Volitional Dysfunction in Self-control Failures and Addictive Behaviors
Study Overview
Status
Status
Conditions
Conditions
Intervention / Treatment
Intervention / Treatment
Detailed Description
Study Type
Study Type
Enrollment (Actual)
Enrollment
Contacts and Locations
Study Locations
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Dresden, Germany, 01062
- Technische Universität Dresden, Faculty of Psychology
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Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
Accepts Healthy Volunteers
Sampling Method
Study Population
Description
Inclusion Criteria (at baseline):
- age 19-27
- fulfill the criteria for one of three groups (SUD, ND, controls)
- written informed consent
Exclusion Criteria (at baseline):
- no written informed consent or limited ability to understand the questionnaires and tasks
- disorders that might influence cognition or motor performance (e.g. craniocerebral injury)
- magnetic resonance contraindications
- current treatment for mental disorders
- current use of psychotropic medication or substances
- lifetime psychotic symptoms, bipolar disorder, or other SUD or ND not under study
- major depression, somatoform, anxiety, obsessive compulsive, or eating disorders within the last 4 weeks
Study Plan
How is the study designed?
Design Details
Number of groups / cohorts
Cohorts and Interventions
Group / CohortGroup / Cohort |
Intervention / TreatmentIntervention / Treatment |
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Substance use disorder (SUD) group
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).
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Non-substance-related addictive disorder (ND) group
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.
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Control group
The control participants had no current or lifetime substance use disorder (SUD) or non-substance-related addictive disorder (ND).
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What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
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Changes in addictive disorder severity
Time Frame: At baseline and 1, 2, 3, 4, 5, 6, 7 years after baseline
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Changes in number of fulfilled criteria according to the Diagnostic and Statistical Manual of Mental Disorders, fifth edition (DSM-5)
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At baseline and 1, 2, 3, 4, 5, 6, 7 years after baseline
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Changes in quantity and frequency of addictive behaviors
Time Frame: At baseline and 1, 2, 3, 4, 5, 6, 7 years after baseline
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Changes in quantity and frequency of addictive behaviours, which are combined into a quantity-frequency index.
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At baseline and 1, 2, 3, 4, 5, 6, 7 years after baseline
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Changes in cognitive control abilities
Time Frame: At baseline and 3 and 6 years after baseline
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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).
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At baseline and 3 and 6 years after baseline
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Changes in impulsive decision-making
Time Frame: At baseline and 3 and 6 years after baseline
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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.
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At baseline and 3 and 6 years after baseline
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Changes in neural correlates of response inhibition
Time Frame: At baseline and 3 and 6 years after baseline
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Blood oxygenation level dependent (BOLD) responses in tasks measuring response inhibition (Go/Nogo, Stroop) using 3 Tesla functional magnetic resonance imaging (fMRI).
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At baseline and 3 and 6 years after baseline
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Changes in neural correlates of error monitoring
Time Frame: At baseline and 3 and 6 years after baseline
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BOLD responses in a task measuring error monitoring (Stroop) using 3 Tesla fMRI.
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At baseline and 3 and 6 years after baseline
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Changes in neural correlates of value-based decision-making
Time Frame: At baseline and 3 and 6 years after baseline
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BOLD responses in a task measuring value-based decision-making using 3 Tesla fMRI.
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At baseline and 3 and 6 years after baseline
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Changes in structural brain characteristics
Time Frame: At baseline and 3 and 6 years after baseline
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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.
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At baseline and 3 and 6 years after baseline
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Changes in real-life self-control
Time Frame: At baseline and 3 and 6 years after baseline
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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.
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At baseline and 3 and 6 years after baseline
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Secondary Outcome Measures
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
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Intelligence
Time Frame: At baseline
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As control variable we assessed the intelligence quotient (IQ) using the Wechsler Intelligence Test for Adults (WIE).
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At baseline
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Personality
Time Frame: At baseline
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As moderator variable we assessed the NEO Five Factor Inventory (NEO-FFI; outcomes are the sum scores).
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At baseline
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Positive and negative affect
Time Frame: At baseline
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As moderator variable we assessed the Positive and Negative Affect Schedule (PANAS; outcomes are the sum scores).
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At baseline
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Changes in the action and state orientation
Time Frame: At baseline and 3 and 6 years after baseline
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As moderator variable we assessed the Action-State Orientation Scale (ACS-90; outcomes are the sum scores).
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At baseline and 3 and 6 years after baseline
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Changes in impulsivity
Time Frame: At baseline and 3 and 6 years after baseline
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As moderator variable we assessed the Barratt Impulsiveness Scale (BIS-11; outcome is the sum score).
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At baseline and 3 and 6 years after baseline
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Changes in self control
Time Frame: At baseline and 3 and 6 years after baseline
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As moderator variable we assessed the Brief Self-Control Scale (BSCS; outcome is the sum score).
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At baseline and 3 and 6 years after baseline
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Changes in chronic stress
Time Frame: At baseline and 3 and 6 years after baseline
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As moderator variable we assessed the Trier Inventory for Chronic Stress (TICS; outcome is the sum score).
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At baseline and 3 and 6 years after baseline
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Collaborators and Investigators
Sponsor
Sponsor
Collaborators
Collaborators
Investigators
Investigators
- Principal Investigator: Thomas Goschke, Prof. Dr., Technische Universität Dresden
- Principal Investigator: Michael N. Smolka, Prof. Dr., Technische Universität Dresden
- Principal Investigator: Gerhard Bühringer, Prof. Dr., Technische Universität Dresden
Publications and helpful links
General Publications
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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
- Kraplin A, Joshanloo M, Wolff M, Frohner JH, Baeuchl C, Kronke KM, Buhringer G, Smolka MN, Goschke T. No evidence for a reciprocal relationship between daily self-control failures and addictive behavior in a longitudinal study. Front Psychol. 2024 May 1;15:1382483. doi: 10.3389/fpsyg.2024.1382483. eCollection 2024.
Study record dates
Study Major Dates
Study Start (Actual)
Study Start
Primary Completion (Actual)
Primary Completion
Study Completion (Actual)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (Actual)
First Posted
Study Record Updates
Last Update Posted (Actual)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
Other Study ID Numbers
- SFB940 C01
- Project number 178833530 (Other Grant/Funding Number: Deutsche Forschungsgemeinschaft (DFG))
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
IPD Plan Description
IPD Sharing Time Frame
IPD Sharing Access Criteria
IPD Sharing Supporting Information Type
- ANALYTIC_CODE
Study Data/Documents
- Official study group website
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English description of the Collaborative Research Centre
Information comments: The study is conducted within the Collaborative Research Centre 940 funded by the Deutsche Forschungsgemeinschaft (DFG).
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.
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