Evidence map›Paper›PMID 42399877›Full record

ArticleBMC oral health2026

Can AI chatbots be reliable in dental emergencies? quality assessment of Arabic responses to dental emergency inquiries and public attitudes toward their use.

Khalid Talal Aboalshamat, Abrar Khalid Demyati, Abdalmalik Osamah Ghandourah, Shumukh Yousef Balhmer, Wareef Omar Ghazzawi, Sali Abdullah Sayed, Refal Abdullah Aljabri, Rama Juwaybir Alhuzali

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Article in BMC oral health, 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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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Khalid Talal AboalshamatDental Public Health Division, Preventative Dentistry Department, College of Dental Medicine, Umm Al-Qura University, Makkah, Saudi Arabia. ktaboalshamat@uqu.edu.sa.ORCID 0000-0001-5957-8681
Abrar Khalid DemyatiOral Maxillofacial Surgery Department, College of Dental Medicine, Umm Al-Qura University, Makkah, Saudi Arabia.
Abdalmalik Osamah GhandourahOral Maxillofacial Surgery Department, College of Dental Medicine, Umm Al-Qura University, Makkah, Saudi Arabia.
Shumukh Yousef BalhmerCollege of Dental Medicine, Umm Al-Qura University, Makkah, Saudi Arabia.
Wareef Omar GhazzawiCollege of Dental Medicine, Umm Al-Qura University, Makkah, Saudi Arabia.
Sali Abdullah SayedCollege of Dental Medicine, Umm Al-Qura University, Makkah, Saudi Arabia.
Refal Abdullah AljabriCollege of Dental Medicine, Umm Al-Qura University, Makkah, Saudi Arabia.
Rama Juwaybir AlhuzaliCollege of Dental Medicine, Umm Al-Qura University, Makkah, Saudi Arabia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundArtificial intelligence (AI) is increasingly penetrating health and dental fields without sufficient monitoring of its quality and applicability.

aimThis study aimed to evaluate public attitudes toward AI chatbots in dental emergencies and assess the quality of Arabic-language responses generated by different AI chatbots for dental emergency inquiries.

methodsThe study had two parts. Part one: A cross-sectional online survey where 441 Saudi residents aged ≥ 18 years answered a 33-item questionnaire in Arabic that included 14 items to measure attitudes about the use of AI chatbots in dental emergencies with a 5-point Likert scale. Part two: From participant answers and oral and maxillofacial surgeons, we selected 50 dental inquiries about dental emergencies and presented them in Arabic to five AI chatbots (ChatGPT-5.1, Google Gemini 3, Claude Sonnet 4.5, Grok 1.3.40, and DeepSeek 3.2). Responses were evaluated by two calibrated oral and maxillofacial surgeons using 5-point Likert scales for accuracy, clarity, comprehensiveness, relevance, and acceptability.

resultsParticipants showed moderately positive attitudes (2.72-3.89/5) about AI chatbots for dental emergencies. AI chatbots had generally high mean scores for accuracy (4.08-4.87), clarity (4.21-4.92), comprehensiveness (4.10-4.67), relevance (4.11-4.91), and acceptance (3.84-4.89). No significant differences were found among the AI chatbots, except Grok, which scored lower than the others on multiple quality measures (all p < 0.001). Inter-rater reliability varied across chatbots, single-measure ICC values ranging from 0.23 to 0.60; however, exact agreement was 69.8%, and 94.5% of paired ratings differed by no more than one point.

conclusionSaudi public attitudes toward AI chatbots in dental emergencies were moderate. Overall, the quality of Arabic AI chatbot responses was high, although Grok had significantly lower ratings. Human supervision remains essential, and continuous "living" evaluations are needed to track rapidly evolving chatbot performance.

Indexed as

Artificial IntelligenceAttitude to HealthEmergenciesPublic OpinionAdolescentAdultCross-Sectional StudiesFemaleHumansMaleMiddle AgedReproducibility of ResultsSaudi ArabiaSurveys and QuestionnairesYoung AdultArabic languageArtificial intelligenceChatbotsChatGPTDental emergenciesPublic attitudes

Identifiers

PMID42399877
PMCPMC13479445

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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.