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Comparing radiographs with signaling improves anomaly detection of dental students: An eye‐tracking study
Author(s) -
Eder Thésése F.,
Richter Juliane,
Scheiter Katharina,
Huettig Fabian,
Keutel Constanze
Publication year - 2021
Publication title -
applied cognitive psychology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.719
H-Index - 100
eISSN - 1099-0720
pISSN - 0888-4080
DOI - 10.1002/acp.3819
Subject(s) - gaze , radiography , psychology , eye tracking , anomaly detection , commit , audiology , medicine , artificial intelligence , radiology , computer science , database , psychoanalysis
Dental students commit many errors when diagnosing radiographs. To improve performance, students were asked to compare radiographs (with and without disease or with the same disease); relevant structures were highlighted in the radiographs. In a crossover design, students were randomly assigned to two groups differing in training order: Students in the peripheral‐central‐group ( N = 39) were first trained to detect anomalies in the periphery before receiving training on anomalies in the center; the trainings in the central‐peripheral‐group ( N = 39) were reversed. We measured detection rates and gaze behavior before and after each training. The detection rates after the first training revealed differences in line with our expectations; moreover, when accounting for varying difficulty of the tests sets there were within‐groups improvements in the peripheral‐central group. Unexpectedly, the gaze behavior was unaffected by the intervention. We discuss shorter learning times and sequence effects as potential causes for our findings.