Evidence map›Paper›PMID 42370309›Full record

ReviewFrontiers in dental medicine2026

Developing a competency framework for artificial intelligence in undergraduate dental education.

Supachai Chuenjitwongsa, Tanit Arunratanothai, Dinesh Rokaya, Lakshman P Samaranayake, Anjalee Vacharaksa, Thanaphum Osathanon

Abstract readReview
In one paragraph

Review in Frontiers in dental medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Supachai ChuenjitwongsaDental Education Unit, Office of Academic Affairs, Faculty of Dentistry, Chulalongkorn University, Bangkok, Thailand.
Tanit ArunratanothaiDental Education Unit, Office of Academic Affairs, Faculty of Dentistry, Chulalongkorn University, Bangkok, Thailand.
Dinesh RokayaClinical Sciences Department, College of Dentistry, Ajman University, Ajman, United Arab Emirates.
Lakshman P SamaranayakeGlobal Research Cell, Dr. D. Y. Patil Dental College and Hospital, Dr. D. Y. Patil Vidyapeeth, Pimpri, Pune, India.
Anjalee VacharaksaMaster of Science Program in Geriatric Dentistry and Special Care Dentistry, Faculty of Dentistry, Chulalongkorn University, Bangkok, Thailand.
Thanaphum OsathanonDental Education Unit, Office of Academic Affairs, Faculty of Dentistry, Chulalongkorn University, Bangkok, Thailand.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Artificial intelligence (AI) technologies are evolving rapidly and are increasingly being adopted across various domains, including dentistry. Therefore, the standardised integration of AI into the dental curriculum is crucial to cultivate students' knowledge, skills, attitudes, and awareness for effective engagement within an increasingly AI-driven educational and clinical ecosystem. To achieve these learning outcomes, a well-structured competency framework is required to outline the specific AI-related competencies expected of dental students. This article presents the development of such a competency framework, focusing on three key domains: i) AI fundamentals, ii) AI implementation, and iii) ethical and professional conduct in AI use. Particular emphasis is placed on the humane dimensions in AI integration, highlighting responsibility, accountability, and ethical considerations. The framework draws on the essential components of AI literacy promulgated by a dental school in Thailand and aligns with similar guidelines from other authoritative international sources. The examples of topic structures and approaches for integrating these competencies into the undergraduate curriculum are also discussed. Ultimately, this competency framework seeks to strengthen AI literacy and prepare a new generation of dental professionals to thrive in the emerging landscape of digital transformation and AI-driven education.

Indexed as

artificial intelligenceclinical integrationcompetency frameworkdental educationethical considerations

Identifiers

PMID42370309
PMCPMC13294060

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.