<clinical_study>
  <!-- This xml conforms to an XML Schema at:
    https://clinicaltrials.gov/ct2/html/images/info/public.xsd -->
  <required_header>
    <download_date>ClinicalTrials.gov processed this data on September 20, 2023</download_date>
    <link_text>Link to the current ClinicalTrials.gov record.</link_text>
    <url>https://clinicaltrials.gov/ct2/show/NCT04498988</url>
  </required_header>
  <id_info>
    <org_study_id>SFB940 C01</org_study_id>
    <secondary_id>Project number 178833530</secondary_id>
    <nct_id>NCT04498988</nct_id>
  </id_info>
  <brief_title>Volitional Dysfunction in Self-control Failures and Addictive Behaviors</brief_title>
  <official_title>Volitional Dysfunction in Self-control Failures and Addictive Behaviors</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>Technische Universität Dresden</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
    <collaborator>
      <agency>German Research Foundation</agency>
      <agency_class>Other</agency_class>
    </collaborator>
  </sponsors>
  <source>Technische Universität Dresden</source>
  <oversight_info>
    <has_dmc>No</has_dmc>
    <is_fda_regulated_drug>No</is_fda_regulated_drug>
    <is_fda_regulated_device>No</is_fda_regulated_device>
  </oversight_info>
  <brief_summary>
    <textblock>
      The aim of this project is to elucidate whether impairments of cognitive control,&#xD;
      performance-monitoring, and value-based decision-making and dysfunctional interactions&#xD;
      between underlying brain systems are mediating mechanisms and vulnerability factors for daily&#xD;
      self-control failures and addictive disorders.&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      Failures of self-control during conflicts between long-term goals and immediate desires are a&#xD;
      key characteristic of many harmful behaviors, including unhealthy eating habits, lack of&#xD;
      exercise and problematic substance use, which often have adverse personal consequences and&#xD;
      incur great societal costs. The project aims to elucidate neurocognitive mechanisms mediating&#xD;
      deficient self-control, both in daily self-control failures and in substance use disorders&#xD;
      and behavioral addictions, which are characterized by a loss of control despite awareness of&#xD;
      adverse consequences. A prospective cohort study was launched using a multi-level approach&#xD;
      that combines (i) a comprehensive clinical assessment, (ii) behavioral task batteries&#xD;
      assessing cognitive control and decision-making functions, (iii) task-related and resting&#xD;
      state fMRI, and (iv) Smartphone-based ecological momentary assessment of daily self-control&#xD;
      failures. From a representative community sample, three groups of participants were recruited&#xD;
      (each n = 100; age 20 - 26) with (a) symptoms of non-substance related and (b)&#xD;
      substance-related addictive disorders and (c) syndrome-free controls. Participants are&#xD;
      invited to yearly clinical follow-up assessments and further multi-level assessments 3 and 6&#xD;
      years after initial recruitment. Results obtained so far (until 06/2020) provide converging&#xD;
      evidence that task performance as well as brain activity in monitoring, control, and&#xD;
      valuation networks is reliably associated with the propensity to commit real-life&#xD;
      self-control failures. Results support a process model, according to which deficient&#xD;
      performance-monitoring leads to an insufficient recruitment of control networks, which&#xD;
      attenuates the impact of long-term goals on neural value signals and increases the likelihood&#xD;
      of self-control failures. In the final funding period (until 06/2024), the clinical follow-up&#xD;
      period will be extended to 7 years. In addition, stress markers will be assessed as possible&#xD;
      moderators of self-control. With the cross-lagged panel design it is expected to make a&#xD;
      substantial contribution to the central unresolved question whether dysfunctions of cognitive&#xD;
      control are causally involved in the development and trajectories of self-control failures&#xD;
      and addictive behaviors, as well as to the disputed question of communalities and differences&#xD;
      between different addictive disorders. Thereby, the project will to contribute to&#xD;
      mechanism-based models of self-control impairments as a foundation for improved prevention&#xD;
      and therapy.&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Active, not recruiting</overall_status>
  <start_date type="Actual">December 1, 2014</start_date>
  <completion_date type="Anticipated">June 30, 2024</completion_date>
  <primary_completion_date type="Anticipated">December 31, 2023</primary_completion_date>
  <study_type>Observational</study_type>
  <has_expanded_access>No</has_expanded_access>
  <study_design_info>
    <observational_model>Ecologic or Community</observational_model>
    <time_perspective>Prospective</time_perspective>
  </study_design_info>
  <primary_outcome>
    <measure>Changes in addictive disorder severity</measure>
    <time_frame>At baseline and 1, 2, 3, 4, 5, 6, 7 years after baseline</time_frame>
    <description>Changes in number of fulfilled criteria according to the Diagnostic and Statistical Manual of Mental Disorders, fifth edition (DSM-5)</description>
  </primary_outcome>
  <primary_outcome>
    <measure>Changes in quantity and frequency of addictive behaviors</measure>
    <time_frame>At baseline and 1, 2, 3, 4, 5, 6, 7 years after baseline</time_frame>
    <description>Changes in quantity and frequency of addictive behaviours, which are combined into a quantity-frequency index.</description>
  </primary_outcome>
  <primary_outcome>
    <measure>Changes in cognitive control abilities</measure>
    <time_frame>At baseline and 3 and 6 years after baseline</time_frame>
    <description>The Cognitive Control Task Battery of the Collaborative Research Center (CRC) 940 with nine executive function tasks (Stroop, AX continuous performance, color-shape, stop signal, letter memory, number-letter, go-nogo, 2-back, category switch) is used to derive a latent variable representing individual differences in general executive functioning (GEF). For the latent variable modelling error rates and reaction times from the tasks were combined, were appropriate, into inverse efficiency scores (IESs).</description>
  </primary_outcome>
  <primary_outcome>
    <measure>Changes in impulsive decision-making</measure>
    <time_frame>At baseline and 3 and 6 years after baseline</time_frame>
    <description>The Value-Based Decision-Making (VBDM) battery of the Collaborative Research Center (CRC) 940 including four decision-making tasks with a Bayesian adaptive algorithm was used to adaptively assess impulsive decision-making. For the delay and probability discounting tasks, a hyperbolic value function was used describing that the subjective values of delayed (or probabilistic) reward decline hyperbolically according to the discounting rate k. For the mixed gambles task, a simple linear function was used in which loss aversion (λ) is the relative weighting of losses to gains in the participant's. Individuals with higher impulsive decision-making are assumed to display higher k values in the delay discounting task, lower k values in probability discounting tasks, and lower λ values in the mixed gambles task.</description>
  </primary_outcome>
  <primary_outcome>
    <measure>Changes in neural correlates of response inhibition</measure>
    <time_frame>At baseline and 3 and 6 years after baseline</time_frame>
    <description>Blood oxygenation level dependent (BOLD) responses in tasks measuring response inhibition (Go/Nogo, Stroop) using 3 Tesla functional magnetic resonance imaging (fMRI).</description>
  </primary_outcome>
  <primary_outcome>
    <measure>Changes in neural correlates of error monitoring</measure>
    <time_frame>At baseline and 3 and 6 years after baseline</time_frame>
    <description>BOLD responses in a task measuring error monitoring (Stroop) using 3 Tesla fMRI.</description>
  </primary_outcome>
  <primary_outcome>
    <measure>Changes in neural correlates of value-based decision-making</measure>
    <time_frame>At baseline and 3 and 6 years after baseline</time_frame>
    <description>BOLD responses in a task measuring value-based decision-making using 3 Tesla fMRI.</description>
  </primary_outcome>
  <primary_outcome>
    <measure>Changes in structural brain characteristics</measure>
    <time_frame>At baseline and 3 and 6 years after baseline</time_frame>
    <description>Gray matter volume, cortical thickness and white matter properties in theoretically motivated regions of interest (e.g., right inferior frontal gyrus (rIFG), ventromedial prefrontal cortex (vmPFC), anterior cingulate cortex (ACC), anterior insula (aINS)) using 3 Tesla structural MRI.</description>
  </primary_outcome>
  <primary_outcome>
    <measure>Changes in real-life self-control</measure>
    <time_frame>At baseline and 3 and 6 years after baseline</time_frame>
    <description>Everyday self-control was assessed using an Ecological Momentary Assessment (EMA) protocol adapted from Hofmann, Baumeister, Förster, and Vohs (2012). Self-control was defined as enactment of desires in conflict-laden situations.</description>
  </primary_outcome>
  <secondary_outcome>
    <measure>Intelligence</measure>
    <time_frame>At baseline</time_frame>
    <description>As control variable we assessed the intelligence quotient (IQ) using the Wechsler Intelligence Test for Adults (WIE).</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Personality</measure>
    <time_frame>At baseline</time_frame>
    <description>As moderator variable we assessed the NEO Five Factor Inventory (NEO-FFI; outcomes are the sum scores).</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Positive and negative affect</measure>
    <time_frame>At baseline</time_frame>
    <description>As moderator variable we assessed the Positive and Negative Affect Schedule (PANAS; outcomes are the sum scores).</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Changes in the action and state orientation</measure>
    <time_frame>At baseline and 3 and 6 years after baseline</time_frame>
    <description>As moderator variable we assessed the Action-State Orientation Scale (ACS-90; outcomes are the sum scores).</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Changes in impulsivity</measure>
    <time_frame>At baseline and 3 and 6 years after baseline</time_frame>
    <description>As moderator variable we assessed the Barratt Impulsiveness Scale (BIS-11; outcome is the sum score).</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Changes in self control</measure>
    <time_frame>At baseline and 3 and 6 years after baseline</time_frame>
    <description>As moderator variable we assessed the Brief Self-Control Scale (BSCS; outcome is the sum score).</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Changes in chronic stress</measure>
    <time_frame>At baseline and 3 and 6 years after baseline</time_frame>
    <description>As moderator variable we assessed the Trier Inventory for Chronic Stress (TICS; outcome is the sum score).</description>
  </secondary_outcome>
  <number_of_groups>3</number_of_groups>
  <enrollment type="Actual">338</enrollment>
  <condition>Addictive Behavior</condition>
  <condition>Alcohol Use Disorder (AUD)</condition>
  <condition>Tobacco Use Disorder</condition>
  <condition>Self-Control</condition>
  <condition>Executive Dysfunction</condition>
  <arm_group>
    <arm_group_label>Substance use disorder (SUD) group</arm_group_label>
    <description>In the substance use disorder (SUD) group, participants had a diagnosis of alcohol and/or tobacco use disorder according to the Diagnostic and Statistical Manual of Mental Disorders, fifth edition (DSM-5) but no lifetime non-substance-related addictive disorder (ND).</description>
  </arm_group>
  <arm_group>
    <arm_group_label>Non-substance-related addictive disorder (ND) group</arm_group_label>
    <description>In the non-substance-related addictive disorder (ND) group, participants were included who fulfilled two or more criteria for a DSM-5 gambling disorder or for an addictive behavior related to Internet use (not for gambling, gaming, or shopping), gaming, or shopping assessed with adapted criteria from DSM-5 substance use disorder (SUD). Participants in the ND group had no lifetime SUD.</description>
  </arm_group>
  <arm_group>
    <arm_group_label>Control group</arm_group_label>
    <description>The control participants had no current or lifetime substance use disorder (SUD) or non-substance-related addictive disorder (ND).</description>
  </arm_group>
  <intervention>
    <intervention_type>Other</intervention_type>
    <intervention_name>Observational study without interventions</intervention_name>
    <arm_group_label>Control group</arm_group_label>
    <arm_group_label>Non-substance-related addictive disorder (ND) group</arm_group_label>
    <arm_group_label>Substance use disorder (SUD) group</arm_group_label>
  </intervention>
  <eligibility>
    <study_pop>
      <textblock>
        The age range was 19 to 27 years at baseline. As expected for our sampling procedure, the&#xD;
        addictive disorder severity was mainly mild (baseline 62%) and moderate (baseline 28%).&#xD;
      </textblock>
    </study_pop>
    <sampling_method>Probability Sample</sampling_method>
    <criteria>
      <textblock>
        Inclusion Criteria (at baseline):&#xD;
&#xD;
          1. age 19-27&#xD;
&#xD;
          2. fulfill the criteria for one of three groups (SUD, ND, controls)&#xD;
&#xD;
          3. written informed consent&#xD;
&#xD;
        Exclusion Criteria (at baseline):&#xD;
&#xD;
          1. no written informed consent or limited ability to understand the questionnaires and&#xD;
             tasks&#xD;
&#xD;
          2. disorders that might influence cognition or motor performance (e.g. craniocerebral&#xD;
             injury)&#xD;
&#xD;
          3. magnetic resonance contraindications&#xD;
&#xD;
          4. current treatment for mental disorders&#xD;
&#xD;
          5. current use of psychotropic medication or substances&#xD;
&#xD;
          6. lifetime psychotic symptoms, bipolar disorder, or other SUD or ND not under study&#xD;
&#xD;
          7. major depression, somatoform, anxiety, obsessive compulsive, or eating disorders&#xD;
             within the last 4 weeks&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>19 Years</minimum_age>
    <maximum_age>27 Years</maximum_age>
    <healthy_volunteers>Accepts Healthy Volunteers</healthy_volunteers>
  </eligibility>
  <overall_official>
    <last_name>Thomas Goschke, Prof. Dr.</last_name>
    <role>Principal Investigator</role>
    <affiliation>Technische Universität Dresden</affiliation>
  </overall_official>
  <overall_official>
    <last_name>Michael N. Smolka, Prof. Dr.</last_name>
    <role>Principal Investigator</role>
    <affiliation>Technische Universität Dresden</affiliation>
  </overall_official>
  <overall_official>
    <last_name>Gerhard Bühringer, Prof. Dr.</last_name>
    <role>Principal Investigator</role>
    <affiliation>Technische Universität Dresden</affiliation>
  </overall_official>
  <location>
    <facility>
      <name>Technische Universität Dresden, Faculty of Psychology</name>
      <address>
        <city>Dresden</city>
        <zip>01062</zip>
        <country>Germany</country>
      </address>
    </facility>
  </location>
  <location_countries>
    <country>Germany</country>
  </location_countries>
  <reference>
    <citation>Kraplin A. Conceptualizing behavioural addiction in children and adolescents. Addiction. 2017 Oct;112(10):1721-1723. doi: 10.1111/add.13846. Epub 2017 May 15. No abstract available.</citation>
    <PMID>28508582</PMID>
  </reference>
  <reference>
    <citation>Kronke KM, Wolff M, Benz A, Goschke T. Successful smoking cessation is associated with prefrontal cortical function during a Stroop task: A preliminary study. Psychiatry Res. 2015 Oct 30;234(1):52-6. doi: 10.1016/j.pscychresns.2015.08.005. Epub 2015 Aug 20.</citation>
    <PMID>26321462</PMID>
  </reference>
  <reference>
    <citation>Wolff M, Kronke KM, Goschke T. Trait self-control is predicted by how reward associations modulate Stroop interference. Psychol Res. 2016 Nov;80(6):944-951. doi: 10.1007/s00426-015-0707-4. Epub 2015 Sep 24.</citation>
    <PMID>26403462</PMID>
  </reference>
  <results_reference>
    <citation>Kraplin A, Hofler M, Pooseh S, Wolff M, Kronke KM, Goschke T, Buhringer G, Smolka MN. Impulsive decision-making predicts the course of substance-related and addictive disorders. Psychopharmacology (Berl). 2020 Sep;237(9):2709-2724. doi: 10.1007/s00213-020-05567-z. Epub 2020 Jun 5.</citation>
    <PMID>32500211</PMID>
  </results_reference>
  <results_reference>
    <citation>Kronke KM, Wolff M, Mohr H, Kraplin A, Smolka MN, Buhringer G, Goschke T. Predicting Real-Life Self-Control From Brain Activity Encoding the Value of Anticipated Future Outcomes. Psychol Sci. 2020 Mar;31(3):268-279. doi: 10.1177/0956797619896357. Epub 2020 Feb 5.</citation>
    <PMID>32024421</PMID>
  </results_reference>
  <results_reference>
    <citation>Wolff M, Kronke KM, Venz J, Kraplin A, Buhringer G, Smolka MN, Goschke T. Action versus state orientation moderates the impact of executive functioning on real-life self-control. J Exp Psychol Gen. 2016 Dec;145(12):1635-1653. doi: 10.1037/xge0000229. Epub 2016 Oct 13.</citation>
    <PMID>27736135</PMID>
  </results_reference>
  <results_reference>
    <citation>Kronke KM, Wolff M, Mohr H, Kraplin A, Smolka MN, Buhringer G, Goschke T. Monitor yourself! Deficient error-related brain activity predicts real-life self-control failures. Cogn Affect Behav Neurosci. 2018 Aug;18(4):622-637. doi: 10.3758/s13415-018-0593-5.</citation>
    <PMID>29654477</PMID>
  </results_reference>
  <results_reference>
    <citation>Kronke KM, Wolff M, Shi Y, Kraplin A, Smolka MN, Buhringer G, Goschke T. Functional connectivity in a triple-network saliency model is associated with real-life self-control. Neuropsychologia. 2020 Dec;149:107667. doi: 10.1016/j.neuropsychologia.2020.107667. Epub 2020 Oct 31.</citation>
    <PMID>33130158</PMID>
  </results_reference>
  <results_reference>
    <citation>Wolff M, Enge S, Kraplin A, Kronke KM, Buhringer G, Smolka MN, Goschke T. Chronic stress, executive functioning, and real-life self-control: An experience sampling study. J Pers. 2021 May;89(3):402-421. doi: 10.1111/jopy.12587. Epub 2020 Sep 3.</citation>
    <PMID>32858777</PMID>
  </results_reference>
  <results_reference>
    <citation>Kronke KM, Mohr H, Wolff M, Kraplin A, Smolka MN, Buhringer G, Ruge H, Goschke T. Real-Life Self-Control is Predicted by Parietal Activity During Preference Decision Making: A Brain Decoding Analysis. Cogn Affect Behav Neurosci. 2021 Oct;21(5):936-947. doi: 10.3758/s13415-021-00913-w. Epub 2021 Jun 1.</citation>
    <PMID>34075542</PMID>
  </results_reference>
  <results_reference>
    <citation>Kraplin A, Joshanloo M, Wolff M, Kronke KM, Goschke T, Buhringer G, Smolka MN. The relationship between executive functioning and addictive behavior: new insights from a longitudinal community study. Psychopharmacology (Berl). 2022 Nov;239(11):3507-3524. doi: 10.1007/s00213-022-06224-3. Epub 2022 Oct 3.</citation>
    <PMID>36190537</PMID>
  </results_reference>
  <results_reference>
    <citation>Kraplin A, Kupka KF, Fröhner JH, Krönke K-M, Wolff M, Smolka MN, Bühringer G, Goschke T. Personality Traits Predict Non-Substance Related and Substance Related Addictive Behaviours. SUCHT. 2022; 68(5), 263-277. doi:10.1024/0939-5911/a000780</citation>
  </results_reference>
  <verification_date>September 2023</verification_date>
  <study_first_submitted>July 27, 2020</study_first_submitted>
  <study_first_submitted_qc>July 30, 2020</study_first_submitted_qc>
  <study_first_posted type="Actual">August 5, 2020</study_first_posted>
  <last_update_submitted>September 6, 2023</last_update_submitted>
  <last_update_submitted_qc>September 6, 2023</last_update_submitted_qc>
  <last_update_posted type="Actual">September 8, 2023</last_update_posted>
  <responsible_party>
    <responsible_party_type>Sponsor</responsible_party_type>
  </responsible_party>
  <keyword>Cognitive control</keyword>
  <keyword>Decision-making</keyword>
  <keyword>Impulsivity</keyword>
  <keyword>Risk-seeking</keyword>
  <condition_browse>
    <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
    <mesh_term>Alcoholism</mesh_term>
    <mesh_term>Tobacco Use Disorder</mesh_term>
    <mesh_term>Behavior, Addictive</mesh_term>
  </condition_browse>
  <patient_data>
    <sharing_ipd>Yes</sharing_ipd>
    <ipd_description>Data and analytic codes within publications will be shared via the Open Science Framework (OSF). Final archiving of the participant data will be conducted with the Open Access Repository and Archive at the Technische Universität Dresden (OpARA).</ipd_description>
    <ipd_info_type>Analytic Code</ipd_info_type>
    <ipd_time_frame>Data and analytic codes within publications will be shared from the time of publications. Final archived data will be shared after the study is completed in 2024.</ipd_time_frame>
    <ipd_access_criteria>Open Access</ipd_access_criteria>
    <ipd_url>https://osf.io/yu5rm/</ipd_url>
  </patient_data>
  <study_docs>
    <study_doc>
      <doc_type>Official study group website</doc_type>
      <doc_url>https://tu-dresden.de/bereichsuebergreifendes/sfb940/</doc_url>
    </study_doc>
    <study_doc>
      <doc_type>English description of the Collaborative Research Centre</doc_type>
      <doc_url>https://gepris.dfg.de/gepris/projekt/178833530</doc_url>
      <doc_comment>The study is conducted within the Collaborative Research Centre 940 funded by the Deutsche Forschungsgemeinschaft (DFG).</doc_comment>
    </study_doc>
  </study_docs>
  <!-- Results have not yet been posted for this study                                          -->
</clinical_study>


download date: ClinicalTrials.gov processed this data on September 20, 2023
link text: Link to the current ClinicalTrials.gov record.
url: https://clinicaltrials.gov/ct2/show/NCT04498988
org study id: SFB940 C01
secondary id: Project number 178833530
nct id: NCT04498988
lead sponsor: 
collaborator: 
has dmc: No
is fda regulated drug: No
is fda regulated device: No
The aim of this project is to elucidate whether impairments of cognitive control,
      performance-monitoring, and value-based decision-making and dysfunctional interactions
      between underlying brain systems are mediating mechanisms and vulnerability factors for daily
      self-control failures and addictive disorders.
Failures of self-control during conflicts between long-term goals and immediate desires are a
      key characteristic of many harmful behaviors, including unhealthy eating habits, lack of
      exercise and problematic substance use, which often have adverse personal consequences and
      incur great societal costs. The project aims to elucidate neurocognitive mechanisms mediating
      deficient self-control, both in daily self-control failures and in substance use disorders
      and behavioral addictions, which are characterized by a loss of control despite awareness of
      adverse consequences. A prospective cohort study was launched using a multi-level approach
      that combines (i) a comprehensive clinical assessment, (ii) behavioral task batteries
      assessing cognitive control and decision-making functions, (iii) task-related and resting
      state fMRI, and (iv) Smartphone-based ecological momentary assessment of daily self-control
      failures. From a representative community sample, three groups of participants were recruited
      (each n = 100; age 20 - 26) with (a) symptoms of non-substance related and (b)
      substance-related addictive disorders and (c) syndrome-free controls. Participants are
      invited to yearly clinical follow-up assessments and further multi-level assessments 3 and 6
      years after initial recruitment. Results obtained so far (until 06/2020) provide converging
      evidence that task performance as well as brain activity in monitoring, control, and
      valuation networks is reliably associated with the propensity to commit real-life
      self-control failures. Results support a process model, according to which deficient
      performance-monitoring leads to an insufficient recruitment of control networks, which
      attenuates the impact of long-term goals on neural value signals and increases the likelihood
      of self-control failures. In the final funding period (until 06/2024), the clinical follow-up
      period will be extended to 7 years. In addition, stress markers will be assessed as possible
      moderators of self-control. With the cross-lagged panel design it is expected to make a
      substantial contribution to the central unresolved question whether dysfunctions of cognitive
      control are causally involved in the development and trajectories of self-control failures
      and addictive behaviors, as well as to the disputed question of communalities and differences
      between different addictive disorders. Thereby, the project will to contribute to
      mechanism-based models of self-control impairments as a foundation for improved prevention
      and therapy.
observational model: Ecologic or Community
time perspective: Prospective
measure: Changes in addictive disorder severity
time frame: At baseline and 1, 2, 3, 4, 5, 6, 7 years after baseline
description: Changes in number of fulfilled criteria according to the Diagnostic and Statistical Manual of Mental Disorders, fifth edition (DSM-5)
measure: Changes in quantity and frequency of addictive behaviors
time frame: At baseline and 1, 2, 3, 4, 5, 6, 7 years after baseline
description: Changes in quantity and frequency of addictive behaviours, which are combined into a quantity-frequency index.
measure: Changes in cognitive control abilities
time frame: At baseline and 3 and 6 years after baseline
description: The Cognitive Control Task Battery of the Collaborative Research Center (CRC) 940 with nine executive function tasks (Stroop, AX continuous performance, color-shape, stop signal, letter memory, number-letter, go-nogo, 2-back, category switch) is used to derive a latent variable representing individual differences in general executive functioning (GEF). For the latent variable modelling error rates and reaction times from the tasks were combined, were appropriate, into inverse efficiency scores (IESs).
measure: Changes in impulsive decision-making
time frame: At baseline and 3 and 6 years after baseline
description: The Value-Based Decision-Making (VBDM) battery of the Collaborative Research Center (CRC) 940 including four decision-making tasks with a Bayesian adaptive algorithm was used to adaptively assess impulsive decision-making. For the delay and probability discounting tasks, a hyperbolic value function was used describing that the subjective values of delayed (or probabilistic) reward decline hyperbolically according to the discounting rate k. For the mixed gambles task, a simple linear function was used in which loss aversion (λ) is the relative weighting of losses to gains in the participant's. Individuals with higher impulsive decision-making are assumed to display higher k values in the delay discounting task, lower k values in probability discounting tasks, and lower λ values in the mixed gambles task.
measure: Changes in neural correlates of response inhibition
time frame: At baseline and 3 and 6 years after baseline
description: Blood oxygenation level dependent (BOLD) responses in tasks measuring response inhibition (Go/Nogo, Stroop) using 3 Tesla functional magnetic resonance imaging (fMRI).
measure: Changes in neural correlates of error monitoring
time frame: At baseline and 3 and 6 years after baseline
description: BOLD responses in a task measuring error monitoring (Stroop) using 3 Tesla fMRI.
measure: Changes in neural correlates of value-based decision-making
time frame: At baseline and 3 and 6 years after baseline
description: BOLD responses in a task measuring value-based decision-making using 3 Tesla fMRI.
measure: Changes in structural brain characteristics
time frame: At baseline and 3 and 6 years after baseline
description: Gray matter volume, cortical thickness and white matter properties in theoretically motivated regions of interest (e.g., right inferior frontal gyrus (rIFG), ventromedial prefrontal cortex (vmPFC), anterior cingulate cortex (ACC), anterior insula (aINS)) using 3 Tesla structural MRI.
measure: Changes in real-life self-control
time frame: At baseline and 3 and 6 years after baseline
description: Everyday self-control was assessed using an Ecological Momentary Assessment (EMA) protocol adapted from Hofmann, Baumeister, Förster, and Vohs (2012). Self-control was defined as enactment of desires in conflict-laden situations.
measure: Intelligence
time frame: At baseline
description: As control variable we assessed the intelligence quotient (IQ) using the Wechsler Intelligence Test for Adults (WIE).
measure: Personality
time frame: At baseline
description: As moderator variable we assessed the NEO Five Factor Inventory (NEO-FFI; outcomes are the sum scores).
measure: Positive and negative affect
time frame: At baseline
description: As moderator variable we assessed the Positive and Negative Affect Schedule (PANAS; outcomes are the sum scores).
measure: Changes in the action and state orientation
time frame: At baseline and 3 and 6 years after baseline
description: As moderator variable we assessed the Action-State Orientation Scale (ACS-90; outcomes are the sum scores).
measure: Changes in impulsivity
time frame: At baseline and 3 and 6 years after baseline
description: As moderator variable we assessed the Barratt Impulsiveness Scale (BIS-11; outcome is the sum score).
measure: Changes in self control
time frame: At baseline and 3 and 6 years after baseline
description: As moderator variable we assessed the Brief Self-Control Scale (BSCS; outcome is the sum score).
measure: Changes in chronic stress
time frame: At baseline and 3 and 6 years after baseline
description: As moderator variable we assessed the Trier Inventory for Chronic Stress (TICS; outcome is the sum score).
arm group label: Substance use disorder (SUD) group
description: In the substance use disorder (SUD) group, participants had a diagnosis of alcohol and/or tobacco use disorder according to the Diagnostic and Statistical Manual of Mental Disorders, fifth edition (DSM-5) but no lifetime non-substance-related addictive disorder (ND).
arm group label: Non-substance-related addictive disorder (ND) group
description: In the non-substance-related addictive disorder (ND) group, participants were included who fulfilled two or more criteria for a DSM-5 gambling disorder or for an addictive behavior related to Internet use (not for gambling, gaming, or shopping), gaming, or shopping assessed with adapted criteria from DSM-5 substance use disorder (SUD). Participants in the ND group had no lifetime SUD.
arm group label: Control group
description: The control participants had no current or lifetime substance use disorder (SUD) or non-substance-related addictive disorder (ND).
intervention type: Other
intervention name: Observational study without interventions
arm group label: Control group
arm group label: Non-substance-related addictive disorder (ND) group
arm group label: Substance use disorder (SUD) group
study pop: 
sampling method: Probability Sample
criteria: 
gender: All
minimum age: 19 Years
maximum age: 27 Years
healthy volunteers: Accepts Healthy Volunteers
last name: Thomas Goschke, Prof. Dr.
role: Principal Investigator
affiliation: Technische Universität Dresden
last name: Michael N. Smolka, Prof. Dr.
role: Principal Investigator
affiliation: Technische Universität Dresden
last name: Gerhard Bühringer, Prof. Dr.
role: Principal Investigator
affiliation: Technische Universität Dresden
facility: 
country: Germany
citation: Kraplin A. Conceptualizing behavioural addiction in children and adolescents. Addiction. 2017 Oct;112(10):1721-1723. doi: 10.1111/add.13846. Epub 2017 May 15. No abstract available.
PMID: 28508582
citation: Kronke KM, Wolff M, Benz A, Goschke T. Successful smoking cessation is associated with prefrontal cortical function during a Stroop task: A preliminary study. Psychiatry Res. 2015 Oct 30;234(1):52-6. doi: 10.1016/j.pscychresns.2015.08.005. Epub 2015 Aug 20.
PMID: 26321462
citation: Wolff M, Kronke KM, Goschke T. Trait self-control is predicted by how reward associations modulate Stroop interference. Psychol Res. 2016 Nov;80(6):944-951. doi: 10.1007/s00426-015-0707-4. Epub 2015 Sep 24.
PMID: 26403462
citation: Kraplin A, Hofler M, Pooseh S, Wolff M, Kronke KM, Goschke T, Buhringer G, Smolka MN. Impulsive decision-making predicts the course of substance-related and addictive disorders. Psychopharmacology (Berl). 2020 Sep;237(9):2709-2724. doi: 10.1007/s00213-020-05567-z. Epub 2020 Jun 5.
PMID: 32500211
citation: Kronke KM, Wolff M, Mohr H, Kraplin A, Smolka MN, Buhringer G, Goschke T. Predicting Real-Life Self-Control From Brain Activity Encoding the Value of Anticipated Future Outcomes. Psychol Sci. 2020 Mar;31(3):268-279. doi: 10.1177/0956797619896357. Epub 2020 Feb 5.
PMID: 32024421
citation: Wolff M, Kronke KM, Venz J, Kraplin A, Buhringer G, Smolka MN, Goschke T. Action versus state orientation moderates the impact of executive functioning on real-life self-control. J Exp Psychol Gen. 2016 Dec;145(12):1635-1653. doi: 10.1037/xge0000229. Epub 2016 Oct 13.
PMID: 27736135
citation: Kronke KM, Wolff M, Mohr H, Kraplin A, Smolka MN, Buhringer G, Goschke T. Monitor yourself! Deficient error-related brain activity predicts real-life self-control failures. Cogn Affect Behav Neurosci. 2018 Aug;18(4):622-637. doi: 10.3758/s13415-018-0593-5.
PMID: 29654477
citation: Kronke KM, Wolff M, Shi Y, Kraplin A, Smolka MN, Buhringer G, Goschke T. Functional connectivity in a triple-network saliency model is associated with real-life self-control. Neuropsychologia. 2020 Dec;149:107667. doi: 10.1016/j.neuropsychologia.2020.107667. Epub 2020 Oct 31.
PMID: 33130158
citation: Wolff M, Enge S, Kraplin A, Kronke KM, Buhringer G, Smolka MN, Goschke T. Chronic stress, executive functioning, and real-life self-control: An experience sampling study. J Pers. 2021 May;89(3):402-421. doi: 10.1111/jopy.12587. Epub 2020 Sep 3.
PMID: 32858777
citation: Kronke KM, Mohr H, Wolff M, Kraplin A, Smolka MN, Buhringer G, Ruge H, Goschke T. Real-Life Self-Control is Predicted by Parietal Activity During Preference Decision Making: A Brain Decoding Analysis. Cogn Affect Behav Neurosci. 2021 Oct;21(5):936-947. doi: 10.3758/s13415-021-00913-w. Epub 2021 Jun 1.
PMID: 34075542
citation: Kraplin A, Joshanloo M, Wolff M, Kronke KM, Goschke T, Buhringer G, Smolka MN. The relationship between executive functioning and addictive behavior: new insights from a longitudinal community study. Psychopharmacology (Berl). 2022 Nov;239(11):3507-3524. doi: 10.1007/s00213-022-06224-3. Epub 2022 Oct 3.
PMID: 36190537
citation: Kraplin A, Kupka KF, Fröhner JH, Krönke K-M, Wolff M, Smolka MN, Bühringer G, Goschke T. Personality Traits Predict Non-Substance Related and Substance Related Addictive Behaviours. SUCHT. 2022; 68(5), 263-277. doi:10.1024/0939-5911/a000780
responsible party type: Sponsor
mesh term: Alcoholism
mesh term: Tobacco Use Disorder
mesh term: Behavior, Addictive
sharing ipd: Yes
ipd description: Data and analytic codes within publications will be shared via the Open Science Framework (OSF). Final archiving of the participant data will be conducted with the Open Access Repository and Archive at the Technische Universität Dresden (OpARA).
ipd info type: Analytic Code
ipd time frame: Data and analytic codes within publications will be shared from the time of publications. Final archived data will be shared after the study is completed in 2024.
ipd access criteria: Open Access
ipd url: https://osf.io/yu5rm/
study doc: 
study doc: 