Volitional Dysfunction in Self-control Failures and Addictive Behaviors

Study Overview
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Brief Summary
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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
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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.

Official Title
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Volitional Dysfunction in Self-control Failures and Addictive Behaviors

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

Intervention / Treatment
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* Other: Observational study without interventions


Participation Criteria
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Eligibility Criteria
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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

Ages Eligible for Study
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Minimum Age: 19 Years
Maximum Age: 27 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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Accepts Healthy Volunteers

Study Plan
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How is the study designed?
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Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Substance use disorder (SUD) group<br>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<br> <br> |
| Non-substance-related addictive disorder (ND) group<br>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<br> <br> |
| Control group<br>The control participants had no current or lifetime substance use disorder (SUD) or non-substance-related addictive disorder (ND). | Other: Observational study without interventions<br> <br> |

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| 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 Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Intelligence | As control variable we assessed the intelligence quotient (IQ) using the Wechsler Intelligence Test for Adults (WIE). | At baseline | 
| Personality | As moderator variable we assessed the NEO Five Factor Inventory (NEO-FFI; outcomes are the sum scores). | At baseline | 
| Positive and negative affect | As moderator variable we assessed the Positive and Negative Affect Schedule (PANAS; outcomes are the sum scores). | 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). | 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). | 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). | 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). | At baseline and 3 and 6 years after baseline | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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Cognitive control, Decision-making, Impulsivity, Risk-seeking