TY - JOUR AU - Crespi, Elizabeth AU - Heller, Johanna AU - Hardesty, Jeffrey J AU - Nian, Qinghua AU - Sinamo, Joshua K AU - Welding, Kevin AU - Kennedy, Ryan David AU - Cohen, Joanna E PY - 2023 DA - 2023/12/13 TI - Exploring Different Incentive Structures Among US Adults Who Use e-Cigarettes to Optimize Retention in Longitudinal Web-Based Surveys: Case Study JO - J Med Internet Res SP - e49354 VL - 25 KW - incentive KW - conditional incentive KW - web-based survey KW - longitudinal study KW - follow-up KW - nicotine KW - e-cigarettes KW - tobacco KW - survey KW - retention KW - demographics KW - case study KW - optimization KW - adults AB - 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 SN - 1438-8871 UR - https://www.jmir.org/2023/1/e49354 UR - https://doi.org/10.2196/49354 UR - http://www.ncbi.nlm.nih.gov/pubmed/38090793 DO - 10.2196/49354 ID - info:doi/10.2196/49354 ER -