Vapes, E-cigs, and Mods: What Do Young Adults Call E-cigarettes?
Vapes, E-cigs, and Mods: What Do Young Adults Call E-cigarettes?
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DOI：
10.1093/ntr/nty223
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发表时间：
2020-05-01
影响因子：
4.7
通讯作者：
Villanti, Andrea C.
中科院分区：
文献类型：
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作者：
Pearson, Jennifer L.;Reed, Domonique M.;Villanti, Andrea C.
导言：电子烟是一种多种多样的产品，由于用来描述亚类型的非标准术语，尤其是在偶尔使用电子烟最普遍的年轻人中，“电子烟”带来了监测和监管方面的挑战。方法：在Truth Initiative第9波(2016年春季)中，年轻人(n=3364)随机观看常见电子烟产品的五张照片中的两张(第一代电子烟有三种，第二代和第三代电子烟各有一种)。定性回答被编码为九类：“电子烟、电子水烟、电子烟相关、MOD、其他或一种以上的电子烟、大麻相关、非电子烟烟草产品、识别错误和不知道。”我们对样本和调查的反应进行了表征，并进行了多变量Logistic回归，以确定与正确识别设备为电子CIG相关的参与者特征。结果：大多数参与者认为图片中的设备是某种类型的电子烟(57.7%-83.6%)。白色的第一代电子烟以及第二代和第三代电子烟造成了最大的混乱，很大比例的人回答“不知道”(12.2%-25.1%，取决于设备)，或者将电子烟误认为非尼古丁产品(3.4%-16.1%，取决于设备)或非电子烟产品(1.4%-14.6%，结论：准确监测和分析电子烟对健康行为和结局的影响依赖于对用户电子烟亚型的准确数据收集。在调查中精心挑选图像可能会改善人口研究中电子烟使用情况的报告。
Introduction: A diverse class of products, "e-cigarettes" present surveillance and regulatory challenges because of nonstandard terminology used to describe subtypes, especially among young adults, where occasional e-cig use is most prevalent.Methods: Young adults (n = 3364) in wave 9 (Spring 2016) of the Truth InitiativeYoung Adult Cohort were randomized to see two of five photos of common e-cig products (three varieties of first-generation e-cigs and one variety each of second- and third-generation e-cigs). Qualitative responses were coded into nine classifications: "e-cigarette, e-hookah, vape-related, mod, other or more than one kind of e-cig, marijuana-related, non-e-cig tobacco product, misidentified, and don't know." We characterized the sample and survey responses and conducted multivariable logistic regression to identify participant characteristics associated with correctly identifying the devices as e-cigs. Data were weighted to represent the young adult population in the United States in 2016.Results: The majority of participants identified the pictured devices as some type of e-cig (57.7%-83.6%). The white first-generation e-cig, as well as the second- and third-generation e-cigs caused the greatest confusion, with a large proportion of individuals responding "don't know" (12.2%-25.1%, depending on device) or misidentifying the e-cig as a non-nicotine product (3.4%-16.1%, depending on device) or non-e-cig tobacco product (1.4%-14.6%, depending on device).Conclusions: Accurate surveillance and analyses of the effect of e-cigs on health behavior and outcomes depend on accurate data collection on users' subtype of e-cig. Carefully chosen images in surveys may improve reporting of e-cig use in population studies.