BACKGROUND: Visual attention in complex environments is shaped by multiple stimulus characteristics, yet most studies have examined only one or two features at a time. Eye-tracking combined with a change blindness paradigm offers a sensitive way to evaluate how different visual features guide the detection of changes in naturalistic scenes. This study aimed to validate visual stimuli with varying characteristics and to determine which factors are most significantly associated with visual attention. METHODS: Fifty university students viewed pairs of real-world scenes while their gaze behavior was recorded using an eye tracking system. Participants were required to detect a single changed item across image pairs. Four visual characteristics were manipulated: social versus nonsocial content, number of distractors, congruency, and level of interest (central vs. marginal). RESULTS: Response times varied significantly across all characteristics. Faster detection was observed for social stimuli, scenes with fewer distractors, congruent changes, and items of central interest. Linear mixed-effects models (LMMs) revealed that level of interest was the strongest predictor of response time, followed by the number of distractors, congruency, and social content. CONCLUSION: Eye-tracking measures, particularly response time to detect change, demonstrated that central interest and fewer distractors were the strongest predictors of visual attention. These findings accentuate the complexity of visual attention and highlight its potential impact on interpreting environmental stimuli and the broader effects on academic performance and daily functioning.
Berger et al. (Mon,) studied this question.