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

E-cigarette Device Type, Source, and Use Behaviors of Youth and Young Adults: Findings from the Truth Longitudinal Cohort (2020-2021)

Background: E-cigarette device types vary in the amount of nicotine delivered to users. Given that youth and young adults are using pod-based and disposable e-cigarettes with high nicotine concentrations, it is important to determine how e-cigarette use behaviors associated with nicotine dependence may differ across e-cigarette device type. Methods: Baseline information was collected from September 2020 to March 2021 and follow-up information was collected from July to October 2021 from the Truth Longitudinal Cohort. The final analytic sample included respondents (aged 15-24) who reported current use of e-cigarettes at either baseline or follow-up and provided information on the 4-item E-cigarette Dependence Scale (EDS). Differences in endorsement of items from the EDS by e-cigarette device type (pod-based, disposable, or tank) were assessed using chi-square tests. Results: Participants (N = 308) were evenly split on age (15-20, 21+) and gender. Most 15-20-year-olds used disposable e-cigarettes, while those 21+ years primarily used tank devices. Although EDS score did not differ by e-cigarette device type, positive endorsement of two items from the EDS significantly differed by e-cigarette device type. More tank users endorsed reaching for a device without thinking about it (tank: 92.6%; pod-based: 79.0%; disposables: 79.9%, p = 0.04) and vaping more before going into a situation where vaping is not allowed (tank: 92.9%; pod-based: 71.0%; disposables: 73.0%, p < 0.01). Conclusions: Findings have the potential to inform policy implementation by providing evidence for specific targets for regulatory action that can help to reduce the burdens of e-cigarette use among youth and young adults, as results suggest that tank device users are more likely to endorse use behaviors associated with nicotine dependence.

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.

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). Participants uploaded a picture of their personal ECIG device/liquid, which was coded by raters to identify product features. Multivariable linear regressions examined device characteristics (e.g., adjustable power, nicotine concentration) and device type (e.g., vape pen, mod, pod, modern disposable) as predictors of dependence controlling for demographics and user behaviors (e.g., ECIG use duration and frequency, other tobacco use).

RESULTS

Longer durations of ECIG use and more use days/week were associated significantly with higher PSECDI (β's = 0.91 and 1.90, respectively; p's < 0.01) and EDS-4 scores (β's = 0.16 and 0.28, respectively; p's < 0.01). Higher nicotine concentrations were associated with higher PSECDI scores only (β = 0.07, p =.011). Dependence scores did not differ as a function of ECIG device types after controlling for covariates.

CONCLUSIONS

ECIG dependence was observed among the never-smoking ECIG users in this sample, regardless of their ECIG device/liquid features. Findings suggest that regulatory efforts aimed at reducing the dependence potential of ECIGs in never smokers should focus on overall nicotine emissions rather than product features.