JMIR Publications

ABSTRACT

Background:

3.2% of U.S. adults report using e-cigarettes every day or some days. The Vaping and Patterns of E-cigarette use Research (VAPER) Study is an online longitudinal survey designed to observe patterns in device and liquid use that suggest 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 fraudulent survey takers who submit falsified responses are threats to data integrity that require mitigation strategies.

Objective:

To describe the protocols for waves 1-3 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:

U.S. adults (21+) who use e-cigarettes five or more days/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 (e.g., 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. 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 mitigate risk and maximize the odds that participants who receive incentives are not bots and are participants likely in possession of an e-cigarette (e.g., required identity check and photo of a device).

Results:

Three waves of data were collected between 2020-2021 (Wave 1: N=1209; Wave 2: N=1218; Wave 3: N=1254). Retention from Waves 1 to 2 was 52% (628/1209) and 33% (454/1209) of the Wave 1 sample completed all three waves. These data were mostly generalizable to daily e-cigarette users in the United States and post-stratification weights were generated for future analyses.

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 (e.g., device wattage). The online nature of the study requires several bot and fraudulent survey taker-related risk mitigation strategies and these strategies can be time-intensive. When these risks are addressed, online cohort studies can be successful. We will continue to explore methods for maximizing recruitment efficiency, data quality, and participant retention in subsequent waves.