Tobacco Use Disorder Clinical Trial
Official title:
Volitional Dysfunction in Self-control Failures and Addictive Behaviors
Verified date | September 2023 |
Source | Technische Universität Dresden |
Contact | n/a |
Is FDA regulated | No |
Health authority | |
Study type | Observational |
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.
Status | Active, not recruiting |
Enrollment | 338 |
Est. completion date | June 30, 2024 |
Est. primary completion date | December 31, 2023 |
Accepts healthy volunteers | Accepts Healthy Volunteers |
Gender | All |
Age group | 19 Years to 27 Years |
Eligibility | Inclusion Criteria (at baseline): 1. age 19-27 2. fulfill the criteria for one of three groups (SUD, ND, controls) 3. written informed consent Exclusion Criteria (at baseline): 1. no written informed consent or limited ability to understand the questionnaires and tasks 2. disorders that might influence cognition or motor performance (e.g. craniocerebral injury) 3. magnetic resonance contraindications 4. current treatment for mental disorders 5. current use of psychotropic medication or substances 6. lifetime psychotic symptoms, bipolar disorder, or other SUD or ND not under study 7. major depression, somatoform, anxiety, obsessive compulsive, or eating disorders within the last 4 weeks |
Country | Name | City | State |
---|---|---|---|
Germany | Technische Universität Dresden, Faculty of Psychology | Dresden |
Lead Sponsor | Collaborator |
---|---|
Technische Universität Dresden | German Research Foundation |
Germany,
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 — View 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. — View 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
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. — View 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. do — View 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. — View 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 — View 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 202 — View 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.2020.1076 — View 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. — View 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. — View 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 — View Citation
* Note: There are 12 references in all — Click here to view all references
Type | Measure | Description | Time frame | Safety issue |
---|---|---|---|---|
Primary | 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 | |
Primary | 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 | |
Primary | 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 | |
Primary | 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 (?) 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 ? values in the mixed gambles task. | At baseline and 3 and 6 years after baseline | |
Primary | 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 | |
Primary | 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 | |
Primary | 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 | |
Primary | 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 | |
Primary | 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 | Intelligence | As control variable we assessed the intelligence quotient (IQ) using the Wechsler Intelligence Test for Adults (WIE). | At baseline | |
Secondary | Personality | As moderator variable we assessed the NEO Five Factor Inventory (NEO-FFI; outcomes are the sum scores). | At baseline | |
Secondary | Positive and negative affect | As moderator variable we assessed the Positive and Negative Affect Schedule (PANAS; outcomes are the sum scores). | At baseline | |
Secondary | Changes in the action and state orientation | As moderator variable we assessed the Action-State Orientation Scale (ACS-90; outcomes are the sum scores). | At baseline and 3 and 6 years after baseline | |
Secondary | Changes in impulsivity | As moderator variable we assessed the Barratt Impulsiveness Scale (BIS-11; outcome is the sum score). | At baseline and 3 and 6 years after baseline | |
Secondary | Changes in self control | As moderator variable we assessed the Brief Self-Control Scale (BSCS; outcome is the sum score). | At baseline and 3 and 6 years after baseline | |
Secondary | Changes in chronic stress | As moderator variable we assessed the Trier Inventory for Chronic Stress (TICS; outcome is the sum score). | At baseline and 3 and 6 years after baseline |
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