Exploring Different Incentive Structures Among US Adults Who Use e-Cigarettes to Optimize Retention in Longitudinal Web-Based Surveys: Case Study.

BACKGROUND: Longitudinal cohort studies are critical for understanding the evolution of health-influencing behaviors, such as e-cigarette use, over time. Optimizing follow-up rates in longitudinal studies is necessary for ensuring high-quality data with sufficient power for analyses. However, achieving high rates of follow-up in web-based longitudinal studies can be challenging, even when monetary incentives are provided. OBJECTIVE: This study compares participant progress through a survey and demographics for 2 incentive structures (conditional and hybrid unconditional-conditional) among US adults using e-cigarettes to understand the optimal incentive structure. METHODS: The data used in this study are from a web-based longitudinal cohort study (wave 4; July to September 2022) of US adults (aged 21 years or older) who use e-cigarettes ≥5 days per week. Participants (N=1804) invited to the follow-up survey (median completion time=16 minutes) were randomly assigned into 1 of 2 incentive structure groups (n=902 each): (1) conditional (US $30 gift code upon survey completion) and (2) hybrid unconditional-conditional (US $15 gift code prior to survey completion and US $15 gift code upon survey completion). Chi-square tests assessed group differences in participant progress through 5 sequential stages of the survey (started survey, completed screener, deemed eligible, completed survey, and deemed valid) and demographics. RESULTS: Of the 902 participants invited to the follow-up survey in each group, a higher proportion of those in the conditional (662/902, 73.4%) than the hybrid (565/902, 62.6%) group started the survey (P<.001). Of those who started the survey, 643 (97.1%) participants in the conditional group and 548 (97%) participants in the hybrid group completed the screener (P=.89), which was used each wave to ensure participants remained eligible. Of those who completed the screener, 555 (86.3%) participants in the conditional group and 446 (81.4%) participants in the hybrid group were deemed eligible for the survey (P=.02). Of those eligible, 514 (92.6%) participants from the conditional group and 401 (89.9%) participants from the hybrid group completed the survey and were deemed valid after data review (P=.14). Overall, more valid completions were yielded from the conditional (514/902, 57%) than the hybrid group (401/902, 44.5%; P<.001). Among those who validly completed the survey, no significant differences were found by group for gender, income, race, ethnicity, region, e-cigarette use frequency, past 30-day cigarette use, or number of waves previously completed. CONCLUSIONS: Providing a US $30 gift code upon survey completion yielded higher rates of survey starts and completions than providing a US $15 gift code both before and after survey completion. These 2 methods yielded participants with similar demographics, suggesting that one approach is not superior in obtaining a balanced sample. Based on this case study, future web-based surveys examining US adults using e-cigarettes could consider providing the full incentive upon completion of the survey. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/38732.

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.

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.

Combinations of electronic nicotine delivery system device and liquid characteristics among U.S. adults.

INTRODUCTION: The combination of electronic nicotine delivery systems (ENDS) device and liquid characteristics affect user nicotine and toxicant exposure, however population-level national survey studies have not reported device and liquid features jointly nor in detail. We examined combinations of characteristics of devices and liquids used by adult ENDS users. METHODS: U.S. adults (21+) using ENDS at least five days/week (n = 1,179) completed an online survey in 2020 and uploaded photos of their most used device and liquid. Device/liquid combinations were analyzed to determine and describe the most common pairings. Data were weighted to the U.S. population of adult daily ENDS users. RESULTS: Five device/liquid combinations accounted for 87 % of those reported. The most prevalent combination, reported by 36.2 %, was re-useable devices with adjustable settings and a tank refilled with a free-base nicotine liquid with a median nicotine concentration of 5.2 mg/mL. The second most frequent combination - re-usable devices with no adjustable settings and a nicotine salt liquid in a disposable pod or cartridge - was reported by 22.8 % and the median nicotine concentration was 49.4 mg/mL. Wattage, voltage and resistance varied across device/liquid combination. Overall, 66.5 % refilled their device's tank or pod and 64.2 % had the ability to manipulate device characteristics (power, airflow, and/or coil). CONCLUSIONS: Analyzing ENDS device/liquid combinations rather than each separately can allow researchers to better evaluate relationships between use and key outcomes, such as quitting cigarettes and abuse liability. Additional research may reveal whether certain combinations are more effective at helping smokers quit and which device/liquid combinations should remain on the market.