Piasecki Thomas M, Korcarz Claudia E, Hansen Kristin M, Bolt Daniel M, Fiore Michael C, Stein James H, Baker Timothy B
Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, USA.
Center for Tobacco Research and Intervention, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, USA.
Nicotine Tob Res. 2024 Dec 19. doi: 10.1093/ntr/ntae302.
Prior research suggests that the e-Cigarette Wisconsin Inventory of Smoking Dependence Motives (e-WISDM) distinguishes primary (e-PDM) and secondary dependence (e-SDM), however, there is little research on these e-WISDM dimensions and prior research comprised dual users (using cigarettes and e-cigarettes) and those using older generations of e-cigarettes.
Those exclusively using contemporary e-cigarettes (N = 164) completed the e-WISDM and a laboratory self-administration session and rated pre-use expectancies and post-use experiences.
Only a 1-factor model limited to the primary scales (Automaticity, Tolerance, Craving, Loss of Control) achieved good model fit. The e-PDM was correlated with the Penn State Electronic Cigarette Dependence Index (PS-ECDI), r = .79, p < .001. The e-PDM and PS-ECDI were similarly correlated with use topography and self-reported measures. Analyses of motive profiles identified Taste, Tolerance, and Automaticity as the most strongly endorsed motives in the full sample. Subgroup analyses indicated primary motives were more elevated in in daily vs. non-daily e-cigarette users and participants with vs. without a history of smoking cigarettes. Taste motives were stronger in users of 3rd vs. 4th generation e-cigarettes.
These findings suggest that the four e-PDM subscales are a concise, reliable, and valid measure of core e-cigarette dependence motives that are related to meaningful dependence attributes.
Electronic cigarettes (e-cigarettes) are dependence-producing. Instruments that measure e-cigarette dependence are necessary to identify users who may have difficulty quitting e-cigarettes and who are at risk for use-related harms. The four subscales of the e-WISDM PDM index self-reported heavy e-cigarette use, craving, automatic or mindless use, and perceived loss of control over use. The current research supports the validity of the e-WISDM PDM as a measure of core e-cigarette dependence in users of today's e-cigarette devices.
先前的研究表明,电子烟威斯康星吸烟依赖动机量表(e-WISDM)能够区分主要依赖(e-PDM)和次要依赖(e-SDM),然而,关于这些e-WISDM维度的研究较少,且先前的研究涵盖了双重使用者(同时使用香烟和电子烟)以及使用较老式电子烟的人群。
仅使用当代电子烟的人群(N = 164)完成了e-WISDM量表以及一次实验室自我给药环节,并对使用前的预期和使用后的体验进行了评分。
仅一个局限于主要量表(自动性、耐受性、渴望、失控感)的单因素模型实现了良好的模型拟合。e-PDM与宾夕法尼亚州立大学电子烟依赖指数(PS-ECDI)相关,r = 0.79,p < 0.001。e-PDM和PS-ECDI与使用特征及自我报告的测量指标具有相似的相关性。动机概况分析确定了口味、耐受性和自动性是整个样本中得到最强烈认可的动机。亚组分析表明,主要动机在每日使用电子烟的人群与非每日使用电子烟的人群中,以及有吸烟史的参与者与无吸烟史的参与者中更为突出。第三代电子烟使用者的口味动机比第四代电子烟使用者更强。
这些发现表明,e-PDM的四个子量表是对与有意义的依赖属性相关的核心电子烟依赖动机的一种简洁、可靠且有效的测量方法。
电子烟会导致成瘾。测量电子烟依赖的工具对于识别可能难以戒烟以及有使用相关危害风险的使用者是必要的。e-WISDM PDM指数的四个子量表自我报告了大量使用电子烟、渴望、自动或无意识使用以及对使用的失控感。当前的研究支持e-WISDM PDM作为当今电子烟设备使用者核心电子烟依赖测量方法的有效性。