Brynte et al. BMC Psychiatry (2022) 22:625 https://doi.org/10.1186/s12888-022-04259-6 RESEARCH Open Access The clinical course of comorbid substance use disorder and attention deficit/hyperactivity disorder: protocol and clinical characteristics of the INCAS study Christoffer Brynte1*, Myriam Aeschlimann2, Csaba Barta3, Alex Hendikus Abraham Begeman4, Amanda Bäcker1, Cleo Lina Crunelle5, Constanza Daigre6,7,8,9, Laura De Fuentes‑Merillas10, Zsolt Demetrovics11,12, Geert Dom13,14, Lara Grau López6,7,8,9, Romain Icick15, Brian Johnson16, Peter Joostens17, Máté Kapitány‑Fövény18,19, Emily Karsinti20, Falk Kiefer21,22, Maija Konstenius1, Frances R. Levin23,24, Mathias Luderer25, Wiebren Markus26, Frieda Matthys5, Franz Moggi27, Raul Felipe Palma‑Alvarez6,7,8,9, Maria Paraskevopoulou28, J. Antoni Ramos‑Quiroga6,7,8,9, Arnt Schellekens28,29, Leila M. Soravia27,30, Norman Therribout20, Anil Thomas31,32, Geurt van de Glind33, Michiel Willem van Kernebeek5, Sabine Vollstädt‑Klein21,22, Florence Vorspan15, Wim van den Brink34 and Johan Franck1 Abstract Background: Substance use disorders (SUD) often co-occur with attention deficit hyperactivity disorder (ADHD). Although the short-term effects of some specific interventions have been investigated in randomized clinical trials, little is known about the long-term clinical course of treatment-seeking SUD patients with comorbid ADHD. Aims: This paper presents the protocol and baseline clinical characteristics of the International Naturalistic Cohort Study of ADHD and SUD (INCAS) designed and conducted by the International Collaboration on ADHD and Sub‑ stance Abuse (ICASA) foundation. The overall aim of INCAS is to investigate the treatment modalities provided to treatment-seeking SUD patients with comorbid ADHD, and to describe the clinical course and identify predictors for treatment outcomes. This ongoing study employs a multicentre observational prospective cohort design. Treatment-seeking adult SUD patients with comorbid ADHD are recruited, at 12 study sites in nine different countries. During the follow-up period of nine months, data is collected through patient files, interviews, and self-rating scales, targeting a broad range of cognitive and clinical symptom domains, at baseline, four weeks, three months and nine months. Results: A clinically representative sample of 578 patients (137 females, 441 males) was enrolled during the recruit‑ ment period (June 2017-May 2021). At baseline, the sample had a mean age (SD) of 36.7 years (11.0); 47.5% were inpa‑ tients and 52.5% outpatients; The most prevalent SUDs were with alcohol 54.2%, stimulants 43.6%, cannabis 33.1%, *Correspondence: christoffer.brynte@ki.se 1 Department of Clinical Neuroscience, Centre for Psychiatry Research, Karolinska Institutet and Stockholm Health Care Services, Region Stockholm, Sweden Full list of author information is available at the end of the article © The Author(s) 2022. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://​creat​iveco​mmons.​org/​licen​ses/​by/4.​0/. The Creative Commons Public Domain Dedication waiver (http://​creat​iveco​ mmons.​org/​publi​cdoma​in/​zero/1.​0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. Brynte et al. BMC Psychiatry (2022) 22:625 Page 2 of 8 and opioids 14.5%. Patients reported previous treatments for SUD in 71.1% and for ADHD in 56.9%. Other comorbid mental disorders were present in 61.4% of the sample: major depression 31.5%, post-traumatic stress disorder 12.1%, borderline personality disorder 10.2%. Conclusions: The first baseline results of this international cohort study speak to its feasibility. Data show that many SUD patients with comorbid ADHD had never received treatment for their ADHD prior to enrolment in the study. Future reports on this study will identify the course and potential predictors for successful pharmaceutical and psy‑ chological treatment outcomes. Trial registration: ISRCTN15998989 20/12/2019. Keywords: ADHD, SUD, Comorbidity Introduction regarding its safety for the treatment of patients with Treatment-seeking patients with substance use disor- SUD + ADHD [23]. ders (SUD) are approximately three times more likely Few studies have investigated the efficacy of non-phar- to meet criteria for attention-deficit/hyperactivity macological treatments for patients with SUD + ADHD. disorder (ADHD)the general population [1–4]. Stud- Although cognitive behavioural therapy (CBT) has been ies have shown that SUD with comorbid ADHD, com- shown to be effective in reducing ADHD symptom in pared to SUD only, is associated with a more severe, patients with ADHD only [24], patients with comorbid chronic, and complex course of illness. This includes SUD have been excluded from these studies. However, an earlier onset of substance use [5, 6], a higher degree of RCT comparing integrated cognitive behavioural ther- poly-substance use [6, 7], more psychiatric comorbid- apy (ICBT) with standard CBT was recently published ity [8], chronicity [6, 7] and poorer SUD treatment out- and found that ICBT and CBT were equally effective in comes [7, 9, 10]. Moreover, patients with SUD + ADHD reducing substance use, while ICBT was more effective in have more psychosocial problems, higher number of reducing ADHD symptoms [25]. A qualitative study sug- care needs and higher rates of suicide-attempts than gests that patients with ADHD + SUD wish for a coach- with SUD only [11, 12]. Finally, studies suggest that ing attitude and a dialectical behavioural therapy-based SUD + ADHD patients have more severe cognitive defi- skills training has shown varying results [26, 27]. To the cits than patients with ADHD only [13–17]. best of our knowledge, the effects of other non-pharma- Although co-occurrence of ADHD in SUD patients cological interventions, have not yet been investigated in has been associated with a poor prognosis of both con- ADHD + SUD. ditions, little is known about the long-term course of Overall, despite evidence that pharmacological and treatment-seeking patients with SUD + ADHD, espe- non-pharmacological treatment should be provided cially in routine clinical practice [9, 10, 18, 19]. The to SUD individuals with comorbid ADHD, very little short-term efficacy of pharmacological treatment of is known regarding the predictors for successful treat- patients with SUD + ADHD has been investigated ment outcomes in this debilitating condition. To fill this in randomized controlled trials (RCT) with conflict- knowledge gap and inform future randomized trials, as ing results [20]. A meta-analysis by Cunill et al. (2015) well as clinicians and policymakers, the International found that standard doses of ADHD medication may Collaboration on ADHD and Substance Abuse (ICASA) lead to a significant, but small reduction of core ADHD foundation (www.​adhda​ndsub​stanc​eabuse.​org) designed symptoms, with limited to no effects on substance use the International Naturalistic Cohort Study of ADHD [10]. However, two later RCTs, not included in the and Substance Use Disorders Study (INCAS). The aims meta-analysis by Cunill et al. (2015), that applied higher of this observational, multi-centre, longitudinal study is doses of extended-release mixed amphetamine salts or to describe the treatment modalities provided to indi- OROS methylphenidate did find a significant reduction viduals with SUD + ADHD entering SUD treatment, and of both ADHD symptoms and substance use, suggest- to identify predictors of successful treatment outcomes, ing that higher doses of stimulants might be warranted as measured by retention in treatment, the reduction in in patients with comorbid stimulant use disorder substance use and ADHD symptoms and the global func- and ADHD [21, 22]. Although stimulant treatment is tioning at three and nine-months follow-up. Further- not linked to the development of SUD among ADHD more, the safety profile of pharmacological treatments patients, and early childhood stimulant treatment may will be recorded. The results will be relevant to gener- even prevent the development of adult SUD, the abuse ate hypotheses for future treatment trials. The current potential of this class of medication has raised concerns paper describes the study protocol of this ongoing study Brynte et al. BMC Psychiatry (2022) 22:625 Page 3 of 8 and presents the baseline characteristics of the study Agency, 2002) and the General Data Protection Regu- participants. lation (GDPR). Information on provided treatment modalities, such as psychological and pharmacological Methods treatments, including stimulant dosing, sociodemo- Participants graphic data (housing, employment, level of education Participants were recruited during the recruitment etc.), age, gender, previous treatments, other psychiat- period (June 2017 – May 2021) at 12 different addiction ric comorbidities, adverse events (in relation to ADHD treatment services in nine countries: Belgium, France, medications) and misuse/diversion of prescriptive Germany, Hungary, the Netherlands, Spain, Sweden, drugs was collected by clinicians at each site through Switzerland, and the USA. At each participating addic- patient interviews and patient files upon entering the tion treatment centre, patients (age ≥ 18 years) with mod- data into the eCRF. erate to severe SUD and with comorbid ADHD according Treatment retention is defined as the number of days to DSM-5, and thus meeting the inclusion criteria, were from the starting date of the new treatment episode invited to participate at the start of a new treatment epi- until (premature) termination of treatment in accord- sode; defined as the first visit in the last three months or ance with or against the clinicians’ advice. Substance the first visit after receiving the diagnosis of adult ADHD. use during the 30 days before baseline and each fol- There were no formal exclusion criteria except incapabil- low-up visit, is quantified through the TimeLine Fol- ity to complete the assessments. lowBack interview (TLFB: Sobell and Sobell 1992), As stated in the pre-registered study protocol available counting the number of standard drinks per drinking at https://​doi.​org/​10.​1186/​ISRCT​N1599​8989, we aimed day and defining a heavy drinking day as a day with at to enrol 600 participants from 12 different sites in the fol- least five standard drinks (12 g alcohol/drink). Use of lowing countries: Belgium, France, Germany, Hungary, other substances is measured dichotomously, i.e., each the Netherlands, Spain, Sweden, Switzerland, and the day of use is coded “yes” or “no” respectively, regardless USA. This study is expected to be finished in May 2022. of the amount that was used on that day. Quantifica- Participants received detailed written and oral study tion of ADHD symptoms is performed at baseline and information before providing written informed consent. at each follow-up visit with the expanded version of the The study was approved by the Swedish Ethical Review Adult ADHD Self-Report Scale (ASRS) [23, 24]. Overall Authority (2017/240–31) and is conducted in accordance global functioning is assessed by the clinician with the with the Declaration of Helsinki – Ethical Principles for Clinical Global Impression Severity/Improvement scale Medical Research Involving Humans Subjects. All partic- (CGI-S/I) [25] and by the participant with the EuroQol- ipating study sites also received formal approval by their 5D (EQ5D) [26]. respective local medical ethical committees. In addition to the aforementioned predictors and out- come measures, seven self-rating scales are used at each Study design assessment, to provide a refined dimensional architecture This ongoing prospective international cohort study of ADHD + SUD and to identify potential mediators of employs a naturalistic observational design in treatment treatment outcomes, including retention: 1) Self-efficacy seeking adult SUD patients with comorbid adult ADHD. through a 1-item question (“How confident are you that During the follow-up period of nine months, data is col- you will achieve the necessary behavioural change in the lected through patient files, interviews and self-rating future – let’s say within the next 6 to 9 months?”). Based scales at admission to treatment (baseline), four weeks, on the self-efficacy question, patients were also asked two three months and at nine months follow-up. Data entry is additional questions, one on motivation for behavioural monitored by a central project coordinator monthly. change related to substance use and one on the relevance of behavioural change related to substance use [28, 29]. 2) Instruments Craving through a 3-item questionnaire [30, 31], 3) anger Assessment of ADHD, SUD and other comorbidities and aggression through an 8-item questionnaire,4) sensi- are done in accordance with local clinical routines and tivity to reward through the 17-item sensitivity to reward regulations. Information on the diagnostic procedure, scale of the shortened version of the Sensitivity to Pun- e.g., the use of structured interviews, along with all ishment and Sensitivity to Reward Questionnaire [32], 5) other data collection, is entered and stored in a web- severity of nicotine use through the 6-item version of the Fagerström Test for Nicotine Dependence [33], 6) emo- by Clindox ®, which fits within the rules of regulation based electronic case report form (eCRF), provided tion regulation through the 16-item short version of the for Good Clinical Practice (GCP: European Medicines Difficulties in Emotion Regulation Scale [34], and 7) reli- gious salience through a 3-item questionnaire [35].. Brynte et al. BMC Psychiatry (2022) 22:625 Page 4 of 8 Statistical analysis stress disorder and borderline personality disorder. Soci- Analyses are mainly descriptive, describing the popula- odemographic data is presented in Table 1, and clinical tion at baseline and follow-up visits. Given the non-inter- characteristics and information on treatment, at baseline, ventional observational design, the targeted sample size are presented in Tables 2 and 3, respectively. of enrolling 600 participants is not based on statistical power, but rather on the goal of providing a solid descrip- Discussion tion of the specific patient population and variation in INCAS is a prospective observational cohort study, with- treatment modalities and clinical course. out prior funding, of treatment-seeking individuals with In the current paper baseline characteristics are pre- SUD and comorbid adult ADHD, designed to describe sented. In future publications additional analyses of the clinical course in different treatment settings and baseline predictors, as independent variables of the main countries. It will provide a rich data set on the treatment outcomes (retention to treatment, substance use as meas- modalities offered, the clinical course of the study popu- ured by TLFB, and ASRS score) as dependent variables, lation, and the potential influence of age, gender, primary will be performed through survival analysis, regression substance of abuse, and other psychiatric comorbidities models and mixed effect models. Other inferential sta- on treatment outcomes. Moreover, the study includes tistical analyses will be considered using both univariate longitudinal data on a broad range of psychological and multivariate models and considering the naturalistic measures, targeting a diverse set of cognitive domains (non-randomized) nature of the study using propensity and symptoms, including core deficits seen in ADHD and score methods. SUD. The power of the proposed analyses will depend on In our sample there is an expected male-to-female factors such as the number of treatment groups, the ratio of approximately 3:1, although sex differences in distribution of patients between the treatment groups, the differences in treatment effect between the different treatment modalities, and missing data. In the optimal Table 1 Sociodemographic data. Age is presented as mean with case when there are only two treatment groups of interest standard deviation (e.g., with and without pharmacotherapy), with approxi- N = 578 mately 300 patients per group, there will be approxi- mately 80% power to detect a small to moderate effect Age 36.7 (11.0) size (Cohen’s d > 0.3) at a two-sided 5% significance level. Female/Male 137/441 (23.7%/76.3%) However, less favourable distributions and possibly more Housing treatment modalities may be found, and thus larger effect Own accommodation 66.1% sizes are needed to be detectable. Homeless 3.5% Room 19.9% Temporary housing 7.3% Results Unknown 3.3% Five hundred and seventy-eight participants, diagnosed Living alone 45.2% with ADHD and comorbid SUD, were enrolled during Living with partner/parent/friend (or anyone) 52.9% the study period (June 2017-May 2021) at 12 addiction Unknown 1.9% treatment centres in nine countries: Belgium (n = 65), Educational level France (n = 8), Germany (n = 56), Hungary (n = 15), the Not completed elementary school 2.1% Netherlands (n = 72), Spain (n = 34), Sweden (n = 152), Completed elementary school 25.6% Switzerland (n = 135) and in the USA (n = 41). Partici- Completed high school 38.9% pants received treatment either as inpatients (47.5%) or Completed tertiary education 30.4% outpatients (52.5%). Unknown 2.9% The majority of the participants were male, and at Employment last 30 days enrolment to the study 53.8% were either unemployed Student 4.3% or on sick leave. Mean age (SD) at baseline was 36.7 Income through work 40.3% (11) years and the most prevalent SUDs were with alco- Unemployed/sick-leave 53.8% hol, stimulants, cannabis and opioids. Most participants Unknown 1.6% reported that they had received previous treatment for Children below 18 years old in the household SUD and/or ADHD. Other comorbid psychiatric disor- Yes 19.9% ders were present in most cases, where the most common No 77.3% comorbidities were major depression, post-traumatic Unknown 2.8% Brynte et al. BMC Psychiatry (2022) 22:625 Page 5 of 8 Table 2 Clinical characteristics. N = 578 Table 3 Current and previous treatment for ADHD and SUD Age when ADHD diagnose was attained Previously received ADHD treatment 0–12 16.3% Yes 56.9% 13–19 12.1% No 40.8%    ≥ 20 69.2% Unknown 2.3% Unknown 2.4% Received pharmacological ADHD treatment before 18 years old ≥ 1 biological parent with SUD Yes 21.3% Yes 44.8% No 51.0% No 44.6% Unknown 27.6% Unknown 10.5% Currently receives ADHD treatment (at inclusion) Moderate to severe SUD: Pharmacological 34.9% Alcohol 54.2% Psychological 20.9% Cannabis 33.2% No 60.7% Hallucinogens 2.4% Unknown 1.7% Inhalants 3.1% Previously received SUD treatment Opioids 14.5% Yes 71.1% Stimulants 43.6% No 24.0% Sedatives/hypnotics/anxiolytics 9.4% Unknown 4.9% Tobacco 63.5% Multiple SUDs (tobacco not included)    ≥ 2 co-current SUDs (moderate to severe) 46.9% treatment. This speaks to the importance of screening    ≥ 3 co-current SUDs (moderate to severe) 14.0% for ADHD in SUD treatment-seeking patients. Further- Psychiatric co-morbidity (other than ADHD/SUD) more, our sample partly consists of participants with a Yes 61.4% severe and complex psychiatric burden, where a major- No 36.0% ity presented with at least one other psychiatric comor- Unknown 2.6% bidity (61.4%), and almost half our sample (46.9%) were Antisocial personality disorder 2.2% diagnosed with two or more co-current SUDs. This will Anxiety disorders 5.5% allow us to explore subgroups within this population Autism spectrum disorder 6.1% and possibly identify important predictors for treatment Bipolar and related disorders 4.3% outcomes. Borderline personality disorder 10.2% Overall, the presented overview of the baseline charac- Depressive disorders 31.5% teristics, reveals that our sample consists of participants Disruptive, impulse-control, and conduct disorders 2.4% with a diverse distribution of socio-economic, psycho- Dissociative disorders 0.5% social, and educational backgrounds. This will improve Feeding and eating disorders 1.7% inference and serve to the generalizability of our findings. Intellectual disability 2.2% In addition, our sample consists of patients with differ- Motor disorder (e.g., Tourette’s) 0.7% ent clinical backgrounds, psychiatric co-morbidities, and Obsessive–compulsive and related disorders 2.1% severity levels, where symptoms and severity of symp- Schizophrenia spectrum and other psychotic disorders 1.7% toms is collected with a high level of detail. Somatic symptom and related disorders 1.2% The main strengths of this study are the naturalistic Trauma- and stressor-related disorders (e.g., PTSD) 12.1% design and the related ecological validity, the use of an identical study design with the same assessments at each treatment facility in various countries, and the large sam- SUD and ADHD are poorly understood [36]. Given ple size allowing subgroup analyses and comparisons. the large sample size in the present study, including a However, the naturalistic design is also one of the most variety of detailed longitudinal data, this dataset pro- important limitations. For instance, the treatments are vides an opportunity to explore sex differences in SUD not blinded nor randomly allocated, thus causing infer- patients with comorbid ADHD, and to analyse the asso- ential challenges and difficulties in controlling for selec- ciation with treatment outcome measures. A large pro- tion and information bias and/or confounding. Finally, portion (40.8%) reported that they had not previously a limitation is that different sites vary in diagnostic and received any ADHD treatment prior to enrolment in our treatment procedures. The main purpose of the study is, study, while most (71.1%) had previously received SUD however, descriptive and aims to describe this specific Brynte et al. BMC Psychiatry (2022) 22:625 Page 6 of 8 patient population and the treatments provided to them. Ethical Review Authority (2017/240–31) and was conducted in accordance with the Declaration of Helsinki – Ethical Principles for Medical Research The study will provide information on treatment effects Involving Humans Subjects. and the clinical course of these disorders with simultane- ously collected data on substance use, ADHD-symptoms, Consent for publication Not applicable. and quality of life. Data analysis will consider limitations, including the Competing interests use of propensity scores to control for baseline differ- LGL has received speaker honorariums from Janssen-Cilag, Lundbeck, Servier, Otsuka, and Pfizer. RI has received honorarium by Pierre Fabre© paid directly ences between groups. Moreover, given the high num- to the non-profit association “Espace Murger”. FRL receives grant support ber of patients and the level of detail in which data is from the NIDA, SAMHSA and US World Meds as well as a consultant for Major collected, it will be possible to analyse associations and League Baseball. She also receives medication from Indivior for research. In addition, FRL was an unpaid member of a Scientific Advisory Board for provide insight on treatment effects on a broad range of Alkermes, Indivior, Novartis, Teva, and US WorldMeds but did not personally treatment modalities and outcomes. Possible statistical receive any compensation in the form of cash payments (honoraria/consult‑ inferential challenges of the findings will be further dis- ing fees) or food/beverage (she declined food/beverages in each circum‑ stance) nor receive compensation in the form of travel reimbursement. ML cussed in subsequent papers. received honoraria for talks and participation in advisory boards for Takeda In conclusion, these first results speak to the feasibility and MEDICE / Arzneimittel Pütter GmbH. RFPA has received speaker hono‑ of the study, despite no prior funding, and will provide rariums from Angelini, Exeltis, Lundbeck, MSD, Mundipharma, and Takeda. J.A.R.Q was on the speakers’ bureau and/or acted as consultant for Janssen- an overall representative, description of the characteris- Cilag, Novartis, Shire, Takeda, Bial, Shionogi, Sincrolab, Novartis, BMS, Medice, tics and the clinical course of treatment-seeking patients Rubió, Uriach and Raffo in the last 3 years. He also received travel awards (air with SUD and comorbid adult ADHD at the international tickets + hotel) for taking part in psychiatric meetings from Janssen-Cilag, Rubió, Shire, Takeda, Shionogi, Bial and Medice. The Department of Psychiatry level. In addition, this study will provide information on chaired by him received unrestricted educational and research support from potential predictors for successful treatment outcomes the following companies in the last 3 years: Janssen- Cilag, Shire, Oryzon, for different treatment modalities and thus hypotheses Roche, Psious, and Rubió. FV received congress fees paid by pharmaceutical companies (CAMURUS AB, RECORDATI, ACCORD Pharmaceutical) and funding for future randomized controlled trials. received through a non-profit association for medical research (Association Robert Debré pour la Recherche Médicale). All other authors declare that they have no competing interests. Abbreviations SUD: Substance Use Disorder; ADHD: Attention Deficit/Hyperactivity Disorder; Author details INCAS: International Naturalistic Cohort Study of ADHD and SUD; ICASA: 1 Department of Clinical Neuroscience, Centre for Psychiatry Research, Karolin‑ International Collaboration on ADHD and Substance Abuse; RCT​: Randomized ska Institutet and Stockholm Health Care Services, Region Stockholm, Sweden. Controlled Trial; CBT: Cognitive Behavioural Therapy; ICBT: Integrated Cognitive 2 University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Behavioural Therapy; DSM-5: Diagnostic and Statistical Manual of Mental Dis‑ Switzerland. 3 Department of Molecular Biology, Institute of Biochemistry orders; eCRF: Electronic Case Report Form; TLFB: Time-Line Follow-Back; ASRS: and Molecular Biology, Semmelweis University, Budapest, Hungary. 4 De Hoop Adult ADHD Self-Report Scale. Ggz, Provincialeweg 70, 3328KP Dordrecht, The Netherlands. 5 Department of Psychiatry, Vrije Universiteit Brussel (VUB), Universitair Ziekenhuis Brussel, Acknowledgements 1090 Jette, Belgium. 6 Department of Psychiatry, Addiction and Dual Diagnosis CB was supported by the Stockholm County Council (combined residency Section, Hospital Universitari Vall d’Hebron, Barcelona, Spain. 7 Psychiatry and PhD training program). We thank Sofie Verspreet, Meike van Vlastuin, Group, Mental Health and Addiction, Vall d’Hebron Research Institute (VHIR), Jacomine de Boer, Michelle van Dusseldorp, Karolien Van der Donck, Anna Barcelona, Spain. 8 Biomedical Network Research Centre On Mental Health Boormans, Cor Verbrugge, Peter Greven, Pol Ibañez Jimenez, Tamás Kárpáti, (CIBERSAM), Madrid, Spain. 9 Department of Psychiatry and Forensic Medicine, Attila Császár, Eva Debusscher, Maeva Fortias, Lucia Romo, Sara Thisner Lind‑ Autonomous University of Barcelona, Barcelona, Spain. 10 Novadic-Kentron stedt, Hannes stenström, Ebba thurezon, Miklos Szabo and Moa Nordin for Addiction Care; Nijmegen Institute for Scientist Practitioners in Addiction, excellent assistance in conducting this study. Nijmegen, the Netherlands. 11 Institute of Psychology, ELTE Eötvös Loránd University, Budapest, Hungary. 12 Centre of Excellence in Responsible Gaming, Authors’ contributions University of Gibraltar, Gibraltar, Gibraltar. 13 University of Antwerp, Ant‑ This study is designed and conducted by the ICASA foundation. CB wrote the werp, Belgium. 14 PC Multiversum, Boechout, Belgium. 15 Université de Paris first draft of this manuscript and analysed data. All authors have been involved Cité, Paris, France. 16 SUNY Upstate University, Syracuse, USA. 17 Alexianen in the study design and/or data acquisition and interpretation of the data. Zorggroep Tienen, Tienen, Belgium. 18 Faculty of Health Sciences, Semmel‑ All authors have contributed to writing the manuscript. All authors read and weis University, Budapest, Hungary. 19 National Institute of Mental Health, approved the final manuscript. Neurology and Neurosurgery – Nyírő Gyula Hospital, Budapest, Hungary. 20 Université Paris-Nanterre, CliPsyD Laboratory FR and APHP, Fernand Widal Funding Hospital, Universitary Department of Psychiatry and Addictology, Paris, France. Open access funding provided by Karolinska Institute. This study has no funding. 21 Department of Addictive Behavior and Addiction Medicine, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Man‑ Availability of data and materials nheim, Germany. 22 Mannheim Center for Translational Neurosciences (MCTN), The datasets used and/or analysed during the current study are available from Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany. the corresponding author on reasonable request. 23 Vagelos College of Physicians and Surgeons, New York City, USA. 24 New York State Psychiatric Institute, New York City, USA. 25 Department of Psychiatry, Psy‑ chosomatic Medicine and Psychoterapy, University Hospital Frankfurt, Goethe Declarations University, Frankfurt am Main, Germany. 26 Iriszorg Addiction Care, Nijmegen Institute for Scientist Practitioners in Addiction, Nijmegen, the Netherlands. Ethics approval and consent to participate 27 University Hospital of Psychiatry, Translational Research Center, University Participants received detailed written and oral study information before of Bern, Bern, Switzerland. 28 Department of Psychiatry, RadboudumcDon‑ providing written informed consent. The study was approved by the Swedish ders Institute for Brain, Cognition and Behavior, Nijmegen, the Netherlands. Brynte et al. BMC Psychiatry (2022) 22:625 Page 7 of 8 29 Nijmegen Institute for Scientist Practitioners in Addiction, Nijmegen, the 16. Crunelle CL, Veltman DJ, van Emmerik-van OK, Booij J, van den Brink W. Netherlands. 30 Südhang Clinic, Kirchlindach, Switzerland. 31 Mt. Sinai, Icahn Impulsivity in adult ADHD patients with and without cocaine depend‑ School of Medicine, New York City, USA. 32 NYU Grossman School of Medicine, ence. Drug Alcohol Depend. 2013;129(1–2):18–24. New York City, USA. 33 University of Applied Sciences-Utrecht, Utrecht, the 17. Miguel CS, Martins PA, Moleda N, Klein M, Chaim-Avancini T, Gobbo Netherlands. 34 Amsterdam University Medical Centers, Location Academic MA, et al. Cognition and impulsivity in adults with attention deficit Medical Center, Amsterdam, the Netherlands. hyperactivity disorder with and without cocaine and/or crack depend‑ ence. Drug Alcohol Depend. 2016;160:97–104. Received: 16 April 2022 Accepted: 12 September 2022 18. Crunelle CL, van den Brink W, Moggi F, Konstenius M, Franck J, Levin FR, et al. International Consensus Statement on Screening, Diagnosis and Treatment of Substance Use Disorder Patients with Comorbid Attention Deficit/Hyperactivity Disorder. Eur Addict Res. 2018;24(1):43–51. References 19. Kooij JJS, Bijlenga D, Salerno L, Jaeschke R, Bitter I, Balazs J, et al. 1. Charach A, Yeung E, Climans T, Lillie E. Childhood Attention-Deficit/ Updated European Consensus Statement on diagnosis and treatment Hyperactivity Disorder and Future Substance Use Disorders: Comparative of adult ADHD. Eur Psychiatry. 2019;56:14–34. Meta-Analyses. J Am Acad Child Adolesc Psychiatry. 2011;50(1):9–21. 20. Carpentier PJ, Levin FR. Pharmacological Treatment of ADHD in 2. Kessler R. The prevalence and correlates of adult ADHD in the United Addicted Patients: What Does the Literature Tell Us? Harv Rev Psychia‑ States: results from the National Comorbidity Survey Replication. Am J try. 2017;25(2):50–64. Psychiatr. 2006;163(4):716–23. 21. Levin FR, Mariani JJ, Specker S, Mooney M, Mahony A, Brooks DJ, 3. van de Glind G, Konstenius M, Koeter MWJ, van Emmerik-van OK, et al. Extended-Release Mixed Amphetamine Salts vs Placebo for Carpentier PJ, Kaye S, et al. Variability in the prevalence of adult ADHD Comorbid Adult Attention-Deficit/Hyperactivity Disorder and in treatment seeking substance use disorder patients: results from an Cocaine Use Disorder: A Randomized Clinical Trial. JAMA Psychiat. international multi-center study exploring DSM-IV and DSM-5 criteria. 2015;72(6):593–602. Drug Alcohol Depend. 2014;134:158–66. 22. Konstenius M, Jayaram-Lindstrom N, Guterstam J, Beck O, Philips B, 4. van Emmerik-van OK, van de Glind G, van den Brink W, Smit F, Crunelle Franck J. Methylphenidate for attention deficit hyperactivity disorder CL, Swets M, et al. Prevalence of attention-deficit hyperactivity disorder and drug relapse in criminal offenders with substance depend‑ in substance use disorder patients: a meta-analysis and meta-regression ence: a 24-week randomized placebo-controlled trial. Addiction. analysis. Drug Alcohol Depend. 2012;122(1–2):11–9. 2014;109(3):440–9. 5. Kaye S, Ramos-Quiroga JA, van de Glind G, Levin FR, Faraone SV, Allsop S, 23. Faraone SV, Wilens TE. Effect of Stimulant Medications for Attention- et al. Persistence and Subtype Stability of ADHD Among Substance Use Deficit_Hyperactivity Disorder on Later Substance Use and the Disorder Treatment Seekers. J Atten Disord. 2019;23(12):1438–53. Potential for Stimulant Misuse, Abuse, and Diversion. J Clin Psychiatr. 6. Fatseas M, Hurmic H, Serre F, Debrabant R, Daulouede JP, Denis C, et al. 2007;2007;68:11:5–22. Addiction severity pattern associated with adult and childhood Atten‑ 24. National Collaborating Centre for Mental H. National Institute for tion Deficit Hyperactivity Disorder (ADHD) in patients with addictions. Health and Clinical Excellence: Guidance. Attention Deficit Hyperactiv‑ Psychiatry Res. 2016;246:656–62. ity Disorder: Diagnosis and Management of ADHD in Children, Young 7. Young JT, Carruthers S, Kaye S, Allsop S, Gilsenan J, Degenhardt L, et al. People and Adults. Leicester (UK): British Psychological Society (UK). Comorbid attention deficit hyperactivity disorder and substance use Copyright © 2009, The British Psychological Society & The Royal Col‑ disorder complexity and chronicity in treatment-seeking adults. Drug lege of Psychiatrists.; 2009. Alcohol Rev. 2015;34(6):683–93. 25. van Emmerik-van OK, Vedel E, Kramer FJ, Blankers M, Dekker JJM, van 8. van Emmerik-van OK, van de Glind G, Koeter MW, Allsop S, Auriacombe den Brink W, et al. Integrated cognitive behavioral therapy for ADHD in M, Barta C, et al. Psychiatric comorbidity in treatment-seeking substance adult substance use disorder patients: Results of a randomized clinical use disorder patients with and without attention deficit hyperactivity trial. Drug Alcohol Depend. 2019;197:28–36. disorder: results of the IASP study. Addiction. 2014;109(2):262–72. 26. Bihlar Muld B, Jokinen J, Bolte S, Hirvikoski T. Skills training groups for 9. Levin FR, Evans SM, Vosburg SK, Horton T, Brooks D, Ng J. Impact of men with ADHD in compulsory care due to substance use disorder: a attention-deficit hyperactivity disorder and other psychopathology on feasibility study. Atten Defic Hyperact Disord. 2016;8(3):159–72. treatment retention among cocaine abusers in a therapeutic community. 27. Kronenberg LM, Verkerk-Tamminga R, Goossens PJ, van den Brink W, Addict Behav. 2004;29(9):1875–82. van Achterberg T. Personal recovery in individuals diagnosed with 10. Cunill R, Castells X, Tobias A, Capella D. Pharmacological treatment of substance use disorder (SUD) and co-occurring attention deficit/ attention deficit hyperactivity disorder with co-morbid drug depend‑ hyperactivity disorder (ADHD) or autism spectrum disorder (ASD). Arch ence. J Psychopharmacol. 2015;29(1):15–23. Psychiatr Nurs. 2015;29(4):242–8. 11. Kronenberg LM, Goossens PJ, van Etten DM, van Achterberg T, van den 28. Ilgen M, McKellar J, Tiet Q. Abstinence self-efficacy and abstinence 1 Brink W. Need for care and life satisfaction in adult substance use disorder year after substance use disorder treatment. J Consult Clin Psychol. patients with and without attention deficit hyperactivity disorder 2005;73(6):1175–80. (ADHD) or autism spectrum disorder (ASD). Perspect Psychiatr Care. 29. Ludwig F, Tadayon-Manssuri E, Strik W, Moggi F. Self-efficacy as a 2015;51(1):4–15. predictor of outcome after residential treatment programs for alcohol 12. Rodriguez-Cintas L, Daigre C, Braquehais MD, Palma-Alvarez RF, Grau- dependence: simply ask the patient one question! Alcohol Clin Exp Lopez L, Ros-Cucurull E, et al. Factors associated with lifetime suicidal Res. 2013;37(4):663–7. ideation and suicide attempts in outpatients with substance use disor‑ 30. Nakovics H, Diehl A, Geiselhart H, Mann K. Development and valida‑ ders. Psychiatry Res. 2018;262:440–5. tion of an overall instrument to measure craving across multiple 13. Vonmoos M, Hulka LM, Preller KH, Jenni D, Baumgartner MR, Stohler R, substances: the Mannheimer Craving Scale (MaCS). Psychiatr Prax. et al. Cognitive dysfunctions in recreational and dependent cocaine 2009;36(2):72–8. users: role of attention-deficit hyperactivity disorder, craving and early 31. Reichenbach F, Burren Y, Flückiger C, Znoj H, Moggi F. Swiss age at onset. Br J Psychiatry. 2013;203(1):35–43. Study to Validate the Mannheimer Craving Scale (MaCS). Sucht. 14. Brooks DJ, Vosburg SK, Evans SM, Levin FR. Assessment of cognitive 2018;64(1):11–20. functioning of methadone-maintenance patients: impact of adult ADHD 32. O’Connor RM, Colder CR, Hawk LW. Confirmatory factor analysis of the and current cocaine dependence. J Addict Dis. 2006;25(4):15–25. Sensitivity to Punishment and Sensitivity to Reward Questionnaire. 15. Duarte NA, Woods SP, Rooney A, Atkinson JH, Grant I, Translational Personality Individ Differ. 2004;37(5):985–1002. Methamphetamine ARCG. Working memory deficits affect risky decision- 33. Heatherton TF, Kozlowski LT, Frecker RC, Fagerström K-O. The Fagerstrom making in methamphetamine users with attention-deficit/hyperactivity Test for Nicotine Dependence: a revision of the Fagerstrom Tolerance disorder. J Psychiatr Res. 2012;46(4):492–9. Questionnaire. Br J Addict. 1991;86:1119–27. Brynte et al. BMC Psychiatry (2022) 22:625 Page 8 of 8 34. Bjureberg J, Ljotsson B, Tull MT, Hedman E, Sahlin H, Lundh LG, et al. Development and Validation of a Brief Version of the Difficulties in Emotion Regulation Scale: The DERS-16. J Psychopathol Behav Assess. 2016;38(2):284–96. 35. Koenig HG, Büssing A. The Duke University Religion Index (DUREL): A Five-Item Measure for Use in Epidemological Studies. Religions (Basel, Switzerland ). 2010;1(1):78–85. 36. Slobodin O, Davidovitch M. Gender Differences in Objective and Subjec‑ tive Measures of ADHD Among Clinic-Referred Children. Front Hum Neurosci. 2019;13:441. Publisher’s Note Springer Nature remains neutral with regard to jurisdictional claims in pub‑ lished maps and institutional affiliations. Ready to submit your research ? Choose BMC and benefit from: • fast, convenient online submission • thorough peer review by experienced researchers in your field • rapid publication on acceptance • support for research data, including large and complex data types • gold Open Access which fosters wider collaboration and increased citations • maximum visibility for your research: over 100M website views per year At BMC, research is always in progress. Learn more biomedcentral.com/submissions