PERCEPTUAL RESPONSES TO GENDERED ANTI-FAT STEREOTYPES: THE ROLE OF INFORMATION SOURCES AND TEXT CONTENT IN EYE MOVEMENT PATTERNS
PERCEPTUAL RESPONSES TO GENDERED ANTI-FAT STEREOTYPES: THE ROLE OF INFORMATION SOURCES AND TEXT CONTENT IN EYE MOVEMENT PATTERNS

Summary/Abstract: This study explores how textual information containing anti-fat stereotypes affects visual attention toward images of fat individuals, using eye-tracking methodology. Thirty-two stimuli paired short stereotype-based texts with images of a fat man and woman. Each text varied along three independent variables: stereotype topic (e.g., laziness, health risk), target gender (men or women), and information source (scientific vs. public opinion). A total of 22 university students (16 women) participated, and gaze data was collected using a Gazepoint GP3 eye tracker. Two eye-tracking indicators were analysed: fixation count and total viewing time. Significant effects were found for stereotype content on fixation count, F(7, 896) = 3.09, p = .003, and viewing time, F(7, 896) = 3.67, p < .001. A significant three-way interaction between topic, gender, and information source on fixation count was also observed, F(7, 896) = 9.01, p < .001. Follow-up tests showed that laziness elicited higher fixation counts for male stimuli, while heart attack risk led to longer viewing times for female stimuli. An interaction between topic and information source, F(7, 896) = 2.12, p = .040, revealed that public opinion increased attention to social stereotypes (e.g., laziness), while scientific sources drew more attention to job and health-related stereotypes. These findings suggest that both textual framing and information source shape how individuals attend to images of fat individuals. While eye-tracking cannot directly measure implicit bias, these perceptual patterns may reflect socially embedded stereotypes. The study highlights the utility of eye-tracking in examining gendered attention to fat-related content and encourages further research using combined measures of bias.

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