Heavy drinkers needed for paid research into tastes, learning and memory
26 April 2017
Update to study advert: female and male participants needed
Researchers from the UCL Clinical Psychopharmacology Unit are looking for beer drinkers who regularly consume 4 or more drinks per day (for males) or 3 or more drinks per day (for females), at least 3 days per week.
Researchers are examining how learning and memory
influences heavy drinkers’ attitudes and behaviour in relation to drinking. They
are specifically recruiting people who currently wish to reduce their drinking
levels. The study will involve three sessions at UCL over course of a two-week period.
Participants will be paid up to £70 for their time.
Please only apply if you meet the following conditions:
- You are female
- You primarily drink beer
- You seriously want to reduce your drinking
- You speak fluent English
- You can make it to UCL for three testing sessions
- You have normal or corrected-to-normal colour vision
- You would be willing to consume beer or orange juice on each day of the study
- You DO NOT have a diagnosis of alcohol dependence or other drug dependence
- You DO NOT have any learning or memory impairments
- You DO NOT have a currently diagnosed mental illness
- You HAVE NOT taken part in an alcohol study in the UCL Clinical Psychopharmacology Unit in the past.
Please note that researchers have other criteria for
taking part in the study and they will be conducting a telephone screen to check participants eligibility before the study begins.
For more information and to apply, please email firstname.lastname@example.org with the subject line ‘ReMIT Behavioural’ and your email address included in the email. Researchers will send you an information sheet to read and can then arrange a screening if you want to take part.
Participation in this study will be confidential and anonymity will be maintained.
This study has been approved by the UCL Research Ethics Committee (Project ID Number): 3901/001
Tiffany Koa, UCL Clinical Psychopharmacology Unit Tracker Lab