ArticlePloS one2020
Pupil diameter differentiates expertise in dental radiography visual search.
Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 13 papers.
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.
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.
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Who cites it
13 citing papers in PubMed.
- Effects of Generative AI-Supported Virtual Reality Dental Skill Training on Learning Performance, Visual Behavior, and Cortical Activation Among Dental Students: Stratified Randomized Controlled Trial.Journal of medical Internet research · 2026Trial
- Exploring the Application Capability of ChatGPT as an Instructor in Skills Education for Dental Medical Students: Randomized Controlled Trial.Journal of medical Internet research · 2025Trial
- Associations Between Eye-Movement Patterns, Pupil Dynamics, and the Interpretation of a Single Mixed-Dentition Panoramic Radiograph Among Dental Students: An Exploratory Eye-Tracking Study.Vision (Basel, Switzerland) · 2026Article
- Assessing the Role of Artificial Intelligence in Caries Detection and Clinical Decision-Making: A Scoping Review.Caries research · 2026Review
- Eye-tracking metrics to compare visual attention in prosthodontic preclinical evaluations.BMC oral health · 2025Observational
- Expert gaze as a usability indicator of medical AI decision support systems: a preliminary study.NPJ digital medicine · 2024Article
- Factors affecting interpretation of dental radiographs.Dento maxillo facial radiology · 2023Article
- A time slice analysis of dentistry students' visual search strategies and pupil dilation during diagnosing radiographs.PloS one · 2023Article
- Eye tracking: empirical foundations for a minimal reporting guideline.Behavior research methods · 2023Review
- Article
- TüEyeQ, a rich IQ test performance data set with eye movement, educational and socio-demographic information.Scientific data · 2021Article
- Comparing the Visual Perception According to the Performance Using the Eye-Tracking Technology in High-Fidelity Simulation Settings.Behavioral sciences (Basel, Switzerland) · 2021Article
- Correction: Pupil diameter differentiates expertise in dental radiography visual search.PloS one · 2020Article
Corrections and comments
- Erratum issued
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Expert behavior is characterized by rapid information processing abilities, dependent on more structured schemata in long-term memory designated for their domain-specific tasks. From this understanding, expertise can effectively reduce cognitive load on a domain-specific task. However, certain tasks could still evoke different gradations of load even for an expert, e.g., when having to detect subtle anomalies in dental radiographs. Our aim was to measure pupil diameter response to anomalies of varying levels of difficulty in expert and student dentists' visual examination of panoramic radiographs. We found that students' pupil diameter dilated significantly from baseline compared to experts, but anomaly difficulty had no effect on pupillary response. In contrast, experts' pupil diameter responded to varying levels of anomaly difficulty, where more difficult anomalies evoked greater pupil dilation from baseline. Experts thus showed proportional pupillary response indicative of increasing cognitive load with increasingly difficult anomalies, whereas students showed pupillary response indicative of higher cognitive load for all anomalies when compared to experts.
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Registered trials
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.