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Background: Electronic nicotine delivery systems (ENDS) use one of two formulations of nicotine-freebase or nicotine salt. This study examines whether maintenance or switching between nicotine formulations is associated with ENDS dependence using longitudinal survey data., Methods: 543 U.S. adults (21+) using ENDS frequently (5+ days/week) self-reported and uploaded photos of their most used ENDS liquids in wave 3-5 online surveys from September 2021 to April 2023. Nicotine formulation from photo data was used if available; otherwise, self-reported data were used. ENDS dependence was measured in each wave by a 4-item E-cigarette Dependence Scale (EDS: range 0-4, 4 being most dependent). Data were analyzed using ANCOVA., Results: Participants using nicotine salt liquids in three waves reported the highest EDS in wave 5 (49.3%, EDS = 2.59), followed by participants switching from salt to freebase (3.2%, EDS = 2.58), participants switching from freebase to salt (10.1%, EDS = 2.52), participants using freebase in three waves (34.9%, EDS = 2.18), and participants changing back and forth (2.4%, EDS = 2.11). After controlling for smoking status, participants stably using nicotine salt and participants switching from freebase to salt reported significantly higher EDS than those stably using freebase ( p  < 0.01)., Conclusions: Over an 18-month period, people consistently using nicotine salt liquids and participants switching from freebase to nicotine salt were more likely to have a higher ENDS dependence than those consistently using freebase liquids. Understanding how switching between nicotine formulations relates to ENDS dependence can inform nicotine formulation and concentration regulations that may impact addiction.

Introduction: Electronic nicotine delivery system (ENDS) device and liquid characteristics (e.g., wattage, nicotine concentration) are diverse and important in determining product appeal, aerosol volume/nicotine levels, and toxicity. Little is known about how device and liquid characteristics vary by flavor; we address this gap to identify potential regulatory implications., Methods: Data are from a longitudinal cohort study (Waves 2 and 3; December 2020-December 2021) of adult (≥21 years) U.S. ENDS users (≥5 days of use/week). Participants (n = 1809) reported on and submitted photos of their most used device and liquid. Participants were categorized into flavor groups of high prevalence in our sample and in prior literature: sweet, menthol/mint, or tobacco. Participants using liquids without nicotine or flavors other than sweet, menthol/mint, or tobacco were excluded (n = 320). Data were analyzed cross-sectionally. Chi-square and linear regression (n = 1489) were used to examine device and liquid characteristics by flavor., Results: Sweet flavors were most common (n = 1135; 76.2%), followed by menthol/mint (n = 214, 14.4%) and tobacco (n = 140, 9.4%). Sweet flavors were less common among participants using reusable devices with disposable pods/cartridges (nicotine salt) than those using other device-liquid groupings (5.2% vs 86.5-93.9%; p < 0.001). Sweet flavors were less common among those using ENDS for non-flavor reasons vs the flavor (73.5% vs 90.4%; p < 0.001). Sweet flavors correlated with lower nicotine concentrations, higher wattages, and lower ages of ENDS first use (p < 0.001)., Conclusions: Regulatory agencies must consider how regulations on device and liquid characteristics may affect ENDS users' behaviors (e.g., limiting availability of sweet flavors may encourage use of non-sweet flavors and lower wattages)., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: e-Cigarette device and liquid characteristics are highly customizable; these characteristics impact nicotine delivery and exposure to toxic constituents. It is critical to understand optimal methods for measuring these characteristics to accurately assess their impacts on user behavior and health., Objective: To inform future survey development, we assessed the agreement between responses from survey participants (self-reports) and photos uploaded by participants and the quantity of usable data derived from each approach., Methods: Adult regular e-cigarette users (≥5 days per week) aged ≥21 years (N=1209) were asked questions about and submitted photos of their most used e-cigarette device (1209/1209, 100%) and liquid (1132/1209, 93.63%). Device variables assessed included brand, model, reusability, refillability, display, and adjustable power. Liquid variables included brand, flavor, nicotine concentration, nicotine formulation, and bottle size. For each variable, percentage agreement was calculated where self-report and photo data were available. Krippendorff α and intraclass correlation coefficient (ICC) were calculated for categorical and continuous variables, respectively. Results were stratified by device (disposable, reusable with disposable pods or cartridges, and reusable with refillable pods, cartridges, or tanks) and liquid (customized and noncustomized) type. The sample size for each calculation ranged from 3.89% (47/1209; model of disposable devices) to 95.12% (1150/1209; device reusability)., Results: Percentage agreement between photos and self-reports was substantial to very high across device and liquid types for all variables except nicotine concentration. These results are consistent with Krippendorff α calculations, except where prevalence bias was suspected. ICC results for nicotine concentration and bottle size were lower than percentage agreement, likely because ICC accounts for the level of disagreement between values. Agreement varied by device and liquid type. For example, percentage agreement for device brand was higher among users of reusable devices (94%) than among users of disposable devices (75%). Low percentage agreement may result from poor participant knowledge of characteristics, user modifications of devices inconsistent with manufacturer-intended use, inaccurate or incomplete information on websites, or photo submissions that are not a participant's most used device or liquid. The number of excluded values (eg, self-report was "don't know" or no photo submitted) differed between self-reports and photos; for questions asked to participants, self-reports had more usable data than photos for all variables except device model and nicotine formulation., Conclusions: Photos and self-reports yield data of similar accuracy for most variables assessed in this study: device brand, device model, reusability, adjustable power, display, refillability, liquid brand, flavor, and bottle size. Self-reports provided more data for all variables except device model and nicotine formulation. Using these approaches simultaneously may optimize data quantity and quality. Future research should examine how to assess nicotine concentration and variables not included in this study (eg, wattage and resistance) and the resource requirements of these approaches., (©Elizabeth Crespi, Jeffrey J Hardesty, Qinghua Nian, Joshua Sinamo, Kevin Welding, Ryan David Kennedy, Joanna E Cohen. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 27.04.2022.)