Evidence map›Paper›PMID 40389919›Full record

ArticleBMC medical education2025

Exploring dental students' attitudes and perceptions toward artificial intelligence in dentistry in Iran.

Amir Ghasemian, Mehrdad Salehi, Vahid Ghavami, Mohammadreza Yari, Seyed Saeed Tabatabaee, Javad Moghri

Abstract read
In one paragraph

Article in BMC medical education, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. Article
  11. Review
  12. 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.

Amir GhasemianStudent Research Committee, Mashhad University of Medical Sciences, Mashhad, Islamic Republic of Iran.
Mehrdad SalehiStudent Research Committee, Mashhad University of Medical Sciences, Mashhad, Islamic Republic of Iran.
Vahid GhavamiDepartment of Biostatistics, School of Health, Mashhad University of Medical Sciences, Mashhad, Islamic Republic of Iran.
Mohammadreza YariSocial Determinants of Health Research Center & Student Research Committee, Mashhad University of Medical Sciences, Mashhad, Islamic Republic of Iran.
Seyed Saeed TabatabaeeSocial Determinants of Health Research Center & Student Research Committee, Mashhad University of Medical Sciences, Mashhad, Islamic Republic of Iran. TabatabaeeS@mums.ac.ir.
Javad MoghriSocial Determinants of Health Research Center & Student Research Committee, Mashhad University of Medical Sciences, Mashhad, Islamic Republic of Iran. MoghriJ@mums.ac.ir.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionAI has the potential to enhance diagnostics, optimize treatment planning, and improve patient care. However, concerns remain regarding professional autonomy, ethical considerations, and the need for adequate training. This research aims to address the gap in understanding how Iranian dental students perceive AI in their future practice. METHODOLOGY: A cross-sectional study was conducted among 235 dental students from different academic years who were selected through stratified sampling. A validated questionnaire with a high Cronbach's alpha coefficient (0.90) was used to assess students' attitudes toward AI. Data were analyzed via descriptive statistics, with a chi-square test examining associations between demographic factors and AI perceptions.

resultsOverall, 80.4% agreed that AI would significantly advance dentistry, particularly in diagnostic applications such as radiographic analysis (75.7%) and periodontal disease detection (78.7%). However, skepticism persisted regarding AI replacing human professionals, with nearly 50% disagreeing that AI could replace dentists and with only 31.1% viewing AI as a definitive diagnostic tool. The attitudes varied by demographic factors, with female students favoring AI inclusion in education and male students exhibiting greater confidence in the diagnostic capabilities of AI. Compared with general dentistry students, specialized students were more confident in AI-assisted implant planning.

conclusionDental students hold a generally positive view of AI's role in dentistry while maintaining caution about its limitations. Integrating AI into dental curricula is essential for addressing knowledge gaps and preparing students for AI-enhanced practice. Future research should balance technological advancements with ethical considerations to ensure that AI effectively contributes to improved dental education and patient care. CLINICAL TRIAL NUMBER: Not applicable.

Indexed as

Artificial IntelligenceAttitude of Health PersonnelDentistryStudents, DentalAdultCross-Sectional StudiesEducation, DentalFemaleHumansIranMaleSurveys and QuestionnairesYoung AdultArtificial intelligenceAttitudesDental studentsDentistryEducationPerceptions

Identifiers

PMID40389919
PMCPMC12090689

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.