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This research project proposes a novel approach to elucidate the biological adaptations associated with Alcohol Use Disorder and to assess whether such adaptations are predictive of higher alcohol craving in response to both alcohol cues and stressors and higher relapse risk and alcohol use in the real world.
Full description
We will use intensive longitudinal data collection and analysis across multiple data streams. We will recruit 25 treatment-seeking individuals with AUD and 25 light social drinkers matched on demographically relevant variables (i.e., age, gender, IQ, race). We will use smartphones to assess subjects' alcohol use and experiences in real-time via ecological momentary assessment (EMA). During three consecutive days of these two weeks, we propose using passive biomonitoring to collect real-time cardiovascular responses, i.e., heart rate variability (HRV), and alcohol use via unobtrusive monitors (i.e., Firstbeat Bodyguard 2, BACtrack Skyn) with scheduled salivary cortisol samples. Individuals with AUD will then be provided with four weeks of behavioral treatment with daily assessments. During the final two weeks of treatment, individuals with AUD will complete another three-day period of intensive self-reports, including another 72-hours physiological and salivary cortisol monitoring.
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Inclusion criteria
Men and women who:
a. Social drinkers: i. Must report a past-year history of alcohol use ii. Must not meet current AUD and may have only met mild AUD during their lifetime (not within the past year) iii. Provide a negative urine toxicology screen. b. Individuals with Alcohol Use Disorder: i. Must meet current criteria for AUD based on the SCID (≤ 2 symptoms in past year); ii. Report at least weekly use of alcohol. iii. Do not meet criteria for any other substance use disorders other than mild Cannabis Use Disorder.
iv. Provide a positive urine toxicology screen for alcohol during intake. 5) Can provide written informed consent.
Exclusion criteria
54 participants in 2 patient groups
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Central trial contact
Stephanie Wemm, PhD
Data sourced from clinicaltrials.gov
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