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Use of a Generative AI (Gen-AI) Chatbot for Anxiety and Depression Among Persons With Cannabis Use

T

Trustees of Dartmouth College

Status and phase

Enrolling
Phase 1

Conditions

Cannabis Use Disorder
Depression, Anxiety
Anxiety
Depression - Major Depressive Disorder

Treatments

Device: Therabot-CALM

Study type

Interventional

Funder types

Other
NIH

Identifiers

NCT06920238
5P30DA029926-14 (U.S. NIH Grant/Contract)
STUDY00033219

Details and patient eligibility

About

The goal of this clinical trial is to learn if Therabot-CALM (Cannabis, Anxiety, Low Mood) has acceptability among users and could work to improve the symptoms of persons with cannabis use disorder and anxiety and/or depression. The main question it aims to answer is:

What is the usability, feasibility, and acceptability of Therabot-CALM in persons with Cannabis Use Disorder and Anxiety and/or Depression?

Participants will

  • Take a screening questionnaire
  • Participate in two virtual 1-hour interviews to provide feedback on app design and suggest features.
  • Engage with Therabot-CALM in a 4-week clinical trial and provide feedback on their app experience in a third virtual interview

Full description

Participants will complete a two-stage screening process via REDCap to determine their eligibility for enrollment. Participants who meet criteria and provide informed consent will be enrolled and participate in three interviews and the 4-week clinical trial.

After the first interview, researchers will fine-tune Therabot-CALM based on feedback received during the interview. After the second interview, experts by experience (EBEs) will engage with Therabot-CALM at least once per day for 4 weeks. After the clinical trial period, participants will receive an email with a link to complete the post-intervention measures delivered via REDCap, including the System Usability Scale (SUS), Treatment Acceptability and Adherence Scale (TAAS), Cannabis Use Disorders Identification Test - Revised (CUDIT-R), the Daily Sessions, Frequency, Age of Onset, and Quantity of Cannabis Use Inventory (DFAQ-CU), the 9-item Patient Health Questionnaire for depression (PHQ-9), and the 7-item generalized anxiety disorder screener for DSM-5 (GAD-7). Participants will then be asked to return for a third interview to provide feedback on their experience with Therabot-CALM.

Researchers will use the IDEAS (Innovate, Develop, Evaluate, Adapt, Scale) Impact Framework to plan and conduct three, one-on-one interviews with a trained research assistant (RA). Each interview script will be developed using the IDEAS Impact Framework and follow a semi-structured design, such that the RA will follow a set of questions, with as-needed probing for follow-up. Interviews will be recorded via a virtual platform.

Enrollment

15 estimated patients

Sex

All

Ages

18+ years old

Volunteers

No Healthy Volunteers

Inclusion criteria

  • Is 18 years or older.
  • Meet criteria for current CUD (CUDIT-R>=12) and MDD (PHQ-9>=10), and/or GAD (GAD-7>=10).
  • Have reliable access to the internet and a compatible device for Therabot-CALM.
  • Have willingness and capacity to provide informed consent and commit to participating in all assessments and interventions during the study.
  • Attend the first interview.

Exclusion criteria

  • Moderate to High risk of STBs as determined by the C-SSRS or baseline questionnaires.
  • Current psychosis (as determined by brief psychosis screen).
  • Current participation in another digital mental health intervention.

Trial design

Primary purpose

Device Feasibility

Allocation

N/A

Interventional model

Single Group Assignment

Masking

None (Open label)

15 participants in 1 patient group

Therabot-CALM
Experimental group
Description:
Participants will engage in three one-hour interviews and a 4-week clinical trial where they may interact with Therabot-CALM as much or as little as they want.
Treatment:
Device: Therabot-CALM

Trial contacts and locations

1

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Central trial contact

Michael V Heinz, MD; Amanda C Collins, Ph.D.

Data sourced from clinicaltrials.gov

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