Evidence map›Paper›PMID 40615869›Full record

ArticleBMC medical education2025

Readiness to use artificial intelligence: a comparative study among dental faculty members and students.

Nahid Ahmadian Yazdi, Ulduz Zamaniahari, Hanieh KhadiviMaleki, Parsa Hasanabadi

Abstract readComparative Study
PubMed Full text at PMC Publisher
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 10 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 2 pooled it
–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

10 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. 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

4 authors.

Nahid Ahmadian YazdiEducation Development Center, Deputy of Education, Ardabil University of Medical Sciences, Ardabil, Iran.
Ulduz ZamaniahariDepartment of Oral Medicine, School of Dentistry, Ardabil University of Medical Sciences, Ardabil, Iran.
Hanieh KhadiviMalekiSchool of Dentistry, Ardabil University of Medical Sciences, Ardabil, Iran.
Parsa HasanabadiStudent Committee of Medical Education Development, education developement center, Kurdistan University of Medical Sciences, Sanandaj, Iran. parsa.has@yahoo.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundArtificial intelligence (AI) is prone to become a key element in dentistry, especially education and practice. Understanding the dental students' perspectives, who will be the next generation of practitioners, is crucial for effective technology integration in practice and education. This study explored the attitudes of dental faculty members and students in Iran toward AI.

methodsThis descriptive-analytical study, conducted in 2024 at Ardabil University of Medical Sciences, involved dental faculty members and students. Participants completed the Persian version of the 22-item Medical Artificial Intelligence Readiness Scale (MAIRS) to assess AI readiness across cognition, ability, insight, and ethics domains. Nonparametric tests, including the Mann-Whitney U and Wilcoxon signed-rank tests, analyzed the data, with significance set at p < 0.05, using SPSS v.26 software.

resultsThe study involved 36 faculty members and 205 dental students from Ardabil University of Medical Sciences. Results indicated that faculty members had a significantly higher AI readiness score (2.99 ± 0.66) compared to students (2.36 ± 2.56, p < 0.001). No demographic factors significantly correlated with AI readiness among faculty members. Among students, only university entrance exam rank showed a significant correlation with readiness scores (p = 0.03). Both groups scored highest in the ethics domain, highlighting a greater sensitivity to ethical issues compared to other domains.

conclusionOur study highlights a readiness gap between faculty members and students. This gap emphasizes the need for a comprehensive AI-focused educational curriculum that enhances theoretical and practical competencies, prepares future dental professionals for an AI-driven healthcare landscape, and offers professional development for faculty members. CLINICAL TRIAL NUMBER: No applicable.

Indexed as

Artificial IntelligenceAttitude of Health PersonnelEducation, DentalFaculty, DentalStudents, DentalAdultFemaleHumansIranMaleSurveys and QuestionnairesYoung AdultArtificial intelligenceDentistryDentistry faculty members and students

Identifiers

PMID40615869
PMCPMC12228260

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.