Fact-Checking Strategies in Web: Lateral Navigation in the Browser Boosts Health Misinformation Detection Even Under Confirmation Bias

Health misinformation poses serious public health risks, yet little is known about how ordinary users verify such content in real time. In this study, we investigate how behavioral fact-checking strategies, specifically, lateral reading (consulting multiple external sources) versus vertical reading (spending more time on fewer sources), affect accuracy in detecting health-related misinformation. We conducted a large-scale online experiment with 1,842 participants using a designed for the experiment purposes standalone web platform that logs respondents' behavioral signals (tab/window switches and time spent outside the experimental interface). This design enables indirect measurement of fact-checking in an ecologically valid setting. Using linear mixed-effects models with semiparametric bootstrap confidence intervals, we find that lateral reading significantly improves accuracy (β = 0.09, 95% CI [0.079, 0.181], p = 0.001), while vertical reading has no effect (β = -0.01, p = 0.332). Crucially, confirmation bias, operationalized as alignment between statement valence and user attitude, does not moderate this relationship (p = 0.876). This suggests that lateral reading remains effective even when users encounter ideologically congruent misinformation. Our results demonstrate that simple, scalable behavioral cues like tab-switch frequency can serve as reliable indicators of verification quality. For web platforms and digital literacy initiatives, this implies that nudging users to ''open another tab'' may be a lightweight, bias-resistant intervention to improve misinformation resilience, especially in health contexts where errors carry real-world consequences.