Trauma and ICD-11 PTSD in treatment for substance use disorders: A Danish multi-site study 

Trauma and ICD-11 PTSD in treatment for substance use disorders: A Danish multi-site study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Trauma and ICD-11 PTSD in treatment for substance use disorders: A Danish multi-site study Sidsel Karsberg, Lisa Najavits, Mads Uffe Pedersen, Ask Elklit, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4918218/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 07 Aug, 2025 Read the published version in BMC Psychiatry → Version 1 posted 4 You are reading this latest preprint version Abstract Background Previous research has indicated high levels of PTSD among people with substance use disorders (SUD), necessitating an exploration of trauma profiles in this population. This study aims to assess the prevalence of ICD-11 PTSD and study demographic, trauma-related, and substance-use related factors among individuals in SUD treatment in Denmark, focusing on differences between alcohol use disorder (AUD) and drug use disorder (DUD). Methods The study utilized a multi-site approach, collecting data from five Danish SUD treatment settings. A total of 1347 adult individuals were interviewed as part of an initial structured screening process for SUD treatment. Participants were assessed using the ICD-11 PTSD criteria. Results The findings indicate that approximately 25% of individuals in treatment met the criteria for probable PTSD, with an additional 15% showing subclinical PTSD symptoms. The prevalence of PTSD was higher in DUD treatment compared to AUD treatment. The study also highlighted significant differences in social functioning and clinical profiles between the two groups. Conclusion The high prevalence of PTSD symptoms among individuals in SUD treatment underscores the need for targeted interventions. The study suggests that PTSD should be a particular focus in DUD treatment due to the higher vulnerability and impact of trauma-related symptoms in this group. PTSD Substance Use Disorder Therapy Trauma Figures Figure 1 Figure 2 Introduction Traumatic experiences are well-known risk factors for substance use disorder (SUD) (1), indeed rates of trauma exposure among adults with SUD are estimated to be as high as 95% (2, 3), and among individuals who report traumatic exposure the prevalence of SUD is three times higher than for non-exposed individuals (4). Child abuse is often identified as a prominent risk factor for substance use behaviors (5-7). Similarly, the comorbidity between SUD and posttraumatic stress disorder (PTSD) after traumatic experiences is common (4). In a systematic review including 42 studies, Debell and colleagues describe prevalence rates of comorbid alcohol use disorder (AUD) at 10%–61% among those with PTSD, and comorbid rates of PTSD for those with AUD of 2– 63%, with most studies reporting rates over 10% (8). Comparatively high rates of PTSD also occur among individuals with drug use disorder (DUD) (9). Preliminary evidence suggests that rates vary based on specific types of drug. For instance, among opiod use disorder (OUD) samples in opiod anagonist treatment, 41% have a lifetime history of PTSD and 33% have current PTSD (10), representing the highest rate of PTSD among drug types (11). Comorbid PTSD in SUD treatment There is a particularly high incidence of PTSD among individuals in SUD treatment, ranging from 20% to 52% (Roberts et al., 2022). PTSD-SUD comorbidity poses many challenges for SUD treatment. Individuals with PTSD-SUD present with a more severe and complex clinical profile than those with either disorder alone (12, 13). A number of studies have indeed indicated that individuals with PTSD, have poorer outcomes of SUD treatment including worse treatment adherence and less improvement during treatment (14-18). Despite the substantial body of literature on the prevalence of trauma and PTSD among individuals in treatment for SUD, the majority of existing studies are from the United States (9). Only one study has reported the co-occurrence in Scandinavian countries. A recent Norwegian study that included 106 individuals in SUD treatment reported prevalences of PTSD of 23.8% and 25.6% among recovered versus current users (19). To this date, no studies have examined the prevalence of PTSD in treatment for SUD in Denmark. Moreover, it is clear from the literature that the link between PTSD-SUD has mainly been examined without distinguishing AUD and DUD. A recent study suggests that individuals with DUD and PTSD are more likely to report greater impairment, to have worse social and psychiatric functioning, and to have received both addiction and mental health treatment compared to individuals with AUD and PTSD (20). This implies that there may be important differences between Individuals with DUD and AUD and comorbid PTSD that are important to investigate. Moreover, a small amount of current European studies are based on updated validated PTSD screening measures. Overall, research using clinical interviews to assess the ICD-11 formulation of PTSD is still scarce. However, Hansen and colleagues (21) reported substantial agreement between the International Trauma Questionnaire (ITQ) (22) self-report and clinical interviews for PTSD in a sample of Danish chronic pain patients. Using the International Trauma Interview, a study of found fair to moderate agreement between self-report and clinical assessed PTSD among a Lithuanian adult trauma exposed sample (23). Hence, surveys using validated self-report measures are an important first step in estimating probable prevalence of ICD-11 PTSD among people in treatment for substance use disorders in Denmark, although not sufficient to establish prevalence rates. Research has supported the validity of the Danish translation of the International Trauma Questionnaire for self-report of symptoms of ICD-11 PTSD and complex PTSD across 5 clinical samples (Vang et al., 2021). While substance abuse in the family is a known predictor of PTSD and complex PTSD in children (24), there has yet to be a test of validity in addition to the prevalence of the ICD-11 formulation of PTSD and CPTSD among adult substance users in treatment (25). Aims and hypotheses Our aim was to estimate the prevalence of ICD-11 PTSD among treatment-seeking substance users. As an initial step, we sought to test the validity of the ICD-11 PTSD in this sample. We also sought to explore demographic and trauma-related factors in SUD treatment. We had the following hypotheses: 1) The factor structure of ICD-11 PTSD among treatment seeking substance users would mirror the factor structure established in European clinical samples (Redican et al., 2022; Vang et al., 2021). 2) Prevalence rates of PTSD would be higher than in the general population (Karsberg et al., 2024, Kessler et al., 2017; Vang et al., 2023), and comparable to those found in SUD treatment samples (9). 3) The number and type of trauma would differ between individuals in treatment for DUD vs. AUD (26). 4) The level of PTSD-symptom severity and prevalence of PTSD would differ between individuals in treatment for DUD vs. AUD (20). 5) Demographic characteristics as well as severity of drug use and alcohol use would differ between individuals with PTSD, individuals with subclinical PTSD, and individuals that did not live up to the criteria for a PTSD-diagnosis in treatment for AUD and DUD, with individuals with probable PTSD reporting higher levels of social vulnerability (i.e., unstable living situation, not in employment/education, psychiatric diagnosis) and substance use (1, 20). Material and methods Participants and procedures The study was performed as a cross-sectional study. Data was collected from the 1st of November 2022 until the 29th of December 2023, corresponding to a total of 13 months across five sites. Figure 1 displays the data flow of the project. Data for the present study was retrieved from structured interviews with adults receiving treatment for DUD and AUD in five Danish treatment centers. The participating treatment centers were part of a larger treatment project aimed at testing two trauma focused treatment methods in treatment for substance use disorders. The treatment centers are placed in five different locations in Denmark and represent both rural and larger cities. One of the participating treatment centers (site 5) offered heroin-assisted treatment only, whereas the remaining sites (site 1 to 4) offered specialized outpatient treatment for SUD. Site one to four offered various types of treatment for SUD including pharmacological treatment, psychological treatment, family counselling, and psychoeducation. All the participating treatment centers are public and free of charge and operate in close collaboration with the social services and the healthcare system. A total of 1347 adult individuals were interviewed as part of an initial structured screening process for SUD treatment at the five participating treatments centers. Due to structural and organizational differences in treatment, the screening interview was fully implemented for treatment of DUD but to a lesser degree for treatment of AUD which meant that 69.5 % of the sample was enrolled in treatment for drug use disorders and 30.5% was enrolled in treatment for alcohol use disorders. Measures Data for the present study was retrieved from AdultMap interviews (27). AdultMap is a Danish structured screening interview consisting of 70 to 90 items (depending on responses) that is specifically developed for SUD treatment. Topics in the interview are living conditions, mental health and behavior, physical health, substance use, social network, adverse experiences, and function level. AdultMap is widely used for SUD treatment in Denmark and is implemented in 68 of the 98 municipalities in Denmark. The primary aim of the interview is to assess current barriers, needs, and resources to offer the most appropriate treatment possible. The questions used for the present study (i.e., demographic data, trauma exposure and substance use) are part of the currently used version of AdultMap. The trauma symptom items in the present study were implemented for the study period and in the five included treatment centers only. Interviews were conducted by treatment counselors at treatment enrollment. Demographic data : Demographic factors were gender (man vs. woman); age; treatment type (i.e., AUD or DUD); employment status (in school, employed, or in training or none of those); source of income (financially supported via full- or part-time occupation or educational support or governmental support, or early retirement, or no income or financial support by relatives); and living situation (stable or partly stable vs. unstable such as homeless, living in an institution, or in prison or detainment). Pre-existing psychiatric disorder was measured by self-reported previous diagnosis by a psychiatrist with any of the following disorders: depression, bipolar, anxiety, ADHD, personality disorder, OCD, autism spectrum disorder, schizophrenia, psychosis. The total number of previous diagnoses was summarized to create a total score. Trauma exposure was assessed using six trauma categories (i.e., accident, sexual abuse or assault, physical or psychological violence, life-threatening illness, sudden accidental death, and other very stressful or violent experience). These categories were selected based on prior research indicating that they are the most common types of traumatic exposure previously identified in general populations (28). Further, an almost identical event checklist was used in a Danish ITQ validation study (21) with the only difference being that a seventh item (i.e. natural disasters) was not included in the present study, as natural disasters are rare in Denmark. Each trauma type was scored dichotomously with 1=Directly exposed or witnessed and 0=Not directly exposed nor witnessed. For trauma exposure, age in years at trauma exposure was assessed (0 to 5 years, 6 to 12 years, 12 to 18 years, throughout the childhood, in adulthood only, or both in childhood and adulthood). ICD-11 PTSD : ICD-11 PTSD symptoms were assessed using a Danish translated and validated version (Hansen et al., 2021) of the International Trauma Questionnaire (ITQ) for PTSD symptoms (22). The concurrent and discriminant validity of the ITQ (29, 30) along with the factorial validity of the ITQ across different countries and cultures, including Denmark, has been demonstrated in several studies (21, 24, 31). The ITQ is a 12-item validated self-report measure developed for assessment of ICD-11 PTSD and Complex PTSD. Only the 6 items for ICD-11 PTSD were used for the current study. In the ITQ, the six PTSD items are accompanied by three items measuring associated functional impairments in the domains of social, occupation, and other important areas of life. Respondents are asked how much each PTSD symptom bothered them in the past month. Items are scored on a five-point Likert scale from 0 (‘Not at all’) to 4 (‘Extremely’). Symptoms are considered endorsed with scores of two (‘Moderately’) or more. To meet criteria for PTSD, one symptom is required in each of the clusters for re-experiencing, avoidance, and sense of threat as well as a score of two or more on one of the three questions assessing associated functional impairment. We operationalized subclinical PTSD as either 1) one symptom in any two of the clusters for re-experiencing, avoidance and sense of threat and functional impairment is required, alternatively, 2) all symptom clusters must be endorsed without functional impairment. Cronbach’s alpha for the ITQ in the present study was 0.84 for the PTSD subscale. Substance use severity Alcohol use severity was measured by a total score on the AUDIT, a 10-item screening tool developed by the World Health Organization (32). The AUDIT assesses the amount and frequency of alcohol use (items 1-3), alcohol dependence (questions 4-6) and problems related to alcohol consumption (items 7-10). Each item is scored from 0 to 4, resulting in a total score range from 0 to 40. The current study relied on cut-off scores established by the WHO whereby scores from 8-14 indicate hazardous or harmful alcohol-use, and scores of 15 or more indicate the likely presence of moderate to severe alcohol use disorder, corresponding to alcohol-dependence (33) Drug use severity was measured by self-reported use of cannabis, amphetamines, cocaine, MDMA, opioids, and other substances within the past 30 days. Responses were coded into a composite score ranging from 0-100 (number of days cannabis + number of days amphetamines + number of days cocaine + number of days MDMA + number of days opioids + number of days sedatives + number of days with other substances) / 210 (i.e, the number of possible days with drug use) x 100. For example: number of days cannabis use (n=20) + number of days cocaine use (n=4): 24/210 x 100=11.4. Drug use is considered severe if the score is 12 or more. Data analysis The data were cleaned as per figure 1, and then we tested each of the five hypotheses. Hypothesis 1 . Two competing models of the latent structure of the ITQ was tested to examine whether the ITQ factor structure among substance users align with existing findings on the ICD-11 model of PTSD (Redican et al., 2022). The first model tested was a one factor model, where all items loaded onto a single latent factor representing PTSD-severity. This model has 18 free parameters and nine degrees of freedom. The second model was a correlated first order model representing the segregation of ITQ-items into three correlated latent factors corresponding to the ICD-11 formulation of PTSD consisting of re-experiencing, avoidance, and sense of threat. This model has 21 free parameters and six degrees of freedom and is statistically equivalent to a one factor second order model where factor correlations are replaced by factor loadings of re-experiencing, avoidance, and sense of threat onto a latent factor of PTSD. Figure 2 displays the competing models. The model fit was evaluated and compared using a standard range of model fit indices. The model with the lowest BIC is preferred, so long as other indicators support the fit of the model to the data. This includes CFI and TLI values above 0.90 or 0.95 for adequate or excellent fit, and RMSEA and SRMR values lower than 0.08 or 0.05 for adequate or close fit to the data, respectively. Hypothesis 2 . We calculated descriptive statistics on each PTSD-symptom cluster and functional impairment, as well as the total rate of positive screens for PTSD and subclinical PTSD as described in Methods. Hypothesis 3 . Chi-square analyses were conducted to test the distribution of types of traumatic events across each treatment-type, and independent samples t-test was used to test differences in total number of traumatic events. Hypothesis 4 . Independent samples t-tests compared PTSD-severity between DUD and AUD treatment. Hypothesis 5 . A series of chi-square analyses and ANOVAs, first on the total sample and then on AUD and DUD samples separately, tested the significance of observed differences across probable PTSD-diagnostic status and demographic and trauma-related variables in each treatment group. Results Participant characteristics In total, 1347 participants across five treatment sites were eligible and screened as part of their enrollment for AUD or DUD treatment. Of these, 61 participants did not want to disclose whether they had been exposed to a stressful experience, resulting in a total sample of N=1286 participants. Out of these, 942 participants responded to the ITQ. The total sample (N=1286) was used as reference group for hypotheses 2 and 3 concerning the prevalence and distribution of trauma and PTSD in the total treatment-seeking group. A reference sample consisting of the participants who reported traumatic experiences as well as symptoms on the ITQ (n=942) was used to test hypotheses 1, 4 and 5 concerning PTSD and trauma-types specifically, as these necessitates participant responses on a selected number of measures that led to a more restricted sample size. Insert table 1 here and figure 1 here. See Figure 1 for participant flow in the project, and Table 1 for participant characteristics in the total sample. Most participants were men (72.7%). The sample had an average age of 36 years (range 13-82 years for both total sample and the ITQ sample). There were more participants in treatment for DUD compared to AUD, and the majority were not employed or in school. Regarding exposure to stressful experiences, 23.5 % of the total sample reported no exposure. Participants in the trauma-exposed group were significantly more likely to be in DUD treatment (adj. res. = 3.0, (χ 2 (2)=13.23, p<.001). Similarly, participants reporting no exposure (adj. res = 6.9) were statistically significantly more likely to be in employment or education, whereas participants in the nondisclosure group were less likely to be in employment (adj. res. = -2.9, χ2(2)=51.10, p<.001). Finally, men were overrepresented in the non-exposed group (adj. res. = 8.4), and women were overrepresented in the exposed (adj. res. = 6.8) and non-disclosure group (adj. res. = 2.4, χ2 (2)=73.11, p<.001). Hypothesis 1: Factor structure of ICD-11 PTSD among substance users See Table 2 displays for the confirmatory factor analysis. Model 2 surpassed model 1 in all aspects of fit and was deemed the best fit with excellent fit statistics according to cut-offs on all indicators. Figure 2 displays the factor loadings and factor correlations of the best fitting models. Hypothesis 2: Rates of probable ICD-11 PTSD Table 1 displays the prevalence rates of ICD-11 PTSD (23.9 %) and subclinical PTSD (14.5 %) among treatment-seeking substance users (N=1286). Rates of PTSD was 18% (n=74) for individuals in AUD treatment, and 26.6 % (n=233) for individuals in DUD treatment. Table 3 displays rates of PTSD and subclinical PTSD between AUD and DUD samples using the more restricted ITQ sample (N=941). There were significantly more PTSD cases among those that sought help for drugs compared to alcohol (χ 2 (1)=6.73, p=.009, adj. res. = 2.7) and no statistically significant differences in rates of probable subclinical PTSD between drug use and alcohol use (χ 2 (1)=0.00, p=1.00, adj. res. = 0). Hypothesis 3 and 4: Trauma-types, number of traumas and PTSD-severity across SUD groups (ITQ sample, N=941) See Table 3 displays for differences between AUD and DUD samples. Overall, women were overrepresented in AUD and men overrepresented in DUD. Participants in DUD treatment were on average more than 10 years younger than participants in AUD and were also more likely to have an unstable living situation compared to AUD-participants. Regarding trauma-exposure, the DUD group was more frequently exposed to all trauma types apart from diseases, where there were no differences, and other types of events that were more frequently reported by the AUD group. Total number of reported trauma-types was higher for the DUD sample. Similarly, PTSD severity was significantly higher for the DUD group. Table 4 displays differences in trauma-related predictors across PTSD diagnostic categories for the ITQ sample (n=941) as well as the AUD and DUD samples. In treatment for DUD there were significant differences across participants with, no PTSD, subclinical PTSD and PTSD, with individuals in the PTSD group reporting more sexual violence, physical/psychological violence, accidents, and unexpected death of a loved one, a higher number of events, and higher rates of life-span exposure than the no-PTSD group and the subclinical PTSD group. For individuals in treatment for AUD there were differences across the PTSD diagnostic categories in relation to physical/psychological violence and number of trauma types with these being more prevalent in the PTSD group. For both AUD and DUD, the prevalence of childhood trauma (only) was less prevalent in the PTSD group compared to the no PTSD group. Hypothesis 5: Demographic differences and differences in substance use severity across probable PTSD-diagnostic categories Differences in gender, age, employment/education, living situation, psychiatric diagnosis as well as substance use across participants with no PTSD, probable subclinical PTSD, and probable PTSD are shown in Table 5 for the ITQ sample (n=942). The proportion of individuals who were women, were not in school/in employment, had unstable living situations, or who had a psychiatric disorder was significantly lower in the no PTSD group, higher in the subclinical PTSD group, and highest in the PTSD group. There were no significant age differences across the PTSD diagnostic groups. Differences in severity of drug use were significant: The proportion of participants with severe drug use was lowest in the no PTSD group (15.9 %), higher in the subclinical group (24.1%) and highest in the PTSD group (36.2%). No significant differences were seen in severity of alcohol use across PTSD diagnostic categories. Table 5 also displays analyses for AUD and DUD separately. There were no statistically significant differences across diagnostic categories in treatment for AUD for neither demographic, substance-related or trauma-related factors. In DUD treatment, women were more likely to be represented in the probable subclinical and clinical PTSD groups, those with PTSD were more likely to be out of employment, more likely to have comorbid psychiatric disorders, and more likely to have a severe drug use compared to those in treatment for DUD that did not endorse the criteria for a probable PTSD-diagnosis. Discussion The aim of the current study was to assess the validity and prevalence of ICD-11 PTSD in treatment for problematic substance use and study demographic, trauma-related, and substance-use related differences across probable PTSD-caseness in AUD and DUD. The study addresses gaps in the literature by identifying important characteristics for comorbid individuals in treatment for SUD. Using the new ICD-11 diagnostic criteria for PTSD, we offer a report on differences in prevalence of traumatic experiences, PTSD status, social functioning, and clinical profiles in treatment for AUD vs. DUD. Our findings add to the growing body of evidence showing that severe trauma-related symptoms are highly prevalent in both treatment for AUD and DUD. In the overall sample approximately every fourth individual in treatment met the diagnostic criteria for probable PTSD. The additional proportion of individuals who reported PTSD symptoms corresponding to the criteria for probable subclinical PTSD, means that approximately 40% of the participants were moderately or severely affected by PTSD symptoms. The high prevalence of PTSD symptoms from the five Danish SUD treatment settings is in accordance with existing studies that find a strong causal and interactional relationship between PTSD and substance use ( 9 ) and indicates that trauma and PTSD are also highly prevalent comorbidities among people in SUD treatment in Denmark. In line with our expectations, we found trauma-related differences between the AUD and DUD samples. Participants in treatment for DUD reported a significantly higher prevalence of exposure to accidents, physical/psychological violence, sexual violence, and unexpected death as well as number of trauma types than individuals in treatment for AUD. In addition, the severity of PTSD-symptoms and the prevalence of probable PTSD was higher for individuals in treatment for DUD. The higher prevalence of PTSD in treatment for DUD may be related to the specific types and severity of traumatic experiences reported. For example, it is well established that interpersonal and intentional trauma exposure such as sexual abuse and physical abuse are more damaging and are associated with a higher conditional risk of PTSD than non-interpersonal and unintentional trauma exposure ( 34 ). In addition, there is evidence that exposure to multiple types of trauma –especially childhood trauma ( 35 ) - places victims at risk for developing PTSD over and above the risk conferred by single types of exposure to traumatic stressors ( 36 ). Therefore, the higher prevalence of interpersonal trauma and the higher number of trauma experiences reported in the DUD sample may imply the presence of more severe trauma profiles among individuals in treatment for DUD. The differences in trauma profiles between those in AUD vs. DUD treatment was further supported by the identified trauma-related differences between the three diagnostic categories (i.e., individuals with probable PTSD, individuals with probable subclinical PTSD, and individuals that did not live up to the criteria for a probable PTSD-diagnosis), where we found distinctive differences between traumatized individuals in treatment for AUD and DUD respectively. Of particular interest, the PTSD group in treatment for DUD was characterized by a comparably high prevalence of interpersonal violence experiences (i.e., physical/psychological violence, and sexual violence). For the PTSD group in AUD treatment the prevalence of sexual violence and physical /psychological violence was 29.7% and 66.2% and in DUD treatment it was 44.2% and 87.1%, respectively. Since the level of trauma severity and PTSD have been linked to a number of factors that are relevant for treatment outcome ( 37 ), such as the therapeutical alliance ( 38 ), treatment drop out ( 39 ), craving ( 40 ), and substance use severity ( 41 ), differences in trauma profiles across AUD and DUD treatment could be important factors to consider for treatment planning and interventions. In addition to differences in trauma severity and PTSD, we identified several interesting sociodemographic differences (gender, employment status, living situation, psychiatric disorder, severity of substance use) across PTSD diagnostic categories in AUD and DUD treatment. Differences were only significant for the DUD sample. In treatment for DUD, the group that lived up to the criteria for probable PTSD was characterized by more women, less employment, less stable living situation, more psychiatric diagnoses, and a more severe use of illicit drugs compared to individuals that did not live up to the diagnostic criteria. In the AUD treatment sample, there were no significant differences for these factors between the three diagnostic categories. This could indicate that traumatized individuals in treatment for DUD are more socially and psychologically vulnerable than non-traumatized individuals in DUD treatment, whereas in AUD treatment, PTSD is not to the same degree associated with other social and psychological risk factors. Overall, the identified differences highlight that treating SUD as a unitary construct in relation to trauma and PTSD may obscure important between-group differences in terms of type of substance used that may be important for practice. Further research of the association between trauma symptomatology and treatment factors would be relevant for a more nuanced understanding of the differences in trauma profiles in treatment for AUD and DUD respectively. Research implications The identified differences in trauma exposure, PTSD symptomatology as well as sociodemographic factors in treatment for AUD and DUD underline the importance investigating traumatization in relation to treatment contexts and types of substance use. Further investigation into different profiles of vulnerability and traumatization in treatment for substance use disorders that assess different types of substance use could indeed be useful. Considering the high level of PTSD, future studies might include the sister diagnosis of Complex PTSD that in addition to PTSD covers disturbances of self-organization. Clinical implications As in many other countries, psychosocial treatment approaches for individuals with PTSD and SUD in Denmark have adhered to the sequential treatment model, in which SUD is treated first, and trauma work is deferred until a period of sustained abstinence has been achieved. However, given the high co-occurrence of PTSD and SUD, there have been important advances such as the development and use of integrated treatment models (treating both disorders at the same time, by the same counselor). In addition, there is a strong consensus that outpatient health care and social services need to deliver trauma-informed and trauma-specific care to reduce the effects of trauma, offer safe treatments, and avoid re-traumatization. In line with these changes in practice, the results of the current study highlight that PTSD is an important focus for SUD treatment in Denmark. Although trauma and PTSD is highly prevalent in both treatment for AUD and DUD, the results further suggest that a higher proportion of individuals in treatment for DUD have a background of interpersonal violence and higher risk of PTSD compared to treatment for AUD. Since interpersonal violence has been related to a number of factors relevant for treatment outcomes ( 37 – 41 ), it could be relevant to specifically target these factors for this group. The identified vulnerability in the PTSD group in DUD treatment compared to the group with no PTSD, further supports the idea that PTSD should be a particular focus in treatment for DUD. Strengths and Limitations The strengths of the present study include a systematically collected and large sample size using a validated ICD-11 PTSD measure, and separate data from AUD and DUD treatment. The most important limitation is that the study sample consisting of patients from five treatment centers may not be representative for the SUD treatment population in Denmark. In addition, trauma experiences and PTSD symptoms may have been underreported. Both men and women tend to underreport abusive experiences ( 42 , 43 ). In addition, many of the counsellors reported that there were many clients who were not able to recognize or feel the trauma-related symptoms in the ITQ due to active substance use, and that the identified prevalence of PTSD may therefore also be underreported. Despite these potential limitations, the proportion of participants reporting exposure to potentially traumatic events (72%) mirrors international estimates (Kessler et al., 2017), and rates of PTSD symptoms were higher than population surveys (Karsberg et al., 2024; Kessler et al., 2017; Vang et al., 2023). However, it is indeed possible that the reported prevalence of traumatic experiences would be even higher if the participants had filled out the questionnaire without the counsellor being present or if they had filled out the questionnaire later in the treatment course when they had obtained a closer relationship with the counsellor and had reduced their substance use. Conclusion Traumatic experiences and PTSD were highly prevalent in a sample of over 1200 individuals seeking AUD or DUD treatment. The results indicate that individuals in DUD treatment may have a more severe trauma profile than individuals in AUD treatment. The results highlight the need for trauma-specific interventions in SUD treatment settings. Declarations Ethics declarations Human Ethics and Consent to Participate declarations The study was conducted in accordance with the Declaration of Helsinki and approved by the Danish Data Protection Agency and the Regional Committee for Medical and Health Research Ethics for the Central Denmark Region (#1-10-72-121-21). Informed consent for use in research and publications was retrieved from all participants. Competing interests There are no competing interests to declare Funding The study was funded by the Tryg Foundation (ID: 154804). Author Contribution Study design, material preparation, data collection, and first draft of the manuscript were performed by SK. Data analysis, figures and tables were performed by MLV. All authors reviewed and commented on previous versions of the manuscript. All authors read and approved the final manuscript. Data Availability Data is available to other researchers at the aggregate level to avoid the sharing of data on individual patients. 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Tables Table 1: Sample characteristics Total sample (N=1286) ITQ sample (n=942) Gender (% female) 364 (28.3 %) 325 (34.5 %) Age (in years) 36.49 (13.65) 35.53 (12.85) Education (yes) 242 (18.8 %) 168 (17.9 %) Income (employment/education) 485 (37.7 %) 306 (32.5 %) Living situation (stable) 1133 (88.1 %) 812 (86.3 %) Drug-treatment 876 (68.1 %) 660 (70.1 %) Alcohol-treatment 410 (31.9 %) 281 (29.9 %) Psychiatric diagnoses (M, SD) 0.86 (1.16) 0.98 (1.23) Stressful experiences 970 (75.4 %) 941 (100 %) Accidents 245 (19.1 %) 245 (26 %) Violence 633 (49.2 %) 631 (67.1 %) Sexual violence 264 (20.5 %) 264 (28 %) Life-threatening illness 190 (14.8 %) 190 (20.2 %) Unexpected death 381 (29.6 %) 381 (40.4 %) Other events 499 (38.8 %) 496 (52.7 %) Nondisclosure 24 (1.9 %) 0 (0 %) N trauma-types (M, SD) 2.28 (1.33) 2.35 (1.30) Child/youth exposure (yes) 337 (26.2 %) 334 (35.5 %) Adult exposure (yes) 377 (29.3 %) 377 (40.1 %) Life-span exposure (yes) 231 (18.0 %) 230 (24.4 %) Re-experiencing (endorsed) 473 (36.8 %) 471 (50.2 %) Avoidance (endorsed) 609 (47.4 %) 609 (64.7 %) Sense of threat (endorsed) 609 (47.4 %) 609 (64.6 %) Functional impairment (endorsed) 579 (45 %) 579 (61.5 %) Probable PTSD (endorsed) 307 (23.9 %) 307 (32.6 %) Probable subclinical PTSD (endorsed) 187 (14.5 %) 187 (19.9 %) Note: No percentages reported are corrected for missing data values. Missing data ranged between 0 % to 7 % for demographic information (age). Violence refers to both physical and sexual violence. Disease refers to life-threatening diseases. Table 2: Fit statistics for competing models of the factor structure of the ITQ Model ꭕ 2 (df) p CFI TLI RMSEA (90 % CI) SRMR BIC MLR One factor 159.23 (9) <.001 0.900 0.833 0.133 (0.115;0.152) 0.048 18751.81 Three factor 6.46 (6) .374 1.000 0.999 0.009 (0.000;0.044) 0.009 18569.96 Note: The three-factor correlated model is statistically equivalent to a 2 nd order one factor model. Table 3: Differences in participant characteristics across AUD and DUD (Sample size variable depending on available data) AUD (N=410, n=281 completed ITQ) DUD (n=876, n=661 completed ITQ) Significance test Gender (% female) 135 (32.9 %), AR = 2.5 229 (26.1 %), AR = -2.5 χ 2 (1)=6.34, p=.014 Age (in years) 45.74 (14.20) 32.25 (11.06) t(613.45)=16.01, p<.001 Education (yes) 52 (12.7 %), AR = -3.9 190 (21.7 %), AR = 3.9 χ 2 (1)=14.25, p<.001 Income (employment/education) 172 (42 %), AR = 2.1 313 (35.7 %), AR = -2.1 χ 2 (1)=4.34, p=.037 Living situation (stable) 22 (5.4 %), AR = -4.9 131 (15.0 %), AR = 4.9 χ 2 (1)=23.59, p<.001 Psychiatric diagnoses (M, SD) 0.73 (1.04) 0.91 (1.21) t(940.03)=-2.48, p=0.019 Stressful experiences 284 (69.3 %), AR = -3.0 686 (74.5 %) χ 2 (1)=12.91, p=.002 Accidents 60 (21.1 %), AR = -1.9 185 (27 %), AR = 1.9 χ 2 (1)=3.33, p=.068 Violence 158 (55.6 %), AR = -4.1 475 (89.2 %), AR = 4.1 χ 2 (1)=15.81, p<.001 Sexual violence 59 (20.8 %), AR = -2.9 205 (29.9 %), AR = 2.9 χ 2 (1)=7.96, p=.005 life-threatening illness 59 (20.8 %), AR = 0.6 131 (19.1 %), AR = -0.6 χ 2 (1)=0.26, p=.610 Unexpected death 99 (34.9 %), AR = -1.8 282 (41.1 %), AR = 1.8 χ 2 (1)=3.03, p=.082 Other events 167 (58.8 %), AR = 3.0 329 (48.4 %), AR = -3.0 χ 2 (1)=8.30, p=.004 N trauma-types (M, SD) 2.12 (1.25) 2.35 (1.37) t(571.02)=-2.51, p=.012 Child/youth exposure (yes) 87 (31 %), AR = -2.0 250 (37.7 %), AR = 2 χ 2 (2)=6.39, p=.041 Adult exposure (yes) 129 (45.9 %), AR = 2.5 248 (37.3 %), AR =-2.5 Life-span exposure (yes) 65 (23.1 %), AR = -0.6 165 (25 %), AR = 0.6 Re-experiencing (endorsed) 125 (44.5 %), AR = -2.3 348 (52.6 %), AR = 2.3 χ 2 (1)=4.94, p=.026 Avoidance (endorsed) 162 (57.7 %), AR =-2.9 447 (67.7 %), AR = 2.9 χ 2 (1)=8.15, p=.004 Sense of threat (endorsed) 169 (60.1 %), AR = -1.9 439 (66.5 %), AR = 1.9 χ 2 (1)=3.29, p=.070 Functional impairment (endorsed) 161 (57.3 %), AR = -1.7 418 (63.3 %), AR = 1.7 χ 2 (1)=2.79, p=.095 Probable PTSD (endorsed) 74 (26.3 %), AR = -2.7 233 (35.3 %), AR = 2.7 χ 2 (2)=8.14, p=.017 Probable subclinical PTSD (endorsed) 56 (19.9 %), AR = 0 131 (19.8 %), AR = 0 PTSD severity (M sum, SD) 8.48 (6.12) 10.49 (6.79) t(582.91)=-4.46, p<.001 Note: Chi-square tests are conducted using continuity correction for 2x2 tables. Percentages reported in parentheses refer to the proportion of people in either AUD or SUD-treatment that have answered the variables in question (valid percent). P-values are not adjusted for multiple testing. Table 4: Trauma-related predictors of PTSD-status in ITQ sample, AUD and DUD samples Total No PTSD Subclinical PTSD PTSD Significance test ITQ sample (n=942) Trauma types Accidents 254 (26 %) 105 (23.5 %), (AR = -1.7) 39 (20.9 %), (AR = -1.8) 101 (32.9 %), (AR = 3.3) χ 2 (2)=11.62, p=.003 Violence 631 (67.1 %) 249 (55.7 %), (AR = -7.0) 130 (69.5 %), (AR = -0.8) 252 (82.1 %), (AR = 6.8) χ 2 (2)=57.97, p<.001 Sexual violence 264 (28.1 %) 86 (19.2 %), (AR = -5.7) 53 (28.3 %), (AR = -0.1) 125 (40.7 %), (AR = 6.0) χ 2 (2)=41.60, p<.001 Life-threatening illness 190 (20.2 %) 78 (17.4 %), (AR = -2.0) 38 (20.3 %), (AR = 0) 74 (24.1 %), (AR = 2.1) χ 2 (2)=5.00, p=.082 Unexpected death 381 (40.5 %) 158 (35.3 %), (AR = -3.1) 79 (42.2 %), (AR = 0.5) 144 (48.9 %), (AR = 2.8) χ 2 (2)=10.39, p=.006 Other events 496 (52.7 %) 233 (52.1 %), (AR = -0.3) 108 (57.8 %), (AR = 1.5) 155 (50.5 %), (AR = -0.9) χ 2 (2)=2.58, p=.276 N trauma-types (M, SD) 2.35 (1.30) 2.03 (1.20) 2.39 (1.26) 2.77 (1.33) F(2,470.31)=30.92, p<.001 Child/youth exposure (yes) 334 (35.5 %) 189 (42.3 %), (AR = 4.1) 63 (33.7 %), (AR = -0.6) 82 (26.7 %), (AR = -3.9) χ 2 (2)=19.61, p<.001 Adult exposure (yes) 377 (40.1 %) 178 (39.8 %), (AR = -0,1) 72 (38.5 %), (AR = -0.5) 127 (41.4 %), (AR = 0.6) χ 2 (2)=0.42. p=.811 Life-span exposure (yes) 230 (24.4 %) 80 (17.9 %), (AR = -4.4) 52 (27.8 %), (AR = 1.2) 98 (31.9 %), (AR = 3.7) χ 2 (2)=20.82, p<.001 AUD (n=281) Trauma types Accidents 60 (21.4 %) 29 (19.2 %), (AR = 0.9) 14 (25 %), (AR = -0.7) 17 (28.3 %), (AR =-0.4) χ 2 (2)=0.97. p=.614 Violence 158 (56.2 %) 73 (48.3 %), (AR = -2.9) 36 (64.3 %), (AR = 1.4) 49 (66.2 %), (AR =2.0) χ 2 (2)=8.29, p<.001 Sexual violence 59 (21 %) 25 (16.6 %), (AR = -2.0) 12 (21.4 %), (AR = 0.1) 22 (29.7 %), (AR = 2.1) χ 2 (2)=5.20, p=.074 Life-threatening illness 59 (21 %) 29 (19.2 %), (AR = -0.8) 13 (23.2 %), (AR = 0.5) 17 (23 %), (AR = 0.5) χ 2 (2)=0.63, p=.729 Unexpected death 99 (35.2 %) 49 (32.5 %), (AR = -1.1) 19 (33.9 %), (AR = -0.2) 31 (41.9 %), (AR = 1.4) χ 2 (2)=1.99, p=.369 Other events 167 (59.4 %) 86 (57 %), (AR = -0.9) 35 (62.5 %), (AR = 0.5) 46 (62.2 %), (AR = 0.6) χ 2 (2)=0.83, p=.660 N trauma-types (M, SD) 2.14 (1.24) 1.93 (1.21) 2.31 (1.16) 2.46 (1.29) F(2,278)=5.36, p=.005 Child/youth exposure (yes) 87 (31 %) 61 (40.4 %), (AR = 3.7) 11 (19.6 %). (AR = -2.0) 15 (20.3 %), (AR = -2.3) χ 2 (2)=13.60, p=.001 Adult exposure (yes) 129 (45.9 %) 62 (41.1 %), (AR = -1.8) 28 (50 %), (AR = 0.7) 39 (52.7 %), (AR = 1.4) χ 2 (2)=3.18, p=.204 Life-span exposure (yes) 65 (23.1 %) 28 (18.5 %), (AR = -2.0) 17 (30.4 %), (AR = 1.4) 20 (27 %), (AR = 0.9) χ 2 (2)=4.06, p=.131 DUD (N=661) Trauma types Accidents 185 (28 %) 76 (25.6 %). (AR = -1.2) 25 (19.1 %), (AR = -2.5) 84 (45.4 %), (AR = 3.4) χ 2 (2)=13.52, p=.001 Violence 474 (71.7 %) 177 (59.6 %), (AR = -6.2) 94 (71.8 %), (AR = 0) 203 (87.1 %), (AR = 6.5) χ 2 (2)=48.77, p<.001 Sexual violence 205 (31 %) 61 (20.5 %), (AR = -5.3) 41 (31.3 %), (AR = 0.1) 103 (44.2 %). (AR = 5.4) χ 2 (2)=31.19, p<.001 Life-threatening illness 131 (19.8 %) 49 (24.5 %), (AR = -1.9) 25 (19.1 %), (AR =-0.2) 57 (24.5 %), (AR = 2.2) χ 2 (2)=5.27, p=.072 Unexpected death 282 (42.7 %) 109 (36.7 %), (AR = -2.8) 60 (45.8 %), (AR = 0.8) 113 (48.5 %), (AR = 2.2) χ 2 (2)=8.09, p=.018 Other events 329 (29.8 %) 147 (49.5 %), (AR = -0.1) 73 (55.7 %), (AR = 1.5) 109 (46.8 %), (AR = -1.1) χ 2 (2)=2.70, p=.259 N trauma-types (M, SD) 2.43 (1.31) 2.08 (1.19) 2.43 (1.31) 2.87 (1.33) F(2,333.92)=24.95, p<.001 Child/youth exposure (yes) 248 (37.5 %) 129 (43.4 %), (AR = 2.8) 52 (39.7 %), (AR = 0.6) 67 (28.8 %), (AR = -3.4) χ 2 (2)=12.33, p=.002 Adult exposure (yes) 248 (37.5 %) 116 (39.1 %), (AR = 0.7) 44 (33.6 %), (AR = -1.0) 88 (37.8 %), (AR = 0.1) χ 2 (2)=1.17, p=.557 Life-span exposure (yes) 165 (25 %) 52 (17.5 %), (AR = -4.0) 35 (26.7 %), (AR = 0.5) 78 (33.5 %), (AR = 3.7) χ 2 (2)=18.04, p<.001 Note: Percentages and adjusted residuals (AR) reported refer to percentages of individuals in the diagnostic groups (no dx, subclinical and full PTSD). Percentages of PTSD caseness are valid percentages Table 5: Differences in participant characteristics across PTSD-diagnostic categories in ITQ sample, AUD and DUD samples ITQ sample (n=942) Total No PTSD (n=448, 47.6 %) Subclinical PTSD (n=187, 19.9 %) PTSD (n=307, 32.6 %) Significance test Gender (% female) 325 (34.5 %) 119 (26.6 %), (AR = -4.9) 73 (39 %), (AR = 1.5) 133 (43.3 %), (AR = 4.0) χ 2 (2)=24.77, p<.001 Age (in years, M, SD) 36 (13.95) 36.30 (13.84) 35.02 (12.07) 34.70 (11.70) F(2,472.72)=1.49, p=.227 Not in employment/education 636 (67.5 %) 280 (62.5 %), (AR = -3.1) 122 (65.2 %), (AR = -0.7) 234 (76.2 %), (AR = 4.0) χ 2 (2)=16.19, p<.001 Unstable living situation 129 (13.7 %) 47 (10.5 %), (AR = -2.7) 22 (11.8 %), (AR = -0.9) 60 (19.5 %), (AR = 3.6) χ 2 (2)=13.37, p<.001 Psychiatric diagnosis (M, SD) 0.85 (1.15) 0.68 (0.94) 1.12 (1.43) 1.33 (1.37) F(2,414.88) = 29.01, p<.001 Severe drug use (12 days or more within the past month) 272 (28.9 %) 116 (15.9 %), (AR = -1.9) 45 (24.1 %), (AR = -1.6) 111 (36.2 %), (AR = 3.4) χ 2 (2)=11.97, p=.003 Alcohol dependence (AUDIT score ≥15) 269 (28.6 %) 134 (30 %), (AR = -0.2) 59 (31.6 %), (AR = 0.5) 76 (24.8 %), (AR = -0.3) χ 2 (2)=0.30, p=.859 AUD (n=281) Gender (% female) 115 (40.9 %) 60 (39.7 %), (AR = -0.4) 24 (42.9 %), (AR = 0.3) 31 (41.9 %), (AR = 0.2) χ 2 (2)=0.204, p=0.903 Age (in years, M, SD) 44.02 (14.03) 45.82 (14.75) 42.37 (13.51) 41.47 (12.37) F(2,617)=0.49, p=0.611 Not in employment/education 180 (64.1 %) 94 (62.3 %), (AR = -0.7) 33 (58.9 %), (AR = -0.9) 53 (71.6 %), (AR = 1.6) χ 2 (2)=2.69, p=0.260 Unstable living situation 16 (13.9 %) >= 5, (AR =-1.9) >=5 (AR = -0.8) 9 (AR = 2.8) χ 2 (2)=7.83, p=0.20, Psychiatric diagnosis (M, SD) 0.86 (1.13) 0.74 (0.98) 1.21 (1.45) 0.85 (1.08) F(2,116.41)=2.57, p=0.069 Severe drug use (12 days or more within the past month) 10 (3.6 %) 6 (4 %), (AR=0.4) >5, (AR=-0.8) >5, (AR=0.3) χ 2 (2)=0-64, p=0.726 Alcohol dependence (AUDIT score ≥15) 166 (59.1 %) 85 (56.3 %), (AR=-1.8) 37 (66.1 %), (AR=1.2) 44 (59.5 %), (AR=1.0) χ 2 (2)=3.45, p=0.178 DUD (n=661) Gender (% female) 210 (31.8 %) 59 (19.9 %), (AR = -5.9) 49 (37.4 %), (AR=1.5) 102 (43.8 %), (AR = 4.9) χ 2 (2)=36.83, p<.001 Age (in years, M, SD) 32 (10.47) 31.55 (10.54) 31.84 (9.87) 32.68 (10.47) F(2,617)=0.49, p=0.611 Not in employment/education 456 (69 %) 186 (62.6 %), (AR = -3.2) 89 (67.9 %), (AR = -0.3) 181 (77.7 %), (AR = 3.6) χ 2 (2)=13.92, p<.001 Unstable living situation 113 (17.1 %) 42 (14.1 %), (AR = -1.8) 20 (15.3 %), (AR = -0.6) 51 (21.9 %), (AR = 2.4) χ 2 (2)=5.91, p=0.052 Psychiatric diagnosis (M, SD) 1.03 (1.27) 0.65 (0.92) 1.08 (1.42) 1.48 (1.42) F(2,297.39)=31.34, p<.001 Severe drug use (12 days or more within the past month) 262 (39.6 %) 110 (37 %), (AR = -1.2) 44 (33.6 %), (AR = -1.6) 108 (46.4 %), (AR = 2.6) χ 2 (2)=7.23, p=0.027 Alcohol dependence (AUDIT score ≥15) 103 (15.6 %) 49 (16.5 %), (AR = -0.1) 22 (16.8 %), (AR = 0) 32 (13.3 %), (AR = 0) χ 2 (2)=0.00, p=0.998 Note: Percentages and adjusted residuals (AR) reported refer to percentages of individuals in the diagnostic groups (no dx, subclinical and full PTSD). Percentages of PTSD caseness are valid percentages Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 07 Aug, 2025 Read the published version in BMC Psychiatry → Version 1 posted Editorial decision: Revision requested 23 Aug, 2024 Editor assigned by journal 19 Aug, 2024 Submission checks completed at journal 19 Aug, 2024 First submitted to journal 15 Aug, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4918218","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":344333877,"identity":"7df149ea-5eed-4088-8494-f052ca2496a8","order_by":0,"name":"Sidsel Karsberg","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAxElEQVRIiWNgGAWjYDACHhBhYwPjMhsQqSUtjXQth0nQIt9zgPFzRcL5PPkZCYyfeRisjQlqMTjbwCx5JuF2scGNBGZpHoZ0M8Ja+BnYGBt/3E7cIJHAANRy2IagFvl+oJaGhHOJ82ckMP8mSgvD2QaQlgOJDTcS2EC2EOGwMwebJRsSkosNzjxss5xjkE7Y+/I9yQc/NiTY5cm3Jx++8abC2rCBsMsYwWoSGAQSgQwiIhIOEhj4D5CgfBSMglEwCkYUAAAq6TbImkTEwgAAAABJRU5ErkJggg==","orcid":"","institution":"Aarhus University","correspondingAuthor":true,"prefix":"","firstName":"Sidsel","middleName":"","lastName":"Karsberg","suffix":""},{"id":344333878,"identity":"52e76999-f8d5-47f5-942d-2281bfd97be4","order_by":1,"name":"Lisa Najavits","email":"","orcid":"","institution":"University of Massachusetts Chan Medical School","correspondingAuthor":false,"prefix":"","firstName":"Lisa","middleName":"","lastName":"Najavits","suffix":""},{"id":344333879,"identity":"11ee645c-a46f-4308-9942-e48e9794f8ed","order_by":2,"name":"Mads Uffe Pedersen","email":"","orcid":"","institution":"Aarhus University","correspondingAuthor":false,"prefix":"","firstName":"Mads","middleName":"Uffe","lastName":"Pedersen","suffix":""},{"id":344333880,"identity":"cd2cc3af-62c2-4df0-94ea-6927d5ab6df3","order_by":3,"name":"Ask Elklit","email":"","orcid":"","institution":"University of Southern Denmark","correspondingAuthor":false,"prefix":"","firstName":"Ask","middleName":"","lastName":"Elklit","suffix":""},{"id":344333882,"identity":"3d2b07ee-cc55-435f-b8f6-b56ed674be43","order_by":4,"name":"Maria Louison Vang","email":"","orcid":"","institution":"University of Southern Denmark","correspondingAuthor":false,"prefix":"","firstName":"Maria","middleName":"Louison","lastName":"Vang","suffix":""}],"badges":[],"createdAt":"2024-08-15 08:56:17","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4918218/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4918218/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12888-025-07164-w","type":"published","date":"2025-08-07T15:57:02+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":66562331,"identity":"e3e7802c-e01a-406a-8841-18228fdff13d","added_by":"auto","created_at":"2024-10-14 10:22:26","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":270808,"visible":true,"origin":"","legend":"\u003cp\u003eFlow chart over participant recruitment\u003c/p\u003e","description":"","filename":"Figure1jpeg.png","url":"https://assets-eu.researchsquare.com/files/rs-4918218/v1/815d1989e7632477535dafa2.png"},{"id":66562332,"identity":"17b3bc5e-ce60-4b68-b6c1-e9edc17155a8","added_by":"auto","created_at":"2024-10-14 10:22:26","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":86445,"visible":true,"origin":"","legend":"\u003cp\u003eCompeting models 1 and 2 of the latent structure of the ITQ including standardized parameters\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNote\u003c/strong\u003e: All factor loadings and correlations were statistically significant at p\u0026lt;.001.\u003c/p\u003e","description":"","filename":"Figure2jpeg.png","url":"https://assets-eu.researchsquare.com/files/rs-4918218/v1/0bc0f549f799e5f12de68a2d.png"},{"id":88814172,"identity":"04666921-c535-43df-9e6b-f4c46ea815b9","added_by":"auto","created_at":"2025-08-11 16:07:56","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1577853,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4918218/v1/5d423004-7a5e-44f8-8587-38ff0d651bcb.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Trauma and ICD-11 PTSD in treatment for substance use disorders: A Danish multi-site study ","fulltext":[{"header":"Introduction","content":"\u003cp\u003eTraumatic experiences are well-known risk factors for substance use disorder (SUD)\u0026nbsp;(1), indeed rates of trauma exposure among adults with SUD are estimated to be as high as 95%\u0026nbsp;(2, 3), and among individuals who report traumatic exposure the prevalence of SUD is three times higher than for non-exposed individuals\u0026nbsp;(4). Child abuse is often identified as a prominent risk factor for substance use behaviors\u0026nbsp;(5-7).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSimilarly, the comorbidity between SUD and posttraumatic stress disorder (PTSD) after traumatic experiences is common\u0026nbsp;(4). In a systematic review including 42 studies, Debell and colleagues describe prevalence rates of comorbid alcohol use disorder (AUD) at 10%\u0026ndash;61% among those with PTSD, and comorbid rates of PTSD for those with AUD of 2\u0026ndash; 63%, with most studies reporting rates over 10%\u0026nbsp;(8). Comparatively high rates of PTSD also occur among individuals with drug use disorder (DUD)\u0026nbsp;(9). Preliminary evidence suggests that rates vary based on specific types of drug. For instance, among opiod use disorder (OUD) samples in opiod anagonist treatment, 41% have a lifetime history of PTSD and 33% have current PTSD\u0026nbsp;(10), representing the highest rate of PTSD among drug types\u0026nbsp;(11).\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003e\u003cem\u003eComorbid PTSD in SUD treatment \u0026nbsp;\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003eThere is a particularly high incidence of PTSD among individuals in SUD treatment, ranging from 20% to 52% (Roberts et al., 2022). PTSD-SUD comorbidity poses many challenges for SUD treatment. Individuals with PTSD-SUD present with a more severe and complex clinical profile than those with either disorder alone\u0026nbsp;(12, 13). A number of studies have indeed indicated that individuals with PTSD, have poorer outcomes of SUD treatment including worse treatment adherence and less improvement during treatment\u0026nbsp;(14-18).\u003c/p\u003e\n\u003cp\u003eDespite the substantial body of literature on the prevalence of trauma and PTSD among individuals in treatment for SUD, the majority of existing studies are from the United States\u0026nbsp;(9). Only one study has reported the co-occurrence in Scandinavian countries. A recent Norwegian study that included 106 individuals in SUD treatment reported prevalences of PTSD of 23.8% and 25.6% among recovered versus current users\u0026nbsp;(19). To this date, no studies have examined the prevalence of PTSD in treatment for SUD in Denmark. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMoreover, it is clear from the literature that the link between PTSD-SUD has mainly been examined without distinguishing AUD and DUD. A recent study suggests that individuals with DUD and PTSD are more likely to report greater impairment, to have worse social and psychiatric functioning, and to have received both addiction and mental health treatment compared to individuals with AUD and PTSD\u0026nbsp;(20). This implies that there may be important differences between Individuals with DUD and AUD and comorbid PTSD that are important to investigate.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMoreover, a small amount of current European studies are based on updated validated PTSD screening measures. \u0026nbsp;Overall, research using clinical interviews to assess the ICD-11 formulation of PTSD is still scarce. However, Hansen and colleagues\u0026nbsp;(21)\u0026nbsp;reported substantial agreement between the International Trauma Questionnaire (ITQ)\u0026nbsp;(22)\u0026nbsp;self-report and clinical interviews for PTSD in a sample of Danish chronic pain patients. Using the International Trauma Interview, a study of found fair to moderate agreement between self-report and clinical assessed PTSD among a Lithuanian adult trauma exposed sample\u0026nbsp;(23). Hence, surveys using validated self-report measures are an important first step in estimating probable prevalence of ICD-11 PTSD among people in treatment for substance use disorders in Denmark, although not sufficient to establish prevalence rates. Research has supported the validity of the Danish translation of the International Trauma Questionnaire for self-report of symptoms of ICD-11 PTSD and complex PTSD across 5 clinical samples (Vang et al., 2021). While substance abuse in the family is a known predictor of PTSD and complex PTSD in children\u0026nbsp;(24), there has yet to be a test of validity in addition to the prevalence of the ICD-11 formulation of PTSD and CPTSD among adult substance users in treatment\u0026nbsp;(25).\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003e\u003cem\u003eAims and hypotheses\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003eOur aim was to estimate the prevalence of ICD-11 PTSD among treatment-seeking substance users. As an initial step, we sought to test the validity of the ICD-11 PTSD in this sample. We also sought to explore demographic and trauma-related factors in SUD treatment. We had the following hypotheses:\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e1) The factor structure of ICD-11 PTSD among treatment seeking substance users would mirror the factor structure established in European clinical samples (Redican et al., 2022; Vang et al., 2021).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e2) Prevalence rates of PTSD would be higher than in the general population (Karsberg et al., 2024, Kessler et al., 2017; Vang et al., 2023), and comparable to those found in SUD treatment samples\u0026nbsp;(9). \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e3) The number and type of trauma would differ between individuals in treatment for DUD vs. AUD\u0026nbsp;(26).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e4) The level of PTSD-symptom severity and prevalence of PTSD would differ between individuals in treatment for DUD vs. AUD\u0026nbsp;(20).\u003c/p\u003e\n\u003cp\u003e5) Demographic characteristics as well as severity of drug use and alcohol use would differ between individuals with PTSD, individuals with subclinical PTSD, and individuals that did not live up to the criteria for a PTSD-diagnosis in treatment for AUD and DUD, with individuals with probable PTSD reporting higher levels of social vulnerability (i.e., unstable living situation, not in employment/education, psychiatric diagnosis) and substance use (1, 20).\u0026nbsp;\u003c/p\u003e"},{"header":"Material and methods","content":"\u003cp\u003e\u003cstrong\u003eParticipants and procedures\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was performed as a cross-sectional study. Data was collected from the 1st of November 2022 until the 29th of December 2023, corresponding to a total of 13 months across five sites. Figure 1 displays the data flow of the project. Data for the present study was retrieved from structured interviews with adults receiving treatment for DUD and AUD in five Danish treatment centers. The participating treatment centers were part of a larger treatment project aimed at testing two trauma focused treatment methods in treatment for substance use disorders. The treatment centers are placed in five different locations in Denmark and represent both rural and larger cities. One of the participating treatment centers (site 5) offered heroin-assisted treatment only, whereas the remaining sites (site 1 to 4) offered specialized outpatient treatment for SUD. Site one to four offered various types of treatment for SUD including pharmacological treatment, psychological treatment, family counselling, and psychoeducation. All the participating treatment centers are public and free of charge and operate in close collaboration with the social services and the healthcare system. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eA total of 1347 adult individuals were interviewed as part of an initial structured screening process for SUD treatment at the five participating treatments centers. Due to structural and organizational differences in treatment, the screening interview was fully implemented for treatment of DUD but to a lesser degree for treatment of AUD which meant that 69.5 % of the sample was enrolled in treatment for drug use disorders and 30.5% was enrolled in treatment for alcohol use disorders.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMeasures\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData for the present study was retrieved from AdultMap interviews\u0026nbsp;(27). AdultMap is a Danish structured screening interview consisting of 70 to 90 items (depending on responses) that is specifically developed for SUD treatment. Topics in the interview are living conditions, mental health and behavior, physical health, substance use, social network, adverse experiences, and function level. AdultMap is widely used for SUD treatment in Denmark and is implemented in 68 of the 98 municipalities in Denmark. The primary aim of the interview is to assess current barriers, needs, and resources to offer the most appropriate treatment possible. The questions used for the present study (i.e., demographic data, trauma exposure and substance use) are part of the currently used version of AdultMap. The trauma symptom items in the present study were implemented for the study period and in the five included treatment centers only. Interviews were conducted by treatment counselors at treatment enrollment.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eDemographic data\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e: \u003c/strong\u003eDemographic factors were gender (man vs. woman); age; treatment type (i.e., AUD or DUD); employment status (in school, employed, or in training or none of those); source of income (financially supported via full- or part-time occupation or educational support or governmental support, or early retirement, or no income or financial support by relatives); and living situation (stable or partly stable vs. unstable such as homeless, living in an institution, or in prison or detainment). Pre-existing psychiatric disorder was measured by self-reported previous diagnosis by a psychiatrist with any of the following disorders: depression, bipolar, anxiety, ADHD, personality disorder, OCD, autism spectrum disorder, schizophrenia, psychosis. The total number of previous diagnoses was summarized to create a total score. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eTrauma exposure\u003c/strong\u003e\u003c/em\u003e was assessed using six trauma categories (i.e., accident, sexual abuse or assault, physical or psychological violence, life-threatening illness, sudden accidental death, and other very stressful or violent experience). These categories were selected based on prior research indicating that they are the most common types of traumatic exposure previously identified in general populations\u0026nbsp;(28). Further, an almost identical event checklist was used in a Danish ITQ validation study\u0026nbsp;(21)\u0026nbsp;with the only difference being that a seventh item (i.e. natural disasters) was not included in the present study, as natural disasters are rare in Denmark. Each trauma type was scored dichotomously with 1=Directly exposed or witnessed and 0=Not directly exposed nor witnessed. For trauma exposure, age in years at trauma exposure was assessed (0 to 5 years, 6 to 12 years, 12 to 18 years, throughout the childhood, in adulthood only, or both in childhood and adulthood).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eICD-11 PTSD\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e: \u003c/strong\u003eICD-11 PTSD symptoms were assessed using a Danish translated and validated version (Hansen et al., 2021) of the International Trauma Questionnaire (ITQ) for PTSD symptoms\u0026nbsp;(22). The concurrent and discriminant validity of the ITQ\u0026nbsp;(29, 30)\u0026nbsp;along with the factorial validity of the ITQ across different countries and cultures, including Denmark, has been demonstrated in several studies\u0026nbsp;(21, 24, 31). The ITQ is a 12-item validated self-report measure developed for assessment of ICD-11 PTSD and Complex PTSD. Only the 6 items for ICD-11 PTSD were used for the current study. In the ITQ, the six PTSD items are accompanied by three items measuring associated functional impairments in the domains of social, occupation, and other important areas of life. Respondents are asked how much each PTSD symptom bothered them in the past month. Items are scored on a five-point Likert scale from 0 (\u0026lsquo;Not at all\u0026rsquo;) to 4 (\u0026lsquo;Extremely\u0026rsquo;). Symptoms are considered endorsed with scores of two (\u0026lsquo;Moderately\u0026rsquo;) or more. To meet criteria for PTSD, one symptom is required in each of the clusters for re-experiencing, avoidance, and sense of threat as well as a score of two or more on one of the three questions assessing associated functional impairment. We operationalized subclinical PTSD as either 1) one symptom in any two of the clusters for re-experiencing, avoidance and sense of threat and functional impairment is required, alternatively, 2) all symptom clusters must be endorsed without functional impairment. Cronbach\u0026rsquo;s alpha for the ITQ in the present study was 0.84 for the PTSD subscale.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eSubstance use severity\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAlcohol use severity was measured by a total score on the AUDIT, a 10-item screening tool developed by the World Health Organization\u0026nbsp;(32). The AUDIT assesses the amount and frequency of alcohol use (items 1-3), alcohol dependence (questions 4-6) and problems related to alcohol consumption (items 7-10). Each item is scored from 0 to 4, resulting in a total score range from 0 to 40. The current study relied on cut-off scores established by the WHO whereby scores from 8-14 indicate hazardous or harmful alcohol-use, and scores of 15 or more indicate the likely presence of moderate to severe alcohol use disorder, corresponding to alcohol-dependence\u0026nbsp;(33)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDrug use severity was measured by self-reported use of cannabis, amphetamines, cocaine, MDMA, opioids, and other substances within the past 30 days. Responses were coded into a composite score ranging from 0-100 (number of days cannabis + number of days amphetamines + number of days cocaine + number of days MDMA + number of days opioids + number of days sedatives + number of days with other substances) / 210 (i.e, the number of possible days with drug use) x 100. For example: number of days cannabis use (n=20) + number of days cocaine use (n=4): 24/210 x 100=11.4. Drug use is considered severe if the score is 12 or more. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eData analysis\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe data were cleaned as per figure 1, and then we tested each of the five hypotheses. \u003cem\u003eHypothesis 1\u003c/em\u003e. Two competing models of the latent structure of the ITQ was tested to examine whether the ITQ factor structure among substance users align with existing findings on the ICD-11 model of PTSD (Redican et al., 2022). The first model tested was a one factor model, where all items loaded onto a single latent factor representing PTSD-severity. This model has 18 free parameters and nine degrees of freedom. The second model was a correlated first order model representing the segregation of ITQ-items into three correlated latent factors corresponding to the ICD-11 formulation of PTSD consisting of re-experiencing, avoidance, and sense of threat. This model has 21 free parameters and six degrees of freedom and is statistically equivalent to a one factor second order model where factor correlations are replaced by factor loadings of re-experiencing, avoidance, and sense of threat onto a latent factor of PTSD. Figure 2 displays the competing models. The model fit was evaluated and compared using a standard range of model fit indices. The model with the lowest BIC is preferred, so long as other indicators support the fit of the model to the data. This includes CFI and TLI values above 0.90 or 0.95 for adequate or excellent fit, and RMSEA and SRMR values lower than 0.08 or 0.05 for adequate or close fit to the data, respectively. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eHypothesis 2\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e. \u003c/strong\u003eWe calculated descriptive statistics on each PTSD-symptom cluster and functional impairment, as well as the total rate of positive screens for PTSD and subclinical PTSD as described in Methods.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eHypothesis 3\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e.\u003c/strong\u003e Chi-square analyses were conducted to test the distribution of types of traumatic events across each treatment-type, and independent samples t-test was used to test differences in total number of traumatic events.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eHypothesis 4\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e.\u003c/strong\u003e Independent samples t-tests compared PTSD-severity between DUD and AUD treatment.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eHypothesis 5\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e.\u003c/strong\u003e A series of chi-square analyses and ANOVAs, first on the total sample and then on AUD and DUD samples separately, tested the significance of observed differences across probable PTSD-diagnostic status and demographic and trauma-related variables in each treatment group.\u0026nbsp;\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eParticipant characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn total, 1347 participants across five treatment sites were eligible and screened as part of their enrollment for AUD or DUD treatment. Of these, 61 participants did not want to disclose whether they had been exposed to a stressful experience, resulting in a total sample of N=1286 participants. Out of these, 942 participants responded to the ITQ.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe total sample (N=1286) was used as reference group for hypotheses 2 and 3 concerning the prevalence and distribution of trauma and PTSD in the total treatment-seeking group. A reference sample consisting of the participants who reported traumatic experiences as well as symptoms on the ITQ (n=942) was used to test hypotheses 1, 4 and 5 concerning PTSD and trauma-types specifically, as these necessitates participant responses on a selected number of measures that led to a more restricted sample size. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eInsert table 1 here and figure 1 here.\u003c/p\u003e\n\u003cp\u003eSee Figure 1 for participant flow in the project, and Table 1 for participant characteristics in the total sample. Most participants were men (72.7%). The sample had an average age of 36 years (range 13-82 years for both total sample and the ITQ sample). There were more participants in treatment for DUD compared to AUD, and the majority were not employed or in school. Regarding exposure to stressful experiences, 23.5 % of the total sample reported no exposure. Participants in the trauma-exposed group were significantly more likely to be in DUD treatment (adj. res. = 3.0, (\u0026chi;\u003csup\u003e2\u003c/sup\u003e (2)=13.23, p\u0026lt;.001). Similarly, participants reporting no exposure (adj. res = 6.9) were statistically significantly more likely to be in employment or education, whereas participants in the nondisclosure group were less likely to be in employment (adj. res. = -2.9, \u0026chi;2(2)=51.10, p\u0026lt;.001). Finally, men were overrepresented in the non-exposed group (adj. res. = 8.4), and women were overrepresented in the exposed (adj. res. = 6.8) and non-disclosure group (adj. res. = 2.4, \u0026chi;2 (2)=73.11, p\u0026lt;.001).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eHypothesis 1: Factor structure of ICD-11 PTSD among substance users \u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eSee Table 2 displays for the confirmatory factor analysis. Model 2 surpassed model 1 in all aspects of fit and was deemed the best fit with excellent fit statistics according to cut-offs on all indicators. Figure 2 displays the factor loadings and factor correlations of the best fitting models.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eHypothesis 2: Rates of probable ICD-11 PTSD \u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eTable 1 displays the prevalence rates of ICD-11 PTSD (23.9 %) and subclinical PTSD (14.5 %) among treatment-seeking substance users (N=1286). Rates of PTSD was 18% (n=74) for individuals in AUD treatment, and 26.6 % (n=233) for individuals in DUD treatment. Table 3 displays rates of PTSD and subclinical PTSD between AUD and DUD samples using the more restricted ITQ sample (N=941). There were significantly more PTSD cases among those that sought help for drugs compared to alcohol (\u0026chi;\u003csup\u003e2\u003c/sup\u003e(1)=6.73, p=.009, adj. res. = 2.7) and no statistically significant differences in rates of probable subclinical PTSD between drug use and alcohol use (\u0026chi;\u003csup\u003e2\u003c/sup\u003e(1)=0.00, p=1.00, adj. res. = 0).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eHypothesis 3 and 4: Trauma-types, number of traumas and PTSD-severity across SUD groups (ITQ sample, N=941)\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSee Table 3 displays for differences between AUD and DUD samples. Overall, women were overrepresented in AUD and men overrepresented in DUD. Participants in DUD treatment were on average more than 10 years younger than participants in AUD and were also more likely to have an unstable living situation compared to AUD-participants. Regarding trauma-exposure, the DUD group was more frequently exposed to all trauma types apart from diseases, where there were no differences, and other types of events that were more frequently reported by the AUD group. Total number of reported trauma-types was higher for the DUD sample. Similarly, PTSD severity was significantly higher for the DUD group.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 4 displays differences in trauma-related predictors across PTSD diagnostic categories for the ITQ sample (n=941) as well as the AUD and DUD samples. In treatment for DUD there were significant differences across participants with, no PTSD, subclinical PTSD and PTSD, with individuals in the PTSD group reporting more sexual violence, physical/psychological violence, accidents, and unexpected death of a loved one, a higher number of events, and higher rates of life-span exposure than the no-PTSD group and the subclinical PTSD group. For individuals in treatment for AUD there were differences across the PTSD diagnostic categories in relation to physical/psychological violence and number of trauma types with these being more prevalent in the PTSD group. For both AUD and DUD, the prevalence of childhood trauma (only) was less prevalent in the PTSD group compared to the no PTSD group.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eHypothesis 5: Demographic differences and differences in substance use severity across probable PTSD-diagnostic categories \u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eDifferences in gender, age, employment/education, living situation, psychiatric diagnosis as well as substance use across participants with no PTSD, probable subclinical PTSD, and probable PTSD are shown in Table 5 for the ITQ sample (n=942). The proportion of individuals who were women, were not in school/in employment, had unstable living situations, or who had a psychiatric disorder was significantly lower in the no PTSD group, higher in the subclinical PTSD group, and highest in the PTSD group. There were no significant age differences across the PTSD diagnostic groups. Differences in severity of drug use were significant: The proportion of participants with severe drug use was lowest in the no PTSD group (15.9 %), higher in the subclinical group (24.1%) and highest in the PTSD group (36.2%). No significant differences were seen in severity of alcohol use across PTSD diagnostic categories.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 5 also displays analyses for AUD and DUD separately. There were no statistically significant differences across diagnostic categories in treatment for AUD for neither demographic, substance-related or trauma-related factors. In DUD treatment, women were more likely to be represented in the probable subclinical and clinical PTSD groups, those with PTSD were more likely to be out of employment, more likely to have comorbid psychiatric disorders, and more likely to have a severe drug use compared to those in treatment for DUD that did not endorse the criteria for a probable PTSD-diagnosis.\u0026nbsp;\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe aim of the current study was to assess the validity and prevalence of ICD-11 PTSD in treatment for problematic substance use and study demographic, trauma-related, and substance-use related differences across probable PTSD-caseness in AUD and DUD. The study addresses gaps in the literature by identifying important characteristics for comorbid individuals in treatment for SUD. Using the new ICD-11 diagnostic criteria for PTSD, we offer a report on differences in prevalence of traumatic experiences, PTSD status, social functioning, and clinical profiles in treatment for AUD vs. DUD.\u003c/p\u003e \u003cp\u003eOur findings add to the growing body of evidence showing that severe trauma-related symptoms are highly prevalent in both treatment for AUD and DUD. In the overall sample approximately every fourth individual in treatment met the diagnostic criteria for probable PTSD. The additional proportion of individuals who reported PTSD symptoms corresponding to the criteria for probable subclinical PTSD, means that approximately 40% of the participants were moderately or severely affected by PTSD symptoms. The high prevalence of PTSD symptoms from the five Danish SUD treatment settings is in accordance with existing studies that find a strong causal and interactional relationship between PTSD and substance use (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e) and indicates that trauma and PTSD are also highly prevalent comorbidities among people in SUD treatment in Denmark.\u003c/p\u003e \u003cp\u003eIn line with our expectations, we found trauma-related differences between the AUD and DUD samples. Participants in treatment for DUD reported a significantly higher prevalence of exposure to accidents, physical/psychological violence, sexual violence, and unexpected death as well as number of trauma types than individuals in treatment for AUD. In addition, the severity of PTSD-symptoms and the prevalence of probable PTSD was higher for individuals in treatment for DUD. The higher prevalence of PTSD in treatment for DUD may be related to the specific types and severity of traumatic experiences reported. For example, it is well established that interpersonal and intentional trauma exposure such as sexual abuse and physical abuse are more damaging and are associated with a higher conditional risk of PTSD than non-interpersonal and unintentional trauma exposure (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). In addition, there is evidence that exposure to multiple types of trauma \u0026ndash;especially childhood trauma (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e) - places victims at risk for developing PTSD over and above the risk conferred by single types of exposure to traumatic stressors (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e). Therefore, the higher prevalence of interpersonal trauma and the higher number of trauma experiences reported in the DUD sample may imply the presence of more severe trauma profiles among individuals in treatment for DUD. The differences in trauma profiles between those in AUD vs. DUD treatment was further supported by the identified trauma-related differences between the three diagnostic categories (i.e., individuals with probable PTSD, individuals with probable subclinical PTSD, and individuals that did not live up to the criteria for a probable PTSD-diagnosis), where we found distinctive differences between traumatized individuals in treatment for AUD and DUD respectively. Of particular interest, the PTSD group in treatment for DUD was characterized by a comparably high prevalence of interpersonal violence experiences (i.e., physical/psychological violence, and sexual violence). For the PTSD group in AUD treatment the prevalence of sexual violence and physical /psychological violence was 29.7% and 66.2% and in DUD treatment it was 44.2% and 87.1%, respectively. Since the level of trauma severity and PTSD have been linked to a number of factors that are relevant for treatment outcome (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e), such as the therapeutical alliance (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e), treatment drop out (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e), craving (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e), and substance use severity (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e), differences in trauma profiles across AUD and DUD treatment could be important factors to consider for treatment planning and interventions.\u003c/p\u003e \u003cp\u003eIn addition to differences in trauma severity and PTSD, we identified several interesting sociodemographic differences (gender, employment status, living situation, psychiatric disorder, severity of substance use) across PTSD diagnostic categories in AUD and DUD treatment. Differences were only significant for the DUD sample. In treatment for DUD, the group that lived up to the criteria for probable PTSD was characterized by more women, less employment, less stable living situation, more psychiatric diagnoses, and a more severe use of illicit drugs compared to individuals that did not live up to the diagnostic criteria. In the AUD treatment sample, there were no significant differences for these factors between the three diagnostic categories. This could indicate that traumatized individuals in treatment for DUD are more socially and psychologically vulnerable than non-traumatized individuals in DUD treatment, whereas in AUD treatment, PTSD is not to the same degree associated with other social and psychological risk factors. Overall, the identified differences highlight that treating SUD as a unitary construct in relation to trauma and PTSD may obscure important between-group differences in terms of type of substance used that may be important for practice. Further research of the association between trauma symptomatology and treatment factors would be relevant for a more nuanced understanding of the differences in trauma profiles in treatment for AUD and DUD respectively.\u003c/p\u003e \u003cp\u003eResearch implications\u003c/p\u003e \u003cp\u003eThe identified differences in trauma exposure, PTSD symptomatology as well as sociodemographic factors in treatment for AUD and DUD underline the importance investigating traumatization in relation to treatment contexts and types of substance use. Further investigation into different profiles of vulnerability and traumatization in treatment for substance use disorders that assess different types of substance use could indeed be useful. Considering the high level of PTSD, future studies might include the sister diagnosis of Complex PTSD that in addition to PTSD covers disturbances of self-organization.\u003c/p\u003e \u003cp\u003eClinical implications\u003c/p\u003e \u003cp\u003eAs in many other countries, psychosocial treatment approaches for individuals with PTSD and SUD in Denmark have adhered to the sequential treatment model, in which SUD is treated first, and trauma work is deferred until a period of sustained abstinence has been achieved. However, given the high co-occurrence of PTSD and SUD, there have been important advances such as the development and use of integrated treatment models (treating both disorders at the same time, by the same counselor). In addition, there is a strong consensus that outpatient health care and social services need to deliver trauma-informed and trauma-specific care to reduce the effects of trauma, offer safe treatments, and avoid re-traumatization. In line with these changes in practice, the results of the current study highlight that PTSD is an important focus for SUD treatment in Denmark. Although trauma and PTSD is highly prevalent in both treatment for AUD and DUD, the results further suggest that a higher proportion of individuals in treatment for DUD have a background of interpersonal violence and higher risk of PTSD compared to treatment for AUD. Since interpersonal violence has been related to a number of factors relevant for treatment outcomes (\u003cspan additionalcitationids=\"CR38 CR39 CR40\" citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e), it could be relevant to specifically target these factors for this group. The identified vulnerability in the PTSD group in DUD treatment compared to the group with no PTSD, further supports the idea that PTSD should be a particular focus in treatment for DUD.\u003c/p\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eStrengths and Limitations\u003c/h2\u003e \u003cp\u003eThe strengths of the present study include a systematically collected and large sample size using a validated ICD-11 PTSD measure, and separate data from AUD and DUD treatment. The most important limitation is that the study sample consisting of patients from five treatment centers may not be representative for the SUD treatment population in Denmark. In addition, trauma experiences and PTSD symptoms may have been underreported. Both men and women tend to underreport abusive experiences (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e). In addition, many of the counsellors reported that there were many clients who were not able to recognize or feel the trauma-related symptoms in the ITQ due to active substance use, and that the identified prevalence of PTSD may therefore also be underreported. Despite these potential limitations, the proportion of participants reporting exposure to potentially traumatic events (72%) mirrors international estimates (Kessler et al., 2017), and rates of PTSD symptoms were higher than population surveys (Karsberg et al., 2024; Kessler et al., 2017; Vang et al., 2023). However, it is indeed possible that the reported prevalence of traumatic experiences would be even higher if the participants had filled out the questionnaire without the counsellor being present or if they had filled out the questionnaire later in the treatment course when they had obtained a closer relationship with the counsellor and had reduced their substance use.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eTraumatic experiences and PTSD were highly prevalent in a sample of over 1200 individuals seeking AUD or DUD treatment. The results indicate that individuals in DUD treatment may have a more severe trauma profile than individuals in AUD treatment. The results highlight the need for trauma-specific interventions in SUD treatment settings.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eEthics declarations\u003c/h2\u003e\n\u003ch2\u003eHuman Ethics and Consent to Participate declarations\u003c/h2\u003e\n\u003cp\u003eThe study was conducted in accordance with the Declaration of Helsinki and approved by the Danish Data Protection Agency and the Regional Committee for Medical and Health Research Ethics for the Central Denmark Region (#1-10-72-121-21). Informed consent for use in research and publications was retrieved from all participants.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThere are no competing interests to declare\u003c/p\u003e\n\u003ch2\u003eFunding\u003c/h2\u003e\n\u003cp\u003eThe study was funded by the Tryg Foundation (ID: 154804).\u003c/p\u003e\n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\n\u003cp\u003eStudy design, material preparation, data collection, and first draft of the manuscript were performed by SK. Data analysis, figures and tables were performed by MLV. All authors reviewed and commented on previous versions of the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003ch2\u003eData Availability\u003c/h2\u003e\n\u003cp\u003eData is available to other researchers at the aggregate level to avoid the sharing of data on individual patients.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eNajavits LM, Hyman SM, Ruglass LM, Hien DA, Read JP. Substance use disorder and trauma. APA handbook of trauma psychology: Foundations in knowledge, Vol 1. APA handbooks in psychology\u0026reg;. Washington, DC, US: American Psychological Association; 2017. p. 195-213.\u003c/li\u003e\n\u003cli\u003eGielen N, Havermans R, Tekelenburg M, Jansen A. Prevalence of post-traumatic stress disorder among patients with substance use disorder: it is higher than clinicians think it is. European Journal of Psychotraumatology. 2012;3(1):17734.\u003c/li\u003e\n\u003cli\u003eWu NS, Schairer LC, Dellor E, Grella C. 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Journal of Counseling \u0026amp; Development. 2020;98(1):29-40.\u003c/li\u003e\n\u003cli\u003eMitchell S, Mitchell R, Shannon C, Dorahy M, Hanna D. Effects of baseline psychological symptom severity on dropout from trauma-focused cognitive behavior therapy for posttraumatic stress disorder: A meta-analysis. Traumatology. 2023;29(2):112-24.\u003c/li\u003e\n\u003cli\u003eWieferink CEM, de Haan HA, Dijkstra BAG, Fledderus M, Kok T. Treatment of substance use disorders: Effects on patients with higher or lower levels of PTSD symptoms. Addictive Behaviors. 2017;74:122-6.\u003c/li\u003e\n\u003cli\u003eMergler M, Driessen M, Havemann-Reinecke U, Wedekind D, L\u0026uuml;decke C, Ohlmeier M, et al. Differential relationships of PTSD and childhood trauma with the course of substance use disorders. Journal of Substance Abuse Treatment. 2018;93:57-63.\u003c/li\u003e\n\u003cli\u003eMathews B, Pacella R, Dunne MP, Simunovic M, Marston C. Improving measurement of child abuse and neglect: A systematic review and analysis of national prevalence studies. PLoS One. 2020;15(1):e0227884.\u003c/li\u003e\n\u003cli\u003eCullen C. Method Matters: The Underreporting of Intimate Partner Violence. The World Bank Economic Review. 2022;37(1):49-73.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1: Sample characteristics\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.612244897959183%\" valign=\"top\"\u003e\n \u003cp\u003eTotal sample (N=1286)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.53061224489796%\" valign=\"top\"\u003e\n \u003cp\u003eITQ sample (n=942)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" valign=\"top\"\u003e\n \u003cp\u003eGender (% female)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.612244897959183%\" valign=\"top\"\u003e\n \u003cp\u003e364 (28.3 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.53061224489796%\" valign=\"top\"\u003e\n \u003cp\u003e325 (34.5 %)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" valign=\"top\"\u003e\n \u003cp\u003eAge (in years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.612244897959183%\" valign=\"top\"\u003e\n \u003cp\u003e36.49 (13.65)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.53061224489796%\" valign=\"top\"\u003e\n \u003cp\u003e35.53 (12.85)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" valign=\"top\"\u003e\n \u003cp\u003eEducation (yes)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.612244897959183%\" valign=\"top\"\u003e\n \u003cp\u003e242 (18.8 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.53061224489796%\" valign=\"top\"\u003e\n \u003cp\u003e168 (17.9 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" valign=\"top\"\u003e\n \u003cp\u003eIncome (employment/education)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.612244897959183%\" valign=\"top\"\u003e\n \u003cp\u003e485 (37.7 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.53061224489796%\" valign=\"top\"\u003e\n \u003cp\u003e306 (32.5 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" valign=\"top\"\u003e\n \u003cp\u003eLiving situation (stable)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.612244897959183%\" valign=\"top\"\u003e\n \u003cp\u003e1133 (88.1 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.53061224489796%\" valign=\"top\"\u003e\n \u003cp\u003e812 (86.3 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" valign=\"top\"\u003e\n \u003cp\u003eDrug-treatment\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.612244897959183%\" valign=\"top\"\u003e\n \u003cp\u003e876 (68.1 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.53061224489796%\" valign=\"top\"\u003e\n \u003cp\u003e660 (70.1 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" valign=\"top\"\u003e\n \u003cp\u003eAlcohol-treatment\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.612244897959183%\" valign=\"top\"\u003e\n \u003cp\u003e410 (31.9 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.53061224489796%\" valign=\"top\"\u003e\n \u003cp\u003e281 (29.9 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" valign=\"top\"\u003e\n \u003cp\u003ePsychiatric diagnoses (M, SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.612244897959183%\" valign=\"top\"\u003e\n \u003cp\u003e0.86 (1.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.53061224489796%\" valign=\"top\"\u003e\n \u003cp\u003e0.98 (1.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" valign=\"top\"\u003e\n \u003cp\u003eStressful experiences\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.612244897959183%\" valign=\"top\"\u003e\n \u003cp\u003e970 (75.4 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.53061224489796%\" valign=\"top\"\u003e\n \u003cp\u003e941 (100 %)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Accidents\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.612244897959183%\" valign=\"top\"\u003e\n \u003cp\u003e245 (19.1 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.53061224489796%\" valign=\"top\"\u003e\n \u003cp\u003e245 (26 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Violence\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.612244897959183%\" valign=\"top\"\u003e\n \u003cp\u003e633 (49.2 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.53061224489796%\" valign=\"top\"\u003e\n \u003cp\u003e631 (67.1 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Sexual violence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.612244897959183%\" valign=\"top\"\u003e\n \u003cp\u003e264 (20.5 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.53061224489796%\" valign=\"top\"\u003e\n \u003cp\u003e264 (28 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Life-threatening illness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.612244897959183%\" valign=\"top\"\u003e\n \u003cp\u003e190 (14.8 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.53061224489796%\" valign=\"top\"\u003e\n \u003cp\u003e190 (20.2 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Unexpected death\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.612244897959183%\" valign=\"top\"\u003e\n \u003cp\u003e381 (29.6 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.53061224489796%\" valign=\"top\"\u003e\n \u003cp\u003e381 (40.4 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Other events\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.612244897959183%\" valign=\"top\"\u003e\n \u003cp\u003e499 (38.8 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.53061224489796%\" valign=\"top\"\u003e\n \u003cp\u003e496 (52.7 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Nondisclosure\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.612244897959183%\" valign=\"top\"\u003e\n \u003cp\u003e24 (1.9 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.53061224489796%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" valign=\"top\"\u003e\n \u003cp\u003eN trauma-types (M, SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.612244897959183%\" valign=\"top\"\u003e\n \u003cp\u003e2.28 (1.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.53061224489796%\" valign=\"top\"\u003e\n \u003cp\u003e2.35 (1.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" valign=\"top\"\u003e\n \u003cp\u003eChild/youth exposure (yes)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.612244897959183%\" valign=\"top\"\u003e\n \u003cp\u003e337 (26.2 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.53061224489796%\" valign=\"top\"\u003e\n \u003cp\u003e334 (35.5 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" valign=\"top\"\u003e\n \u003cp\u003eAdult exposure (yes)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.612244897959183%\" valign=\"top\"\u003e\n \u003cp\u003e377 (29.3 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.53061224489796%\" valign=\"top\"\u003e\n \u003cp\u003e377 (40.1 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" valign=\"top\"\u003e\n \u003cp\u003eLife-span exposure (yes)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.612244897959183%\" valign=\"top\"\u003e\n \u003cp\u003e231 (18.0 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.53061224489796%\" valign=\"top\"\u003e\n \u003cp\u003e230 (24.4 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" valign=\"top\"\u003e\n \u003cp\u003eRe-experiencing (endorsed)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.612244897959183%\" valign=\"top\"\u003e\n \u003cp\u003e473 (36.8 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.53061224489796%\" valign=\"top\"\u003e\n \u003cp\u003e471 (50.2 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" valign=\"top\"\u003e\n \u003cp\u003eAvoidance (endorsed)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.612244897959183%\" valign=\"top\"\u003e\n \u003cp\u003e609 (47.4 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.53061224489796%\" valign=\"top\"\u003e\n \u003cp\u003e609 (64.7 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" valign=\"top\"\u003e\n \u003cp\u003eSense of threat (endorsed)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.612244897959183%\" valign=\"top\"\u003e\n \u003cp\u003e609 (47.4 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.53061224489796%\" valign=\"top\"\u003e\n \u003cp\u003e609 (64.6 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" valign=\"top\"\u003e\n \u003cp\u003eFunctional impairment (endorsed)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.612244897959183%\" valign=\"top\"\u003e\n \u003cp\u003e579 (45 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.53061224489796%\" valign=\"top\"\u003e\n \u003cp\u003e579 (61.5 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" valign=\"top\"\u003e\n \u003cp\u003eProbable PTSD (endorsed)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.612244897959183%\" valign=\"top\"\u003e\n \u003cp\u003e307 (23.9 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.53061224489796%\" valign=\"top\"\u003e\n \u003cp\u003e307 (32.6 %)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" valign=\"top\"\u003e\n \u003cp\u003eProbable subclinical PTSD (endorsed)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.612244897959183%\" valign=\"top\"\u003e\n \u003cp\u003e187 (14.5 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.53061224489796%\" valign=\"top\"\u003e\n \u003cp\u003e187 (19.9 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote: No percentages reported are corrected for missing data values. Missing data ranged between 0 % to 7 % for demographic information (age). Violence refers to both physical and sexual violence. Disease refers to life-threatening diseases. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 2:\u0026nbsp;Fit statistics for competing models of the factor structure of the ITQ\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"643\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.1993769470405%\" valign=\"top\"\u003e\n \u003cp\u003eModel\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.280373831775702%\" valign=\"top\"\u003e\n \u003cp\u003eꭕ\u003csup\u003e2\u0026nbsp;\u003c/sup\u003e(df)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.059190031152648%\" valign=\"top\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.461059190031152%\" valign=\"top\"\u003e\n \u003cp\u003eCFI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.878504672897197%\" valign=\"top\"\u003e\n \u003cp\u003eTLI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.1993769470405%\" valign=\"top\"\u003e\n \u003cp\u003eRMSEA\u0026nbsp;\u003cbr\u003e\u0026nbsp;(90 % CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.461059190031152%\" valign=\"top\"\u003e\n \u003cp\u003eSRMR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.461059190031152%\" valign=\"top\"\u003e\n \u003cp\u003eBIC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.1993769470405%\" valign=\"top\"\u003e\n \u003cp\u003eMLR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.280373831775702%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.059190031152648%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.461059190031152%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.878504672897197%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.1993769470405%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.461059190031152%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.461059190031152%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.1993769470405%\" valign=\"top\"\u003e\n \u003cp\u003eOne factor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.280373831775702%\" valign=\"top\"\u003e\n \u003cp\u003e159.23 (9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.059190031152648%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.461059190031152%\" valign=\"top\"\u003e\n \u003cp\u003e0.900\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.878504672897197%\" valign=\"top\"\u003e\n \u003cp\u003e0.833\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.1993769470405%\" valign=\"top\"\u003e\n \u003cp\u003e0.133 (0.115;0.152)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.461059190031152%\" valign=\"top\"\u003e\n \u003cp\u003e0.048\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.461059190031152%\" valign=\"top\"\u003e\n \u003cp\u003e18751.81\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.1993769470405%\" valign=\"top\"\u003e\n \u003cp\u003eThree factor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.280373831775702%\" valign=\"top\"\u003e\n \u003cp\u003e6.46\u0026nbsp;\u003cbr\u003e\u0026nbsp;(6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.059190031152648%\" valign=\"top\"\u003e\n \u003cp\u003e.374\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.461059190031152%\" valign=\"top\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.878504672897197%\" valign=\"top\"\u003e\n \u003cp\u003e0.999\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.1993769470405%\" valign=\"top\"\u003e\n \u003cp\u003e0.009 (0.000;0.044)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.461059190031152%\" valign=\"top\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.461059190031152%\" valign=\"top\"\u003e\n \u003cp\u003e18569.96\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote: The three-factor correlated model is statistically equivalent to a 2\u003csup\u003end\u003c/sup\u003e order one factor model. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 3:\u0026nbsp;Differences in participant characteristics across AUD and DUD\u0026nbsp;(Sample size variable depending on available data)\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.6530612244898%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\" valign=\"top\"\u003e\n \u003cp\u003eAUD (N=410,\u0026nbsp;\u003cbr\u003e\u0026nbsp;n=281 completed ITQ)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.428571428571427%\" valign=\"top\"\u003e\n \u003cp\u003eDUD (n=876,\u0026nbsp;\u003cbr\u003e\u0026nbsp;n=661 completed ITQ)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.428571428571427%\" valign=\"top\"\u003e\n \u003cp\u003eSignificance test\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.6530612244898%\" valign=\"top\"\u003e\n \u003cp\u003eGender (% female)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\" valign=\"top\"\u003e\n \u003cp\u003e135 (32.9 %), AR = 2.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.428571428571427%\" valign=\"top\"\u003e\n \u003cp\u003e229 (26.1 %), AR = -2.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.428571428571427%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e(1)=6.34, \u003cstrong\u003ep=.014\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.6530612244898%\" valign=\"top\"\u003e\n \u003cp\u003eAge (in years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\" valign=\"top\"\u003e\n \u003cp\u003e45.74 (14.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.428571428571427%\" valign=\"top\"\u003e\n \u003cp\u003e32.25 (11.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.428571428571427%\" valign=\"top\"\u003e\n \u003cp\u003et(613.45)=16.01, \u003cstrong\u003ep\u0026lt;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.6530612244898%\" valign=\"top\"\u003e\n \u003cp\u003eEducation (yes)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\" valign=\"top\"\u003e\n \u003cp\u003e52 (12.7 %), AR = -3.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.428571428571427%\" valign=\"top\"\u003e\n \u003cp\u003e190 (21.7 %), AR = 3.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.428571428571427%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e(1)=14.25, \u003cstrong\u003ep\u0026lt;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.6530612244898%\" valign=\"top\"\u003e\n \u003cp\u003eIncome (employment/education)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\" valign=\"top\"\u003e\n \u003cp\u003e172 (42 %), AR = 2.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.428571428571427%\" valign=\"top\"\u003e\n \u003cp\u003e313 (35.7 %), AR = -2.1\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.428571428571427%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e(1)=4.34, \u003cstrong\u003ep=.037\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.6530612244898%\" valign=\"top\"\u003e\n \u003cp\u003eLiving situation (stable)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\" valign=\"top\"\u003e\n \u003cp\u003e22 (5.4 %), AR = -4.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.428571428571427%\" valign=\"top\"\u003e\n \u003cp\u003e131 (15.0 %), AR = 4.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.428571428571427%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e(1)=23.59, \u003cstrong\u003ep\u0026lt;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.6530612244898%\" valign=\"top\"\u003e\n \u003cp\u003ePsychiatric diagnoses (M, SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\" valign=\"top\"\u003e\n \u003cp\u003e0.73 (1.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.428571428571427%\" valign=\"top\"\u003e\n \u003cp\u003e0.91 (1.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.428571428571427%\" valign=\"top\"\u003e\n \u003cp\u003et(940.03)=-2.48, \u003cstrong\u003ep=0.019\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.6530612244898%\" valign=\"top\"\u003e\n \u003cp\u003eStressful experiences\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\" valign=\"top\"\u003e\n \u003cp\u003e284 (69.3 %), AR = -3.0\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.428571428571427%\" valign=\"top\"\u003e\n \u003cp\u003e686 (74.5 %)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.428571428571427%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e(1)=12.91, \u003cstrong\u003ep=.002\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.6530612244898%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Accidents\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\" valign=\"top\"\u003e\n \u003cp\u003e60 (21.1 %), AR = -1.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.428571428571427%\" valign=\"top\"\u003e\n \u003cp\u003e185 (27 %), AR = 1.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.428571428571427%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e(1)=3.33, p=.068\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.6530612244898%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Violence\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\" valign=\"top\"\u003e\n \u003cp\u003e158 (55.6 %), AR = -4.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.428571428571427%\" valign=\"top\"\u003e\n \u003cp\u003e475 (89.2 %), AR = 4.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.428571428571427%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e(1)=15.81, \u003cstrong\u003ep\u0026lt;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.6530612244898%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Sexual violence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\" valign=\"top\"\u003e\n \u003cp\u003e59 (20.8 %), AR = -2.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.428571428571427%\" valign=\"top\"\u003e\n \u003cp\u003e205 (29.9 %), AR = 2.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.428571428571427%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e(1)=7.96, \u003cstrong\u003ep=.005\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.6530612244898%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; life-threatening illness\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\" valign=\"top\"\u003e\n \u003cp\u003e59 (20.8 %), AR = 0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.428571428571427%\" valign=\"top\"\u003e\n \u003cp\u003e131 (19.1 %), AR = -0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.428571428571427%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e(1)=0.26, p=.610\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.6530612244898%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Unexpected death\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\" valign=\"top\"\u003e\n \u003cp\u003e99 (34.9 %), AR = -1.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.428571428571427%\" valign=\"top\"\u003e\n \u003cp\u003e282 (41.1 %), AR = 1.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.428571428571427%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e(1)=3.03, p=.082\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.6530612244898%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Other events\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\" valign=\"top\"\u003e\n \u003cp\u003e167 (58.8 %), AR = 3.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.428571428571427%\" valign=\"top\"\u003e\n \u003cp\u003e329 (48.4 %), AR = -3.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.428571428571427%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e(1)=8.30, \u003cstrong\u003ep=.004\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.6530612244898%\" valign=\"top\"\u003e\n \u003cp\u003eN trauma-types (M, SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\" valign=\"top\"\u003e\n \u003cp\u003e2.12 (1.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.428571428571427%\" valign=\"top\"\u003e\n \u003cp\u003e2.35 (1.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.428571428571427%\" valign=\"top\"\u003e\n \u003cp\u003et(571.02)=-2.51, \u003cstrong\u003ep=.012\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.6530612244898%\" valign=\"top\"\u003e\n \u003cp\u003eChild/youth exposure (yes)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\" valign=\"top\"\u003e\n \u003cp\u003e87 (31 %), AR = -2.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.428571428571427%\" valign=\"top\"\u003e\n \u003cp\u003e250 (37.7 %), AR = 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.428571428571427%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e(2)=6.39, \u003cstrong\u003ep=.041\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.55844155844156%\" valign=\"top\"\u003e\n \u003cp\u003eAdult exposure (yes)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.16883116883117%\" valign=\"top\"\u003e\n \u003cp\u003e129 (45.9 %), AR = 2.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e248 (37.3 %), AR =-2.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.55844155844156%\" valign=\"top\"\u003e\n \u003cp\u003eLife-span exposure (yes)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.16883116883117%\" valign=\"top\"\u003e\n \u003cp\u003e65 (23.1 %), AR = -0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e165 (25 %), AR = 0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.6530612244898%\" valign=\"top\"\u003e\n \u003cp\u003eRe-experiencing (endorsed)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\" valign=\"top\"\u003e\n \u003cp\u003e125 (44.5 %), AR = -2.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.428571428571427%\" valign=\"top\"\u003e\n \u003cp\u003e348 (52.6 %), AR = 2.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.428571428571427%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e(1)=4.94, \u003cstrong\u003ep=.026\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.6530612244898%\" valign=\"top\"\u003e\n \u003cp\u003eAvoidance (endorsed)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\" valign=\"top\"\u003e\n \u003cp\u003e162 (57.7 %), AR =-2.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.428571428571427%\" valign=\"top\"\u003e\n \u003cp\u003e447 (67.7 %), AR = 2.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.428571428571427%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e(1)=8.15, \u003cstrong\u003ep=.004\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.6530612244898%\" valign=\"top\"\u003e\n \u003cp\u003eSense of threat (endorsed)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\" valign=\"top\"\u003e\n \u003cp\u003e169 (60.1 %), AR = -1.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.428571428571427%\" valign=\"top\"\u003e\n \u003cp\u003e439 (66.5 %), AR = 1.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.428571428571427%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e(1)=3.29, p=.070\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.6530612244898%\" valign=\"top\"\u003e\n \u003cp\u003eFunctional impairment (endorsed)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\" valign=\"top\"\u003e\n \u003cp\u003e161 (57.3 %), AR = -1.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.428571428571427%\" valign=\"top\"\u003e\n \u003cp\u003e418 (63.3 %), AR = 1.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.428571428571427%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e(1)=2.79, p=.095\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.6530612244898%\" valign=\"top\"\u003e\n \u003cp\u003eProbable PTSD (endorsed)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\" valign=\"top\"\u003e\n \u003cp\u003e74 (26.3 %), AR = -2.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.428571428571427%\" valign=\"top\"\u003e\n \u003cp\u003e233 (35.3 %), AR = 2.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.428571428571427%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e(2)=8.14, \u003cstrong\u003ep=.017\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.55844155844156%\" valign=\"top\"\u003e\n \u003cp\u003eProbable subclinical PTSD (endorsed)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.16883116883117%\" valign=\"top\"\u003e\n \u003cp\u003e56 (19.9 %), AR = 0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e131 (19.8 %), AR = 0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.6530612244898%\" valign=\"top\"\u003e\n \u003cp\u003ePTSD severity (M sum, SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\" valign=\"top\"\u003e\n \u003cp\u003e8.48 (6.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.428571428571427%\" valign=\"top\"\u003e\n \u003cp\u003e10.49 (6.79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.428571428571427%\" valign=\"top\"\u003e\n \u003cp\u003et(582.91)=-4.46, \u003cstrong\u003ep\u0026lt;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote: Chi-square tests are conducted using continuity correction for 2x2 tables. Percentages reported in parentheses refer to the proportion of people in either AUD or SUD-treatment that have answered the variables in question (valid percent). P-values are not adjusted for multiple testing. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eTable 4: Trauma-related predictors of PTSD-status in ITQ sample, AUD and DUD samples\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"105%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.587628865979383%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" valign=\"top\"\u003e\n \u003cp\u003eTotal\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003eNo PTSD\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003eSubclinical PTSD\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003ePTSD\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.649484536082475%\" valign=\"top\"\u003e\n \u003cp\u003eSignificance test\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.587628865979383%\" valign=\"top\"\u003e\n \u003cp\u003eITQ sample (n=942)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.649484536082475%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.587628865979383%\" valign=\"top\"\u003e\n \u003cp\u003eTrauma types\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.649484536082475%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.587628865979383%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Accidents\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" valign=\"top\"\u003e\n \u003cp\u003e254 (26 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e105 (23.5 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = -1.7)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e39 (20.9 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = -1.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e101 (32.9 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = 3.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.649484536082475%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e(2)=11.62, \u003cstrong\u003ep=.003\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.587628865979383%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Violence\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" valign=\"top\"\u003e\n \u003cp\u003e631 (67.1 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e249 (55.7 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = -7.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e130 (69.5 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = -0.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e252 (82.1 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = 6.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.649484536082475%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e(2)=57.97, \u003cstrong\u003ep\u0026lt;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.587628865979383%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Sexual violence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" valign=\"top\"\u003e\n \u003cp\u003e264 (28.1 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e86 (19.2 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = -5.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e53 (28.3 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = -0.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e125 (40.7 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = 6.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.649484536082475%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e(2)=41.60, \u003cstrong\u003ep\u0026lt;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.587628865979383%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Life-threatening illness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" valign=\"top\"\u003e\n \u003cp\u003e190 (20.2 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e78 (17.4 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = -2.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e38 (20.3 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = 0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e74 (24.1 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = 2.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.649484536082475%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e(2)=5.00, p=.082\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.587628865979383%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Unexpected death\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" valign=\"top\"\u003e\n \u003cp\u003e381 (40.5 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e158 (35.3 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = -3.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e79 (42.2 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = 0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e144 (48.9 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = 2.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.649484536082475%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e(2)=10.39, \u003cstrong\u003ep=.006\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.587628865979383%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Other events\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" valign=\"top\"\u003e\n \u003cp\u003e496 (52.7 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e233 (52.1 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = -0.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e108 (57.8 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = 1.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e155 (50.5 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = -0.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.649484536082475%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e(2)=2.58, p=.276\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.587628865979383%\" valign=\"top\"\u003e\n \u003cp\u003eN trauma-types (M, SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" valign=\"top\"\u003e\n \u003cp\u003e2.35 (1.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e2.03 (1.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e2.39 (1.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e2.77 (1.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.649484536082475%\" valign=\"top\"\u003e\n \u003cp\u003eF(2,470.31)=30.92, \u003cstrong\u003ep\u0026lt;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.587628865979383%\" valign=\"top\"\u003e\n \u003cp\u003eChild/youth exposure (yes)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" valign=\"top\"\u003e\n \u003cp\u003e334 (35.5 %)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e189 (42.3 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = 4.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e63 (33.7 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = -0.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e82 (26.7 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = -3.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.649484536082475%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e(2)=19.61, \u003cstrong\u003ep\u0026lt;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.587628865979383%\" valign=\"top\"\u003e\n \u003cp\u003eAdult exposure (yes)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" valign=\"top\"\u003e\n \u003cp\u003e377 (40.1 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e178 (39.8 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = -0,1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e72 (38.5 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = -0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e127 (41.4 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = 0.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.649484536082475%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e(2)=0.42. p=.811\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.587628865979383%\" valign=\"top\"\u003e\n \u003cp\u003eLife-span exposure (yes)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" valign=\"top\"\u003e\n \u003cp\u003e230 (24.4 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e80 (17.9 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = -4.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e52 (27.8 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = 1.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e98 (31.9 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = 3.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.649484536082475%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e(2)=20.82, \u003cstrong\u003ep\u0026lt;.001\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.587628865979383%\" valign=\"top\"\u003e\n \u003cp\u003eAUD (n=281)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.649484536082475%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.587628865979383%\" valign=\"top\"\u003e\n \u003cp\u003eTrauma types\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.649484536082475%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.587628865979383%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Accidents\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" valign=\"top\"\u003e\n \u003cp\u003e60 (21.4 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e29 (19.2 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = 0.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e14 (25 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = -0.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e17 (28.3 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR =-0.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.649484536082475%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e(2)=0.97. p=.614\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.587628865979383%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Violence\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" valign=\"top\"\u003e\n \u003cp\u003e158 (56.2 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e73 (48.3 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = -2.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e36 (64.3 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = 1.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e49 (66.2 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR =2.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.649484536082475%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e(2)=8.29, \u003cstrong\u003ep\u0026lt;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.587628865979383%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Sexual violence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" valign=\"top\"\u003e\n \u003cp\u003e59 (21 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e25 (16.6 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = -2.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e12 (21.4 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = 0.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e22 (29.7 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = 2.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.649484536082475%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e(2)=5.20, p=.074\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.587628865979383%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Life-threatening illness\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" valign=\"top\"\u003e\n \u003cp\u003e59 (21 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e29 (19.2 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = -0.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e13 (23.2 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = 0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e17 (23 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = 0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.649484536082475%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e(2)=0.63, p=.729\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.587628865979383%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Unexpected death\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" valign=\"top\"\u003e\n \u003cp\u003e99 (35.2 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e49 (32.5 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = -1.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e19 (33.9 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = -0.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e31 (41.9 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = 1.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.649484536082475%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e(2)=1.99, p=.369\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.587628865979383%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Other events\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" valign=\"top\"\u003e\n \u003cp\u003e167 (59.4 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e86 (57 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = -0.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e35 (62.5 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = 0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e46 (62.2 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = 0.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.649484536082475%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e(2)=0.83, p=.660\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.587628865979383%\" valign=\"top\"\u003e\n \u003cp\u003eN trauma-types (M, SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" valign=\"top\"\u003e\n \u003cp\u003e2.14 (1.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e1.93 (1.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e2.31 (1.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e2.46 (1.29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.649484536082475%\" valign=\"top\"\u003e\n \u003cp\u003eF(2,278)=5.36, \u003cstrong\u003ep=.005\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.587628865979383%\" valign=\"top\"\u003e\n \u003cp\u003eChild/youth exposure (yes)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" valign=\"top\"\u003e\n \u003cp\u003e87 (31 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e61 (40.4 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = 3.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e11 (19.6 %).\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = -2.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e15 (20.3 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = -2.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.649484536082475%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e(2)=13.60, \u003cstrong\u003ep=.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.587628865979383%\" valign=\"top\"\u003e\n \u003cp\u003eAdult exposure (yes)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" valign=\"top\"\u003e\n \u003cp\u003e129 (45.9 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e62 (41.1 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = -1.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e28 (50 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = 0.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e39 (52.7 %),\u003cbr\u003e\u0026nbsp;(AR = 1.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.649484536082475%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e(2)=3.18, p=.204\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.587628865979383%\" valign=\"top\"\u003e\n \u003cp\u003eLife-span exposure (yes)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" valign=\"top\"\u003e\n \u003cp\u003e65 (23.1 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e28 (18.5 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = -2.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e17 (30.4 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = 1.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e20 (27 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = 0.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.649484536082475%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e(2)=4.06, p=.131\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.587628865979383%\" valign=\"top\"\u003e\n \u003cp\u003eDUD (N=661)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.649484536082475%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.587628865979383%\" valign=\"top\"\u003e\n \u003cp\u003eTrauma types\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.649484536082475%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.587628865979383%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Accidents\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" valign=\"top\"\u003e\n \u003cp\u003e185 (28 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e76 (25.6 %).\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = -1.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e25 (19.1 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = -2.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e84 (45.4 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = 3.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.649484536082475%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e(2)=13.52, \u003cstrong\u003ep=.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.587628865979383%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Violence\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" valign=\"top\"\u003e\n \u003cp\u003e474 (71.7 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e177 (59.6 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = -6.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e94 (71.8 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = 0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e203 (87.1 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = 6.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.649484536082475%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e(2)=48.77, \u003cstrong\u003ep\u0026lt;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.587628865979383%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Sexual violence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" valign=\"top\"\u003e\n \u003cp\u003e205 (31 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e61 (20.5 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = -5.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e41 (31.3 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = 0.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e103 (44.2 %).\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = 5.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.649484536082475%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e(2)=31.19, \u003cstrong\u003ep\u0026lt;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.587628865979383%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Life-threatening illness\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" valign=\"top\"\u003e\n \u003cp\u003e131 (19.8 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e49 (24.5 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = -1.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e25 (19.1 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR =-0.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e57 (24.5 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = 2.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.649484536082475%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e(2)=5.27, p=.072\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.587628865979383%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Unexpected death\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" valign=\"top\"\u003e\n \u003cp\u003e282 (42.7 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e109 (36.7 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = -2.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e60 (45.8 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = 0.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e113 (48.5 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = 2.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.649484536082475%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e(2)=8.09, \u003cstrong\u003ep=.018\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.587628865979383%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Other events\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" valign=\"top\"\u003e\n \u003cp\u003e329 (29.8 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e147 (49.5 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = -0.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e73 (55.7 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = 1.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e109 (46.8 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = -1.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.649484536082475%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e(2)=2.70, p=.259\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.587628865979383%\" valign=\"top\"\u003e\n \u003cp\u003eN trauma-types (M, SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" valign=\"top\"\u003e\n \u003cp\u003e2.43 (1.31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e2.08 (1.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;2.43 (1.31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e2.87 (1.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.649484536082475%\" valign=\"top\"\u003e\n \u003cp\u003eF(2,333.92)=24.95, \u003cstrong\u003ep\u0026lt;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.587628865979383%\" valign=\"top\"\u003e\n \u003cp\u003eChild/youth exposure (yes)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" valign=\"top\"\u003e\n \u003cp\u003e248 (37.5 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e129 (43.4 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = 2.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e52 (39.7 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = 0.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e67 (28.8 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = -3.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.649484536082475%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e(2)=12.33, \u003cstrong\u003ep=.002\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.587628865979383%\" valign=\"top\"\u003e\n \u003cp\u003eAdult exposure (yes)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" valign=\"top\"\u003e\n \u003cp\u003e248 (37.5 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e116 (39.1 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = 0.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e44 (33.6 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = -1.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e88 (37.8 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = 0.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.649484536082475%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e(2)=1.17, p=.557\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.587628865979383%\" valign=\"top\"\u003e\n \u003cp\u003eLife-span exposure (yes)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" valign=\"top\"\u003e\n \u003cp\u003e165 (25 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e52 (17.5 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = -4.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e35 (26.7 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = 0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003e78 (33.5 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = 3.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.649484536082475%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e(2)=18.04, \u003cstrong\u003ep\u0026lt;.001\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;Note: Percentages and adjusted residuals (AR) reported refer to percentages of individuals in the diagnostic groups (no dx, subclinical and full PTSD). Percentages of PTSD caseness are valid percentages\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 5: Differences in participant characteristics across PTSD-diagnostic categories in ITQ sample, AUD and DUD samples\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"105%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.46938775510204%\" valign=\"top\"\u003e\n \u003cp\u003eITQ sample (n=942)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" valign=\"top\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.26530612244898%\" valign=\"top\"\u003e\n \u003cp\u003eNo PTSD\u003c/p\u003e\n \u003cp\u003e(n=448, 47.6 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eSubclinical PTSD\u003c/p\u003e\n \u003cp\u003e(n=187, 19.9 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003ePTSD\u003c/p\u003e\n \u003cp\u003e(n=307, 32.6 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\" valign=\"top\"\u003e\n \u003cp\u003eSignificance test\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.46938775510204%\" valign=\"top\"\u003e\n \u003cp\u003eGender (% female)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" valign=\"top\"\u003e\n \u003cp\u003e325 (34.5 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.26530612244898%\" valign=\"top\"\u003e\n \u003cp\u003e119 (26.6 %),\u003c/p\u003e\n \u003cp\u003e(AR = -4.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e73 (39 %),\u003cbr\u003e\u0026nbsp;(AR = 1.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e133 (43.3 %),\u003cbr\u003e\u0026nbsp;(AR = 4.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e (2)=24.77, \u003cstrong\u003ep\u0026lt;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.46938775510204%\" valign=\"top\"\u003e\n \u003cp\u003eAge (in years, M, SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" valign=\"top\"\u003e\n \u003cp\u003e36 (13.95)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.26530612244898%\" valign=\"top\"\u003e\n \u003cp\u003e36.30 (13.84)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e35.02 (12.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e34.70 (11.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\" valign=\"top\"\u003e\n \u003cp\u003eF(2,472.72)=1.49, p=.227\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.46938775510204%\" valign=\"top\"\u003e\n \u003cp\u003eNot in employment/education\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" valign=\"top\"\u003e\n \u003cp\u003e636 (67.5 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.26530612244898%\" valign=\"top\"\u003e\n \u003cp\u003e280 (62.5 %),\u003c/p\u003e\n \u003cp\u003e(AR = -3.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e122 (65.2 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = -0.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e234 (76.2 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = 4.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e (2)=16.19, \u003cstrong\u003ep\u0026lt;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.46938775510204%\" valign=\"top\"\u003e\n \u003cp\u003eUnstable living situation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" valign=\"top\"\u003e\n \u003cp\u003e129 (13.7 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.26530612244898%\" valign=\"top\"\u003e\n \u003cp\u003e47 (10.5 %),\u003c/p\u003e\n \u003cp\u003e(AR = -2.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e22 (11.8 %),\u003c/p\u003e\n \u003cp\u003e(AR = -0.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e60 (19.5 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = 3.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e(2)=13.37, \u003cstrong\u003ep\u0026lt;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.46938775510204%\" valign=\"top\"\u003e\n \u003cp\u003ePsychiatric diagnosis (M, SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" valign=\"top\"\u003e\n \u003cp\u003e0.85 (1.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.26530612244898%\" valign=\"top\"\u003e\n \u003cp\u003e0.68 (0.94)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e1.12 (1.43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e1.33 (1.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\" valign=\"top\"\u003e\n \u003cp\u003eF(2,414.88) = 29.01, \u003cstrong\u003ep\u0026lt;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.46938775510204%\" valign=\"top\"\u003e\n \u003cp\u003eSevere drug use (12 days or more within the past month)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" valign=\"top\"\u003e\n \u003cp\u003e272 (28.9 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.26530612244898%\" valign=\"top\"\u003e\n \u003cp\u003e116 (15.9 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = -1.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e45 (24.1 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = -1.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e111 (36.2 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = 3.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e (2)=11.97, \u003cstrong\u003ep=.003\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.46938775510204%\" valign=\"top\"\u003e\n \u003cp\u003eAlcohol dependence\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(AUDIT score \u0026ge;15)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" valign=\"top\"\u003e\n \u003cp\u003e269 (28.6 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.26530612244898%\" valign=\"top\"\u003e\n \u003cp\u003e134 (30 %),\u003cbr\u003e\u0026nbsp;(AR = -0.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e59 (31.6 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = 0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e76 (24.8 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = -0.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e (2)=0.30, p=.859\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp; AUD (n=281)\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"105%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.46938775510204%\" valign=\"top\"\u003e\n \u003cp\u003eGender (% female)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" valign=\"top\"\u003e\n \u003cp\u003e115 (40.9 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.26530612244898%\" valign=\"top\"\u003e\n \u003cp\u003e60 (39.7 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = -0.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e24 (42.9 %),\u003cbr\u003e\u0026nbsp;(AR = 0.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e31 (41.9 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = 0.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e(2)=0.204, p=0.903\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.46938775510204%\" valign=\"top\"\u003e\n \u003cp\u003eAge (in years, M, SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" valign=\"top\"\u003e\n \u003cp\u003e44.02 (14.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.26530612244898%\" valign=\"top\"\u003e\n \u003cp\u003e45.82 (14.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e42.37 (13.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e41.47 (12.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\" valign=\"top\"\u003e\n \u003cp\u003eF(2,617)=0.49, p=0.611\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.46938775510204%\" valign=\"top\"\u003e\n \u003cp\u003eNot in employment/education\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" valign=\"top\"\u003e\n \u003cp\u003e180 (64.1 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.26530612244898%\" valign=\"top\"\u003e\n \u003cp\u003e94 (62.3 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = -0.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e33 (58.9 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = -0.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e53 (71.6 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = 1.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e(2)=2.69, p=0.260\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.46938775510204%\" valign=\"top\"\u003e\n \u003cp\u003eUnstable living situation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" valign=\"top\"\u003e\n \u003cp\u003e16 (13.9 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.26530612244898%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026gt;= 5, (AR =-1.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026gt;=5 (AR = -0.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e9 (AR = 2.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e(2)=7.83, p=0.20,\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.46938775510204%\" valign=\"top\"\u003e\n \u003cp\u003ePsychiatric diagnosis (M, SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" valign=\"top\"\u003e\n \u003cp\u003e0.86 (1.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.26530612244898%\" valign=\"top\"\u003e\n \u003cp\u003e0.74 (0.98)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e1.21 (1.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e0.85 (1.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\" valign=\"top\"\u003e\n \u003cp\u003eF(2,116.41)=2.57, p=0.069\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.46938775510204%\" valign=\"top\"\u003e\n \u003cp\u003eSevere drug use (12 days or more within the past month)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" valign=\"top\"\u003e\n \u003cp\u003e10 (3.6 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.26530612244898%\" valign=\"top\"\u003e\n \u003cp\u003e6 (4 %), (AR=0.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026gt;5, (AR=-0.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026gt;5, (AR=0.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e(2)=0-64, p=0.726\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.46938775510204%\" valign=\"top\"\u003e\n \u003cp\u003eAlcohol dependence\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(AUDIT score \u0026ge;15)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" valign=\"top\"\u003e\n \u003cp\u003e166 (59.1 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.26530612244898%\" valign=\"top\"\u003e\n \u003cp\u003e85 (56.3 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR=-1.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e37 (66.1 %), (AR=1.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e44 (59.5 %), (AR=1.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e(2)=3.45, p=0.178\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eDUD (n=661)\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"105%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.46938775510204%\" valign=\"top\"\u003e\n \u003cp\u003eGender (% female)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" valign=\"top\"\u003e\n \u003cp\u003e210 (31.8 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.26530612244898%\" valign=\"top\"\u003e\n \u003cp\u003e59 (19.9 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = -5.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e49 (37.4 %), (AR=1.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e102 (43.8 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = 4.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e(2)=36.83, \u003cstrong\u003ep\u0026lt;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.46938775510204%\" valign=\"top\"\u003e\n \u003cp\u003eAge (in years, M, SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" valign=\"top\"\u003e\n \u003cp\u003e32 (10.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.26530612244898%\" valign=\"top\"\u003e\n \u003cp\u003e31.55 (10.54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e31.84 (9.87)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e32.68 (10.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\" valign=\"top\"\u003e\n \u003cp\u003eF(2,617)=0.49, p=0.611\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.46938775510204%\" valign=\"top\"\u003e\n \u003cp\u003eNot in employment/education\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" valign=\"top\"\u003e\n \u003cp\u003e456 (69 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.26530612244898%\" valign=\"top\"\u003e\n \u003cp\u003e186 (62.6 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = -3.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e89 (67.9 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = -0.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e181 (77.7 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = 3.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e(2)=13.92, \u003cstrong\u003ep\u0026lt;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.46938775510204%\" valign=\"top\"\u003e\n \u003cp\u003eUnstable living situation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" valign=\"top\"\u003e\n \u003cp\u003e113 (17.1 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.26530612244898%\" valign=\"top\"\u003e\n \u003cp\u003e42 (14.1 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = -1.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e20 (15.3 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = -0.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e51 (21.9 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = 2.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e(2)=5.91, p=0.052\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.46938775510204%\" valign=\"top\"\u003e\n \u003cp\u003ePsychiatric diagnosis (M, SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" valign=\"top\"\u003e\n \u003cp\u003e1.03 (1.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.26530612244898%\" valign=\"top\"\u003e\n \u003cp\u003e0.65 (0.92)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e1.08 (1.42)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e1.48 (1.42)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\" valign=\"top\"\u003e\n \u003cp\u003eF(2,297.39)=31.34, \u003cstrong\u003ep\u0026lt;.001\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.46938775510204%\" valign=\"top\"\u003e\n \u003cp\u003eSevere drug use (12 days or more within the past month)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" valign=\"top\"\u003e\n \u003cp\u003e262 (39.6 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.26530612244898%\" valign=\"top\"\u003e\n \u003cp\u003e110 (37 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = -1.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e44 (33.6 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = -1.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e108 (46.4 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = 2.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e(2)=7.23, \u003cstrong\u003ep=0.027\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.46938775510204%\" valign=\"top\"\u003e\n \u003cp\u003eAlcohol dependence\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(AUDIT score \u0026ge;15)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" valign=\"top\"\u003e\n \u003cp\u003e103 (15.6 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.26530612244898%\" valign=\"top\"\u003e\n \u003cp\u003e49 (16.5 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = -0.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e22 (16.8 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = 0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e32 (13.3 %),\u0026nbsp;\u003cbr\u003e\u0026nbsp;(AR = 0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e(2)=0.00, p=0.998\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote: Percentages and adjusted residuals (AR) reported refer to percentages of individuals in the diagnostic groups (no dx, subclinical and full PTSD). Percentages of PTSD caseness are valid percentages\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-psychiatry","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bpsy","sideBox":"Learn more about [BMC Psychiatry](http://bmcpsychiatry.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bpsy/default.aspx","title":"BMC Psychiatry","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"PTSD, Substance Use Disorder, Therapy, Trauma","lastPublishedDoi":"10.21203/rs.3.rs-4918218/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4918218/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003ePrevious research has indicated high levels of PTSD among people with substance use disorders (SUD), necessitating an exploration of trauma profiles in this population. This study aims to assess the prevalence of ICD-11 PTSD and study demographic, trauma-related, and substance-use related factors among individuals in SUD treatment in Denmark, focusing on differences between alcohol use disorder (AUD) and drug use disorder (DUD).\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThe study utilized a multi-site approach, collecting data from five Danish SUD treatment settings. A total of 1347 adult individuals were interviewed as part of an initial structured screening process for SUD treatment. Participants were assessed using the ICD-11 PTSD criteria.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe findings indicate that approximately 25% of individuals in treatment met the criteria for probable PTSD, with an additional 15% showing subclinical PTSD symptoms. The prevalence of PTSD was higher in DUD treatment compared to AUD treatment. The study also highlighted significant differences in social functioning and clinical profiles between the two groups.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThe high prevalence of PTSD symptoms among individuals in SUD treatment underscores the need for targeted interventions. The study suggests that PTSD should be a particular focus in DUD treatment due to the higher vulnerability and impact of trauma-related symptoms in this group.\u003c/p\u003e","manuscriptTitle":"Trauma and ICD-11 PTSD in treatment for substance use disorders: A Danish multi-site study ","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-10-14 10:22:21","doi":"10.21203/rs.3.rs-4918218/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-08-23T18:29:54+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-08-19T08:19:55+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-08-19T06:24:03+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Psychiatry","date":"2024-08-15T08:54:44+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-psychiatry","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bpsy","sideBox":"Learn more about [BMC Psychiatry](http://bmcpsychiatry.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bpsy/default.aspx","title":"BMC Psychiatry","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"93276f74-a9fa-463c-bf53-d72e6a466d02","owner":[],"postedDate":"October 14th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-08-11T16:02:29+00:00","versionOfRecord":{"articleIdentity":"rs-4918218","link":"https://doi.org/10.1186/s12888-025-07164-w","journal":{"identity":"bmc-psychiatry","isVorOnly":false,"title":"BMC Psychiatry"},"publishedOn":"2025-08-07 15:57:02","publishedOnDateReadable":"August 7th, 2025"},"versionCreatedAt":"2024-10-14 10:22:21","video":"","vorDoi":"10.1186/s12888-025-07164-w","vorDoiUrl":"https://doi.org/10.1186/s12888-025-07164-w","workflowStages":[]},"version":"v1","identity":"rs-4918218","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4918218","identity":"rs-4918218","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}