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

doi:10.21203/rs.3.rs-4918218/v1

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

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).

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.

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, (χ² (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 (χ²(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 (χ²(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.

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.

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.

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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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	ꭕ²(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	χ²(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	χ²(1)=14.25, p<.001
Income (employment/education)	172 (42 %), AR = 2.1	313 (35.7 %), AR = -2.1	χ²(1)=4.34, p=.037
Living situation (stable)	22 (5.4 %), AR = -4.9	131 (15.0 %), AR = 4.9	χ²(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 %)	χ²(1)=12.91, p=.002
Accidents	60 (21.1 %), AR = -1.9	185 (27 %), AR = 1.9	χ²(1)=3.33, p=.068
Violence	158 (55.6 %), AR = -4.1	475 (89.2 %), AR = 4.1	χ²(1)=15.81, p<.001
Sexual violence	59 (20.8 %), AR = -2.9	205 (29.9 %), AR = 2.9	χ²(1)=7.96, p=.005
life-threatening illness	59 (20.8 %), AR = 0.6	131 (19.1 %), AR = -0.6	χ²(1)=0.26, p=.610
Unexpected death	99 (34.9 %), AR = -1.8	282 (41.1 %), AR = 1.8	χ²(1)=3.03, p=.082
Other events	167 (58.8 %), AR = 3.0	329 (48.4 %), AR = -3.0	χ²(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	χ²(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	χ²(1)=4.94, p=.026
Avoidance (endorsed)	162 (57.7 %), AR =-2.9	447 (67.7 %), AR = 2.9	χ²(1)=8.15, p=.004
Sense of threat (endorsed)	169 (60.1 %), AR = -1.9	439 (66.5 %), AR = 1.9	χ²(1)=3.29, p=.070
Functional impairment (endorsed)	161 (57.3 %), AR = -1.7	418 (63.3 %), AR = 1.7	χ²(1)=2.79, p=.095
Probable PTSD (endorsed)	74 (26.3 %), AR = -2.7	233 (35.3 %), AR = 2.7	χ²(2)=8.14, p=.017
Probable subclinical PTSD (endorsed)	56 (19.9 %), AR = 0	131 (19.8 %), AR = 0	χ²(2)=8.14, p=.017
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)	χ²(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)	χ²(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)	χ²(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)	χ²(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)	χ²(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)	χ²(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)	χ²(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)	χ²(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)	χ²(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)	χ²(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)	χ²(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)	χ²(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)	χ²(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)	χ²(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)	χ²(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)	χ²(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)	χ²(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)	χ²(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)	χ²(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)	χ²(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)	χ²(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)	χ²(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)	χ²(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)	χ²(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)	χ²(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)	χ²(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)	χ²(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)	χ² (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)	χ² (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)	χ²(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)	χ² (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)	χ² (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)	χ²(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)	χ²(2)=2.69, p=0.260
Unstable living situation	16 (13.9 %)	>= 5, (AR =-1.9)	>=5 (AR = -0.8)	9 (AR = 2.8)	χ²(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)	χ²(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)	χ²(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)	χ²(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)	χ²(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)	χ²(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)	χ²(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)	χ²(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

No competing interests reported.

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

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Comorbid PTSD in SUD treatment

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