Employing Data-Driven Techniques to Explore the Lay Public's Health Concerns with Vaping E-Cigarettes

While the public perceives e-cigarettes as less harmful than combustible tobacco, little is known about their specific health concerns regarding vaping. We demonstrate a data-driven strategy to discover the public's health concerns about vaping e-cigarettes expressed on social media. We obtained all public posts from the largest e-cigarette-related subreddit, r/electronic_cigarette, from its inception on September 17, 2008, through April 1, 2022 (N = 10,403,433). We identified health concerns attributed to vaping by (a) selecting all cause phrases containing "cause" and its inflections, (b) calculating the empirical frequency ratio of words and bi-grams occurring in these phrases relative to random phrases, (c) retaining the 10% of words with the greatest empirical frequency of occurring in cause phrases, and (d) annotating this sample for health-relevant concerns and their subjects. In total, 76,342 posts contained cause phrases, with increased volume over time. Of the 425 words most strongly associated with cause phrases compared to random phrases, 53.4% (95%CI, 48.7-58.1) were identified as health-relevant. The top health-related concern was lipoid pneumonia, cited in 5.9% (95%CI, 5.0-6.8) of all cause phrases, followed by pneumonia (4.1%; 95%CI, 3.3-4.9), and nausea (2.7%;95%CI, 2.0-3.4). The top health concern subjects were respiratory, representing 23.7% (95%CI, 18.5-29.5) of all cause phrases, followed by gastrointestinal (12.7%; 95%CI, 8.8-17.2) and cardiovascular (8.5%; 95%CI, 5.3-12.3) concerns. Other subjects included neurological, dermatological, oral health, sexual health, psychiatric, oncologic, addiction, and sleep concerns. Because our strategy relies on data-driven techniques, our analysis can be integrated into routine social media monitoring and applied across different types of social media and text data, potentially leading to more timely identification of emerging concerns and a broader understanding across platforms. As a result, experts can craft messaging that accounts for current perceptions held by the public using our method.