Observational studyBMC pediatrics2026
An AI-Assisted pictorial measure of children's dental anxiety during the initial child-dentist interaction.
Observational study in BMC pediatrics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07387055 (The Effect of Artificial Intelligence on the Development of Projective Methods Used in the Determination of Dental Anxiety in Children), which is not on this map. Not yet cited in PubMed.
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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.
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The Effect of Artificial Intelligence on the Development of Projective Methods Used in the Determination of Dental Anxiety in Children
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2 authors.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundThe potential influence of the initial child-dentist interaction on dental anxiety (DA) in preschool children remains insufficiently understood. Accurate assessment of DA using pictorial measures is essential to better characterize this relationship. However, pictorial self-report measures still have several limitations from a contemporary perspective, and evidence regarding the impact of the initial interaction on DA remains limited. This study aimed to evaluate the effect of the initial child-dentist interaction on DA and to explore potential Artificial Intelligence (AI)-based refinements in traditional pictorial measures.
methodsAn observational pre-post (within-subject repeated-measures) study included 171 children aged 3-6 years attending their first dental visit. An AI-assisted pictorial measure (AI-PM) was designed through an expert panel process addressing the limitations of existing tools. DA was assessed before and after the initial child-dentist interaction using the Facial Image Scale (FIS), Venham Picture Test (VPT), Raghavendra, Madhuri, Sujata Pictorial Scale (RMS-PS), and the new tool. Validity, reliability (intraclass correlation coefficient), and inter-measurement agreement (Bland-Altman analysis) were evaluated. Changes in anxiety levels were analyzed using the Wilcoxon signed-rank test (p < 0.05).
resultsAnxiety scores decreased significantly post initial child-dentist interaction (p < 0.005). The AI-PM demonstrated good-to-excellent validity and reliability, with strong correlations with established pictorial measures (Spearman r = 0.72-0.96, p < 0.001). The reliability analysis using the intraclass correlation coefficient demonstrated good-to-excellent agreement between the AI-based assessment and the traditional measures. Agreement with traditional measures (FIS and RMS-PS) was good-to-excellent, with no evidence of proportional bias in Bland-Altman analyses (p > 0.05).
conclusionsThe findings suggest that the initial child-dentist interaction may play an important role in children's DA and that the AI-PM may provide a basis for further refinement of traditional pictorial measures used to assess DA in early childhood. CLINICAL
trial registrationThe study has been retrospectively registered in ClinicalTrials.gov (Identifier: NCT07387055).
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