Evaluation of AC-IOTN and Facial Attractiveness in Men Via Eye-tracking

Objectives: To ascertain the visual attention to the mouth in men with varying dental esthetics (IOTN levels) and background attractiveness, for both male and female raters, using eye-tracking as an objective measurement tool.
Methods: Male facial images rated as unattractive, average, and attractive were digitally manipulated and paired with validated oral images, IOTN levels 1 (no treatment need), 7 (borderline definite treatment need) and 10 (definite treatment need). Following the completion of a power analysis, sixty-four participants meeting the inclusion criteria were recruited after IRB approval. Each participant was calibrated in the eye tracker and, randomly viewed the composite images for 3 seconds, twice for reliability.
Results: Reliability was good-very good at the eye, nose, and mouth (ICC: 0.6-0.9). Significant interactions (p<.0001) were observed with ANOVA for the interactions of model attractiveness by area of the face, dental esthetics (IOTN) by area of the face, and rater gender by area of the face (p: 0.029). There were also independent significant interactions in occlusion by attractiveness by area by rater gender using the Tukey test to control for multiple comparisons.
Conclusions:
1. A significant malocclusion does significantly attract and affect visual attention.
2. Female raters preferred the eyes significantly more than the mouth or nose and males the mouth and eye versus the nose.
3. Visual attention to the mouth is the greatest in average attractiveness males, where it surpasses the eyes.
4. With male raters viewing average and unattractive models more visual attention was paid to the most severe dental esthetics versus normal and borderline dental esthetics.
5. Attractive men overall had less attention to the mouth versus others regardless of dental esthetics.
6. Background attractiveness in attractive male models does not play as significant a role in visual attention to dental esthetics as it does in attractive female models.