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Recent research underscored the resurgence of webcam-based eye tracking as a cost-effective, ecologically valid, and scalable choice, attributed to advancements in machine learning-assisted calibration methods. Online gambling poses a public health concern, necessitating innovative research methods and evidence-based strategies for harm reduction. This study investigates users' fixation patterns on responsible gambling (RG) information in different formats on gambling websites using webcam-based eye tracking. Participants browsed six gambling websites to search for RG information. 19 participants' data were analyzed on Areas of Interest (AOIs) categorized based on RG formats. The study has found that usability varied across RG formats and also highlights both feasibility and challenges of webcam-based eye tracking for online behavior research, with practical implications to gambling stakeholders.
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Wang et al. (2024) studied this question.
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