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

Related Experiment Video

Updated: Jun 30, 2026

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

Engagement Patterns with an AI Health Coach for Systemic Sclerosis Self-Management: A Mixed Methods Study.

Nirali Shah1, Melanie Morris2, Cristina Daraban1

  • 1University of Michigan, Ann Arbor, Michigan, USA.

Arthritis Care & Research
|June 29, 2026
PubMed
Summary
This summary is machine-generated.

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

A Beginner's Guide to Applying Large Language Models in Behavioral Interventions.

JMIR mHealth and uHealth·2026
Same author

Integrating social work into oral health care: a collaborative approach to achieving health equity.

Frontiers in public health·2026
Same author

Understanding barriers and facilitators to pediatric surgical access for rural patients: A qualitative study.

Journal of pediatric surgery·2026
Same author

The impact of pediatric surgery global travel fellowships: A study by the Canadian Association of Paediatric Surgeons Global Partnership Committee.

Journal of pediatric surgery·2026
Same author

Translation and Cultural Adaptation of the Measure Yourself Concerns and Wellbeing (MYCaW) Questionnaire Into German: Protocol for the iSWOP Study.

JMIR research protocols·2025
Same author

Indigenous Elders and Academic Leaders' Perspectives on Training Residents to Work With Indigenous Populations: A Constructivist Grounded Theory Study.

The clinical teacher·2025
Same journal

Associations Between Social Risk Factors and Acute Care Use Among Patients with Rheumatic Conditions.

Arthritis care & research·2026
Same journal

Anorectal Dysfunction in Systemic Sclerosis: Clinical Phenotypes and Functional Patterns.

Arthritis care & research·2026
Same journal

Determinants of body mass index in early systemic sclerosis: implications for nutritional risk stratification.

Arthritis care & research·2026
Same journal

Frailty Predicts Incident Osteoporotic Fractures in Veterans with Rheumatoid Arthritis.

Arthritis care & research·2026
Same journal

Assessing Reliability of an Electronic Gout Flare Assessment Protocol.

Arthritis care & research·2026
Same journal

Patient and Physician Global Disease Assessments in Systemic Sclerosis: Distinct and Complementary Constructs.

Arthritis care & research·2026
See all related articles

An artificial intelligence (AI) health coach shows promise for systemic sclerosis (SSc) self-management. High engagement, characterized by action-oriented and companionship interactions, was linked to potential fatigue improvements.

Area of Science:

  • Medical Informatics
  • Artificial Intelligence in Healthcare
  • Chronic Disease Management

Background:

  • Systemic sclerosis (SSc) requires ongoing self-management to mitigate disease progression and improve quality of life.
  • Traditional self-management support may not fully address the complex needs of SSc patients.
  • Emerging technologies like AI offer novel avenues for personalized patient support.

Purpose of the Study:

  • To assess the utility of an AI health coach for supporting self-management in individuals with systemic sclerosis.
  • To identify patterns of participant engagement with the AI health coach.
  • To explore the relationship between engagement levels and self-management outcomes.

Main Methods:

  • A mixed-methods study involving 20 participants with SSc interacting with an AI health coach for 4 weeks.

Related Experiment Videos

Last Updated: Jun 30, 2026

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

  • Quantitative usage metrics (conversations, messages, duration) classified participants into high and low engagement groups.
  • Qualitative analysis of chat transcripts identified interaction purposes, integrated with quantitative data.

    • Main Results:

    • Participants used the AI coach for goal setting, information seeking, companionship, and monitoring.
    • High engagement participants exhibited significantly more interactions related to goals, information, and companionship.
    • Exploratory analysis indicated potential fatigue improvements in the high engagement group.

    Conclusions:

    • Quantitative usage metrics alone may not fully capture AI health coach engagement.
    • Engagement is better understood through interaction frequency, action orientation, and companionship seeking.
    • AI health coaches represent a potentially valuable tool for SSc self-management support.