Visual attention to blu's parody warnings and the FDA's warning on e-cigarette advertisements

How does health communication on social media influence e-cigarette perception and use? A trend analysis from 2017 to 2020

OBJECTIVE

E-cigarettes have achieved a high prevalence rapidly. While social media is among the most influential platforms for health communication, its impact on attitudes and behaviors of e-cigarettes and its changes over time remain underexplored. This study aims to address the gap.

METHODS

Four years of data (2017-2020) were derived from the U.S. Health Information National Trends Survey (HINTS) (aged 18-64 years, n = 9,914). Initially, key variables were compared across years. Furthermore, guided by the health belief model, we employed a moderated mediation model to examine the influence of social media health communication on the public's perceptions and behaviors related to e-cigarettes, distinguishing between smokers and non-smokers throughout the four-year period.

RESULTS

The evidence shows a process of dynamic interaction between communication, perception, and behavior. (1) We observed an increasing trend of social media health communication (SMH) and perceived relative harm of e-cigarettes (PHE). (2) Higher SMH was associated with more e-cigarette use directly in 2019. (3) Higher SMH was associated with less e-cigarette use indirectly through PHE in 2020. (4) Smokers consistently displayed heightened sensitivity in responding to harm perception compared to non-smokers.

CONCLUSIONS

The findings support two mechanisms underlying the association between SMH and e-cigarette use: direct and indirect. The changes in the pathways during the timespan may have been influenced by increased e-cigarette information on social media and public health events like COVID-19. Stricter regulations for unverified e-cigarette advertisements and anti-e-cigarette education on social media are called for to curtail e-cigarette use.

Examining Visual Attention to Tobacco Marketing Materials among Young Adult Smokers: A Protocol for a Remote Webcam-based Eye-Tracking Experiment (Preprint)

BACKGROUND

Eye tracking provides an objective way to measure attention, which can advance researchers' and policy makers' understanding of tobacco marketing influences. The development of remote webcam-based eye-tracking technology, integrated with web-based crowdsourcing studies, may be a cost-effective and time-efficient alternative to laboratory-based eye-tracking methods. However, research is needed to evaluate the utility of remote eye-tracking methods.

OBJECTIVE

This study aimed to detail the process of designing a remote webcam-based eye-tracking experiment and provide data on associations between participant characteristics and the outcomes of experiment completion.

METHODS

A total of 2023 young adult (aged 18-34 years) cigarette smokers in the United States were recruited to complete a web-based survey that included a 90-second remote eye-tracking experiment that examined attention to e-cigarette marketing materials. Primary outcome measures assessed the completion of the remote eye-tracking experiment-specifically, experiment initiated versus not initiated, experiment completed versus not completed, and usable versus nonusable eye-tracking data generated. Multivariable logistic regressions examined the associations between outcome measures and participants' sociodemographic backgrounds, tobacco use history, and electronic devices (mobile vs desktop) used during the experiment.

RESULTS

Study recruitment began on April 14, 2022, and ended on May 3, 2022. Of the 2023 survey participants, 1887 (93.28%) initiated the experiment, and 777 (38.41%) completed the experiment. Of the 777 participants who completed the experiment, 381 (49%) generated usable data. Results from the full regression models show that non-Hispanic Black participants (adjusted odds ratio [AOR] 0.64, 95% CI 0.45-0.91) were less likely to complete the eye-tracking experiment than non-Hispanic White participants. In addition, female (vs male) participants (AOR 1.46, 95% CI 1.01-2.11), those currently using (vs not using) e-cigarettes (AOR 2.08, 95% CI 1.13-3.82), and those who used mobile (vs desktop) devices (AOR 5.10, 95% CI 3.05-8.52) were more likely to generate usable eye-tracking data.

CONCLUSIONS

Young adult participants were willing to try remote eye-tracking technology, and nearly half of those who completed the experiment generated usable eye-tracking data (381/777, 49%). Thus, we believe that the use of remote eye-tracking tools, integrated with crowdsourcing recruitment, can be a useful approach for the tobacco regulatory science research community to collect high-quality, large-scale eye-tracking data in a timely fashion and thereby address research questions related to the ever-evolving tobacco marketing landscape. It would be useful to investigate techniques to enhance completion rates and data usability.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR1-10.2196/43512.