Department of Health Promotion and Behavioral Sciences, University of Texas Health Science Center, Houston, TX, USA.
Department of Statistics, Pennsylvania State University, University Park, PA, USA.
Nicotine Tob Res. 2021 Aug 18;23(9):1484-1489. doi: 10.1093/ntr/ntab050.
Existing e-cigarette dependence scales are mainly validated based on retrospective overall consumption or perception. Further, given that the majority of adult e-cigarette users also use combustible cigarettes, it is important to determine whether e-cigarette dependence scales capture the product-specific dependence. This study fills in the current knowledge gaps by validating e-cigarette dependence scales using novel indices of dynamic patterns of e-cigarette use behaviors and examining the association between dynamic patterns of smoking and e-cigarette dependence among dual users.
Secondary analysis was conducted on the 2-week ecological momentary assessment data from 116 dual users. The Smoothly Clipped Absolute Deviation penalty (SCAD) was adopted to select important indices for dynamic patterns of consumption or craving and estimate their associations with e-cigarette dependence scales.
The fitted linear regression models support the hypothesis that higher e-cigarette dependence is associated with higher levels of e-cigarette consumption and craving as well as lower instability of e-cigarette consumption. Controlling for dynamic patterns of vaping, dual users with lower e-cigarette dependence tend to report higher day-to-day dramatic changes in combustible cigarette consumption but not higher average levels of smoking.
We found that more stable use patterns are related to higher levels of dependence, which has been demonstrated in combustible cigarettes and we have now illustrated in e-cigarettes. Furthermore, the e-cigarette dependence scales may capture the product-specific average consumption but not product-specific instability of consumption.
This study provides empirical support for three e-cigarette dependence measures: PS-ECDI, e-FTCD, and e-WISDM, based on dynamic patterns of e-cigarette consumption and craving revealed by EMA data that have great ecological validity. This is the first study that introduces novel indices of dynamic patterns and demonstrates their potential applications in vaping research.
现有的电子烟依赖量表主要基于回顾性的总体消费或感知进行验证。此外，由于大多数成年电子烟使用者也同时使用可燃香烟，因此确定电子烟依赖量表是否能捕捉到特定产品的依赖是很重要的。本研究通过使用电子烟使用行为动态模式的新指标验证电子烟依赖量表，并检查双重使用者中吸烟和电子烟依赖的动态模式之间的关联，填补了当前知识空白。
对 116 名双重使用者的 2 周生态瞬时评估数据进行二次分析。采用平滑剪辑绝对偏差惩罚（SCAD）选择消费或渴求的重要指标，并估计它们与电子烟依赖量表之间的关联。
拟合的线性回归模型支持这样一种假设，即更高的电子烟依赖与更高水平的电子烟消费和渴求以及更低的电子烟消费不稳定性相关。控制电子烟吸食的动态模式后，依赖性较低的双重使用者倾向于报告更高的可燃香烟消费的日常剧烈变化，但不会报告更高的平均吸烟量。
我们发现，更稳定的使用模式与更高的依赖性相关，这在可燃香烟中已经得到了证明，而我们现在在电子烟中也已经说明了这一点。此外，电子烟依赖量表可能捕捉到特定产品的平均消费，但不能捕捉到特定产品的消费不稳定性。
本研究基于 EMA 数据揭示的电子烟消费和渴求的动态模式，为三种电子烟依赖测量方法（PS-ECDI、e-FTCD 和 e-WISDM）提供了实证支持，这些方法具有很强的生态有效性。这是第一个引入动态模式新指标并展示其在电子烟研究中潜在应用的研究。
