Volitional Dysfunction in Self-control Failures and Addictive Behaviors

NCT04498988 | Completed

• 2 other identifiers: SFB940 C01Project number 178833530
• Study Type: observational
• Target: 338
• Locations: 1 country
• Sites: 1

Brief 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.

Conditions

Addictive Behavior; Alcohol Use Disorder (AUD); Tobacco Use Disorder; Self-Control; Executive Dysfunction

Keywords

Cognitive control; Decision-making; Impulsivity; Risk-seeking

Outcome Measures

Primary Outcomes (9)

• 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)

  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.

  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).

  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.

  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).

  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.

  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.

  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.

  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.

  At baseline and 3 and 6 years after baseline

Secondary Outcomes (7)

• Intelligence

  At baseline

• Personality

  At baseline

• Positive and negative affect

  At baseline

• Changes in the action and state orientation

  At baseline and 3 and 6 years after baseline

• Changes in impulsivity

  At baseline and 3 and 6 years after baseline

Study Arms (3)

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).

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.

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).

Other: Observational study without interventions

Interventions

Observational study without interventions OTHER

Control group; Non-substance-related addictive disorder (ND) group; Substance use disorder (SUD) group

Eligibility Criteria

• Age: 19 Years - 27 Years
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64)
• Sampling Method: Probability Sample

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%).

You may qualify if:

• age 19-27
• fulfill the criteria for one of three groups (SUD, ND, controls)
• written informed consent

You may not qualify if:

• 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

Sponsors & Collaborators

• Technische Universität Dresden: lead
• German Research Foundation: collaborator

Study Sites (1)

Technische Universität Dresden, Faculty of Psychology

Dresden, 01062, Germany

Location

Related Publications (13)

• 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 BACKGROUND

• 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 BACKGROUND

• 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 BACKGROUND

• 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 RESULT

• 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 RESULT

• 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 RESULT

• 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 RESULT

• 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 RESULT

• 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 RESULT

• 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 RESULT

• 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 RESULT

• 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

  RESULT

• 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.

  PMID: 38751764 RESULT

MeSH Terms

Conditions

Behavior, Addictive; Alcoholism; Tobacco Use Disorder; Self-Control; Impulsive Behavior

Interventions

Observation; Methods

Condition Hierarchy (Ancestors)

Compulsive Behavior; Behavior; Alcohol-Related Disorders; Substance-Related Disorders; Chemically-Induced Disorders; Mental Disorders; Social Behavior

Intervention Hierarchy (Ancestors)

Investigative Techniques

Study Officials

• 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

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: observational
• Observational Model: ECOLOGIC OR COMMUNITY
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: July 27, 2020
• First Posted: August 5, 2020
• Study Start: December 1, 2014
• Primary Completion: March 31, 2024
• Study Completion: June 30, 2024
• Last Updated: August 9, 2024

Record last verified: 2024-08

Data Sharing

• IPD Sharing: Will share
• Shared Documents: ANALYTIC CODE
• 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.
• Access Criteria: Open Access

Locations

DE (1)