Addictive BehaviorNCT04498988
Volitional Dysfunction in Self-control Failures and Addictive Behaviors
An observational study of Addictive Behavior and Alcohol Use Disorder (AUD), run by Technische Universität Dresden at 1 site in Germany.
Trial summary
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. Read more about this study
- Who is it for?
- Ages 19 to 27 yearsHealthy volunteers can take part
- Conditions the study is for
- Addictive Behavior, Alcohol Use Disorder (AUD), Tobacco Use Disorder
- What is being tested?
- Observational study without interventions
- How many people
- 338 participants
- Where
- 1 siteGermany
- Study dates
- 1 Dec 2014to 30 Jun 2024
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 19 to 27 years
- All sexes
- Healthy volunteers accepted
- Adult
Study population: The age range was 19 to 27 years at baseline. As expected for our sampling procedure, the addictive disorder severity was mainly mild (baseline 62%) and moderate (baseline 28%).
Who may be able to join
- age 19-27
- fulfill the criteria for one of three groups (SUD, ND, controls)
- written informed consent
Who cannot join
- 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
Trial locations and contacts
1 site in 1 country.
Germany1 site
Technische Universität Dresden, Faculty of Psychology
Dresden, 01062
About this study
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.
Read the detailed description
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.
- Conditions
- Addictive Behavior, Alcohol Use Disorder (AUD), Tobacco Use Disorder, Self-Control, Executive Dysfunction
- Being tested
- Observational study without interventions
- Keywords
- Cognitive control, Decision-making, Impulsivity, Risk-seeking
- Medical subject headings
- Behavior, Addictive, Alcoholism, Tobacco Use Disorder, Self-Control, Impulsive Behavior
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Observational study without interventionsOther
| Study group | Role | What they receive |
|---|---|---|
| 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). Receives: Other: Observational study without interventions | |
| 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. Receives: Other: Observational study without interventions | |
| Control group | The control participants had no current or lifetime substance use disorder (SUD) or non-substance-related addictive disorder (ND). Receives: Other: Observational study without interventions |
What is being measured
The primary outcome is the main question the study is designed to answer.
Changes in addictive disorder severity
Changes in number of fulfilled criteria according to the Diagnostic and Statistical Manual of Mental Disorders, fifth edition (DSM-5)
Measured: At baseline and 1, 2, 3, 4, 5, 6, 7 years after baseline
Changes in quantity and frequency of addictive behaviors
Changes in quantity and frequency of addictive behaviours, which are combined into a quantity-frequency index.
Measured: At baseline and 1, 2, 3, 4, 5, 6, 7 years after baseline
Changes in cognitive control abilities
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).
Measured: At baseline and 3 and 6 years after baseline
Changes in impulsive decision-making
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.
Measured: At baseline and 3 and 6 years after baseline
Changes in neural correlates of response inhibition
Blood oxygenation level dependent (BOLD) responses in tasks measuring response inhibition (Go/Nogo, Stroop) using 3 Tesla functional magnetic resonance imaging (fMRI).
Measured: At baseline and 3 and 6 years after baseline
Changes in neural correlates of error monitoring
BOLD responses in a task measuring error monitoring (Stroop) using 3 Tesla fMRI.
Measured: At baseline and 3 and 6 years after baseline
Changes in neural correlates of value-based decision-making
BOLD responses in a task measuring value-based decision-making using 3 Tesla fMRI.
Measured: At baseline and 3 and 6 years after baseline
Changes in structural brain characteristics
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.
Measured: At baseline and 3 and 6 years after baseline
Changes in real-life self-control
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.
Measured: At baseline and 3 and 6 years after baseline
Secondary outcomes (7)
Intelligence
As control variable we assessed the intelligence quotient (IQ) using the Wechsler Intelligence Test for Adults (WIE).
Measured: At baseline
Personality
As moderator variable we assessed the NEO Five Factor Inventory (NEO-FFI; outcomes are the sum scores).
Measured: At baseline
Positive and negative affect
As moderator variable we assessed the Positive and Negative Affect Schedule (PANAS; outcomes are the sum scores).
Measured: At baseline
Changes in the action and state orientation
As moderator variable we assessed the Action-State Orientation Scale (ACS-90; outcomes are the sum scores).
Measured: At baseline and 3 and 6 years after baseline
Changes in impulsivity
As moderator variable we assessed the Barratt Impulsiveness Scale (BIS-11; outcome is the sum score).
Measured: At baseline and 3 and 6 years after baseline
Changes in self control
As moderator variable we assessed the Brief Self-Control Scale (BSCS; outcome is the sum score).
Measured: At baseline and 3 and 6 years after baseline
Changes in chronic stress
As moderator variable we assessed the Trier Inventory for Chronic Stress (TICS; outcome is the sum score).
Measured: At baseline and 3 and 6 years after baseline
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted5 Aug 2020
- Study start1 Dec 2014
- Primary completion31 Mar 2024
- Study completion30 Jun 2024
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (13)Papers the sponsor has linked to this study.
- Other trials for Addictive BehaviorStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Ecologic or community
- Time perspective
- Prospective
- Enrolment
- 338 participants (actual)
Sponsor and investigators
- Lead sponsor
- Technische Universität Dresden
- Sponsor type
- University, hospital or other
- Collaborators
- German Research Foundation
- Responsible party
- Sponsor
- Investigators
- Thomas Goschke, Prof. Dr., Principal investigator, Technische Universität DresdenMichael N. Smolka, Prof. Dr., Principal investigator, Technische Universität DresdenGerhard Bühringer, Prof. Dr., Principal investigator, Technische Universität Dresden
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04498988
- Sponsor's protocol ID
- SFB940 C01
- Other IDs
- Project number 178833530
- Status last verified
- Aug 2024
- First submitted
- 27 Jul 2020
- Last updated
- 9 Aug 2024
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Yes: 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).
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.
PubMed 28508582Kronke 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.
PubMed 26321462Wolff 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.
PubMed 26403462Kraplin 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.
PubMed 32500211Kronke 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.
PubMed 32024421Wolff 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.
PubMed 27736135Kronke 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.
PubMed 29654477Kronke 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.
PubMed 33130158Wolff 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.
PubMed 32858777Kronke 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.
PubMed 34075542Kraplin 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.
PubMed 36190537Kraplin 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.
PubMed 38751764
Study at a glance
From the registry record, last updated by the sponsor on 9 Aug 2024. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Volitional Dysfunction in Self-control Failures and Addictive Behaviors
- ClinicalTrials.gov ID
- NCT04498988
- Acronym / sponsor ID
- SFB940 C01
- Conditions
- Addictive Behavior, Alcohol Use Disorder (AUD), Tobacco Use Disorder, Self-Control, Executive Dysfunction
- Keywords
- Cognitive control, Decision-making, Impulsivity, Risk-seeking
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 338 participants (actual)
- Lead sponsor
- Technische Universität DresdenUniversity, hospital or other
- Collaborators
- German Research Foundation
- Study start
- 1 Dec 2014 (actual)
- Primary completion
- 31 Mar 2024 (actual)
- Study completion
- 30 Jun 2024 (actual)
- First posted
- 5 Aug 2020 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Detailed description
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.
Study design
- Observational model
- Ecologic or community
- Time perspective
- Prospective
- Number of arms
- 3
| Arm | Type | Receives |
|---|---|---|
| Substance use disorder (SUD) group | – | Other: Observational study without interventionsIn 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). |
| Non-substance-related addictive disorder (ND) group | – | Other: Observational study without interventionsIn 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. |
| Control group | – | Other: Observational study without interventionsThe control participants had no current or lifetime substance use disorder (SUD) or non-substance-related addictive disorder (ND). |
Who may qualify
- Ages
- 19 to 27 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult
- Study population
- The age range was 19 to 27 years at baseline. As expected for our sampling procedure, the addictive disorder severity was mainly mild (baseline 62%) and moderate (baseline 28%).
Key inclusion criteria (3 listed)
- age 19-27
- fulfill the criteria for one of three groups (SUD, ND, controls)
- written informed consent
Key exclusion criteria (7 listed)
- 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
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Observational study without interventions | Other | Control group, Non-substance-related addictive disorder (ND) group, Substance use disorder (SUD) group |
Primary outcome
Changes in addictive disorder severity
Time frame: At baseline and 1, 2, 3, 4, 5, 6, 7 years after baseline
Changes in number of fulfilled criteria according to the Diagnostic and Statistical Manual of Mental Disorders, fifth edition (DSM-5)
Changes in quantity and frequency of addictive behaviors
Time frame: At baseline and 1, 2, 3, 4, 5, 6, 7 years after baseline
Changes in quantity and frequency of addictive behaviours, which are combined into a quantity-frequency index.
Changes in cognitive control abilities
Time frame: At baseline and 3 and 6 years after baseline
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).
Changes in impulsive decision-making
Time frame: At baseline and 3 and 6 years after baseline
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.
Changes in neural correlates of response inhibition
Time frame: At baseline and 3 and 6 years after baseline
Blood oxygenation level dependent (BOLD) responses in tasks measuring response inhibition (Go/Nogo, Stroop) using 3 Tesla functional magnetic resonance imaging (fMRI).
Changes in neural correlates of error monitoring
Time frame: At baseline and 3 and 6 years after baseline
BOLD responses in a task measuring error monitoring (Stroop) using 3 Tesla fMRI.
Changes in neural correlates of value-based decision-making
Time frame: At baseline and 3 and 6 years after baseline
BOLD responses in a task measuring value-based decision-making using 3 Tesla fMRI.
Changes in structural brain characteristics
Time frame: At baseline and 3 and 6 years after baseline
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.
Changes in real-life self-control
Time frame: At baseline and 3 and 6 years after baseline
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.
7 secondary outcomes
Intelligence
Time frame: At baseline
Personality
Time frame: At baseline
Positive and negative affect
Time frame: At baseline
Changes in the action and state orientation
Time frame: At baseline and 3 and 6 years after baseline
Changes in impulsivity
Time frame: At baseline and 3 and 6 years after baseline
Changes in self control
Time frame: At baseline and 3 and 6 years after baseline
Changes in chronic stress
Time frame: At baseline and 3 and 6 years after baseline
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 9 Aug 2024.
- Background: PubMed 28508582Kraplin 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.
- Background: PubMed 26321462Kronke 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.
- Background: PubMed 26403462Wolff 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.
- Results publication: PubMed 32500211Kraplin 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.
- Results publication: PubMed 32024421Kronke 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.
- Results publication: PubMed 27736135Wolff 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.
- Results publication: PubMed 29654477Kronke 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.
- Results publication: PubMed 33130158Kronke 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.
- Results publication: PubMed 32858777Wolff 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.
- Results publication: PubMed 34075542Kronke 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.
- Results publication: PubMed 36190537Kraplin 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.
- Results publicationKraplin 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
- Individual participant dataSharing planned: Yes. 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).
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Thomas Goschke, Prof. Dr. principal investigator
Technische Universität Dresden
Michael N. Smolka, Prof. Dr. principal investigator
Technische Universität Dresden
Gerhard Bühringer, Prof. Dr. principal investigator
Technische Universität Dresden
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Addictive Behavior and Alcohol Use Disorder (AUD), run by Technische Universität Dresden at 1 site in Germany.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 3 inclusion and 7 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 9 Aug 2024. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Germany. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Changes in addictive disorder severity (time frame: At baseline and 1, 2, 3, 4, 5, 6, 7 years after baseline). The study lists 9 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT04498988, which also lists 13 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 9 Aug 2024.