Traci Hong

Objectives: This systematic review examines eye-tracking experiments evaluating the effects of tobacco health warning labels (HWLs) on visual attention. We focus on eye-tracking metrics (dwell time, fixation counts and time to first fixation) to inform tobacco control strategies. Data sources: Controlled keyword searches were conducted in APA PsycINFO, ASSIA, CMMC, CINAHL, Embase, Psychology & Behavioral Sciences Collection, PubMed and Web of Science from January 2018 to December 2023. Study selection: Eligible articles ( n =25) were peer-reviewed, written in English, involved human participants and included eye-tracking technology to assess attention to HWLs. Data extraction: Extracted data included article information, HWL characteristics (product type, context, format, source), study design, sample demographics and eye-tracking outcomes. Two trained reviewers collaboratively screened and extracted data following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Data synthesis: Across 31 experiments, dwell time was consistently longer for pictorial than textual HWLs, fixation counts increased when packs contained fewer visual distractions, and time to first fixation was shorter for more visually salient HWLs. Greater visual attention was also associated with lower liking of tobacco products and stronger negative emotional responses. Independent t-tests on summary data showed that participants (mostly adult males) spent more time viewing and less time locating pictorial HWLs than text-only HWLs, while fixation counts did not differ significantly. Conclusions: This review provides eye-tracking evidence aligned with WHO recommendations for pictorial HWLs and highlights key research gaps that future studies should address to strengthen global tobacco control efforts.

UNSTRUCTURED Throughout the COVID-19 pandemic, the proliferation and uptake of misinformation and disinformation revealed widespread misunderstanding of health and infectious diseases that hampered effective response to a global pandemic. Viewing this as a challenge of public health literacy—oriented to the interconnectedness of self and community health—we sought guidance from the literature to better define public health literacy in outbreak settings. We attempted to conduct a scoping literature review to identify relevant concepts and gaps in the literature on public health literacy in the context of infectious disease outbreaks. Although literature with this emphasis was sparse, we identified four papers with unique definitions of health and public health literacy that incorporated community themes. We then used these definitions to develop a new framework and definition of public health literacy in outbreaks. Public health literacy in outbreaks (PHLiO) encompasses an individual’s and a community’s ability to obtain, understand, evaluate, and respond to the complexity of rapidly changing public health and scientific information, with the goal of empowering individual and collective agency to make public health decisions that benefit the community and promote comprehensive societal responses. Elements of PHLiO appear to have been useful in successful responses to a range of public health challenges. The proposed PHLiO framework provides a foundation for developing educational materials, measurement tools, and research. The framework also outlines minimum competencies required to effectively avoid mis/disinformation, move from a self/individual-care model of disease prevention to a model of community care, and improve effectiveness at preventing disease during outbreaks.

While there is ample research on the influence of retracted scientific publications on author reputation, less is known about how a health organization's retraction of scientific guidance can impact public perceptions of the organization. This study centers on the aerosol guidance retraction of the Centers for Disease Control and Prevention (CDC) in 2020. X/Twitter social media data were collected via ForSight from September 15 to October 8, 2020, with a machine learning algorithm specifically developed and used to detect sentiment toward the CDC. Regression analyses of the non-bot sample (N = 265,326) tested for differences in CDC sentiment across four stages: 1) baseline; 2) CDC guidance change; 3) CDC retraction of the prior guidance change; and 4) CDC reversion to a tempered form of the initial guidance change. The results show that sentiment toward the CDC increased from Time 1 to Time 2, then decreased for Time 3 with the "posted in error" retraction, but then increased for Time 4 back to a level similar to Time 2. That public perceptions of the CDC could improve after these changes in scientific guidance may be attributed to its self-report of the retraction and reporting that the retraction was a result of unintentional error. This study connects theories of reputation management and trust repair with the growing empirical research on retractions of published scientific research to provide a theoretical explanation for how a major public health organization can mitigate damage to its reputation in the short term.

Background: Co-use of alcohol and e-cigarettes (often called vaping) has been linked with long-term health outcomes, including increased risk for substance use disorder. Co-use may have been exacerbated by the COVID-19 pandemic. Social networking sites may offer insights into current perspectives on polysubstance use. Objective: The aims of this study were to investigate concurrent mentions of vaping and alcohol on Twitter (subsequently rebranded X) during a time of changing vaping regulations in the United States and the emergence of the COVID-19 pandemic. Methods: Tweets including both vape- and alcohol-related terms posted between October 2019 and September 2020 were analyzed using latent Dirichlet allocation modeling. Distinct topics were identified and described. Results: Three topics were identified across 6437 tweets: (1) flavors and flavor ban (n=3334, 51.8% of tweets), (2) co-use discourse (n=1119, 17.4%), and (3) availability and access regulation (n=1984, 30.8%). Co-use discussions often portrayed co-use as positive and prosocial. Tweets focused on regulation often used alcohol regulations for comparison. Some focused on the perceived overregulation of vaping (compared to alcohol), while others supported limiting youth access but not at the expense of adult access (eg, stronger age verification over product bans). Across topics, vaping was typically portrayed as less harmful than alcohol use. The benefits of flavors for adult smoking cessation were also discussed. The distribution of topics across time varied across both pre– and post–regulatory change and pre– and post–COVID-19 pandemic declaration periods, suggesting shifts in topic focus salience across time. Conclusions: Co-use discussions on social media during this time of regulatory change and social upheaval typically portrayed both vaping and alcohol use in a positive light. It also included debates surrounding the differences in regulation of the 2 substances—particularly as it related to limiting youth access. Emergent themes from the analysis suggest that alcohol was perceived as more harmful but less regulated and more accessible to underage youth than vaping products. Frequent discussions and comparisons of the 2 substances as it relates to their regulation emphasize the still-evolving vaping policy landscape. Social media content analyses during times of change may help regulators and policy makers to better understand and respond to common concerns and potential misconceptions surrounding drug-related policies and accessibility.

Importance: Synthetic nicotine is increasingly used in e-cigarette liquids along with flavors to appeal to youths. Regulatory loopholes have allowed tobacco manufacturers to use social media to target youths.Objective: To analyze the extent to which synthetic nicotine e-cigarette brands have implemented US Food and Drug Administration (FDA) health warning requirements and to evaluate the association between health warnings and user engagement on Instagram.Design, Setting, and Participants: In this cross-sectional study, posts from 25 brands were analyzed across a 14-month period (August 2021 to October 2022). A content analysis was paired with Warning Label Multi-Layer Image Identification, a computer vision algorithm designed to detect the presence of health warnings and whether the detected health warning complied with FDA guidelines by (1) appearing on the upper portion of the advertisement and (2) occupying at least 20% of the advertisement’s area. Data analysis was performed from March to June 2024.Exposure: Synthetic nicotine e-cigarette advertisement on Instagram.Main Outcomes and Measures: The outcome variables were user engagement (number of likes and comments). Negative binomial regression analyses were used to evaluate the association between the presence and characteristics of health warnings and user engagement.Results: Of a total of 2071 posts, only 263 (13%) complied with both FDA health warning requirements. Among 924 posts with health warnings, 732 (79%) displayed warnings in the upper image portion, and 270 (29%) had a warning covering at least 20% of the pixel area. Posts with warnings received fewer comments than posts without warnings (mean [SD], 1.8 [2.5] vs 5.4 [11.7] comments; adjusted incident rate ratio [aIRR], 0.70; 95% CI, 0.57-0.86; P < .001). For posts containing warnings, a larger percentage of the warning label’s pixel area was associated with fewer comments (aIRR, 0.96; 95% CI, 0.93-0.99; P = .003). Flavored posts with health warnings placed in the upper image portion received more likes than posts with warnings in the lower portion (mean [SD], 34.6 [35.2] vs 19.9 [19.2] likes; aIRR, 1.48; 95% CI, 1.07-2.06; P = .02).Conclusions and Relevance: In this cross-sectional study of synthetic nicotine brand Instagram accounts, 87% of sampled posts did not adhere to FDA health warning requirements in tobacco promotions. Enforcement of FDA compliant health warnings on social media may reduce youth engagement with tobacco marketing.

This systematic review evaluates health messaging strategies for the prevention and cessation of e-cigarette use among youth and young adults. Health messaging strategies were defined as the strategic process of developing messages with the intent to shape, reinforce, or change recipients' health attitudes and behaviors. McGuire's Communication/Persuasion Model guided the analysis of the messaging strategies, focusing on the model's five communication inputs (i.e. source, message, channel, audience, destination) and 14 persuasive outcomes. Nine databases were searched from January 2007 to September 2023. The inclusion criteria encompassed studies in English that presented quantitative data on messaging strategies aimed at discouraging vaping among youth and young adults. Each study was also coded for study characteristics and the utilization of theory. Out of 6,045 studies, 25 met the inclusion criteria. The reviewed studies exhibit a diverse array of research methods and a consistent integration of theories. The review emphasizes the nuanced main and interaction effects of various communication inputs, such as message features and audience characteristics, while also pointing out a research gap in message sources. In addition, the utilization of social media for effective messaging to engage the audience requires further research. Only one study specifically evaluated messaging strategies for vaping cessation. More research is imperative to develop targeted and tailored messages that effectively prevent and reduce vaping, especially among populations at higher risk of vaping-related harms, while also leveraging effective channels and innovative communication technologies to engage the audience.

This paper introduces a multilingual dataset of COVID-19 vaccine misinformation, consisting of annotated tweets from three middle-income countries: Brazil, Indonesia, and Nigeria. The expertly curated dataset includes annotations for 5,952 tweets, assessing their relevance to COVID-19 vaccines, presence of misinformation, and the themes of the misinformation. To address challenges posed by domain specificity, the low-resource setting, and data imbalance, we adopt two approaches for developing COVID-19 vaccine misinformation detection models: domain-specific pre-training and text augmentation using a large language model. Our best misinformation detection models demonstrate improvements ranging from 2.7 to 15.9 percentage points in macro F1-score compared to the baseline models. Additionally, we apply our misinformation detection models in a large-scale study of 19 million unlabeled tweets from the three countries between 2020 and 2022, showcasing the practical application of our dataset and models for detecting and analyzing vaccine misinformation in multiple countries and languages. Our analysis indicates that percentage changes in the number of new COVID-19 cases are positively associated with COVID-19 vaccine misinformation rates in a staggered manner for Brazil and Indonesia, and there are significant positive associations between the misinformation rates across the three countries.

BACKGROUND Co-use of alcohol and e-cigarettes (often called vaping) has been linked with long-term health outcomes, including increased risk for substance use disorder. Co-use may have been exacerbated by the COVID-19 pandemic. Social networking sites may offer insights into current perspectives on polysubstance use. OBJECTIVE The aims of this study were to investigate concurrent mentions of vaping and alcohol on Twitter (subsequently rebranded X) during a time of changing vaping regulations in the United States and the emergence of the COVID-19 pandemic. METHODS Tweets including both vape- and alcohol-related terms posted between October 2019 and September 2020 were analyzed using latent Dirichlet allocation modeling. Distinct topics were identified and described. RESULTS Three topics were identified across 6437 tweets: (1) flavors and flavor ban (n=3334, 51.8% of tweets), (2) co-use discourse (n=1119, 17.4%), and (3) availability and access regulation (n=1984, 30.8%). Co-use discussions often portrayed co-use as positive and prosocial. Tweets focused on regulation often used alcohol regulations for comparison. Some focused on the perceived overregulation of vaping (compared to alcohol), while others supported limiting youth access but not at the expense of adult access (eg, stronger age verification over product bans). Across topics, vaping was typically portrayed as less harmful than alcohol use. The benefits of flavors for adult smoking cessation were also discussed. The distribution of topics across time varied across both pre– and post–regulatory change and pre– and post–COVID-19 pandemic declaration periods, suggesting shifts in topic focus salience across time. CONCLUSIONS Co-use discussions on social media during this time of regulatory change and social upheaval typically portrayed both vaping and alcohol use in a positive light. It also included debates surrounding the differences in regulation of the 2 substances—particularly as it related to limiting youth access. Emergent themes from the analysis suggest that alcohol was perceived as more harmful but less regulated and more accessible to underage youth than vaping products. Frequent discussions and comparisons of the 2 substances as it relates to their regulation emphasize the still-evolving vaping policy landscape. Social media content analyses during times of change may help regulators and policy makers to better understand and respond to common concerns and potential misconceptions surrounding drug-related policies and accessibility.