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Accepted for/Published in: JMIR Diabetes

Date Submitted: Jun 21, 2024
Date Accepted: Apr 25, 2025

The final, peer-reviewed published version of this preprint can be found here:

“Digital Clinicians” Performing Obesity Medication Self-Injection Education: Feasibility Randomized Controlled Trial

Coleman S, Lynch C, Worlikar H, Kelly E, Loveys K, Simpkin AJ, Walsh JC, Broadbent E, Finucane FM, O' Keeffe D

“Digital Clinicians” Performing Obesity Medication Self-Injection Education: Feasibility Randomized Controlled Trial

JMIR Diabetes 2025;10:e63503

DOI: 10.2196/63503

PMID: 40737494

PMCID: 12309861

Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

OBESITY Medication Self-Injection Education Using “Digital Clinicians”: A Feasibility Randomised Controlled Trial

  • Sean Coleman; 
  • Caitríona Lynch; 
  • Hemendra Worlikar; 
  • Emily Kelly; 
  • Kate Loveys; 
  • Andrew J Simpkin; 
  • Jane C Walsh; 
  • Elizabeth Broadbent; 
  • Francis M Finucane; 
  • Derek O' Keeffe

ABSTRACT

Background:

Artificial Intelligence (AI) chatbots have shown competency in a range of areas including clinical note taking, diagnosis, research and emotional support. An obesity epidemic, alongside a growth in novel injectable pharmacological solutions has put a strain on limited resources.

Objective:

This study investigates the use of an AI chatbot integrated with a digital avatar to create a “digital clinician”. This was used to provide mandatory patient education for those beginning semaglutide once-weekly self-administered injections for the treatment of overweight and obesity at a national centre.

Methods:

A “Digital Clinician” with facial and vocal recognition technology was generated with a bespoke 10-to-15-minute clinician-validated tutorial. A feasibility randomised controlled noninferiority trial compared knowledge test scores, self-efficacy, consultation satisfaction, and trust levels between those using the AI-powered clinician avatar and those receiving conventional semaglutide education from nursing staff. Attitudes were recorded immediately after the intervention and again at two-weeks after the education session.

Results:

43 participants were recruited, 27 to the intervention group and 16 to the control group. Patients in the “digital clinician” group were significantly more knowledgeable post-consultation (p<0.001) and had better feelings about their injections (p=.079). Patients in the control group were more satisfied with their consultation (p<0.001) and had more trust in their education provider (p<0.001). There was no significant difference in reported levels of self-efficacy. 81% of participants said they would use the resource in their own time.

Conclusions:

Bespoke AI chatbots integrated with digital avatars to create a “digital clinician” may perform healthcare education in a clinical environment. They can ensure higher levels of knowledge transfer yet are not as trusted as their human counterparts. “Digital clinicians” may have the potential to aid the redistribution of resources, alleviating pressure on bariatric services and healthcare systems. The extent to which remains to be determined in future studies. Clinical Trial: -


 Citation

Please cite as:

Coleman S, Lynch C, Worlikar H, Kelly E, Loveys K, Simpkin AJ, Walsh JC, Broadbent E, Finucane FM, O' Keeffe D

“Digital Clinicians” Performing Obesity Medication Self-Injection Education: Feasibility Randomized Controlled Trial

JMIR Diabetes 2025;10:e63503

DOI: 10.2196/63503

PMID: 40737494

PMCID: 12309861

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