Evidence map›Paper›PMID 39379636›Full record

ArticleOral radiology2025

Patients' attitudes toward artificial intelligence in dentistry and their trust in dentists.

Hasibe Sevilay Bahadir, Neslihan Büşra Keskin, Emine Şebnem Kurşun Çakmak, Gürkan Güneç, Kader Cesur Aydin, Fatih Peker

Abstract read
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In one paragraph

Article in Oral radiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 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

7 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  3. Article
  4. Review
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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

6 authors.

Hasibe Sevilay BahadirFaculty of Dentistry, Department of Restorative Dentistry, Ankara Yıldırım Beyazıt University, Ankara, Turkey. sevilay.bahadir@hotmail.com.ORCID 0000-0001-8577-4408
Neslihan Büşra KeskinFaculty of Dentistry, Department of Endodontics, Ankara Yıldırım Beyazıt University, Ankara, Turkey.ORCID 0000-0002-1053-7675
Emine Şebnem Kurşun ÇakmakFaculty of Dentistry, Department of Dentomaxillofacial Radiology, Ankara Yıldırım Beyazıt University, Ankara, Turkey.ORCID 0000-0002-7113-5450
Gürkan GüneçDepartment of Endodontics, Health Sciences University Hamidiye Faculty of Dentistry, Istanbul, Turkey.ORCID 0000-0002-7056-7876
Kader Cesur AydinFaculty of Dentistry, Department of Dentomaxillofacial Radiology, Istanbul Medipol University, Istanbul, Turkey.ORCID 0000-0002-6429-4197
Fatih PekerFaculty of Dentistry, Department of Dentomaxillofacial Radiology, Ankara Yıldırım Beyazıt University, Ankara, Turkey.ORCID 0009-0001-0491-7938

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThis study intended to evaluate patients' attitudes toward the use of AI in dental radiographic detection of occlusal caries and the impact of AI-based diagnosis on their trust in dentists.

methodsA total of 272 completed questionnaires were included in this study. In the first part of the study, approval was obtained from the patients, and data were collected about their socio-demographic characteristics. In the second part the 11-item Dentist Trust Scale was applied. In the third and fourth parts, there were questions about two clinical scenarios, the patients' knowledge of attitudes toward AI, and how the AI-based diagnosis had affected their trust. Evaluation was performed using a Likert-type scale. Data were analyzed with the Chi-square, one-way ANOVA, and ordinal logistic regression tests (p < 0.05).

resultsThe patients believed that "AI is useful" (3.86 ± 1.03) and were not afraid of the use of AI in dentistry (2.40 ± 1.05). Educational level was considerably related to the patients' attitudes to the use of AI for dental diagnostics (p < 0.05). The patients stated that "dentists are extremely thorough and careful" (4.39 ± 0.77).

conclusionsThe patients displayed a positive attitude to AI-based diagnosis in the dental field and appear to exhibit trust in dentists. The use of Al in routine clinical practice can provide important benefit to physicians as a clinical decision support system in dentistry and understanding patients' attitudes may allow dentists to shape AI-supported dentistry in the future.

Indexed as

Artificial IntelligenceAttitude to HealthDental CariesDentist-Patient RelationsTrustAdultAgedFemaleHumansMaleMiddle AgedSurveys and QuestionnairesArtificial intelligenceCommunicationDentist trustDiagnosisMachine learningPatients

Identifiers

PMID39379636

What OpenQuestion holds

Textmetadata
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.