Testing the utility of Mouseview.js for measuring associations between alcohol related attentional bias and problematic alcohol use

This study examined the utility of Mouseview.js, an alternative to webcam-based eye-tracking, to assess associations between alcohol-related attentional bias and problematic alcohol use. Canadians recruited through Academic Prolific ( N = 526) completed an online free-viewing task using Mouseview.js to measure biased attention to alcohol-related images. Eighteen alcohol-related images were paired with neutral images matched on visual characteristics. Attentional bias was estimated as the differences in trial-level dwell times for the image pairs. The sample consisted of 132 non-drinkers, 241 recreational drinkers, and 153 problematic drinkers. Participants’ mean age was 33.5 years, 50.8% were men, and 40.4% identified as a racialized minority. Multi-level modelling was used for statistical analyses. The difference in dwell times between alcohol-related and neutral images was larger for problematic drinkers compared to non-drinkers, B = 3.75, z = 2.61, p = .009. There were no significant differences between recreational drinkers and non-drinkers, or between recreational and problematic drinkers. Reliability for dwell times and dwell time differences ranged from acceptable (≥ .70) to good (≥ 0.80). There was an attentional bias for alcohol-related images among problematic drinkers relative to non-drinkers and the Mouseview.js indices of bias demonstrated adequate reliability. These findings provide preliminary support for the utility of Mouseview.js as a measure of attentional bias in problematic drinkers. With further validation studies, Mouseview.js may prove to be a powerful tool for conducting high-powered online studies of attentional biases associated with addictive behaviors. • Mouseview.js can identify an attentional bias for alcohol-related images. • Problematic drinkers displayed an attentional bias for alcohol-related images. • Results using Mouseview.js ranged from acceptable to good reliability.