Evidence map›Paper›PMID 41522299›Full record

ArticleF1000Research2025

Knowledge, Attitudes, and Practices of Artificial Intelligence in Dentistry: A cross-sectional survey.

Usha Gv, Bhuvaneshwari Nadar, Sultan Almalki, Tushar Bhagat, Inderjit M Gowdar

Abstract read
In one paragraph

Article in F1000Research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
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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

5 authors.

Usha GvPublic Health Dentistry, Bapuji Dental College and Hospital, Davangere, Karnataka, 577004, India.ORCID https://orcid.org/0000-0003-3194-2626
Bhuvaneshwari NadarPublic Health Dentistry, Terna Dental College and Hospital, Nerul, Navi Mumbai, Maharashtra, 400706, India.ORCID https://orcid.org/0000-0002-9267-9297
Sultan AlmalkiPreventive Dental Sciences, Prince Sattam bin Abdulaziz University College of Dentistry, Al Kharj, Riyadh Province, 11942, Saudi Arabia.ORCID https://orcid.org/0000-0002-3369-9925
Tushar BhagatProsthodontics, Prince Sattam bin Abdulaziz University College of Dentistry, Al Kharj, Riyadh Province, 11942, Saudi Arabia.
Inderjit M GowdarPreventive Dental Sciences, Prince Sattam bin Abdulaziz University College of Dentistry, Al Kharj, Riyadh Province, 11942, Saudi Arabia.ORCID https://orcid.org/0000-0002-3920-8082

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Artificial intelligence (AI) is rapidly reshaping various aspects of human life, including healthcare. In the Western world, AI is increasingly applied in education and clinical practice through algorithms designed to analyze health data, aid in prediction, and assist with disease diagnosis. However, developing countries like India face obstacles in adopting AI due to limited resources and socio-cultural factors. Aim: This study seeks to assess and compare the knowledge, attitudes, and practices related to AI in dentistry among undergraduate and postgraduate students in South India. Methodology: A descriptive cross-sectional online survey was conducted among dental students in South India. The survey included 21 validated, structured, close-ended questions addressing demographic details, self-assessment of knowledge, attitudes toward AI applications in dentistry, and self-perceived understanding of AI practice in the field. Results: Of 208 respondents (81.8% response rate), 95.6% were familiar with the term AI. Postgraduates demonstrated significantly greater awareness of AI applications (90.9%) compared to undergraduates (25.8%). About 78.3% of undergraduates believed AI supports diagnosis and treatment planning, while 33.4% of undergraduates and 43.2% of postgraduates expressed concern that AI may replace dentists in the future. Most respondents acknowledged AI's role in oral radiology (UG: 79.1%; PG: 72.2%). Interest in future learning was high (UG: 82.5%; PG: 92.2%). Level of education was a significant predictor of knowledge (p<0.01), while male students showed more positive attitudes (p<0.01). First-year postgraduates reported better AI-related practices than other groups (p<0.01). Conclusion: Although most dental students lacked sufficient knowledge regarding the use of AI in dentistry, they displayed positive and encouraging attitudes toward its application. A large proportion expressed willingness to learn AI technologies to apply them in clinical practice. It is therefore recommended that universities and government bodies work together to integrate AI related topics into the dental curriculum to strengthen dental education in India.

Indexed as

Artificial IntelligenceDentistryHealth Knowledge, Attitudes, PracticeStudents, DentalAdultCross-Sectional StudiesFemaleHumansIndiaMaleSurveys and QuestionnairesYoung AdultArtificial IntelligenceAttitudeDental studentsKnowledgePractice

Identifiers

PMID41522299
PMCPMC12780518

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Registered trials

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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.