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AI Avatar-Delivered Ear Nose Throat (ENT) Induction: A Pilot Feasibility Study of Confidence and Acceptability

Abstract:
BackgroundJunior doctors in otolaryngology (ENT) often start with varied prior experience, making effective induction essential. Artificial intelligence (AI) avatars are a novel method for delivering standardised educational content. This study evaluated whether an AI avatar-delivered ENT induction course could improve trainee confidence and explored participant perceptions.MethodsA modular online induction course was developed using AI-generated video avatars (HeyGen platform; HeyGen Inc., Santa Clara, CA, USA). Thirty junior doctors at a tertiary hospital completed the course and rated their confidence in seven ENT skills before and after training on a 10-point Likert scale. Post-course surveys assessed clarity, willingness to use AI in the future, and comparisons with traditional teaching.ResultsAll 30 participants completed pre- and post-course assessments. Confidence improved significantly across all domains (e.g., identifying normal endoscopic anatomy: 3.3 → 7.6, pConclusionsAn AI avatar-delivered ENT induction course significantly improved self-reported confidence and was broadly acceptable, though not universally preferred. Most trainees perceived little difference in learning or retention compared with traditional teaching. These findings support AI avatars as a feasible adjunct for induction training, warranting further evaluation with larger, standardised cohorts and objective outcomes.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.7759/cureus.94230

Authors

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Institution:
University of Oxford
Role:
Author
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Institution:
University of Oxford
Role:
Author


Publisher:
Springer
Journal:
Cureus: Journal of Medical Science More from this journal
Volume:
17
Issue:
10
Pages:
e94230
Publication date:
2025-10-09
Acceptance date:
2025-10-09
DOI:
EISSN:
2168-8184
ISSN:
2168-8184
Pmid:
41209936


Language:
English
Keywords:
Pubs id:
2350325
UUID:
uuid_cae224ba-9e85-4c03-baf2-6e970f6e79b6
Local pid:
pubs:2350325
Source identifiers:
3479560
Deposit date:
2025-11-18
ARK identifier:
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