Agreement Between Self-reports and Photos to Assess e-Cigarette Device and Liquid Characteristics in Wave 1 of the Vaping and Patterns of e-Cigarette Use Research Study: Web-Based Longitudinal Cohort Study

Is Maintenance or Switching Between Freebase and Nicotine Salt Liquid Associated with Electronic Nicotine Delivery Systems Dependence?

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.

Decisions of the FDA on premarket tobacco product applications: Changes in the number of unique devices and liquids used by US adults who frequently use electronic nicotine delivery systems, 2020-2023

INTRODUCTION

The majority of decisions on electronic nicotine delivery system (ENDS) premarket tobacco product applications (PMTAs) were made from October 2020 to February 2023; 99% (>25 million) had determinations by March 2023 and just twenty-three received marketing granted orders. We examined the unique devices and liquids used among US adults frequently using ENDS before, during, and after a majority of PMTA decisions were made.

METHODS

Data are from waves 1-5 (W1: May-Oct 2020, n=1179; W5: Feb-Apr 2023, n=1290) of a longitudinal survey of US adults (≥21 years) using ENDS ≥5 days/week. User-submitted photos of participants' most used devices and liquids were coded. Descriptive analyses and Wilcoxon signed-rank tests were used to understand the number and types of unique devices and liquids used in W1-W5, and the top brands in each wave.

RESULTS

From W1-W5, the number of unique ENDS device models and liquid products used by participants increased from 279 to 357 (p<0.001) and 546 to 695 (p<0.001), respectively. More unique devices in W5 versus W1 were disposable (W1: 16.5%; W5: 36.1%); fewer were disposable pod (W1: 6.5%; W5: 3.1%) or tank (W1: 53.8%; W5: 30.8%) devices. Liquids were primarily sweet-flavored (W1: 81.1%; W5: 82.0%). The median liquid nicotine concentration increased from 12 to 50 mg/mL. In W5, few participants used FDA-approved devices (n=17; 1.3%) or liquids (n=6; 0.5%), and Elf Bar was the most commonly used device and liquid brand. Results for all waves are reported.

CONCLUSIONS

Despite PMTA decisions, an increase in the number of unique device models and liquid products used among adults who frequently use ENDS was observed from 2020 to 2023. Few participants in 2023 were using FDA-approved devices or liquids. Further research and monitoring are needed to inform how FDA prioritizes enforcement actions and what types of enforcement actions are effective.

Transitions in device and liquid characteristic groupings among US adults frequently using electronic nicotine delivery systems (ENDS) over three timepoints, 2020-2021

INTRODUCTION

Electronic nicotine delivery system (ENDS) and liquid characteristics affect nicotine and toxicant exposure and use behaviors. Little is known about how adults who frequently use ENDS transition between ENDS device/liquid groupings.

METHODS

A total of 379 US adults (≥21 years) using ENDS frequently (≥5 days/week) self-reported and uploaded photos of their most used ENDS device and liquid in three waves of online surveys (May 2020 - November 2021). Device/liquid grouping was defined by device (i.e. disposable/refillable tank/refillable pod or cartridge/disposable pod or cartridge, adjustable/no adjustable settings) and liquid (i.e. salt/freebase) characteristics. Participants using the same grouping across waves were considered stable users.

RESULTS

The most prevalent wave (W) 1 grouping was tank (freebase, adjustable settings; 36.8%). From W1 to W3, the number of disposable device (salt, no adjustable settings) users increased 156.4% and the number of disposable pod/cartridge (salt, no adjustable settings) users decreased 15.2%. In W2 and W3, compared to stable users, participants using tank (freebase, adjustable settings) in W1 and another grouping in W2 and/or W3 reported significantly higher nicotine concentrations (mg/mL) (W2: 15.1 vs 5.5, p<0.001; W3: 22.9 vs 5.6, p<0.001) and lower device power (watt) (W2: 46.8 vs 58.7, p=0.02; W3: 34.0 vs 57.2, p<0.001).

CONCLUSIONS

Over a 1.5-year period, a rapid growth in disposable device (salt, no adjustable settings) use and a decrease in disposable pod/cartridge (salt, no adjustable settings) use were observed. Participants who transitioned from tank (freebase, adjustable settings) to other groupings were more likely to increase liquid nicotine concentration and reduce device power compared to stable users.

Ocular Symptoms in Adolescents and Young Adults With Electronic Cigarette, Cigarette, and Dual Use

Importance

Despite increasing use of cigarettes and electronic cigarettes (e-cigarettes) and related health effects among youth, few studies have reported their effects on eyes.

Objective

To examine the frequency and severity of ocular symptoms (ocular discomfort, pain, burning, itching, redness, dryness, glare, blurriness, strain, and headaches) in young e-cigarette and cigarette users.

Design, Setting, and Participants

In an observational cross-sectional study, a survey conducted in May 6 to 14, 2020, asked participants about use (ever, past 30 days, and past 7 days) of e-cigarettes and cigarettes. The participants included US individuals aged 13 to 24 years.

Main Outcomes and Measures

Associations between vision-related outcomes (general vision, severity/frequency of ocular symptoms) and tobacco use were analyzed using weighted multivariable logistic regressions, adjusting for sociodemographic factors, contact lens use, and other combustible use.

Results

There were 2168 never users, 2183 ever users, 1092 past 30-day users, and 919 past 7-day users of e-cigarettes; 55.9% of e-cigarette ever users also used cigarettes (dual users). Of the 4351 respondents, 63.8% identified as female, and mean (SD) age was 19.1 (2.9) years. Between 1.1% and 3.9% of ever dual users reported severe to very severe ocular symptoms; between 0.9% and 4.3% reported daily symptoms, which was higher than the proportion of symptoms in e-cigarette- or cigarette-only users. Past 7-day dual users had more severe itching (adjusted odds ratio [AOR], 2.37; 95% CI, 1.36-4.13; P = .002), redness (AOR, 2.58; 95% CI, 1.50-4.46; P = .001), dryness (AOR, 2.89; 95% CI, 1.64-5.08; P < .001), glare (AOR, 2.56; 95% CI, 1.50-4.35; P = .001), blurriness (AOR, 2.47; 95% CI, 1.36-4.50; P = .003), headaches (AOR, 2.31; 95% CI, 1.34-4.00; P = .003); and more frequent pain (AOR, 3.45; 95% CI, 2.09-5.68; P < .001), burning (AOR, 3.08; 95% CI, 1.86-5.09; P < .001), and redness (AOR, 2.72; 95% CI, 1.69-4.36; P < .001) than all other participants. Past 30-day dual users had more severe dryness (AOR, 2.65; 95% CI, 1.61-4.36; P < .001) and more frequent pain (AOR, 3.33; 95% CI, 2.12-5.21; P < .001) than all other participants. Ever dual users experienced more severe dryness (AOR, 1.60; 95% CI, 1.05-2.43; P = .03) and blurriness (AOR, 1.79; 95% CI, 1.21-2.64; P = .003) and more frequent pain (AOR, 1.69; 95% CI, 1.13-2.53; P = .01) and blurriness (AOR, 1.63; 95% CI, 1.13-2.36; P = .009) than never users.

Conclusions and Relevance

In this cross-sectional US study, adolescents and young adult users of both e-cigarettes and cigarettes had a higher likelihood of experiencing severe and frequent ocular symptoms, with past 7-day users reporting more symptoms than past 30-day users or ever users. These findings provide additional reasons for users of e-cigarettes and cigarettes to reduce their tobacco use to possibly prevent or minimize ocular symptoms.

Device and liquid characteristics used with sweet, menthol/mint, and tobacco ENDS liquid flavors: The population-based VAPER study

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).

Assessing Electronic Nicotine Delivery Systems Device Type Accurately in Surveys

INTRODUCTION

The electronic nicotine delivery systems (ENDS) market is highly heterogeneous and changing rapidly in the United States, making classification of devices complicated, especially for surveys. We assessed the percentage of concordant responses between self-reported device type and device type reported by manufacturer/retailer sites for three ENDS brands.

AIMS AND METHODS

Population Assessment of Tobacco and Health Study wave 5 (2018-2019) asked adult ENDS users about their ENDS device type with the following multiple-choice question: "What kind of electronic nicotine product [is/was] it?" with response options: (1) A disposable device, (2) A device that uses replaceable prefilled cartridges, (3) A device with a tank that you refill with liquids (4) A mod system, and (5) Something else. Participants using only one ENDS device and reporting brands of JUUL (n = 579), Markten (n = 30), or Vuse (n = 47) were included. Responses were dichotomized as "concordant=1" (prefilled cartridge for these three brands) and "discordant = 0" (other responses) to assess the concordance.

RESULTS

The overall concordance between self-reports and manufacturer/retail sites was 81.8% (n = 537). This percentage was 82.7% (n = 37) among Vuse users, 82.6% (n = 479) among JUUL users, and 69.1% (n = 21) among Markten users. Almost one in three people who use Markten did not indicate that their device uses replaceable prefilled cartridges.

CONCLUSIONS

While at least 70% concordance could be acceptable, collecting more information about device type (eg, liquid container (pod/cartridge/tank), refillability; and submitting pictures) may improve the accuracy of the information.

IMPLICATIONS

This study is particularly relevant for researchers analyzing smaller samples for example when examining disparities. Monitoring the characteristics of ENDS accurately in population-based studies is critical for regulatory authorities to understand ENDS toxicity, addiction, health effects, and use behaviors at the population level. There is evidence that higher concordance can be achieved with other questions- and methods. Adjusting survey questions about ENDS device type (eg, more descriptive response options, inclusion of separate questions asking about tank, pod, cartridge) and potentially including photos of participants' devices may help to classify ENDS device types more accurately.

E-cigarette Use Patterns, Flavors, and Device Characteristics Associated With Quitting Smoking Among a U.S. sample of Adults Using E-cigarettes in a Smoking Cessation Attempt

INTRODUCTION

Many adults who smoke cigarettes use e-cigarettes to try to quit smoking; however, some are not successful. Identifying factors that are associated with successfully quitting smoking using e-cigarettes is important for maximizing cigarette cessation.

AIMS AND METHODS

Online survey data were collected in 2021 from 857 adults in the United States who reported using e-cigarettes in a recent attempt to quit smoking. Survey items assessed patterns of e-cigarette use and device characteristics (flavors, device, and nicotine) used when trying to quit smoking. Multivariable linear regression models examined characteristics associated with the longest duration of smoking abstinence when using e-cigarettes to try to quit.

RESULTS

The average duration of smoking abstinence when using e-cigarettes during a quit attempt was 65 days (SD = 104). In the multivariable model, greater frequency of e-cigarette use when quitting and abruptly switching to e-cigarettes from cigarettes (vs. gradually reducing) were significantly associated with longer durations of abstinence (p < .001). Preference for non-tobacco (relative to tobacco) flavors and nicotine concentration were not associated with duration of abstinence, although preference for rechargeable pod and mod device types (vs. cig-a-likes) was associated with longer durations of abstinence.

CONCLUSIONS

Patterns of e-cigarette use were related to abstinence duration, which may provide guidance for adults who are using e-cigarettes to quit smoking to encourage complete substitution and maximize smoking cessation. Findings indicate that non-tobacco e-cigarette flavors and nicotine strength are not related to longer durations of cessation success for adults, which may inform tobacco regulatory policies limiting these constituents to protect public health.

IMPLICATIONS

This study provides important new information about the characteristics of e-cigarettes used during an attempt to quit smoking among adults across the United States and identifies factors associated with quitting success. Patterns of e-cigarette use were associated with longer durations of abstinence. In contrast, few e-cigarette characteristics were associated with abstinence. Although preference for some pod and mod device types was associated with longer abstinence duration compared to earlier cig-a-like devices, preference for non-tobacco (vs. tobacco) flavor and nicotine concentration were not associated with abstinence. Findings may help inform guidance for adults using e-cigarettes to quit smoking and support tobacco regulatory policies.

The Vaping and Patterns of e-Cigarette Use Research Study: Protocol for a Web-Based Cohort Study

BACKGROUND

In total, 3.2% of American adults report using e-cigarettes every day or some days. The Vaping and Patterns of E-cigarette Use Research (VAPER) Study is a web-based longitudinal survey designed to observe patterns in device and liquid use that suggest the benefits and unintended consequences of potential e-cigarette regulations. The heterogeneity of the e-cigarette devices and liquids on the market, the customizability of the devices and liquids, and the lack of standardized reporting requirements result in unique measurement challenges. Furthermore, bots and survey takers who submit falsified responses are threats to data integrity that require mitigation strategies.

OBJECTIVE

This paper aims to describe the protocols for 3 waves of the VAPER Study and discuss recruitment and data processing experiences and lessons learned, including the benefits and limitations of bot- and fraudulent survey taker-related strategies.

METHODS

American adults (aged ≥21 years) who use e-cigarettes ≥5 days per week are recruited from up to 404 Craigslist catchment areas covering all 50 states. The questionnaire measures and skip logic are designed to accommodate marketplace heterogeneity and user customization (eg, different skip logic pathways for different device types and customizations). To reduce reliance on self-report data, we also require participants to submit a photo of their device. All data are collected using REDCap (Research Electronic Data Capture; Vanderbilt University). Incentives are US $10 Amazon gift codes delivered by mail to new participants and electronically to returning participants. Those lost to follow-up are replaced. Several strategies are applied to maximize the odds that participants who receive incentives are not bots and are likely to possess an e-cigarette (eg, required identity check and photo of a device).

RESULTS

In total, 3 waves of data were collected between 2020 and 2021 (wave 1: n=1209; wave 2: n=1218; wave 3: n=1254). Retention from waves 1 to 2 was 51.94% (628/1209), and 37.55% (454/1209) of the wave 1 sample completed all 3 waves. These data were mostly generalizable to daily e-cigarette users in the United States, and poststratification weights were generated for future analyses. Our data offer a detailed examination of users' device features and specifications, liquid characteristics, and key behaviors, which can provide more insights into the benefits and unintended consequences of potential regulations.

CONCLUSIONS

Relative to existing e-cigarette cohort studies, this study methodology has some advantages, including efficient recruitment of a lower-prevalence population and collection of detailed data relevant to tobacco regulatory science (eg, device wattage). The web-based nature of the study requires several bot- and fraudulent survey taker-related risk-mitigation strategies, which can be time-intensive. When these risks are addressed, web-based cohort studies can be successful. We will continue to explore methods for maximizing recruitment efficiency, data quality, and participant retention in subsequent waves.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/38732.

Evaluation of the Psychometric Properties of Dependence Measures for Exclusive Electronic Cigarette Users

INTRODUCTION

Extant electronic cigarette (ECIG) dependence measures are largely adapted from those designed for cigarette smoking, though few have been evaluated for their psychometric properties.

AIMS AND METHODS

Never-smoking ECIG users (N = 134) participating in an online survey completed four dependence measures: Penn state electronic cigarette dependence index (PSECDI), e-cigarette dependence scale (EDS-4), diagnostic and statistical manual for tobacco use disorder (DSM-5), and Glover Nilsson behavioral questionnaire (GNBQ). They also reported on their ECIG use characteristics (eg, behaviors and reasons).

RESULTS

Internal consistency was highest for the EDS-4 (Cronbach's α = 0.88) followed by the GNBQ (α = 0.75), PSECDI (α = 0.72), and DSM (α = 0.71). Confirmatory factor analyses revealed a single-factor structure for the PSECDI, EDS-4, and GNBQ. For the DSM-5, however, two items did not load significantly (ECIG use interferes with responsibilities; reduce/give up activities because of ECIG use). Significant correlations were observed between all measures and the number of ECIG use days/week and/or years using ECIGs, as well as between DSM-5 scores and the number of ECIG quit attempts and initiation age. Endorsement of using ECIGs because "I like flavors" was correlated positively with DSM-5 and GNBQ scores.

CONCLUSIONS

All dependence measures evaluated herein demonstrated adequate reliability and construct validity. Future work should focus on determining which aspects of dependence are those that are unique to ECIG use, and subsequently developing a more comprehensive measure of ECIG dependence.

IMPLICATIONS

The measures assessed herein-PSECDI, EDS-4, DSM-5, and GNBQ-demonstrated adequate to good reliability and construct validity among a sample of never-smoking ECIG users. The dependence domains covered across measures were related yet distinct. Findings demonstrate the need for future evaluation of these different domains to determine which are the most salient characteristics of ECIG dependence.