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Abstract
Studying how vaping is framed on various knowledge dissemination platforms (e.g., Quora, Reddit, Wikipedia) is central to understanding the process of knowledge dissemination around vaping. Such understanding can help us craft tools specific to each platform, to dispel vaping misperceptions and reinforce evidence-based information. We analyze 1,888 articles and 1,119,453 vaping posts to study how vaping is framed across multiple knowledge dissemination platforms (Wikipedia, Quora, Medium, Reddit, Stack Exchange, wikiHow). We use NLP techniques to understand these differences. As an example, regarding question answering results, for the question What is vaping for?, we note answers framing vaping as a smoking cessation tool in Quora, Medium, and Stack Exchange. Reddit tended to frame vaping as a hobby. Wikipedia had a mix of answers, some centered on EVALI, and others on vaping as harm reduction. Broadly, results indicate that Quora is an appropriate venue for those looking to transition from smoking to vaping. Other platforms (Reddit, wikiHow) are more for vaping hobbyists and may not sufficiently dissuade youth vaping. Conversely, Wikipedia may exaggerate vaping harms, dissuading smokers from transitioning. A strength of our work is how the different techniques we have applied validate each other. Stakeholders may utilize our findings to design vaping regulation that clarifies the role of vapes as a smoking cessation tool.
... While there have been studies on preventing vaping among adolescents [12,13], and the effect of vaping misinformation on attitudes toward vapes [1], and vaping misinformation more broadly [10,14,15], there is limited research on interventions to mitigate misinformation about vapes. Thus, we are far from knowing when and how to intervene best. ...
Background
The impact of misinformation about vapes’ relative harms compared with smoking may lead to increased tobacco-related burden of disease. To date, no systematic efforts have been made to chart interventions that mitigate vaping-related misinformation. We plan to conduct a scoping review that seeks to fill gaps in the current knowledge of interventions that mitigate vaping-related misinformation.
Methods
A scoping review focusing on interventions that mitigate vaping-related misinformation will be conducted. We will search (no date restrictions) MEDLINE, Scopus, EMBASE, CINAHL, PsycINFO, Web of Science Core Collection, Global Health, ERIC, and Sociological Abstracts. Gray literature will be identified using Disaster Lit, Google Scholar, Open Science Framework, governmental websites, and preprint servers (e.g., EuropePMC, PsyArXiv, MedRxiv, JMIR Preprints). Study selection will conform to Joanna Briggs Institute Reviewers’ Manual 2020 Methodology for JBI Scoping Reviews. Only English language, original studies will be considered for inclusion. Two reviewers will independently screen all citations, full-text articles, and abstract data. A narrative summary of findings will be conducted. Data analysis will involve quantitative (e.g., frequencies) and qualitative (e.g., content and thematic analysis) methods. Where possible, a single effect size of exposure to the mitigation of vaping-related misinformation will be calculated per sample.
Similarly, where possible, each study will be coded for moderating characteristics to find and account for systematic differences in the size of the effect or outcome that is being analyzed. Quality will be appraised with the study quality assessment tools utilized by the National Heart, Lung, and Blood Institute.
Findings will be subjected to several different publication bias tests: Egger’s regression test, Begg and Mazumdar’s ran correlation test, and generation of a funnel plot with effect sizes plotted against a corresponding standard error.
Discussion
Original research is urgently needed to design interventions to mitigate vaping-related misinformation. The planned scoping review will help to address this gap.
Systematic review registration
Open Science Framework osf/io/hy3tk.
Background: The impact of misinformation about vapes’ relative harms compared with smoking may lead to increased tobacco-related burden of disease. To date, no systematic efforts have been made to chart interventions that mitigate vaping-related misinformation. We plan to conduct a scoping review that seeks to fill gaps in the current knowledge of interventions that mitigate vaping-related misinformation.
Methods: A scoping review focusing on interventions that mitigate vaping-related misinformation will be conducted. We will search (no date restrictions) MEDLINE, Scopus, EMBASE, CINAHL, PsycINFO, Web of Science Core Collection, Global Health, ERIC and Sociological Abstracts. Grey literature will be identified using Disaster Lit, Google Scholar, Open Science Framework, governmental websites and preprint servers (e.g. EuropePMC, PsyArXiv, MedRxiv, JMIR Preprints). Study selection will conform to Joanna Briggs Institute Reviewers’ Manual 2020 Methodology for JBI Scoping Reviews. Only English language, original studies will be considered for inclusion. Two reviewers will independently screen all citations, full-text articles, and abstract data. A narrative summary of findings will be conducted. Data analysis will involve quantitative (e.g. frequencies) and qualitative (e.g. content and thematic analysis) methods.
Discussion: Original research is urgently needed to design interventions to mitigate vaping-related misinformation. The planned scoping review will help to address this gap.
Systematic Review registrations: Systematic Review Registration: Open Science Framework (osf/io/hy3tk).
Polarization among US political parties, media and elites is a widely studied topic. Prominent lines of prior research across multiple disciplines have observed and analyzed growing polarization in social media. In this paper, we present a new methodology that offers a fresh perspective on interpreting polarization through the lens of machine translation. With a novel proposition that two sub-communities are speaking in two different "languages", we demonstrate that modern machine translation methods can provide a simple yet powerful and interpretable framework to understand the differences between two (or more) large-scale social media discussion data sets at the granularity of words. Via a substantial corpus of 86.6 million comments by 6.5 million users on over 200,000 news videos hosted by YouTube channels of four prominent US news networks, we demonstrate that simple word-level and phrase-level translation pairs can reveal deep insights into the current political divide -- what is "black lives matter" to one can be "all lives matter" to the other.
The impact of misinformation about vapes' relative harms compared with smoking may lead to increased tobacco-related burden of disease and youth vaping. Unfortunately, vaping misinformation has proliferated. Despite growing attempts to mitigate vaping misinformation, there is still considerable ambiguity regarding the ability to effectively curb the negative impact of misinformation. To address this gap, we use a meta-analysis to evaluate the relative impact of interventions designed to mitigate vaping-related misinformation. We searched (from January 2020 till August 2021) various databases and gray literature. Only English language, original studies that employed experimental designs where participants were randomly assigned either to receive mitigating information or to a no-mitigation condition (either misinformation-only or neutral control) were included. Meta-analysis was conducted for the four eligible studies. The mean effect size of attempts to mitigate vaping misinformation was positive but not statistically significant (d = 0.383, 95% CI [-0.029, 0.796], p = .061, k = 5) with lack of evidence for publication bias. Given limited studies included, we were unable to determine factors affecting the efficacy of interventions. The limited focus on non-US studies and youth populations is concerning given the popularity of vaping in low- to middle-income countries (LMICs) and among youth. The findings of this meta-analysis describe the current state of the literature and prescribe specific recommendations to better address the proliferation of vaping misinformation, providing insights helpful in limiting the tobacco mortality burden and curtailing youth vaping.
Background:
Electronic cigarettes (ECs) are handheld electronic vaping devices which produce an aerosol formed by heating an e-liquid. Some people who smoke use ECs to stop or reduce smoking, but some organizations, advocacy groups and policymakers have discouraged this, citing lack of evidence of efficacy and safety. People who smoke, healthcare providers and regulators want to know if ECs can help people quit and if they are safe to use for this purpose. This is an update conducted as part of a living systematic review.
Objectives:
To examine the effectiveness, tolerability, and safety of using electronic cigarettes (ECs) to help people who smoke tobacco achieve long-term smoking abstinence.
Search methods:
We searched the Cochrane Tobacco Addiction Group's Specialized Register, the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, Embase, and PsycINFO to 1 May 2021, and reference-checked and contacted study authors. We screened abstracts from the Society for Research on Nicotine and Tobacco (SRNT) 2021 Annual Meeting. SELECTION CRITERIA: We included randomized controlled trials (RCTs) and randomized cross-over trials, in which people who smoke were randomized to an EC or control condition. We also included uncontrolled intervention studies in which all participants received an EC intervention. Studies had to report abstinence from cigarettes at six months or longer or data on safety markers at one week or longer, or both.
Data collection and analysis:
We followed standard Cochrane methods for screening and data extraction. Our primary outcome measures were abstinence from smoking after at least six months follow-up, adverse events (AEs), and serious adverse events (SAEs). Secondary outcomes included the proportion of people still using study product (EC or pharmacotherapy) at six or more months after randomization or starting EC use, changes in carbon monoxide (CO), blood pressure (BP), heart rate, arterial oxygen saturation, lung function, and levels of carcinogens or toxicants or both. We used a fixed-effect Mantel-Haenszel model to calculate risk ratios (RRs) with a 95% confidence interval (CI) for dichotomous outcomes. For continuous outcomes, we calculated mean differences. Where appropriate, we pooled data in meta-analyses.
Main results:
We included 61 completed studies, representing 16,759 participants, of which 34 were RCTs. Five of the 61 included studies were new to this review update. Of the included studies, we rated seven (all contributing to our main comparisons) at low risk of bias overall, 42 at high risk overall (including all non-randomized studies), and the remainder at unclear risk. There was moderate-certainty evidence, limited by imprecision, that quit rates were higher in people randomized to nicotine EC than in those randomized to nicotine replacement therapy (NRT) (risk ratio (RR) 1.53, 95% confidence interval (CI) 1.21 to 1.93; I2 = 0%; 4 studies, 1924 participants). In absolute terms, this might translate to an additional three quitters per 100 (95% CI 1 to 6). There was low-certainty evidence (limited by very serious imprecision) that the rate of occurrence of AEs was similar (RR 0.98, 95% CI 0.80 to 1.19; I2 = 0%; 2 studies, 485 participants). SAEs were rare, but there was insufficient evidence to determine whether rates differed between groups due to very serious imprecision (RR 1.30, 95% CI 0.89 to 1.90: I2 = 0; 4 studies, 1424 participants). There was moderate-certainty evidence, again limited by imprecision, that quit rates were higher in people randomized to nicotine EC than to non-nicotine EC (RR 1.94, 95% CI 1.21 to 3.13; I2 = 0%; 5 studies, 1447 participants). In absolute terms, this might lead to an additional seven quitters per 100 (95% CI 2 to 16). There was moderate-certainty evidence of no difference in the rate of AEs between these groups (RR 1.01, 95% CI 0.91 to 1.11; I2 = 0%; 3 studies, 601 participants). There was insufficient evidence to determine whether rates of SAEs differed between groups, due to very serious imprecision (RR 1.06, 95% CI 0.47 to 2.38; I2 = 0; 5 studies, 792 participants). Compared to behavioural support only/no support, quit rates were higher for participants randomized to nicotine EC (RR 2.61, 95% CI 1.44 to 4.74; I2 = 0%; 6 studies, 2886 participants). In absolute terms this represents an additional six quitters per 100 (95% CI 2 to 15). However, this finding was of very low certainty, due to issues with imprecision and risk of bias. There was some evidence that non-serious AEs were more common in people randomized to nicotine EC (RR 1.22, 95% CI 1.12 to 1.32; I2 = 41%, low certainty; 4 studies, 765 participants), and again, insufficient evidence to determine whether rates of SAEs differed between groups (RR 1.51, 95% CI 0.70 to 3.24; I2 = 0%; 7 studies, 1303 participants). Data from non-randomized studies were consistent with RCT data. The most commonly reported AEs were throat/mouth irritation, headache, cough, and nausea, which tended to dissipate with continued use. Very few studies reported data on other outcomes or comparisons, hence evidence for these is limited, with CIs often encompassing clinically significant harm and benefit.
Authors' conclusions:
There is moderate-certainty evidence that ECs with nicotine increase quit rates compared to NRT and compared to ECs without nicotine. Evidence comparing nicotine EC with usual care/no treatment also suggests benefit, but is less certain. More studies are needed to confirm the effect size. Confidence intervals were for the most part wide for data on AEs, SAEs and other safety markers, with no difference in AEs between nicotine and non-nicotine ECs. Overall incidence of SAEs was low across all study arms. We did not detect evidence of harm from nicotine EC, but longest follow-up was two years and the number of studies was small. The main limitation of the evidence base remains imprecision due to the small number of RCTs, often with low event rates, but further RCTs are underway. To ensure the review continues to provide up-to-date information to decision-makers, this review is now a living systematic review. We run searches monthly, with the review updated when relevant new evidence becomes available. Please refer to the Cochrane Database of Systematic Reviews for the review's current status.
Introduction
Studies have indicated that youth who use e-cigarettes are more likely to progress to cigarette smoking; however, the likelihood that these youth would have used tobacco products in the pre-vaping era is unclear. This study sought to determine whether youth who used e-cigarettes in 2014-2018 would have likely been smokers in the period preceding e-cigarette availability.
Methods
Analyzing Monitoring the Future 12 th grade data (USA, 2009-2018), we forecasted the prevalence of current smoking with logistic regression-derived propensity scores. Models predicted smoking for all subsequent years, incorporating sociodemographic, family, alcohol, and school-related variables, and a linear time trend. We compared forecasted to observed smoking prevalence annually, and prevalence of current e-cigarette use among non-smokers across smoking propensity tertiles.
Results
Until 2014, observed smoking prevalence mirrored forecasted prevalence. Afterward, forecasted rates consistently overestimated prevalence. Among non-smoking youth, e-cigarette use was lowest among those with lowest predicted probability of cigarette smoking (3.8%; 95% CI: 3.3, 4.4) and highest among those with highest probability (23.5%; 95% CI: 22.2, 24.9).
Discussion
Youth e-cigarette use has increased rapidly, with high prevalence among non-smoking youth. However, the decline in current smoking among 12 th graders has accelerated since e-cigarettes have become available. E-cigarette use is largely concentrated among youth who share characteristics with smokers of the pre-vaping era, suggesting e-cigarettes may have replaced cigarette smoking.
Implications
Vaping is largely concentrated among non-smoking youth who would likely have smoked prior to the introduction of e-cigarettes, and the introduction of e-cigarettes has coincided with an acceleration in the decline in youth smoking rates. E-cigarettes may be an important tool for population-level harm reduction, even considering their impact on youth.