A Feasibility and Acceptability Study of a Large Language Model-based Chatbot for Brief Alcohol Intervention Among Emerging Adults
Key facts
- Who runs it
- Massachusetts General Hospital
- Where
- Boston, United StatesSee the site
- Trial code
- Status
- Not yet recruiting
- People taking part
- 20 people, planned
- Starts
- 1 Jun 2027
- Expected to end
- 31 Aug 2028
- Type of study
- Interventional
- Treatments tested
- Large language model-based chatbot brief alcohol intervention session
- Record updated
- 22 October 2025
Who can take part
- Age
- 18 years to 29 years
- Sex
- Women and men
- Healthy volunteers
- Cannot take part
The registry criteria, word for word
Show all 8 criteriaShow less
Who can take part
- 18-29 years old
- Engaged in past-month hazardous drinking (consuming ≥ 5/4 drinks for men/women on two or more occasions in the past month) or exceeded recommended guidelines for risky drinking (> 14/7 drinks per week for men/women)
- Able to read and comprehend English at a 5th grade level
Who cannot take part
- Previous or current engagement in alcohol or drug treatment
- Report a history of or active psychosis
- Risk for alcohol withdrawal as evidenced by very heavy weekly drinking reports on the alcohol screener (> 40 standard drinks in a typical week in the past month)
- Demonstrate inability or unwillingness to attend in-person office visits
- Demonstrate inability or unwillingness to identify an emergency contact who could be contacted in case the participant becomes lost to follow-up
Check if you might fit
Answer for yourself. This is not a decision: only the study team can say whether you can take part.
- Are you between 18 and 29 years old?
Where in United States
- Massachusetts General HospitalBoston, United StatesContact: Research CoordinatorNot yet recruiting
About the trial
What the trial wants to find out
American emerging adults (EAs; aged 18-29 years) have the highest rates of alcohol use disorder (AUD) and the lowest levels of treatment engagement of any age group. Innovative, scalable, and cost-effective strategies are needed to expand early detection and intervention for EAs engaged in patterns of drinking associated with AUD. Because digital technology use is frequent among EAs, digital interventions may be a particularly suitable way to reach this population. Prior studies of digital alcohol interventions demonstrate modest but consistent reductions in alcohol use, but these tools are often limited by a lack of interactivity and personalization. Large language model (LLM)-based chatbots, such as ChatGPT, may address these limitations by enabling personalized, adaptive, and human-like engagement. These features have the potential to increase uptake and engagement with screening and brief interventions among EAs. This study will develop, validate, and conduct an open trial of an LLM-based chatbot-delivered brief intervention designed to reduce alcohol use and problems among EAs, with the primary goal of establishing preliminary feasibility and acceptability.
The group in the trial
- Large language model-based chatbot brief alcohol interventionTreatment being tested
All participants will interact with a large language model-based chatbot designed to deliver a brief alcohol intervention session.
Treatment: Large language model-based chatbot brief alcohol intervention session
Questions to ask the study team
- How often do I need to come in, and for how long each time?
- Are travel costs paid?
- Can I keep my own doctor?
- What happens if I want to stop?
Contact the study team: see the registry record → Contacts and Locations
Print a page for my doctorData and sources
- Registry record
- Listed on ClinicalTrials.gov.
- Official title
- A Feasibility and Acceptability Study of a Large Language Model-based Conversational Agent for Brief Alcohol Intervention Among Emerging Adults
- Fit questions
- Built from NCT07214831, who can take part
- Record updated
- 22 October 2025