantly increased risk of CPTSD classification as compared to PTSD. A dose-response relationship was observed between exposure to multiple forms of childhood interpersonal trauma and risk of CPTSD classification, as compared to PTSD. CONCLUSIONS: Results provide empirical support for the ICD-11 proposals that childhood interpersonal traumatic exposure increases risk of CPTSD symptom development.