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Using Neuroeconomics to Characterize State-Based Increases and Decreases in Alcohol Value

Using Neuroeconomics to Characterize State-Based Increases and Decreases in Alcohol Value

Status
Completed
Phases
NA
Study type
Interventional
Source
ClinicalTrials.gov
Registry ID
NCT04067765
Enrollment
72
Registered
2019-08-26
Start date
2020-01-01
Completion date
2023-12-31
Last updated
2025-09-09

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Alcohol Use Disorder, Alcohol Drinking

Keywords

Alcohol, Neuroeconomics, Demand, Cues

Brief summary

This study uses techniques from an area of research known as neuroeconomics, which integrates concepts and methods from psychology, neuroscience, and economics to better understand how people make decisions and how these decisions are supported by the brain. One neuroeconomic concept that is especially relevant in the area of addictions is substance demand, or how consumption of a commodity (e.g., alcohol, tobacco, or drugs) is influenced by price and other factors. Previous studies have shown that alcohol demand is related to severity of alcohol misuse, drinking quantity/frequency, and treatment outcomes. In addition, we know that alcohol demand can also fluctuate in response to environmental cues such as alcohol-related stimuli or external contingencies such as important responsibilities the following day. These increase and decreases in consumption and value are clinically significant because they help us understand how people with alcohol use disorders are able to successfully or unsuccessfully modulate their drinking behaviors. This study is examining how the brain responds in these situations and whether these responses differ as a function of severity of alcohol misuse. This study will use functional magnetic resonance imaging (fMRI) to understand brain activity patterns associated with changes in the value of alcohol in the presence of alcohol-related beverage cues relative to neutral-related beverage cue. Participants will be non-treatment-seeking adult heavy drinkers who are recruited from the community to participate in an fMRI scan. During the scan, participants will make decisions about how many alcohol beverages they would consume (hypothetically) at various prices while their brain activity during those decisions is measured. The experimental manipulation involves an in-scanner alcohol cue exposure task in which the drinking decisions will be made after viewing high-quality images of alcoholic (beer/wine/liquor) beverages or neutral (water/juice/soft drinks) beverages.

Detailed description

Neuroeconomics integrates concepts and methods from psychology, economics, and cognitive neuroscience to understand the neurobiological foundations of decision making, and has been increasingly applied to understanding alcohol use disorder (AUD). A novel application of neuroeconomics is the study of alcohol demand, or the value of alcohol as measured by cost-benefit preferences. Alcohol demand paradigms have considerable ecological validity by measuring the impact of internal and external influences on alcohol decision-making, such as price, environmental cues, affective states, or external contingencies. Behaviorally, alcohol demand is elevated among individuals with higher levels of alcohol misuse and predicts treatment response. Alcohol demand also exhibits state-like properties, including increases following exposure to alcohol-related cues. The overall goal of the proposed studies is to characterize the neural activity that subserves these established behavioral findings using a novel functional MRI paradigm. The primary aim is to examine the patterns of neural activation underlying increases in the value of alcohol in response to alcohol cues. The study will use a within-subjects design to identify differences in neural activity associated with demand decisions following a validated in-scanner cue exposure protocol consisting of exposure to neutral beverage cues and exposure to alcohol beverage cues in a sample of adult heavy drinkers. Using a novel neuroeconomics approach, this study combines a highly ecologically-valid alcohol demand paradigm with an experimental manipulation that models clinically-relevant influences on drinking decisions. Studying these contextual influences may help clarify the neural signatures that underlie drinking moderation vs. unconstrained drinking, and how these processes are impacted by AUD. If successful, this study will provide a foundation for examining neural predictors of successful recovery or response to treatment vs. relapse. More broadly, findings from this study have high potential to significantly enhance the clinical relevance of alcohol neuroscience.

Interventions

BEHAVIORALCue Exposure

Participants will undergo a validated in-scanner alcohol cue and neutral cue exposure protocol involving passive viewing of images of alcohol beverages (beer, wine, or liquor) and neutral beverages (water).

Sponsors

McMaster University
Lead SponsorOTHER

Study design

Allocation
NA
Intervention model
SEQUENTIAL
Primary purpose
OTHER
Masking
NONE

Intervention model description

Participants will undergo a validated cue exposure protocol involving exposure to neutral beverage cues followed by exposure to alcohol beverage cues

Eligibility

Sex/Gender
ALL
Age
21 Years to 55 Years
Healthy volunteers
Yes

Inclusion criteria

* 21-55 years old; * Right-handed; * Fluent English speaker; * Heavy drinker (i.e., on average \> 14/7 drinks per week for males/females in past three months; * Average of 1 heavy drinking episode weekly (heavy drinking episode = 5+/4+ for males/females) over past three months

Exclusion criteria

* Currently receiving treatment, or seeking treatment, for alcohol related problems; * Current Diagnostic and Statistical Manual (DSM-5) substance use disorder other than alcohol or tobacco; * Weekly or more frequent use of recreational drugs; * History of schizophrenia-spectrum disorders, psychotic disorders, bipolar disorder, or PTSD; * History of neurocognitive disorder or impairment; * MRI contraindications (e.g., metal in body, history of seizure, etc.); * History of serious brain injury; * Currently taking psychotropic medications or medications that could affect cerebral blood flow; * Pregnancy (females); * Attending any study session with a positive breath alcohol concentration (BrAC \> 0.00g%)

Design outcomes

Primary

MeasureTime frameDescription
Alcohol Demand IntensityCollected during each of 4 runs of the FMRI Alcohol Purchase Task. Duration of each run was approximately 6 minutes and included 26 trials.Intensity is defined as the self-consumption in standard drinks at free price. Participants could select between 0-10 standard sized alcohol drinks on the in-scanner alcohol purchase task paradigm. The mean intensity was calculated separately for the two neutral cue runs and the two alcohol cue runs.
Alcohol Demand BreakpointCollected during each of 4 runs of the FMRI Alcohol Purchase Task. Duration of each run was approximately 6 minutes and included 26 trials.Breakpoint is defined as the first price on the alcohol purchase task that suppressed consumption to zero drinks. The mean breakpoint was calculated separately for the two neutral cue runs and the two alcohol cue runs.
Alcohol Demand OmaxCollected during each of 4 runs of the FMRI Alcohol Purchase Task. Duration of each run was approximately 6 minutes and included 26 trials.Omax is defined as the maximum total expenditure on alcohol for the in-scanner alcohol purchase task. The mean Omax was calculated separately for the two neutral cue runs and the two alcohol cue runs.
Alcohol Demand ElasticityCollected during each of 4 runs of the FMRI Alcohol Purchase Task. Duration of each run was approximately 6 minutes and included 26 trials.Elasticity is defined as the change in consumption (in drinks) as a function of increases in price per drink (in dollars). This index was modeled using an exponentiated demand curve model as reported in \[Koffarnus, M. N., Franck, C. T., Stein, J. S., & Bickel, W. K. (2015). A modified exponential behavioral economic demand model to better describe consumption data. Experimental and clinical psychopharmacology, 23(6), 504-512. https://doi.org/10.1037/pha0000045\]. This nonlinear model generates a best fitting value for an alpha parameter, reflecting the rate of change in elasticity over increasing price. Higher alpha values reflect greater elasticity (greater sensitivity in consumption with increases in price). There is no theoretical range as this is a free parameter in the model. Mean alpha values were calculated separately for the two neutral cue runs and the two alcohol cue runs.

Secondary

MeasureTime frameDescription
Alcohol CravingCollected immediately after the first neutral cue exposure and immediately after the first alcohol cue exposure.Subjective alcohol craving was assessed using three 100-point scales, including how much they want alcohol, crave alcohol, and their urge for alcohol. A score of 0 indicates the lowest level of craving; a score of 100 indicates the highest amount of craving. The three items were averaged into a composite craving score.

Countries

Canada

Participant flow

Participants by arm

ArmCount
Alcohol Cue Exposure
Within subjects assignment to receive complete both an alcohol cue exposure and neutral cue exposure in a sequential order.
72
Total72

Baseline characteristics

CharacteristicAlcohol Cue Exposure
30 Day Timeline Follow-Back Interview20.3 Drinks/week
STANDARD_DEVIATION 12.9
Age, Categorical
<=18 years
0 Participants
Age, Categorical
>=65 years
0 Participants
Age, Categorical
Between 18 and 65 years
72 Participants
Alcohol Use Disorders Identification Test (AUDIT)12.0 units on a scale
STANDARD_DEVIATION 5.4
Daily Drinking Questionnaire (DDQ)22.3 Drinks/week
STANDARD_DEVIATION 13.1
Diagnostic Assessment Research Tool (DART) for DSM-5 Alcohol Use Disorder49 Participants
Education16.3 Years
STANDARD_DEVIATION 2
Ethnicity (NIH/OMB)
Hispanic or Latino
1 Participants
Ethnicity (NIH/OMB)
Not Hispanic or Latino
71 Participants
Ethnicity (NIH/OMB)
Unknown or Not Reported
0 Participants
Race (NIH/OMB)
American Indian or Alaska Native
0 Participants
Race (NIH/OMB)
Asian
0 Participants
Race (NIH/OMB)
Black or African American
0 Participants
Race (NIH/OMB)
More than one race
5 Participants
Race (NIH/OMB)
Native Hawaiian or Other Pacific Islander
0 Participants
Race (NIH/OMB)
Unknown or Not Reported
0 Participants
Race (NIH/OMB)
White
67 Participants
Sex: Female, Male
Female
37 Participants
Sex: Female, Male
Male
35 Participants

Adverse events

Event typeEG000
affected / at risk
EG001
affected / at risk
deaths
Total, all-cause mortality
0 / 720 / 72
other
Total, other adverse events
0 / 720 / 72
serious
Total, serious adverse events
0 / 720 / 72

Outcome results

Primary

Alcohol Demand Breakpoint

Breakpoint is defined as the first price on the alcohol purchase task that suppressed consumption to zero drinks. The mean breakpoint was calculated separately for the two neutral cue runs and the two alcohol cue runs.

Time frame: Collected during each of 4 runs of the FMRI Alcohol Purchase Task. Duration of each run was approximately 6 minutes and included 26 trials.

ArmMeasureGroupValue (MEAN)Dispersion
Alcohol Cue ExposureAlcohol Demand BreakpointAlcohol Cue Exposure32.48 DollarsStandard Error 1.45
Alcohol Cue ExposureAlcohol Demand BreakpointNeutral Cue Exposure28.77 DollarsStandard Error 1.67
Primary

Alcohol Demand Elasticity

Elasticity is defined as the change in consumption (in drinks) as a function of increases in price per drink (in dollars). This index was modeled using an exponentiated demand curve model as reported in \[Koffarnus, M. N., Franck, C. T., Stein, J. S., & Bickel, W. K. (2015). A modified exponential behavioral economic demand model to better describe consumption data. Experimental and clinical psychopharmacology, 23(6), 504-512. https://doi.org/10.1037/pha0000045\]. This nonlinear model generates a best fitting value for an alpha parameter, reflecting the rate of change in elasticity over increasing price. Higher alpha values reflect greater elasticity (greater sensitivity in consumption with increases in price). There is no theoretical range as this is a free parameter in the model. Mean alpha values were calculated separately for the two neutral cue runs and the two alcohol cue runs.

Time frame: Collected during each of 4 runs of the FMRI Alcohol Purchase Task. Duration of each run was approximately 6 minutes and included 26 trials.

ArmMeasureGroupValue (MEAN)Dispersion
Alcohol Cue ExposureAlcohol Demand ElasticityNeutral Cue Exposure0.006 drinks consumed/price (dollars)Standard Error 0.001
Alcohol Cue ExposureAlcohol Demand ElasticityAlcohol Cue Exposure0.003 drinks consumed/price (dollars)Standard Error 0.001
Primary

Alcohol Demand Intensity

Intensity is defined as the self-consumption in standard drinks at free price. Participants could select between 0-10 standard sized alcohol drinks on the in-scanner alcohol purchase task paradigm. The mean intensity was calculated separately for the two neutral cue runs and the two alcohol cue runs.

Time frame: Collected during each of 4 runs of the FMRI Alcohol Purchase Task. Duration of each run was approximately 6 minutes and included 26 trials.

ArmMeasureGroupValue (MEAN)Dispersion
Alcohol Cue ExposureAlcohol Demand IntensityNeutral Cue Exposure7.42 DrinksStandard Error 0.3
Alcohol Cue ExposureAlcohol Demand IntensityAlcohol Cue Exposure7.85 DrinksStandard Error 0.27
Primary

Alcohol Demand Omax

Omax is defined as the maximum total expenditure on alcohol for the in-scanner alcohol purchase task. The mean Omax was calculated separately for the two neutral cue runs and the two alcohol cue runs.

Time frame: Collected during each of 4 runs of the FMRI Alcohol Purchase Task. Duration of each run was approximately 6 minutes and included 26 trials.

ArmMeasureGroupValue (MEAN)Dispersion
Alcohol Cue ExposureAlcohol Demand OmaxNeutral Cue Exposure49.54 DollarsStandard Error 6.32
Alcohol Cue ExposureAlcohol Demand OmaxAlcohol Cue Exposure60.63 DollarsStandard Error 8.39
Secondary

Alcohol Craving

Subjective alcohol craving was assessed using three 100-point scales, including how much they want alcohol, crave alcohol, and their urge for alcohol. A score of 0 indicates the lowest level of craving; a score of 100 indicates the highest amount of craving. The three items were averaged into a composite craving score.

Time frame: Collected immediately after the first neutral cue exposure and immediately after the first alcohol cue exposure.

ArmMeasureGroupValue (MEAN)Dispersion
Alcohol Cue ExposureAlcohol Cravingalcohol cue exposure27.99 PointsStandard Error 2.84
Alcohol Cue ExposureAlcohol Cravingneutral cue exposure19.72 PointsStandard Error 2.49

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026