Electronic Cigarette Device and Liquid Characteristics: Comparison of Self-Reports to User-Provided Pictures.

Introduction:  Self-reports of electronic cigarette (ECIG) device and liquid characteristics are not always accurate or consistent with characteristics as measured by researchers. Two methods for measuring ECIG characteristics were compared: user self-reports and rater-coded pictures.

Methods:  Exclusive ECIG users ( = 321) reported on device (disposable, refillable, adjustable power, brand) and liquid (nicotine concentration, formulation, flavor) characteristics.

Factors associated with transitions in tobacco product use states among young adults aged 18-29 years.

Background And Objectives: This study examined young adults' tobacco use transitions based on their past 30-day use states, and identified factors associated with their transitions.

Methods: Participants (N = 12377) were young adults aged 18-29 years at Wave 1 of the Population Assessment of Tobacco and Health (PATH) study. Self-reported tobacco use states were categorized by the number of past-month use days (0, 1-4, 5-8, 9-12, 13-30 days) for cigarettes, electronic cigarettes [e-cigarettes], traditional cigars, filtered cigars, cigarillos, smokeless tobacco (SLT), and hookah.

Longitudinal transitions in adolescent polytobacco use across waves 1-4 of the Population Assessment of Tobacco and Health study.

Aims: This study aims to identify adolescent patterns of polytobacco use and measure transitions between patterns over time.

Design: Longitudinal analysis using data derived from waves 1-4 (2013-18) of the Population Assessment of Tobacco and Health (PATH) study. Transitions in tobacco use patterns were examined via latent transition analysis, and then, socio-demographic characteristics were used to predict transitions via logistic regression.

Predictors of electronic cigarette dependence among non-smoking electronic cigarette users: User behavior and device characteristics.

Introduction: ECIGs differ in their ability to deliver nicotine to the user and, consequently, they may differ in their ability to produce dependence. This study examined individual device characteristics, device type, and user behaviors as predictors of ECIG dependence in a sample of never-smoking ECIG users.

Methods: Participants (N = 134) completed an online survey that assessed demographics, ECIG use behavior, and ECIG dependence as measured via the Penn State Electronic Nicotine Dependence Index (PSECDI) and E-cigarette Dependence Scale (EDS-4).

Transitions in tobacco use profiles among adolescents: Results from the Population Assessment of Tobacco and Health (PATH) study waves 3 and 4.

Introduction: Despite increases in adolescents' polytobacco use, little work has utilized recent national data to examine transitions in polytobacco use over time or predictors of such transitions.

Methods: Data derived from the Population Assessment of Tobacco and Health (PATH) study. Participants used at least one tobacco product (cigarettes, electronic cigarettes [ECIGs], traditional cigars, cigarillos, filtered cigars, snus, smokeless tobacco [SLT], hookah) at Wave 3 (W3; 2015-2016) or 4 (W4; 2016-2018) and had Wave 1 (W1) data (N = 1072; M= 13.

Device features and user behaviors as predictors of dependence among never-smoking electronic cigarette users: PATH Wave 4.

Electronic cigarettes (ECIGs) vary greatly in their ability to deliver nicotine, which suggests they may also vary in their ability to produce dependence. This study examined individual and combined ECIG device features, and also user behaviors, as predictors of dependence in never-smoking ECIG users. Methods Data were collected from 711 current ECIG users who had smoked <100 cigarettes in their lifetime at Wave 4 of the Population Assessment of Tobacco and Health (PATH) Study.

Electronic Cigarette Terminology: Where Does One Generation End and the Next Begin?

The electronic cigarette (ECIG) research community faces several challenges when it comes to regulatory science; not only is the ECIG market changing at a rapid pace, but the terms used by researchers, health organizations, ECIG users, and ECIG manufacturers/distributors to describe devices are inconsistent. These discrepancies make it difficult to advance science and develop regulations. Although researchers have used "generations" to categorize ECIG device types based on various characteristics, with the constantly evolving ECIG market, it is unclear where one "generation" of devices ends and the next begins.