Abstract
Health prevention campaigns often face challenges in reaching their target audience and achieving the desired impact on health behaviors. These campaigns, particularly those aimed at reducing tobacco use, require rigorous evaluation methods to assess their effectiveness. This study aims to use immersive virtual reality (iVR) to systematically evaluate recall, attitudinal, and craving responses to antitobacco prevention messages when presented in a realistic virtual environment, thereby exploring the potential of iVR as a novel tool to improve the effectiveness of public health campaigns. A total of 121 undergraduate students (mean age 19.6, SD 3.7 years), mostly female (n=99, 82.5%), were invited to take a guided walk in the virtual environment, where they were randomly exposed to a different ratio of prevention and general advertising posters (80/20 or 20/80) depending on the experimental condition. Participants' gaze was tracked throughout the procedure, and outcomes were assessed after the iVR exposure. Incidental exposure to antitobacco prevention and general advertising posters did not significantly alter attitudes toward tobacco. Memorization of prevention posters was unexpectedly better in the condition where advertising was more frequent (β=-6.15; P<.001), and high contrast between poster types led to a better memorization of the less frequent type. Despite a nonsignificant trend, directing attention to prevention posters slightly improved their memorization (β=.02; P=.07). In addition, the duration of exposure to prevention posters relative to advertisements negatively affected memorization of advertising posters (β=-2.30; P=.01). Although this study did not find significant changes in attitudes toward tobacco after exposure to prevention campaigns using iVR, the technology does show promise as an evaluation tool. To fully evaluate the use of iVR in public health prevention strategies, future research should examine different types of content, longer exposure durations, and different contexts. Open Science Framework E3YK7; https://osf.io/e3yk7.
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