Alcohol Use Disorder
Conditions
Brief summary
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.
Detailed description
This feasibility and acceptability study will develop, validate, and conduct a Phase I single-arm open trial of a large language model (LLM)-based chatbot-delivered brief intervention designed to reduce alcohol use and problems among EAs. To develop the augmented LLM, the investigators will use instruction fine-tuning to enhance conversational abilities within the context of brief interventions based on high-fidelity recordings of sessions from prior clinical trials and simulated patient-provider interactions. A retrieval augmented generation system will be developed to ensure the model delivers accurate information. The augmented LLM will be incorporated into a chatbot interface delivered through a user-friendly web application. To validate the chatbot's capability for delivering brief alcohol interventions, patient actors (clinical or counseling psychology PhD students) will be assigned clinical vignettes depicting diverse EAs with patterns of drinking associated with alcohol use disorder. Patient actors will engage in two randomly ordered online text-based brief intervention sessions for each vignette (one with the chatbot and one with a human clinician). Blinded transcripts from sessions will be reviewed by experts to assess treatment fidelity. To maximize and test initial feasibility and acceptability of the intervention, the investigators will conduct semi-structured interviews with 20 EAs who report hazardous drinking, followed by an open trial with another 20 EAs.
Interventions
BEHAVIORALLarge language model-based chatbot brief alcohol intervention session
The intervention is a large language model-based chatbot designed to delivered brief alcohol interventions using motivational interviewing-consistent strategies. The chatbot session will last approximately 45 minutes and will include a decisional balance exercise, feedback on drinking patterns, normative beliefs about drinking, alcohol-related consequences, goal setting, and harm-reduction strategies.
Sponsors
National Institute on Alcohol Abuse and Alcoholism (NIAAA)
Massachusetts General Hospital
Study design
Allocation
NA
Intervention model
SINGLE_GROUP
Primary purpose
TREATMENT
Masking
NONE
Eligibility
Sex/Gender
ALL
Age
18 Years to 29 Years
Healthy volunteers
No
Inclusion criteria
* 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
Exclusion criteria
* Report a history of or active psychosis * Previous or current engagement in alcohol or drug treatment * 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
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Acceptability - recommend to others | Immediate post-intervention session | Percentage of participants who agree or strongly agree they would recommend the chatbot to others |
| Time to achieve target enrollment | Enrollment | Recruitment feasibility will be evaluated based on the length of time needed to recruit target enrollment (N = 20) |
| Rate of participant retention | 1-month post intervention1-month post intervention | Retention feasibility will be achieved if \>80% of participants who consented to participating in the study complete one-month follow-up assessment. |
| Acceptability (System Usability Scale) | Immediate post-intervention session | Acceptability of the conversational agent-delivered intervention will be measured using the 10-item System Usability Scale. Each question is rated on a Likert-type scale ranging from (1) strongly disagree to (5) strongly agree. |
| Acceptability - intervention delivery method | Immediate post-intervention session | Percentage of participants who agree or strongly agree the intervention delivery method was acceptable |
| Acceptability - usable | Immediate post-intervention session | Percentage of participants who agree or strongly agree the intervention was easy to interact with |
| Acceptability - helpful | Immediate post-intervention session | Percentage of participants who agree or strongly agree the intervention was helpful |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Daily drinking questionnaire (DDQ) | Enrollment and 1 month post-intervention | Past-month typical drinks per week and frequency of heavy drinking will be assessed using the DDQ. Respondents are asked to record the number of drinks they consume each day of a typical week over the previous month. |
| Alcohol Use Disorders Identification Test (AUDIT) | Enrollment and 1 month post-intervention | Past-month frequency of heavy drinking will be assessed using the AUDIT, a 10-item screening tool used to identify hazardous and harmful drinking patterns. Total scores range from 0 to 40, with higher scores indicating more hazardous or harmful drinking patterns. |
| Young Adult Alcohol Consequences Questionnaire (YAACQ) | Enrollment and 1 month post-intervention | Alcohol-related problems will be assessed using the YAACQ. Respondents will be asked to indicate (yes/no) which of the 48 potential problems they have experienced as a result of their drinking over the previous month. |
| Protective behavioral strategies scale (PBSS) | Enrollment and 1 month post-intervention | Protective behavioral strategies will be assessed using the 15-item PBSS. Participants will be asked to indicate how often they used each strategy when drinking alcohol during the previous month. Response options are presented on a 6-point Likert type scale ranging from 1 (never) to 6 (always). |
| Alcohol treatment utilization | Enrollment and 1 month post-intervention | Alcohol treatment utilization, including a variety of options, will be measured by asking respondents to indicate (yes/no) which of the potential options they have utilized. |
| Motivation to change drinking (Readiness Ruler) | Enrollment, immediate post-intervention session, and 1 month post-intervention | Motivation to change drinking will measured using the Readiness Ruler. |
Countries
United States
Contacts
Primary ContactAlex M Russell, PhD
Backup ContactSamuel F Acuff, PhD
Outcome results
None listed