Evidence map›Paper›PMID 42683727›Full record

ArticleOral health & preventive dentistry2026

Trust in Artificial Intelligence-Generated Oral Health Information and Its Influence on Patient Decision-Making: A Cross-Sectional Study.

Berrak Ulu Emir, Bilkan Kara, Sayna Behkar, Erkan Özcan

Abstract read
In one paragraph

Article in Oral health & preventive dentistry, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Berrak Ulu Emir
Bilkan Kara
Sayna Behkar
Erkan Özcan

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeArtificial intelligence (AI)-assisted applications are increasingly used to obtain health-related information; however, concerns remain regarding the reliability of AI-generated responses and their influence on patient attitudes and decision-making. This study aimed to evaluate the use of AI-assisted applications among patients, their trust in AI-generated information, and the influence of these applications on oral-health-related decision-making. METHODS AND MATERIALS: This cross-sectional questionnaire-based study included 430 patients attending the Department of Periodontology. Participants completed a structured questionnaire evaluating AI-assisted application use, trust in AI-generated oral health information, and the effects of AI on oral-health-related attitudes. Categorical variables were presented as frequencies (n) and percentages (%). Associations between categorical variables were analysed using the chi-square test. Effect sizes were evaluated using Cramér's V coefficient. Statistical significance was set at p 0.05.

resultsA total of 430 participants completed the questionnaire, including 300 AI users. AI usage rates were generally similar across reasons for admission, although the highest usage was observed among individuals attending routine check-ups (18/19; 94.7%). In treatment-related decisions, most participants preferred dentists' opinions over AI-generated recommendations (80.8%; p 0.01). Trust was significantly associated with AI usage frequency (p 0.01), whereas education level was significantly associated with AI usage (p 0.001). Education level was also associated with willingness to consult AI-assisted programmes regarding dentist-created treatment plans (p = 0.033).

conclusionAI-assisted applications have become an important part of health information-seeking behaviour, particularly among younger and more educated individuals. However, patients remain cautious about the reliability of AI-generated information and continue to prioritise professional dental expertise in treatment-related decisions.

Indexed as

Artificial IntelligenceDecision MakingOral HealthTrustAdultAgedCross-Sectional StudiesFemaleHumansMaleMiddle AgedSurveys and QuestionnairesYoung Adultartificial intelligenceChatGPToral healthsurveytrust

Identifiers

PMID42683727
PMCPMC13536940

What OpenQuestion holds

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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.