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Coping motives mediate the relationship between PTSD and MDMA use in adolescents with substance use disorders



Post-traumatic stress disorder (PTSD) and substance use disorders (SUDs) often co-occur in adolescent patients. Previous research has shown that these patients differ from SUD patients without PTSD in terms of their substance use patterns. In this study, we aimed to test whether substance use in this population is related to an attempt to self-medicate PTSD-related symptoms.


German adolescent patients (aged 13–18 years) at an outpatient clinic for SUD treatment, n = 111 (43% female), completed a self-designed questionnaire on use motives, a measure of PTSD-related experiences, and underwent a standardized psychiatric interview including structured substance use questions. Participants were subsequently classified as ‘no traumatic experiences (‘noTEs’ but SUD), ‘traumatic experiences but no current PTSD diagnosis’ (‘TEs’ with SUD), and ‘PTSD’ with SUD. After establishing a self-designed motive measurement through exploratory and confirmatory factor analyses, we calculated non-parametric group differences and a mediation analysis in a linear regression framework.


The past-year frequency of MDMA use was highest in the PTSD group and lowest in the noTE group (H (2) = 7.2, p = .027, η2 = .058), but no differences were found for frequencies of tobacco, alcohol, cannabis, or stimulant use (all H ≤ 4.9, p ≥ .085, η2 ≤ .033). While controlling for sex, the three groups showed a similar pattern (highest in the PTSD group and lowest in the noTE group) for coping scores (F (103) = 5.77, p = .004, η2 = .101). Finally, mediation analyses revealed an indirect effect of coping score (b = 0.61, 95% CI [0.29, 1.58], p = .145) on the association between group membership and MDMA use frequency.


In adolescent SUD patients, we found an association of current PTSD and lifetime traumatic experiences with higher MDMA use that could be partially explained by substance use being motivated by an attempt to cope with mental health symptoms. This indicates a coping process involved specifically in MDMA use compared to the use of other psychoactive substances, possibly due to unique psychoactive effects of MDMA.


Post-traumatic stress disorder (PTSD) has been linked repeatedly to chronic substance use as well as substance use disorders (SUDs), such that psychiatric patients with either disorder often fulfil diagnostic criteria for the other one as well [1,2,3,4,5]. For example, 20–54% of adolescent SUD patients fulfil PTSD criteria [6, 7], while 30% of adolescent PTSD patients present with SUD [8]. Similar patterns have been shown for adult patients [2, 5] as well as adolescents [1, 3, 4]. Several explanations have been hypothesized for these findings. First, a common biological dysfunction or vulnerability might increase the likelihood to develop either disorder in the course of their life [9] (given the appropriate environmental variables, such as a traumatic events), as indicated by data showing that both disorders have a similar age of onset, namely around adolescence [10]. Accordingly, some studies have found genetic markers that are related to PTSD as well as SUD, such as polymorphism of the GABA receptor [11,12,13]. Second, circumstances promoting development of SUD in adolescents often include adverse life events or traumatic experiences (TEs) [14], and this increased exposure to TEs might also facilitate the development of PTSD [15, 16]. Finally, a co-occurrence of PTSD and SUD might be a result of substance use as a coping mechanism for dealing with PTSD symptoms [17]. Dealing with PTSD symptoms like hyperarousal, avoidance, or intrusion [18] presents a challenge for adolescents that is happening during the same time period in life where experimentation with psychoactive substances is most likely [19]. It is likely, that some substances can alter the acute experience of the PTSD symptoms in a sense that promotes future substance use, i.e., through negative reinforcement [20, 21], which increases the risk of experimental or recreational use developing into a problematic pattern as exhibited by the presence of a SUD. The hypothesis suggesting this pattern of development is commonly referred to as the self-medication hypothesis [22, 23].

The latter has been repeatedly invoked in the description of the PTSD-SUD relationship [24,25,26,27]. While previous research has focussed on adult patients with PTSD and SUD who reported coping motives with regard to their substance use [17], or on adolescents without SUD or PTSD [28] little research has been conducted to directly explore the relationship between PTSD, substance use, and coping motives. In two studies with adult participants drawn from the general population, it has been shown that coping motives act as mediator in the relationship between TEs and problematic substance use [29, 30]. In contrast, one study in adolescent SUD patients has shown that coping motives are increased in participants with co-occurring SUD and PTSD, instead of TEs alone [31].

In the present study, we aim to explore the relationship between adolescent PTSD and SUD in the context of the self-medication hypothesis. To do so we investigate differences in reported coping motives between adolescents with a SUD, adolescents with a SUD and TEs but no PTSD, and adolescents with a SUD and PTSD. Additionally we explore differences in past-year substance use between these three groups and aim to understand the connection between these three variables (PTSD group, coping motives, and substance use frequency) through a mediation analysis. Given the substance-specific psychoactive effects that might interact with PTSD symptoms, we conduct analyses for several substances, but restrict the mediation analyses to those substances whose use differed between groups.



Between November 2017 and April 2021, n = 303 treatment-seeking adolescents at a German outpatient clinic for adolescents with SUD consented to participate in the study. Since our sample consists of adolescent patients, the main driver for treatment-seeking are the wishes of their parents. This setting of borderline involuntary treatment leads to very low motivation on the side of the adolescents to participate in additional effort regarding research participation. Therefore only n = 162 (41% female) participants filled out the use motives questionnaire and were selected for exploratory and confirmatory factor analyses. For the main analysis, participants were selected who had answered at least 80% of the items in the relevant questionnaires (n = 111, 43% female). Participants were divided into three groups according to their trauma status resulting from the PTSD questionnaire: no history of traumatic experiences (‘noTEs’), a history of traumatic experiences but no PTSD (‘TEs’), and past-year PTSD (‘PTSD’).


TEs and PTSD

The University of California at Los Angeles Post Traumatic Stress Disorder Reaction Index for DSM-IV [32], German version by [33], is a self-report questionnaire assessing TEs and PTSD symptoms in adolescents. The instrument contains a Criterion A section, in which patients select the lifetime TE that currently afflicts them the most. The next section assesses the frequency of occurrence of PTSD symptoms during the past month (rated from 0 = none of the time to 4 = most of the time). The items map directly onto the DSM-IV intrusion (Criterion B), avoidance (Criterion C), and hyperarousal (Criterion D) symptom clusters. PTSD is considered to be present when all four criteria (Criterion A, B, C, & D) are fulfilled [32]. Outcomes for this questionnaire were presence of a PTSD (yes/no) and presence of a TE (yes/no).

Use motives

To assess use motives, we used a self-designed questionnaire asking twenty-two questions that are answered on a scale with zero (“never applies”), one (“rarely applies”), two (“sometimes applies”), three (“mostly applies”) or four (“always applies”) points. The questionnaire has been designed to provide details about a patients substance use and ten of the items allow for the extraction of three scores for different use motives: ‘coping’ (4 items), ‘social motives’ (3 items), and ‘other’ (3 items). A detailed overview over the ten use motive items of the questionnaire can be found in Additional file 1: Table S3. The remaining twelve items refer to the participants rating of their ability to control their drug use (e.g. “I have the feeling that I have no control over my drug use”; “I feel like I relapse often”), which are not analysed here. To determine if the theoretical structure of the questionnaire is empirically supported, we perform preliminary exploratory and confirmatory factor analyses. The main outcome is the combined score of the ‘coping’ items, with a maximum score of 16, and a higher score indicating more frequent substance use because of coping motives.

Comorbid diagnoses

The Mini-International Neuropsychiatric Interview for Children and Adolescents (MINI-KID) [34] is a structured diagnostic interview used to evaluate the presence of psychiatric disorders, according to DSM-5 criteria. All interviews were conducted by psychologists working in our department of adolescent substance abuse using a German translation of the original MINI-KID [35]. Outcomes were the presence of any SUD, psychotic, mood (major depression or bipolar disorder), anxiety (general anxiety disorder, panic disorder, agoraphobia, separation anxiety disorder, social phobia, specific phobia), behavioural (attention deficit hyperactivity disorder, conduct disorder, oppositional defiant disorder) or obsessive–compulsive (OCD) disorder. The MINI-KID was conducted in the context of a study registered at (NCT03444974), with all licensed administrations (invoice #20220315.1) conducted before March 15th 2022.

Substance use interview

The pattern of substance use was assessed via interview [36], asking for the number of days each substance was used per month over the past year. Outcome variables from this assessment were the presence (yes/no) of past-year use of tobacco, alcohol, cannabis, cocaine, benzodiazepines, opioids, solvents, methylenedioxymethamphetamine (MDMA), and stimulants (= amphetamine and methamphetamine), and the past-year use frequency of each substance in average number of use days per month. However, since none of our participants reported regular past-year use of cocaine, opioids, benzodiazepines or solvents we excluded these substances from the analyses.


Data collection was embedded into standard diagnostic procedures. During the first clinical appointment, participants as well as legal guardians were asked to provide written informed consent to the study. Questionnaires were handed out and substance use was evaluated by the hospital staff member (therapist, psychologist, or physician). The MINI-KID was conducted approx. 1–4 weeks later. The study was conducted in accordance with the Declaration of Helsinki and all procedures were approved by the Institutional Review Board of the University Hospital C. G. Carus Dresden (EK 66022018).

Statistical analysis

Exploratory factor analysis

To account for the non-normal distribution of motive items (Shapiro–Wilk test for each questionnaire items p < 0.001), we used factor analysis extraction methods. The number of latent factors were explored with Scree plot, Kaiser-Guttman criterion, the revised MAP test as well as Parallel Analyses with principal components and raw data permutation [37]. Possible item-factor assignments (factor structures) were deducted with exploratory factor analyses (EFA) in IBM SPSS Statistics 27.0 using Principal Axis extraction with Promax-rotation (kappa = 4).

Confirmatory factor analysis

The adequacy of factor structures was tested for the given empirical data with confirmatory factor analysis (CFA) using the lavaan package [38] in RStudio [39]. We tested the theoretical model (the three factors, ‘coping’, ‘social motives’ and ‘other’ consisting of distinct items), the empirical model build upon the results from the EFA, and the combined model that integrates theoretical considerations into the empirical model using the diagonally weighted least-squares (DWLS) method of estimation to account for non-normality within the categorical items. A good absolute model fit would be indicated by a Χ2 to degrees of freedom ratio < than 2 (a ration between 2 and 3 is acceptable), a Comparative Fit Index (CFI) ≥ 0.95 (0.90–0.94 acceptable), a standardized root mean square residual (SRMR) ≤ 0.05 (0.05–0.10 acceptable), and a root mean square error of approximation (RMSEA) ≤ 0.05 (0.05–0.10 acceptable) [40].

Main analysis

All the following analyses were conducted with IBM SPSS Statistics 27.0. In cases were at least 80% of questions were answered, missing values were replaced by the mean value of the remaining items for that participant (n = 9). Categorical demographic variables (presence of anxiety, mood, behavioural disorders, presence of OCD, gender) were chi-square tested. For our continuous sociodemographic variable ‘age’, we conducted an analysis of variance.

Since all our continuous main outcomes (coping score, use frequency for tobacco, alcohol, cannabis, MDMA, and stimulants) did not fulfil the criterion for normality (see Additional file 1: Table S1), non-parametric testing was applied. To predict the presence (yes/no) of past-year tobacco, alcohol, cannabis, MDMA, and stimulant use, five binary logistic regressions were calculated with group membership (noTEs, TEs, PTSD), and sociodemographic variables (other mental disorders, gender, age) that differed between the three groups as predictors, and the presence of past-year use of each substance as outcome. To control for differences in sociodemographic variables regarding the continuous outcomes (coping score, use frequency for tobacco, alcohol, cannabis, MDMA, and stimulants) differences in these outcomes were calculated with the Mann–Whitney U test. If the Mann–Whitney U test was non-significant, group (noTEs, TEs, PTSD) differences in substance use frequency were calculated with a Kruskal–Wallis test. In case the Mann–Whitney U test detected significant differences for sociodemographic variables, Quade’s test [41] was used to perform a non-parametric test while controlling for a covariate. Additionally Spearman’s correlation coefficient ρ was calculated for the association between coping score and use frequency for each substance for which significant group differences could be detected. Mediation analyses for all substances for which significant group differences were detected, were performed with the PROCESS macro [42]. PROCESS provides both a significance test and an effect size estimate with 95% confidence interval for the mediational effect of mediator variable M (‘coping score’) on the relationship between a predictor X (‘group membership’) and an outcome Y (‘substance use frequency’). This indirect effect (ab) describes by how much the relationship between X and Y (c’) is affected by the relationship between X and M (a), and the relationship between M and Y (b), see Fig. 1. The significance level for all analyses were set to α = 0.05.

Fig. 1
figure 1

Exemplary mediation model


Sample description

Between-group differences in sociodemographic variables and the presence of mental disorders are shown in Table 1. Females were significantly underrepresented in the noTEs group [X2 (2) = 14.2, p < 0.001] while several co-occurring mental disorders were overrepresented in the PTSD group [X2 (2) = 14.0, p ≤ 0.007]. Based on group differences in the presence of OCD we excluded the n = 5 participants with an OCD diagnosis from the analysis, leaving n = 106 participants. Based on the sociodemographic differences we controlled for gender and presence of anxiety disorder in our main analysis.

Table 1 Demographic information about the three samples

Confirmation of the use motive questionniare

Data from the use motive questionnaire was suitable for factor analyses with Kaiser–Meyer–Olkin coefficient = 0.83, a significant Bartlett test with p < 0.001 and a measures of sample adequacy coefficient of 0.80. In the exploratory factor analysis, items had satisfying communalities after extraction. The only exception was item 18 (‘I am scared to loose friends when I stop using drugs.’) from the’social motives’ scale (h2 = 0.041) that was therefore not used within the following CFA analysis. Solutions with either two factors (indicated by Parallel Analysis and MAP test) or three factors (indicated by Kaiser-Guttman criterion) were suggested. The two-factor model explaining 63% of variance and producing one cross-loading item was deemed improper for further analysis as it collapsed all but the ‘social’ items into one large factor. The ‘empirical’ three-factorial model was selected for further CFA testing given that it was more theoretically sound by reproducing most of the theorized item assignments and that it explained variance to a rather large degree (67%). However, it deviated from the ‘theoretical’ three-factor model by having two ‘coping’ items with cross-loadings on the third factor, and one ‘other’ item loading on ‘coping’ only. A ‘combined’ model was defined for further CFA analysis based on the ‘empirical’ model; however, the ‘other’ item was therein assigned to the ‘other’ scale in order to have all scales more theoretically sound.

In the CFA, the ‘combined’ model was deemed appropriate within our sample due to mostly acceptable model fit values, with Χ2/df-ratio = 2.05, CFI = 0.94, SRMR = 0.05, but RMSEA 90%CI = 0.08-0.18, see Additional file 1: Table S2. Fit indices for the theoretical and empirical models were in comparable ranges, but less advantageous. Therefore, we assume that all four items theorized to measure a common construct (presumably ‘coping’) indeed measure a common construct that differed from what other motive items measure. However, two of those items covering substance use due to stressful events, or substance use due to inner tension, were also cross-loading on another factor.

Substance use

The logistic regression models showed that the presence of past-year MDMA use (b = 0.66, p = 0.034, OR = 1.94) was significantly predicted by group membership (noTEs, TEs, PTSD) when controlling for sex and presence of anxiety disorders, while there were no relationships between group membership and the presence of tobacco use (b =—0.19, p = 0.721, OR = 0.83) alcohol use (b = 0.40, p = 0.289, OR = 1.49), cannabis use (b = − 0.38, p = 0.392, OR = 0.68), or stimulant use (b = 0.42, p = 0.196, OR = 1.52).

The presence of anxiety disorders was not associated with the frequency of past-year use of tobacco (U = 685, p = 0.746, η2 = 0.001), alcohol (U = 402, p = 0.687, η2 = 0.002), cannabis (U = 395, p = 0.193, η2 = 0.018), MDMA (U = 407, p = 0.080, η2 = 0.026), or stimulants (U = 225, p = 0.240, η2 = 0.015). Similarly, both genders did not differ in past-year tobacco use frequency (U = 1005, p = 0.161, η2 = 0.011), alcohol use frequency (U = 867.5, p = 0.351, η2 = 0.010), cannabis use frequency (U = 967, p = 0.703, η2 = 0.002), MDMA use frequency (U = 897, p = 0.197, η2 = 0.014), or stimulant use frequency (U = 609, p = 0.561, η2 = 0.004).

The past-year frequency of MDMA use differed between the noTEs, TEs and PTSD group (H (2) = 7.2, p = 0.027, η2 = 0.058), but no differences were detected regarding the past-year frequency of tobacco (H (2) = 1.6, p = 0.457, η2 = 0.004), alcohol (H (2) = 2.8, p = 0.256, η2 = 0.008), cannabis (H (2) = 4.9, p = 0.085, η2 = 0.033), or stimulant (H (2) = 1.3, p = 0.512, η2 = 0.009) use. Details regarding the patterns of substance use in the different groups are displayed in Table 2.

Table 2 Group differences in substance use and coping

Coping score

While the presence of anxiety disorders was not associated with differences in coping score (U = 613.5, p = 0.340, η2 = 0.008), the two sexes showed a significant difference in coping score (U = 993, p = 0.012, η2 = 0.057); making it necessary to control for this variable in calculating the association between group membership (noTEs, TEs, PTSD) and coping score. While controlling for sex, the three groups differed significantly in terms of coping scores (F (103) = 5.77, p = 0.004, η2 = 0.101), with level of reported coping motive being highest in the PTSD group and lowest in the noTEs group. Additionally, the frequency of past-year MDMA use correlated significantly and positively with coping score (ρ = 0.287, p = 0.004).

Meditation analysis

The mediation analyses for the effect of group membership (noTEs, TEs, PTSD) on past-year MDMA use frequency resulted in an indirect effect of coping score (b = 0.61, 95% CI [0.29, 1.58], p = 0.145), see Fig. 2. Although the p-value is larger than the α-level of 0.05, the CI not including zero indicates a true effect. That is, coping motives mediate how the presence of TEs and/or PTSD is associated with the past-year frequency of MDMA use in adolescents treated for SUD.

Fig. 2
figure 2

Mediation model for the effect of PTSD group on MDMA use frequency mediated by coping score


In the present study, we investigated the relationship between lifetime TEs and current PTSD diagnosis, substance use frequency and coping motives related to substance use in German adolescent SUD patients. We found that adolescents with co-occurrence of SUD and PTSD reported stronger coping motives and, in turn, a higher frequency and likelihood of MDMA use in the past year. Associations were specific to MDMA; they did not exist for tobacco, alcohol, cannabis, or stimulants.

Similarly to previous research from our group investigating past-month substance use [25], a co-occurrence of PTSD and SUD was associated with a higher frequency of past-year MDMA use in adolescents seeking treatment for SUD. Previous research supports our finding in so far as MDMA use has been associated with the presence of general psychopathological symptoms [43], use of multiple psychoactive substances [44] and with higher rates of PTSD [45]. However, in studies with adults, PTSD has mostly been associated with the use of alcohol [5, 46, 47] when compared to non-using populations. Since our sample showed high levels of alcohol use (amongst other substance use) as well, it might be more accurate to say that we showed MDMA use to be associated with PTSD in a sample of adolescents with high levels of co-occurring substance use.

A first possible explanation for this relationship between MDMA use and PTSD might be a detrimental effect of MDMA use on PTSD development. Specifically, a more frequent MDMA use might lead to an escalation of sub-clinical PTSD symptoms until the criteria for a PTSD diagnosis are fulfilled. Support for this line of argument could be found in previous research that has shown that psychopathological symptoms like depression or aggression might develop after MDMA use [43, 45]. Another explanation, supported by the results of our mediation analysis, suggests that an increased use of MDMA is observed in patients with PTSD symptoms because of a stronger need to cope with PTSD-related symptoms. Our analysis has shown that part of the effect of TEs/PTSD on MDMA use frequency is explained by the level of reported coping motives for substance use. Plainly, if a higher frequency of coping motives was reported by a patient, the effect of PTSD on MDMA use frequency was increased as well. This finding is in line with the hypothesis that substance use might serve as a coping measure [22, 23]. This specific relationship of PTSD symptoms with MDMA has been shown previously [48,49,50], while MDMA use in recreational non-pathological users is mainly related to enhancement or expansion motives instead of coping [51]. Specifically, Jansen [48] described a case report of a patient with PTSD who unambiguously ascribes his symptom relief to the acute effects of MDMA. Further, Scott et al. [50] have shown that higher levels of coping motives are related to higher levels of MDMA use which is in line with our correlational analysis as well. Additionally, their research and one other study support our conclusion, that it are PTSD symptoms specifically that are related to increased MDMA use [31], not TEs in general [30, 50]. Furthermore, Moonzwe et al. [49] showed in great detail how, for young adults, MDMA use has been described by users as particularly effective in terms of coping with negative consequences of TEs. However, the authors also point out that this relationship is present only in participants who did not receive satisfactory mental health treatment, while in well-treated participants, MDMA use was not related to a significant coping effect [49]. This literature and our results may be relevant regarding recent systematic reviews [52,53,54] and phase-3 studies [55] indicating that MDMA-supported psychotherapy might be beneficial in PTSD patients. While the effects of MDMA-supported psychotherapy seem promising in adult patients with treatment-resistant PTSD, often military veterans [56], there are no studies so far investigating this process in adolescent patients. Importantly, our participants use MDMA in recreational settings (clubs, festivals, raves, etc.), without psychotherapeutic support and mostly in form of pills with little to no knowledge of its contents, indicating a large difference to therapeutically administered MDMA.

It remains speculative why specifically MDMA was involved in coping activities as compared to other substances with anxiolytic and sedative effects such as alcohol (which is known from adult studies) or opiates with their potentially more symptom-relieving properties [57]. One issue is that alcohol is more available and more commonly used among adolescents in the study region compared to MDMA [58]. Its use might simply be much too high and prevalent in our sample, resulting in a ceiling effect that prevents us from detecting self-medicating patterns due to high use in non-self-medicating adolescents. Opiates, on the other hand, may not have been encountered by these patients, may have been less available compared to MDMA or more difficult to afford on a regular basis in the study region. In fact, only 3 of 201 adolescent patients in our institution reported any opiate use in the 12 months before admission [58].

While at first glance it might seem like MDMA-related coping is beneficial for these patients, this practice is also related to a variety of negative outcomes. Specifically, the relief from distress is thought to act as a negative reinforcement, increasing the likelihood for further use in the future and increasing the risk for the aetiology of a MDMA use disorder according to current learning theories related to SUDs [20, 21]. Likewise, reporting coping motives for substance use during adolescence is associated with higher rates of SUDs later in life [59], indicating that the patients we saw in our study, might go on to develop more severe patterns of substance use later on. Further, a coping motive is not equivalent to a successful symptom reduction. For example, some participants report that MDMA use is more of a temporary break from PTSD symptomatology instead of having any substantial effect beyond the acute high [49]. Finally, a reduction in substance is made much more difficult as long as a coping behaviour is in place, leading to higher rates of relapse in patients with this use pattern [31].


First, we did not use a validated measure to assess substance use motives. Our measure was based on a self-designed questionnaire that was available in our research group, which did assess use motives but was not specifically designed for this purpose. Consequently, our coping score might not reflect a measure of coping motives but instead might represent another unclear factor related to PTSD presence and MDMA use frequency. However, we did provide exploratory and confirmatory factor analyses for the questionnaire providing some preliminary support for it being psychometrically sound.

Second, our sample consisted entirely of treatment-seeking patients, which does not allow for generalizations of the relationship between MDMA use, coping motives, and TEs for MDMA substance users outside this clinical setting.

Third, our cross-sectional design does not allow for conclusions about causal relationships. While we argue that patients take MDMA to reduce PTSD symptoms and might therefore facilitate a development of a SUD, this is mere association. To determine a causal chain in this relationship longitudinal studies are needed.

Fourth, the three groups in our sample differed in terms of gender distribution and the presence of mental disorders. However, we controlled for these factors in our main analysis, and examined if they were associated with our main outcomes. Based on these analyses we concluded that the gender and psychopathological differences did not influence our main outcomes.

Fifth, our adolescent patients are mostly motivated externally (e.g. through parents) to participate in research, which resulted in a large number of questionnaires not being filled out.

Finally, our argument for a coping effect rests on MDMA relieving PTSD related symptoms. However, we did not ask participants to report coping motives specific for PTSD. Instead, participants reported general coping motives dealing with the relief of negative emotional states. Future research should take care to include measures that specifically ask if substances were used to reduce PTSD symptoms specifically.


This study in German adolescent psychiatric patients showed that a co-occurring PTSD and SUD is related to higher MDMA use compared to patients without a co-occurring PTSD. This use was increased even when controlling for other substance use, gender, and comorbid disorders. Additionally, we showed that the effect of PTSD on MDMA use frequency is mediated by the level of coping motives, indicating that MDMA use might be higher in this population, partly because of a coping motive.

Availability of data and materials

The datasets used and analysed during the current study are available from the corresponding author on reasonable request.


  1. Basedow LA, Kuitunen-Paul S, Roessner V, Golub Y. Traumatic events and substance use disorders in adolescents. Front Psychiatry. 2020;11:559.

    PubMed  PubMed Central  Article  Google Scholar 

  2. Fergusson DM, Boden JM, Horwood LJ. The developmental antecedents of illicit drug use: evidence from a 25-year longitudinal study. Drug Alcohol Depend. 2008;96(1–2):165–77.

    PubMed  Article  Google Scholar 

  3. Kuitunen-Paul S, Roessner V, Basedow LA, Golub Y. Beyond the tip of the iceberg: a narrative review to identify research gaps on comorbid psychiatric disorders in adolescents with methamphetamine use disorder or chronic methamphetamine use. Subst Abuse. 2021;42(1):13–32.

    Article  Google Scholar 

  4. Simmons S, Suárez L. Substance abuse and trauma. Child Adolesc Psychiatr Clin N Am. 2016;25(4):723–34.

    PubMed  Article  Google Scholar 

  5. de Subbie-Saenz VS, Pandey A, Pandey G, Kamarajan C, Smith R, Anokhin A, et al. Pathways to post-traumatic stress disorder and alcohol dependence: trauma, executive functioning and family history of alcoholism in adolescents and young adults. Brain Behav. 2020;10:11.

    Article  Google Scholar 

  6. Turner WC, Muck RD, Muck RJ, Stephens RL, Sukumar B. Co-occurring disorders in the adolescent mental health and substance abuse treatment systems. J Psychoactive Drugs. 2004;36(4):455–62.

    PubMed  Article  Google Scholar 

  7. Williams JK, Smith DC, An H, Hall JA. Clinical outcomes of traumatized youth in adolescent substance abuse treatment: a longitudinal multisite study. J Psychoactive Drugs. 2008;40(1):77–84.

    PubMed  Article  Google Scholar 

  8. Essau, Conradt J, Petermann F. Häufigkeit der posttraumatischen belastungsstörung bei jugendlichen: ergebnisse der bremer jugendstudie. Z Für Kinder Jugendpsychiatr Psychother. 1999;27(1):37–45.

    CAS  Article  Google Scholar 

  9. Enman NM, Zhang Y, Unterwald EM. Connecting the pathology of posttraumatic stress and substance use disorders: monoamines and neuropeptides. Pharmacol Biochem Behav. 2014;117:61–9.

    CAS  PubMed  Article  Google Scholar 

  10. Kessler RC, Berglund P, Demler O, Jin R, Merikangas KR, Walters EE. Lifetime prevalence and age-of-onset distributions of DSM-IV disorders in the national comorbidity survey replication. Arch Gen Psychiatry. 2005;62(6):593–602.

    PubMed  Article  Google Scholar 

  11. Kapfhammer H-P, von Komorbidität ZP. Belastungsstörung und Sucht in biopsychosozialer Perspektive. Neuropsychiatrie. 2021.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Sartor CE, McCutcheon VV, Pommer NE, Nelson EC, Grant JD, Duncan AE, et al. Common genetic and environmental contributions to post-traumatic stress disorder and alcohol dependence in young women. Psychol Med. 2011;41(7):1497–505.

    CAS  PubMed  Article  Google Scholar 

  13. Xian H, Chantarujikapong SI, Scherrer JF, Eisen SA, Lyons MJ, Goldberg J, et al. Genetic and environmental influences on posttraumatic stress disorder, alcohol and drug dependence in twin pairs. Drug Alcohol Depend. 2000;61(1):95–102.

    CAS  PubMed  Article  Google Scholar 

  14. Kaysen D, Neighbors C, Martell J, Fossos N, Larimer ME. Incapacitated rape and alcohol use: a prospective analysis. Addict Behav. 2006;31(10):1820–32.

    PubMed  PubMed Central  Article  Google Scholar 

  15. Kilpatrick DG, Acierno R, Resnick HS, Saunders BE, Best CL. A 2-year longitudinal analysis of the relationships between violent assault and substance use in women. J Consult Clin Psychol. 1997;65(5):834–47.

    CAS  PubMed  Article  Google Scholar 

  16. Kilpatrick DG, Ruggiero KJ, Acierno R, Saunders BE, Resnick HS, Best CL. Violence and risk of PTSD, major depression, substance abuse/dependence, and comorbidity: results from the national survey of adolescents. J Consult Clin Psychol. 2003;71(4):692–700.

    PubMed  Article  Google Scholar 

  17. Read JP, Griffin MJ, Wardell JD, Ouimette P. Coping, PTSD symptoms, and alcohol involvement in trauma-exposed college students in the first three years of college. Psychol Addict Behav J Soc Psychol Addict Behav. 2014;28(4):1052–64.

    Article  Google Scholar 

  18. American Psychiatric Association. Diagnostic and statistical manual of mental disorders: DSM-5. 5th ed. Washington, D.C.: American Psychiatric Association; 2013.

    Book  Google Scholar 

  19. ESPASD Group. ESPAD Report 2019: Results from the European school survey project on alcohol and other drugs, Luxembourg: Publications Office of the European Union; 2020. (EMCDDA Joint Publications).

  20. Müller CP, Schumann G. Drugs as instruments: a new framework for non-addictive psychoactive drug use. Behav Brain Sci. 2011;34(6):293–310.

    PubMed  Article  Google Scholar 

  21. Redish AD, Jensen S, Johnson A. A unified framework for addiction: vulnerabilities in the decision process. Behav Brain Sci. 2008;31(4):415–87.

    PubMed  PubMed Central  Article  Google Scholar 

  22. Khantzian EJ. The self-medication hypothesis of addictive disorders: focus on heroin and cocaine dependence. Am J Psychiatry. 1985;142(11):1259–64.

    CAS  PubMed  Article  Google Scholar 

  23. Khantzian EJ. The self-medication hypothesis of substance use disorders: a reconsideration and recent applications. Harv Rev Psychiatry. 1997;4(5):231–44.

    CAS  PubMed  Article  Google Scholar 

  24. Alexander AC, Ward KD. Understanding postdisaster substance use and psychological distress using concepts from the self-medication hypothesis and social cognitive theory. J Psychoactive Drugs. 2018;50(2):177–86.

    PubMed  Article  Google Scholar 

  25. Basedow LA, Kuitunen-Paul S, Wiedmann MF, Roessner V, Golub Y. Self-reported PTSD is associated with increased use of MDMA in adolescents with substance use disorders. Eur J Psychotraumatol. 2021;12(1):1968140.

  26. Fegert J, Freyberger HJ. Post-traumatic stress disorders (PTSD) and trauma sequel disorders in adolescence. Fortschr Neurol Psychiatr. 2019;87(11):638–41.

    PubMed  Article  Google Scholar 

  27. Garrey SK, Welch AE, Jacobson MH, Brackbill RM, Gargano LM. The intentional self-medication of 9/11-related PTSD symptoms with alcohol: 15 years after the disaster. Int J Environ Res Public Health. 2020;17(15):5327.

    CAS  PubMed Central  Article  Google Scholar 

  28. Lammers J, Kuntsche E, Engels RCME, Wiers RW, Kleinjan M. Mediational relations of substance use risk profiles, alcohol-related outcomes, and drinking motives among young adolescents in the Netherlands. Drug Alcohol Depend. 2013;133(2):571–9.

    PubMed  Article  Google Scholar 

  29. Shin SH, Jiskrova GK, Yoon SH, Kobulsky JM. Childhood maltreatment, motives to drink and alcohol-related problems in young adulthood. Child Abuse Negl. 2020;108: 104657.

    PubMed  Article  Google Scholar 

  30. Ullman SE, Relyea M, Peter-Hagene L, Vasquez AL. Trauma histories, substance use coping, PTSD, and problem substance use among sexual assault victims. Addict Behav. 2013;38(6):2219–23.

    PubMed  PubMed Central  Article  Google Scholar 

  31. Staiger PK, Melville F, Hides L, Kambouropoulos N, Lubman DI. Can emotion-focused coping help explain the link between posttraumatic stress disorder severity and triggers for substance use in young adults? J Subst Abuse Treat. 2009;36(2):220–6.

    PubMed  Article  Google Scholar 

  32. Steinberg AM, Brymer MJ, Decker KB, Pynoos RS. The university of California at Los Angeles post-traumatic stress disorder reaction index. Curr Psychiatry Rep. 2004;6(2):96–100.

    PubMed  Article  Google Scholar 

  33. Ruf M, Schauer M, Elbert T. UPID : UCLA PTSD Index for DSM IV (Child version, revision 1, deutsche Fassung). 2011

  34. Sheehan DV, Sheehan KH, Shytle RD, Janavs J, Bannon Y, Rogers JE, et al. Reliability and validity of the Mini international neuropsychiatric interview for children and adolescents (MINI-KID). J Clin Psychiatry. 2010;71(3):313–26.

    PubMed  Article  Google Scholar 

  35. Plattner B, Giger J, Bachmann F, Brühwiler K, Steiner H, Steinhausen H-C, et al. Psychopathology and offense types in detained male juveniles. Psychiatry Res. 2012;198(2):285–90.

    PubMed  Article  Google Scholar 

  36. Golub Y, Basedow LA, Meiron Zwipp J, Kuitunen-Paul S, Roessner V. DELTA—Dresdner multimodale therapie für jugendliche mit chronischem suchtmittelkonsum. 1st ed. Boston: Hogrefe; 2021.

    Book  Google Scholar 

  37. Ledesma R, Valero-Mora P. Determining the number of factors to retain in EFA: an easy-to-use computer program for carrying out parallel analysis. Pract Assess Res Eval. 2019;12(1):2.

    Google Scholar 

  38. Rosseel Y. lavaan: an r package for structural equation modeling. J Stat Softw. 2012;48(2):1–36.

    Article  Google Scholar 

  39. RStudio Team. RStudio: Integrated development environment for R. Boston, MA: RStudio, PBC.; 2020.

  40. Schermelleh-Engel K, Moosbrugger H, Müller H. Evaluating the fit of structural equation models: tests of significance and descriptive goodness-of-fit measures. Methods Psychol Res. 2003;8(2):23–74.

    Google Scholar 

  41. Conover WJ. Practical nonparametric statistics. 3rd ed. Hoboken: Wiley; 1999.

    Google Scholar 

  42. Hayes A. Introduction to mediation, moderation, and conditi: a regression-based approach. 2nd ed. New york: Guilford Publications; 2018.

    Google Scholar 

  43. Verheyden SL, Hadfield J, Calin T, Curran VH. Sub-acute effects of MDMA (±3,4-methylenedioxymethamphetamine, ‘ecstasy’) on mood: evidence of gender differences. Psychopharmacology. 2002;161(1):23–31.

    CAS  PubMed  Article  Google Scholar 

  44. Schifano F, Di Furia L, Forza G, Minicuci N, Bricolo R. MDMA ('ecstasy’) consumption in the context of polydrug abuse: a report on 150 patients. Drug Alcohol Depend. 1998;52(1):85–90.

    CAS  PubMed  Article  Google Scholar 

  45. Lieb R, Schuetz CG, Pfister H, von Sydow K, Wittchen H-U. Mental disorders in ecstasy users: a prospective-longitudinal investigation. Drug Alcohol Depend. 2002;68(2):195–207.

    PubMed  Article  Google Scholar 

  46. Dworkin ER, Wanklyn S, Stasiewicz PR, Coffey SF. PTSD symptom presentation among people with alcohol and drug use disorders: comparisons by substance of abuse. Addict Behav. 2018;76:188–94.

    PubMed  Article  Google Scholar 

  47. Hawn SE, Cusack SE, Amstadter AB. A systematic review of the self-medication hypothesis in the context of posttraumatic stress disorder and comorbid problematic alcohol use. J Trauma Stress. 2020;33(5):699–708.

    PubMed  PubMed Central  Article  Google Scholar 

  48. Jansen KLR. Ecstasy (MDMA) dependence. Drug Alcohol Depend. 1999;53(2):121–4.

    CAS  PubMed  Article  Google Scholar 

  49. Moonzwe LS, Schensul JJ, Kostick KM. The role of MDMA (Ecstasy) in coping with negative life situations among urban young adults. J Psychoactive Drugs. 2011;43(3):199–210.

    PubMed  PubMed Central  Article  Google Scholar 

  50. Scott RM, Hides L, Allen JS, Lubman DI. Coping style and ecstasy use motives as predictors of current mood symptoms in ecstasy users. Addict Behav. 2013;38(10):2465–72.

    PubMed  Article  Google Scholar 

  51. Boys A, Marsden J, Strang J. Understanding reasons for drug use amongst young people: a functional perspective. Health Educ Res. 2001;16(4):457–69.

    CAS  PubMed  Article  Google Scholar 

  52. Thal SB, Lommen MJJ. Current perspective on MDMA-assisted psychotherapy for posttraumatic stress disorder. J Contemp Psychother. 2018;48(2):99–108.

    PubMed  PubMed Central  Article  Google Scholar 

  53. Sessa B, Higbed L, Nutt D. A Review of 3,4-methylenedioxymethamphetamine (MDMA)-Assisted Psychotherapy. Front Psychiatry. 2019

  54. Amoroso T. The psychopharmacology of ±3,4 methylenedioxymethamphetamine and its role in the treatment of posttraumatic stress disorder. J Psychoactive Drugs. 2015;47(5):337–44.

    PubMed  Article  Google Scholar 

  55. Mitchell JM, Bogenschutz M, Lilienstein A, Harrison C, Kleiman S, Parker-Guilbert K, et al. MDMA-assisted therapy for severe PTSD: a randomized, double-blind, placebo-controlled phase 3 study. Nat Med. 2021;27(6):1025–33.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  56. Mithoefer MC, Mithoefer AT, Feduccia AA, Jerome L, Wagner M, Wymer J, et al. 3,4-methylenedioxymethamphetamine (MDMA)-assisted psychotherapy for post-traumatic stress disorder in military veterans, firefighters, and police officers: a randomised, double-blind, dose-response, phase 2 clinical trial. Lancet Psychiatry. 2018;5(6):486–97.

    PubMed  Article  Google Scholar 

  57. Klee H, Reid P. Drug use among the young homeless: coping through self-medication. Health (N Y). 1998;2(2):115–34.

    Google Scholar 

  58. Wiedmann M, Atzendorf J, Basedow LA, Roessner V, Golub Y, Kuitunen-Paul S. Substanzkonsum, Störungen durch Substanzkonsum und begleitende psychische Störungen bei Jugendlichen. Z Für Kinder- Jugendpsychiatrie Psychother. 2022.

    Article  Google Scholar 

  59. Patrick ME, Schulenberg JE, O’malley PM, JohnstonBachman LDJG. Adolescents’ reported reasons for alcohol and marijuana use as predictors of substance use and problems in adulthood*. J Stud Alcohol Drugs. 2011;72(1):106–16.

    PubMed  PubMed Central  Article  Google Scholar 

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Open Access funding enabled and organized by Projekt DEAL. The Sächsische Aufbaubank—Förderbank- (grant 100362999 to YG), funded this study. The funding body had no role in designing the study, data collection, analysis and interpretation of the data, or writing the manuscript.

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Authors and Affiliations



Conceptualization: LAB, Yulia Golub and SK-P. Data Curation: LAB and SK-P. Formal Analysis: LAB and SK-P. Funding Acquisition: YG. Investigation: LAB, MFW and SK-P. Methodology: LAB, YG and SK-P. Project Administration: LAB, YG and SK-P. Resources: VR. Supervision: VR, YG and SK-P. Validation: LAB, MFW, Veit Roessner, YG and SK-P. Visualization: LAB. Writing—Original Draft Preparation: LAB. Writing—Review & Editing: LAB, MFW, VR, YG and SK-P. All authors read and approved the final manuscript.

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Correspondence to Lukas Andreas Basedow.

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The study was conducted in accordance with the Declaration of Helsinki and all procedures were approved by the Institutional Review Board of the University Hospital C. G. Carus Dresden (EK 66022018).

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Competing interests

Regarding the past 36 months, the authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Supplementary Information

Additional file 1: Table S1.

Shapiro-Wilk test for normality of the 5 outcome variables. Table S2. Results from the confirmatory factor analysis. Table S3. The 10 use motive items from the self-designed questionnaire.

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Basedow, L.A., Wiedmann, M.F., Roessner, V. et al. Coping motives mediate the relationship between PTSD and MDMA use in adolescents with substance use disorders. Addict Sci Clin Pract 17, 46 (2022).

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  • Addiction
  • Drugs
  • Ecstasy
  • Self-medication
  • Trauma disorders