Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies
  1. Home
  3. Real-world Engagement With A Generative Ai Conversational Agent For Mental Health Support: Retrospective Descriptive Study.
  1. Home
  3. Real-world Engagement With A Generative Ai Conversational Agent For Mental Health Support: Retrospective Descriptive Study.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Family-Focused Digital Mental Health Care for Pediatric Oppositional Symptoms and Caregiver Outcomes: Retrospective Analysis.

JMIR pediatrics and parenting·2026
Same author

Building a Science-Driven Business: How National Institutes of Health Funding Enabled an Evidence-Based Approach to Maternal Mental Health Innovation.

JMIR formative research·2026
Same author

Sources of perceived stress in people with aphasia: a qualitative study.

Aphasiology·2026
Same author

What predicts meditation app engagement? an evaluation of user characteristics and motivation.

Psychology & health·2026
Same author

School and Community Stakeholder Perceptions of a Free, Confidential Digital Mental Health Platform (Soluna): Mixed Methods Study Examining Barriers and Facilitators to Real-World Implementation at Scale and Early Impact.

JMIR formative research·2026
Same author

Clinically Meaningful Improvement in Depression and Anxiety Among Psychiatry Patients Within a Measurement-Based Care Digital Mental Health Intervention: A Retrospective Analysis of Real-World Data from Rula Health.

Inquiry : a journal of medical care organization, provision and financing·2026
Same journal

Remote Assessment of Parkinson Disease Using Deep Learning on Structured Mouse-Trace Data From Suspected Cases: Machine-Learning Pilot Feasibility Study.

JMIR formative research·2026
Same journal

Perspectives on Continuous Glucose Monitoring Among Adults with Type 2 Diabetes in the United Kingdom: Cross-Sectional Survey.

JMIR formative research·2026
Same journal

Improving Models to Predict Care Utilization Using Machine Learning: Retrospective Observational Study.

JMIR formative research·2026
Same journal

Implementing a Commercial AI Fracture Detection Tool in Health Care Using the Non-Adoption, Abandonment, Scale-Up, Spread, and Sustainability Framework: A Formative Evaluation Study.

JMIR formative research·2026
Same journal

An Evaluation of the Usability and Feasibility of the 50K4Life Mobile App for Delivering Walking Challenges to Public School Administrative Employees: Beta Testing Study.

JMIR formative research·2026
Same journal

Young Adults' Perspectives on an Ecological Momentary Intervention for Drinking to Cope: Qualitative Study.

JMIR formative research·2026
See all related articles

Related Experiment Video

Virtual Agent for Real-Time Motivational Interviewing by Integrating Adaptive Nonverbal Behavior and Language Models
07:14

Virtual Agent for Real-Time Motivational Interviewing by Integrating Adaptive Nonverbal Behavior and Language Models

Published on: December 23, 2025

Real-World Engagement With a Generative AI Conversational Agent for Mental Health Support: Retrospective Descriptive

Kelsey McAlister1, Courtney Jewell1, Jennifer Huberty1

  • 1Fit Minded, Inc, 2901 E Greenway Road PO Box, Phoenix, AZ, 30271, United States, 1 (602) 935-6986.

JMIR Formative Research
|June 26, 2026

View abstract on PubMed

Summary
This summary is machine-generated.

Generative artificial intelligence (GenAI) conversational agents in digital mental health interventions show high user engagement and satisfaction. These agents may support individuals facing barriers to traditional mental health care.

Keywords:
chatbotsdigital mental health interventionsdigital therapeuticsindustry sciencereal-world settinguser satisfaction

Related Experiment Videos

Virtual Agent for Real-Time Motivational Interviewing by Integrating Adaptive Nonverbal Behavior and Language Models
07:14

Virtual Agent for Real-Time Motivational Interviewing by Integrating Adaptive Nonverbal Behavior and Language Models

Published on: December 23, 2025

Area of Science:

  • Digital mental health interventions
  • Artificial intelligence in healthcare
  • User engagement studies

Background:

  • Generative artificial intelligence (GenAI) conversational agents are increasingly integrated into digital mental health interventions (DMHIs).
  • Empirical data on real-world engagement, usage patterns, and satisfaction with these agents are limited.

Purpose of the Study:

  • To characterize users of the GenAI conversational agent within the Mental DMHI.
  • To examine real-world usage patterns, satisfaction, and feedback.
  • To explore predictors of engagement with the GenAI conversational agent.

Main Methods:

  • Retrospective analysis of naturalistic user data from 5082 paid subscribers (October 2024 - March 2026).
  • Collected onboarding characteristics and session satisfaction via app-native items.
  • Captured session-level engagement metrics through backend data; analyzed using descriptive statistics, ANOVAs, t-tests, and mixed-effects logistic regression.

Main Results:

  • High user engagement with 59,602 sessions, primarily in evenings and outside business hours.
  • High mean session satisfaction (4.5/5), with "Insightful," "Felt seen," and "Good advice" as top descriptors.
  • High session-to-session return rate (92.6%), with satisfaction predicting return (OR 1.35).

Conclusions:

  • GenAI conversational agents in DMHIs demonstrate sustained real-world engagement, particularly outside traditional care hours.
  • Objective engagement data suggest GenAI may support individuals facing barriers to traditional mental health services.
  • Future research should investigate if these engagement patterns lead to clinically meaningful outcomes.