Methodology Differences Impacting Prevalence Estimates of Youth Use of Electronic Nicotine Delivery Systems (ENDS) across Waves 5-7 of the Population Assessment of Tobacco and Health

Methodology Differences Impacting Prevalence Estimates of Youth Use of Electronic Nicotine Delivery Systems (ENDS) across Waves 5-7 of the Population Assessment of Tobacco and Health | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Methodology Differences Impacting Prevalence Estimates of Youth Use of Electronic Nicotine Delivery Systems (ENDS) across Waves 5-7 of the Population Assessment of Tobacco and Health Arielle Selya, Michael J. Hannon, Sooyong Kim, Saul Shiffman This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6264312/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background : The Population Assessment of Tobacco and Health (PATH) is a commonly-used longitudinal survey on nicotine/tobacco product use. Accurate surveillance to prevent youth use of electronic nicotine delivery systems (ENDS) requires understanding the impact of methodological differences in Wave 6 (~2021), specifically older ages (14–17 vs. usual 12–17) and survey mode (some telephone interviews vs. usual self-completed). Methods : Changes in past-30-day (P30D) youth ENDS prevalence and patterns of use (i.e., frequency, device type, flavors, and brand) were examined year-over-year and for the 3-year period (2019–2022) . Analyses compared combined age groups and survey modes (i.e. among all youth in each wave regardless of survey mode) with methodologically-comparable subgroups (i.e. same age range and survey mode). The impact of age on point estimates and trends (i.e. interaction with wave) was examined. Results : Youth P30D ENDS prevalence significantly declined over the prior 3 years, but not over the prior 1 year in either the naïve or methodologically-comparable analyses. However, 14-17-year olds reported higher prevalence and steeper declines (age-wave interaction p <0.0001) over the past 3 years (12.2% to 7.5%) than 12-13-year olds (1.7% to 1.2%). Age differences had more modest impacts on patterns of ENDS use. Discussion : Methodological differences in PATH Wave 6 introduced artifacts in estimates of prevalence, and to a lesser extent, patterns of youth ENDS use. Waves 5 and 7 are approximately comparable with respect to these differences. Future research examining prevalence trends over these waves should account for differences in survey mode and age range. Epidemiology Behavior electronic cigarettes nicotine prevalence surveillance youth Figures Figure 1 Introduction Ongoing surveillance of youth use of nicotine and tobacco products is a public health priority, especially for the most commonly used product, electronic nicotine delivery systems (ENDS). 1 The nationally-representative Population Assessment of Tobacco and Health (PATH) survey 2 is a main source of data for research on nicotine and tobacco product behavior, including trends over time. 3 – 5 Accordingly, accurate data analysis and interpretation of findings are paramount to the integrity of ongoing research on youth ENDS use. However, there are important methodological differences that complicate comparisons across waves of PATH. Specifically, we previously documented two methodological differences that impact youth ENDS use prevalence estimates in Waves 5.5 (~ 2020) and 6 (~ 2021): survey mode and age range. 6 Regarding survey mode differences, PATH is typically self-administered by participants in a secure home setting on a laptop with privacy and security features (through Wave 5, ~ 2020), but due to COVID restrictions, this changed to telephone interviews during Wave 5.5 (~ 2020; 100% telephone interview) and partly continued into Wave 6 (~ 2021; approximately two-thirds telephone interviews). 6 , 7 Reported ENDS use was significantly lower in telephone interviews than in self-completed assessments, likely due in part to social desirability bias. 6 This survey-mode artifact has a substantial impact on the interpretation of youth ENDS use trends: a naïve comparison appears to show a large decline in ENDS use prevalence from Waves 5 to 5.5 followed by an uptick in Wave 6, but analyzing within survey modes shows a more modest decline followed by a plateau. 6 That is, the interpretation of youth ENDS use trends qualitatively differs based on whether or not the survey-mode difference is accounted for. Regarding differences in age range across waves, typically PATH samples participants aged 12–17 for the youth survey. 7 As PATH is a longitudinal survey, most waves enroll new participants at the younger end of this age range to maintain a similar age range as previous participants age – either through previously-sampled “shadow” youth or through the Wave 4 and 7 replenishment samples. However, there were very few newly-enrolled youth (~ 12–13 years) at Waves 5.5 and 6, resulting in an older minimum age (~ 14–17 years) of the youth sample compared to other waves. 6 , 7 This age difference likely introduces an artifact in estimates of youth ENDS use prevalence, as ENDS use is more common at older ages. That is, youth ENDS use prevalence estimates may be inflated for Waves 5.5 and 6 in analyses that are naïve to the age-range difference; it unknown whether this artifact could also impact patterns of ENDS use (i.e., frequency, device type, flavor, and brand use). In our previous article documenting PATH’s survey mode artifact in Waves 5.5 and 6, we pointed out the existence of the age-range difference but were unable to examine its precise impact on prevalence estimates due to the lack of younger ages (12–13 years) in these waves. The newly-released Wave 7 (~ 2022) affords the opportunity to examine age-related changes in ENDS use prevalence, as it includes a replenishment sample that restores the full youth age range (12–17), making it approximately comparable to Wave 5. Specifically, we compare naïve vs. methodologically-comparable analyses (i.e. among youth with the same age range and survey mode) of changes in youth ENDS use prevalence and patterns of use over the prior 1 year (i.e., Waves 6–7, ~ 2021–2022) and 3 years (i.e. Waves 5–7, ~ 2019–2022). Methods Data PATH restricted-use files from youth Waves 5 (~ 2019; N = 11,976), 6 (~ 2021; N = 5,585), and 7 (~ 2022; N = 10,650) were analyzed. Wave 5.5 (~ 2020) was not included in the current analysis as it was 100% telephone interview, 7 making it fully incomparable with the other waves, as we previously reported. 6 Wave 7 included a replenishment sample and initiated a third survey mode, a web interview (administered to 3.1% of participants). This secondary data analysis was determined exempt from IRB oversight. Measures Prevalence of past 30-day ENDS use was assessed as any use of ENDS in the past 30 days (P30D). Patterns of ENDS use included frequency of use, device type, flavor, and brand. Frequency of ENDS use was derived from the number of days in P30D the participant reported using ENDS, and was categorized here as 1–5, 6–19, and 20 + days in P30D. Youth reporting P30D ENDS were asked to characterize the device type usually used as “disposable,” “replaceable filled cartridges” (pod/cartridge), “tank,” “mod,” or “something else.” Current analyses combined “mod” and “something else” into a single category due to low endorsement rates. The question structure changed from a single-choice (i.e. the device type used most often) to select-all-that-apply (i.e. any use of each device type, with those using more than one type asked which was used most often) starting in Wave 6. ENDS flavor was assessed as check-all-that-apply among youth reporting P30D ENDS use. Wave 5 assessed mint and menthol as a combined category, but these flavors were assessed separately at Waves 6 and 7. Usual/last-used ENDS brand is a PATH-derived variable that assesses usual brand among P30D users who have a usual brand, and last-used brand among those who do not have a usual brand (including those who used ENDS only once). We restricted analyses to the four most common brands at each wave, as well as “no regular brand” and “don’t know”/ “refused to answer.” Analyses P30D ENDS use prevalence and patterns of ENDS use were compared in the prior 1-year (i.e. Waves 6–7, ~ 2021–2022) and 3-year (i.e. Waves 5–7, ~ 2019–2022) periods, both naïvely (i.e. in the full youth sample from each wave, without accounting differences in age range and survey modes) as well as among the subgroup of youth who were comparable across all waves, i.e. youth aged 14–17 who self-administered the survey (Table 1 ). To examine how age-range differences may impact both point estimates and trends over time, interactions between age group (12–17 vs. 14–17) and wave were examined in those interviewed in-person; for these analyses, only the prior 3-year period (Waves 5–7) were analyzed, i.e. excluding Wave 6 which lacked the younger age group. SAS version 9.4 (Cary, NC) was used for all analyses and the provided single-wave weights were used with balanced repeated replication to account for the survey design and the presence of some respondents in more than one wave (HHS, 2022). Listwise deletion was used for missing data. Weighted frequencies are provided to estimate prevalences and Rao-Scott chi-square tests were used to compare differences in these across waves 5, 6 and 7. Logistic regression models were used to study the interaction of age and wave with least squares means used to estimate the prevalence controlling for the interaction. Because significance testing for ENDS flavor and brand was done as a series of dummy-coding (one response vs. all others), Bonferroni correction was applied to these p-values. Results The survey-mode and age-range differences primarily affect PATH Wave 6 (Table 1 ); since Wave 7 returned nearly entirely (~ 95%) to self-administration and the newly-enrolled replenishment sample restored the typical age range of 12–17, Waves 5 and 7 are approximately comparable with respect to these methodological differences. Table 1 Methodology Differences between PATH Waves 5 – 7. Wave 5 Wave 5.5 Wave 6 Wave 7 Dates of administration Dec 1, 2018 – Nov 30, 2019 July 3, 2020 – Dec 31, 2020 Mar 1, 2021 – Nov 31, 2021 Jan 6, 2022 – April 2, 2023 Survey mode Self-administered Telephone interview Web interview 100% 0% -- 0% 100% -- 33.9% 66.1% -- 95.1% 2.8% 3.1% Age range (years) 12–17 Not analyzed 14–17 12–17 Sample size (N) Full sample Comparable across waves: Age 14–17 and self-administered 11,976 8,797 Not analyzed 5,585 1,616 10,650 6,829 Note : Gray cells indicate that Wave 5.5 is not analyzed in detail due to incomparability with other waves (i.e. 0% self-administered). Prevalence of youth ENDS use Figure 1 shows the naïve vs. methodologically-comparable estimates of youth ENDS use prevalence and use patterns over Waves 5–7. Results showed a statistically-significant decline in P30D youth ENDS use over the prior 3 years for both the naïve (8.6–5.4%, p < 0.0001) and comparable-subgroup analyses (12.2–7.5%, p < 0.0001); we also previously reported a significant decline between Waves 5–6. 6 In the prior 1-year period (Waves 6–7), ENDS use prevalence declined, but not significantly, according to both analyses (naïve analysis: 5.9–5.4%, p = 0.1886; comparable-subgroup analysis: 8.5–7.5%, p = 0.1337). However, point estimates were considerably higher in the comparable-subgroup analysis at all time points. For the prevalence of ENDS use, the interaction between age and wave over the prior 3 years was significant (p < .0001). Specifically, youth aged 14–17 (vs. 12–13) had higher prevalence overall (Wave 5: 12.2% vs 1.2; Wave 7: 7.5% vs. 1.7%, p < .0001) and decreased their ENDS use over the prior 3 years (12.2–7.5%), while youth aged 12–13 showed a modest increase. Controlling for this interaction resulted in a net non-significant main effect of wave, p = 0.3214). Patterns of ENDS use Frequency of ENDS use did not significantly change over the prior 1-year or 3-year periods in either analysis and point estimates were generally similar across the naïve vs. comparable-subgroup analyses (differences of ~ 5.0 percentage points or less; same rank order of frequency groups). With respect to device type, there was a large shift over the prior 3 years away from pod/cartridge and tank devices and towards disposable devices, which largely occurred during the first of those 3 years (i.e. Waves 5–6), as previously reported. 8 Device type patterns were approximately stable over the prior 1 year in both the naïve and comparable-subgroup analyses (differences < 2.0 percentage points). Use of fruit- and candy/sweet-flavored ENDS were fairly consistent across all waves analyzed, reported by 70% and 33% of youth reporting P30D ENDS use, in both naïve and comparable-subgroup analyses. However, there were significant changes in the use of other flavors over the prior 3 years: use of menthol/mint significantly decreased (from ~ 55% to ~ 44%, in both naïve and comparable-subgroup analyses) and the use of tobacco flavor, which was uncommon, fell by approximately half (from ~ 10% to ~ 5%, p < .0001). These declines in use of menthol/mint and tobacco flavors appear to have continued over the prior 1 year, though the comparisons did not reach statistical significance, possibly due to lower sample size in Wave 6 (see Table 1 ). With respect to usual/last-used brand (Table 2 ), JUUL declined over the prior 3 years as reported previously 8 as Vuse, Hyde, and Puff Bar increased; brand use was similar over the 1 year prior to Wave 7. Neither brand prevalence nor changes over time were materially different across naïve vs. comparable-subgroup analyses. Additional interaction analyses examined how age-range differences may be associated with trends in patterns of use over the prior 3 years. For most flavors, there was no interaction between age range and wave, with the sole exception of tobacco flavor where the mean effects of age group and wave were significant as was their interaction (p < .05 for all with a Bonferroni correction of 5 flavor comparisons), reflecting the fact that the effect of age on use of tobacco-flavored ENDS varied by wave, while the effects on use of other flavors use did not. With respect to device type, an interaction of age range and wave was found only with trends in pod/cartridge ENDS products: while there was no main effect on use of cartridges overall (i.e. across waves), there was an interaction between age and wave ( p = 0.0055) such that youth aged 14–17 showed larger declines in use of cartridges over the prior 3 years (55.6–17.5%) than youth aged 12–13 (30.8% vs. 24.8%, respectively). Age was not significantly associated with prevalence or trends in other device types. Finally, with respect to JUUL as usual/last-used brand, there were strongly significant main effects of both age and wave as well as their interaction (p < .0001 for al) on estimates of JUUL as usual/last-used ENDS brand. Specifically, at Wave 5, youth aged 12–13 (vs. 14–17) were more likely to report JUUL as their usual/last-used brand (29.2% vs. 23.7%, respectively). However, in addition to an overall decline in use of JUUL as usual/last-used brand over the prior 3 years ( p < 0.0001), this age difference reversed in Wave 7 ( p < 0.0001 for interaction between age and wave), when no 12–13 year-olds reported JUUL use (vs. 5.4% of 14–17 year-olds). Table 2 Usual/last-used ENDS brand, naively and within comparable subgroups, PATH Waves 5–7. Wave 5 (~ 2019) Wave 6 (~ 2021) Wave 7 (~ 2022) p -value c,d (W5à7) p -value c,d (W6à7) Naïve analysis a No regular brand 62.4% 45.3% 44.2% NA NA Most common named brands JUUL: 23.9% Blu: 3.0% SMOK: 1.8% E-Swisher: 1.5% Hyde: 10.0% Vuse: 7.8% JUUL: 6.5% Puff: 9.3% Hyde: 12.1% Vuse: 6.1% JUUL: 4.8% Puff: 4.8% Hyde: NA Vuse: <0.0001 JUUL: <0.0001 Puff: NA Hyde: 0.4041 Vuse: 0.2746 JUUL: 0.2924 Puff: 0.0126 All other listed brands 1.9% 4.1% 5.6% NA NA Other brand (not listed) 3.2% 11.6% 10.8% < 0.0001 0.6954 Comparable subgroup b No regular brand 62.7% 51.3% 43.2% NA NA Most common named brands JUUL: 23.7% blu: 3.1% Smok: 1.9% Vuse: 0.4% Hyde: 12.5% Vuse: 9.4% JUUL: 7.8% Puff: 6.5% Hyde: 13.0% Vuse: 6.2% JUUL: 5.5% Puff: 5.1% Hyde: NA Vuse: <0.0001 JUUL: <0.0001 Puff: NA Hyde: 0.8863 Vuse: 0.2338 JUUL: 0.3579 Puff: 0.5216 All other listed brands 1.8% 2.4% 5.1% NA NA Other brand (not listed) 3.1% 3.7% 10.5% < 0.0001 0.0128 Notes : Gray cells indicate that Wave 5.5 is not analyzed due to incomparability with other waves (i.e. 0% self-administered). a: Naïve analysis includes all youth participants, regardless of methodological differences between waves. b: Comparable subgroup analysis includes only youth participants aged 14–17 who self-administered the survey. c: An overall significance test was not possible due to different lists of most common brands across waves; thus, separate significance tests were performed for each brand vs. all others. d: The alpha level for brand comparisons is 0.01, using a Bonferroni correction for 5 tests. Discussion This analysis extends previous analyses 6 documenting methodological artifacts in PATH that impact estimates of youth ENDS use prevalence, here focusing on the impact of Wave 6 youth being older than usual (14–17 vs. 12–17), in combination with the previously-reported survey-mode difference. Prevalence estimates of P30D ENDS use differ substantially between naïve analyses and comparable-subset analyses, with higher prevalence among self-interviewed and older (14–17) youth. In addition to age group having an effect on estimates of ENDS use prevalence, it also had an effect on age-specific trends (i.e., an interaction between age and wave) such that older youth showed larger declines over the prior 3 years. Methodological differences generally impacted patterns of ENDS use (including frequency of use, device type, flavors, and usual brand) to a lesser degree, in that both patterns of use and trends over time were similar across naïve vs. comparable-subgroup analyses. Age range did, however, impact both prevalence and trends in use of tobacco-flavored ENDS, use of JUUL as usual/last-used brand (such that 12-13-year-olds had larger declines in JUUL use over the prior 3 years), and use of pod/cartridge device types (such that 14-17-year-olds had larger declines in pod/cartridge use). These analyses are consistent with prior work in PATH 6 and NYTS 9 , 10 showing that COVID-related changes in survey methodology introduce artifacts that complicate comparisons across waves. The survey-mode artifact seems to be at least partly explained by social desirability bias, 6 , 9 as youth who interact with a live person to give their responses are less likely to report on sensitive behaviors including ENDS use. 11 , 12 The current analysis extends this work to highlight the impact of an age-range difference which further complicates prevalence comparisons, as Wave 6’s relative absence of younger participants (~ 12–13 years) who are less likely to use ENDS, may result in higher apparent prevalence, all else (including survey mode) being equal. On the other hand, patterns of ENDS use are not substantially impacted by methodological changes across waves, suggesting that among youth who use ENDS, those who are willing to disclose that behavior in the survey also go on to also report their detailed patterns of use in similar fashion. That is, social desirability may impact the initial reporting of ENDS use but does usually appear to bias responses to more detailed questions on patterns of use once the participant has initially disclosed ENDS use. A similar phenomenon may apply to age, whereby older youth (14–17 vs. 12–17) are more likely to use ENDS, but among those who do use ENDS, patterns of use are similar. There were some exceptions, notably use of tobacco flavor (but no other flavors), use of JUUL as usual/last-used brand (though other brands could not be evaluated), and use of pod/cartridge ENDS (but not other device types). The reason why age impacted prevalence and trends of these specific patterns of use is unclear, but could be due to the diversification of the ENDS market: younger youth (12–13) may have initiated after the proliferation of non-tobacco flavors and disposable devices, explaining their lower use of tobacco flavor and pod/cartridge ENDS (and accordingly, use of JUUL, a brand that sells pod/cartridge products) over the prior year. Similarly, migrating to flavors also explains the steeper decline in use of tobacco flavor and pod/cartridge devices among older youth (14–17). Trends in patterns of use over time are consistent with other sources. In particular, there has been a large shift away from pod/cartridge devices and towards disposable device types since 2020, 8 , 13 , 14 and the current analysis shows that this trend continues in PATH W7. Use of common brands has changed accordingly, i.e. away from JUUL in Wave 5 to Puff and Hyde in Waves 6 and 7 (brands that sell disposables). Use of fruit and candy/sweet flavors remains consistently high. Frequency continues to be bimodally distributed—with approximately 33–40% (across analyses) using frequently (i.e. 20 + days in P30D), just under half using on only 1–5 days per week, and few using on an intermediate number of days—consistent with youth use of nicotine/tobacco products in general. 15 Limitations include the self-reported nature of data, which may be inaccurate due to recall bias and (as discussed above) social desirability bias. Additionally, there is the possibility of a self-selection bias in the survey mode in Wave 6, as some participants who were eligible for in-person self-administered survey completion nevertheless elected a telephone interview. Unfortunately, there are no data indicating which telephone-interviewed participants elected vs. were assigned a telephone interview. Regardless of this possible self-selection, however, there remains a significant difference in ENDS use prevalence by survey mode that future research should take into account. Conclusions Methodological differences in survey mode and age range complicate comparisons of youth ENDS use prevalence in PATH Waves affected by COVID-related changes and, generally to a lesser extent, patterns of ENDS use (i.e., frequency of use, usual device type, flavors, and brands). Future analyses of PATH prevalence trends that include Waves 5.5 and 6 must account for survey mode and age; or alternatively, only directly compare Waves 5 and Wave 7, which are approximately equivalent. Declarations IRB : The corresponding author has confirmed the study was reviewed by the appropriate committee and the need for IRB was waived. Disclosures AS, SK, and MH are employes of Pinney Associates, Inc. (PA) and SS is an advisor to PA. Since October 2019, PA has been and continues to consult to Juul Labs on nicotine vapor products to advance tobacco harm reduction. JLI funded the preparation of this manuscript and reviewed a near-final copy. In addition, as of October 2024, PA consults to Philip Morris International (PMI) solely on US regulatory pathways for non-combustible, non-tobacco, nicotine products. PA does not consult on combustible tobacco products. AS also individually consults on behavioral science to the Center of Excellence for the Acceleration of Harm Reduction (CoEHAR) through ECLAT Srl, which received funding from the Foundation for a Smoke-Free World (FSFW; now the Global Action to End Smoking (GA)). Neither PMI, CoEHAR, nor FSFW/GA had any role in, or oversight of, this manuscript. References Park-Lee E, Jamal A, Cowan H, et al. Notes from the Field: E-Cigarette and Nicotine Pouch Use Among Middle and High School Students—United States, 2024. 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Jul 2022;117(7):2067-2074. doi:10.1111/add.15808 Selya A, Hannon MJ, Shiffman S. Youth use of electronic nicotine delivery systems (ENDS) in the Population Assessment of Tobacco and Health (PATH) Wave 6: Impact of survey mode. Addict Behav . Nov 2024;158:108124. doi:10.1016/j.addbeh.2024.108124 Health USDo, Abuse HSNIoHNIoD, Health USDo, Food HS, Products DACfT. Population Assessment of Tobacco and Health (PATH) Study [United States] Restricted-Use Files User Guide . 2024. Selya A, Shiffman S, Hannon MJ. Youth patterns of use of electronic nicotine delivery systems (ENDS), Population Assessment of Tobacco and Health (PATH) waves 4-5.5. Addict Behav . Oct 2023;145:107783. doi:10.1016/j.addbeh.2023.107783 Chen-Sankey J, Bover Manderski MT, Young WJ, Delnevo CD. Examining the Survey Setting Effect on Current E-Cigarette Use Estimates among High School Students in the 2021 National Youth Tobacco Survey. Int J Environ Res Public Health . May 26 2022;19(11)doi:10.3390/ijerph19116468 Park-Lee E, Gentzke AS, Ren C, et al. Impact of Survey Setting on Current Tobacco Product Use: National Youth Tobacco Survey, 2021. Journal of Adolescent Health . 2023;72(3):365-374. Tourangeau R, Yan T. Sensitive questions in surveys. Psychol Bull . Sep 2007;133(5):859-83. doi:10.1037/0033-2909.133.5.859 Yan T. Consequences of asking sensitive questions in surveys. Annual Review of Statistics and Its Application . 2021;8:109-127. Kasza KA, Hammond D, Reid JL, Rivard C, Hyland A. Youth Use of e-Cigarette Flavor and Device Combinations and Brands Before vs After FDA Enforcement. JAMA Netw Open . Aug 1 2023;6(8):e2328805. doi:10.1001/jamanetworkopen.2023.28805 McCauley DM, Gaiha SM, Lempert LK, Halpern-Felsher B. Adolescents, Young Adults, and Adults Continue to Use E-Cigarette Devices and Flavors Two Years after FDA Discretionary Enforcement. Int J Environ Res Public Health . Jul 18 2022;19(14)doi:10.3390/ijerph19148747 Villanti AC, Pearson JL, Glasser AM, et al. Frequency of Youth E-Cigarette and Tobacco Use Patterns in the United States: Measurement Precision Is Critical to Inform Public Health. Nicotine Tob Res . Nov 1 2017;19(11):1345-1350. doi:10.1093/ntr/ntw388 Additional Declarations The authors declare potential competing interests as follows: AS, SK, and MH are employes of Pinney Associates, Inc. (PA) and SS is an advisor to PA. Since October 2019, PA has been and continues to consult to Juul Labs on nicotine vapor products to advance tobacco harm reduction. JLI funded the preparation of this manuscript and reviewed a near-final copy. In addition, as of October 2024, PA consults to Philip Morris International (PMI) solely on US regulatory pathways for non-combustible, non-tobacco, nicotine products. PA does not consult on combustible tobacco products. AS also individually consults on behavioral science to the Center of Excellence for the Acceleration of Harm Reduction (CoEHAR) through ECLAT Srl, which received funding from the Foundation for a Smoke-Free World (FSFW; now the Global Action to End Smoking (GA)). Neither PMI, CoEHAR, nor FSFW/GA had any role in, or oversight of, this manuscript. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6264312","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":433371857,"identity":"660eaf25-f493-46c5-99ed-f4d5311bfa3a","order_by":0,"name":"Arielle Selya","email":"data:image/png;base64,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","orcid":"https://orcid.org/0000-0001-7026-6988","institution":"Pinney Associates, Inc.","correspondingAuthor":true,"prefix":"","firstName":"Arielle","middleName":"","lastName":"Selya","suffix":""},{"id":433371858,"identity":"1883bd24-9e7a-4eac-b649-b32f10845a59","order_by":1,"name":"Michael J. Hannon","email":"","orcid":"","institution":"Pinney Associates, Inc.","correspondingAuthor":false,"prefix":"","firstName":"Michael","middleName":"J.","lastName":"Hannon","suffix":""},{"id":433371859,"identity":"dbbc245c-7499-47ec-999d-585efbd1cb99","order_by":2,"name":"Sooyong Kim","email":"","orcid":"https://orcid.org/0000-0002-5131-5892","institution":"Pinney Associates, Inc.","correspondingAuthor":false,"prefix":"","firstName":"Sooyong","middleName":"","lastName":"Kim","suffix":""},{"id":433371860,"identity":"f7649956-bd5d-4e17-8904-f108903ba9bb","order_by":3,"name":"Saul Shiffman","email":"","orcid":"https://orcid.org/0000-0002-9639-490X","institution":"Pinney Associates, Inc.","correspondingAuthor":false,"prefix":"","firstName":"Saul","middleName":"","lastName":"Shiffman","suffix":""}],"badges":[],"createdAt":"2025-03-19 20:13:03","currentVersionCode":1,"declarations":{"humanSubjects":true,"vertebrateSubjects":false,"conflictsOfInterestStatement":true,"humanSubjectEthicalGuidelines":true,"humanSubjectConsent":true,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-6264312/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6264312/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":79326849,"identity":"fa987856-dbc5-44cc-abf9-e6aa806f0e50","added_by":"auto","created_at":"2025-03-27 05:39:36","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":966395,"visible":true,"origin":"","legend":"\u003cp\u003eYouth ENDS use prevalence and patterns of use, PATH Waves 5–7.\u003c/p\u003e","description":"","filename":"CompositeF1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6264312/v1/67de1b967674e32bcb14741d.jpg"},{"id":79328654,"identity":"4e8469ca-34f3-47d4-beaf-853861eb41b8","added_by":"auto","created_at":"2025-03-27 06:03:41","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1485184,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6264312/v1/3103d254-146c-41f4-9ab8-617843d22527.pdf"}],"financialInterests":"The authors declare potential competing interests as follows: AS, SK, and MH are employes of Pinney Associates, Inc. (PA) and SS is an advisor to PA. Since October 2019, PA has been and continues to consult to Juul Labs on nicotine vapor products to advance tobacco harm reduction. JLI funded the preparation of this manuscript and reviewed a near-final copy.\n\nIn addition, as of October 2024, PA consults to Philip Morris International (PMI) solely on US regulatory pathways for non-combustible, non-tobacco, nicotine products. PA does not consult on combustible tobacco products. AS also individually consults on behavioral science to the Center of Excellence for the Acceleration of Harm Reduction (CoEHAR) through ECLAT Srl, which received funding from the Foundation for a Smoke-Free World (FSFW; now the Global Action to End Smoking (GA)). Neither PMI, CoEHAR, nor FSFW/GA had any role in, or oversight of, this manuscript.\n","formattedTitle":"Methodology Differences Impacting Prevalence Estimates of Youth Use of Electronic Nicotine Delivery Systems (ENDS) across Waves 5-7 of the Population Assessment of Tobacco and Health","fulltext":[{"header":"Introduction","content":"\u003cp\u003eOngoing surveillance of youth use of nicotine and tobacco products is a public health priority, especially for the most commonly used product, electronic nicotine delivery systems (ENDS).\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e The nationally-representative Population Assessment of Tobacco and Health (PATH) survey\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e is a main source of data for research on nicotine and tobacco product behavior, including trends over time.\u003csup\u003e\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eAccordingly, accurate data analysis and interpretation of findings are paramount to the integrity of ongoing research on youth ENDS use. However, there are important methodological differences that complicate comparisons across waves of PATH. Specifically, we previously documented two methodological differences that impact youth ENDS use prevalence estimates in Waves 5.5 (~\u0026thinsp;2020) and 6 (~\u0026thinsp;2021): survey mode and age range.\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eRegarding survey mode differences, PATH is typically self-administered by participants in a secure home setting on a laptop with privacy and security features (through Wave 5, ~\u0026thinsp;2020), but due to COVID restrictions, this changed to telephone interviews during Wave 5.5 (~\u0026thinsp;2020; 100% telephone interview) and partly continued into Wave 6 (~\u0026thinsp;2021; approximately two-thirds telephone interviews).\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e Reported ENDS use was significantly lower in telephone interviews than in self-completed assessments, likely due in part to social desirability bias.\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e This survey-mode artifact has a substantial impact on the interpretation of youth ENDS use trends: a na\u0026iuml;ve comparison appears to show a large decline in ENDS use prevalence from Waves 5 to 5.5 followed by an uptick in Wave 6, but analyzing \u003cem\u003ewithin\u003c/em\u003e survey modes shows a more modest decline followed by a plateau.\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e That is, the interpretation of youth ENDS use trends \u003cem\u003equalitatively\u003c/em\u003e differs based on whether or not the survey-mode difference is accounted for.\u003c/p\u003e \u003cp\u003eRegarding differences in age range across waves, typically PATH samples participants aged 12\u0026ndash;17 for the youth survey.\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e As PATH is a longitudinal survey, most waves enroll new participants at the younger end of this age range to maintain a similar age range as previous participants age \u0026ndash; either through previously-sampled \u0026ldquo;shadow\u0026rdquo; youth or through the Wave 4 and 7 replenishment samples. However, there were very few newly-enrolled youth (~\u0026thinsp;12\u0026ndash;13 years) at Waves 5.5 and 6, resulting in an older minimum age (~\u0026thinsp;14\u0026ndash;17 years) of the youth sample compared to other waves.\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e This age difference likely introduces an artifact in estimates of youth ENDS use prevalence, as ENDS use is more common at older ages. That is, youth ENDS use prevalence estimates may be inflated for Waves 5.5 and 6 in analyses that are na\u0026iuml;ve to the age-range difference; it unknown whether this artifact could also impact \u003cem\u003epatterns\u003c/em\u003e of ENDS use (i.e., frequency, device type, flavor, and brand use).\u003c/p\u003e \u003cp\u003eIn our previous article documenting PATH\u0026rsquo;s survey mode artifact in Waves 5.5 and 6, we pointed out the \u003cem\u003eexistence\u003c/em\u003e of the age-range difference but were unable to examine its precise \u003cem\u003eimpact\u003c/em\u003e on prevalence estimates due to the lack of younger ages (12\u0026ndash;13 years) in these waves. The newly-released Wave 7 (~\u0026thinsp;2022) affords the opportunity to examine age-related changes in ENDS use prevalence, as it includes a replenishment sample that restores the full youth age range (12\u0026ndash;17), making it approximately comparable to Wave 5. Specifically, we compare na\u0026iuml;ve vs. methodologically-comparable analyses (i.e. among youth with the same age range and survey mode) of changes in youth ENDS use prevalence and patterns of use over the prior 1 year (i.e., Waves 6\u0026ndash;7, ~\u0026thinsp;2021\u0026ndash;2022) and 3 years (i.e. Waves 5\u0026ndash;7, ~\u0026thinsp;2019\u0026ndash;2022).\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData\u003c/h2\u003e \u003cp\u003ePATH restricted-use files from youth Waves 5 (~\u0026thinsp;2019; N\u0026thinsp;=\u0026thinsp;11,976), 6 (~\u0026thinsp;2021; N\u0026thinsp;=\u0026thinsp;5,585), and 7 (~\u0026thinsp;2022; N\u0026thinsp;=\u0026thinsp;10,650) were analyzed. Wave 5.5 (~\u0026thinsp;2020) was not included in the current analysis as it was 100% telephone interview,\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e making it fully incomparable with the other waves, as we previously reported.\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e Wave 7 included a replenishment sample and initiated a third survey mode, a web interview (administered to 3.1% of participants). This secondary data analysis was determined exempt from IRB oversight.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eMeasures\u003c/h3\u003e\n\u003cp\u003ePrevalence of past 30-day ENDS use was assessed as any use of ENDS in the past 30 days (P30D).\u003c/p\u003e \u003cp\u003ePatterns of ENDS use included frequency of use, device type, flavor, and brand. Frequency of ENDS use was derived from the number of days in P30D the participant reported using ENDS, and was categorized here as 1\u0026ndash;5, 6\u0026ndash;19, and 20\u0026thinsp;+\u0026thinsp;days in P30D.\u003c/p\u003e \u003cp\u003eYouth reporting P30D ENDS were asked to characterize the device type usually used as \u0026ldquo;disposable,\u0026rdquo; \u0026ldquo;replaceable filled cartridges\u0026rdquo; (pod/cartridge), \u0026ldquo;tank,\u0026rdquo; \u0026ldquo;mod,\u0026rdquo; or \u0026ldquo;something else.\u0026rdquo; Current analyses combined \u0026ldquo;mod\u0026rdquo; and \u0026ldquo;something else\u0026rdquo; into a single category due to low endorsement rates. The question structure changed from a single-choice (i.e. the device type used most often) to select-all-that-apply (i.e. any use of each device type, with those using more than one type asked which was used most often) starting in Wave 6.\u003c/p\u003e \u003cp\u003eENDS flavor was assessed as check-all-that-apply among youth reporting P30D ENDS use. Wave 5 assessed mint and menthol as a combined category, but these flavors were assessed separately at Waves 6 and 7.\u003c/p\u003e \u003cp\u003eUsual/last-used ENDS brand is a PATH-derived variable that assesses usual brand among P30D users who have a usual brand, and last-used brand among those who do not have a usual brand (including those who used ENDS only once). We restricted analyses to the four most common brands at each wave, as well as \u0026ldquo;no regular brand\u0026rdquo; and \u0026ldquo;don\u0026rsquo;t know\u0026rdquo;/ \u0026ldquo;refused to answer.\u0026rdquo;\u003c/p\u003e\n\u003ch3\u003eAnalyses\u003c/h3\u003e\n\u003cp\u003eP30D ENDS use prevalence and patterns of ENDS use were compared in the prior 1-year (i.e. Waves 6\u0026ndash;7, ~\u0026thinsp;2021\u0026ndash;2022) and 3-year (i.e. Waves 5\u0026ndash;7, ~\u0026thinsp;2019\u0026ndash;2022) periods, both na\u0026iuml;vely (i.e. in the full youth sample from each wave, without accounting differences in age range and survey modes) as well as among the subgroup of youth who were comparable across all waves, i.e. youth aged 14\u0026ndash;17 who self-administered the survey (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTo examine how age-range differences may impact both point estimates and trends over time, interactions between age group (12\u0026ndash;17 vs. 14\u0026ndash;17) and wave were examined in those interviewed in-person; for these analyses, only the prior 3-year period (Waves 5\u0026ndash;7) were analyzed, i.e. excluding Wave 6 which lacked the younger age group.\u003c/p\u003e \u003cp\u003eSAS version 9.4 (Cary, NC) was used for all analyses and the provided single-wave weights were used with balanced repeated replication to account for the survey design and the presence of some respondents in more than one wave (HHS, 2022). Listwise deletion was used for missing data. Weighted frequencies are provided to estimate prevalences and Rao-Scott chi-square tests were used to compare differences in these across waves 5, 6 and 7. Logistic regression models were used to study the interaction of age and wave with least squares means used to estimate the prevalence controlling for the interaction. Because significance testing for ENDS flavor and brand was done as a series of dummy-coding (one response vs. all others), Bonferroni correction was applied to these p-values.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eThe survey-mode and age-range differences primarily affect PATH Wave 6 (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e); since Wave 7 returned nearly entirely (~\u0026thinsp;95%) to self-administration and the newly-enrolled replenishment sample restored the typical age range of 12\u0026ndash;17, Waves 5 and 7 are approximately comparable with respect to these methodological differences.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMethodology Differences between PATH Waves 5\u003cem\u003e\u0026ndash;\u003c/em\u003e7.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWave 5\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWave 5.5\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eWave 6\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eWave 7\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDates of administration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDec 1, 2018 \u0026ndash;\u003c/p\u003e \u003cp\u003eNov 30, 2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eJuly 3, 2020 \u0026ndash;\u003c/p\u003e \u003cp\u003eDec 31, 2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMar 1, 2021 \u0026ndash;\u003c/p\u003e \u003cp\u003eNov 31, 2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eJan 6, 2022 \u0026ndash;\u003c/p\u003e \u003cp\u003eApril 2, 2023\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSurvey mode\u003c/p\u003e \u003cp\u003eSelf-administered\u003c/p\u003e \u003cp\u003eTelephone interview\u003c/p\u003e \u003cp\u003eWeb interview\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003cp\u003e0%\u003c/p\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003cp\u003e100%\u003c/p\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33.9%\u003c/p\u003e \u003cp\u003e66.1%\u003c/p\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e95.1%\u003c/p\u003e \u003cp\u003e2.8%\u003c/p\u003e \u003cp\u003e3.1%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge range (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12\u0026ndash;17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eNot analyzed\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14\u0026ndash;17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12\u0026ndash;17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSample size (N)\u003c/p\u003e \u003cp\u003eFull sample\u003c/p\u003e \u003cp\u003eComparable across waves: Age 14\u0026ndash;17 and self-administered\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11,976\u003c/p\u003e \u003cp\u003e8,797\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eNot analyzed\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5,585\u003c/p\u003e \u003cp\u003e1,616\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10,650\u003c/p\u003e \u003cp\u003e6,829\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003cem\u003eNote\u003c/em\u003e: Gray cells indicate that Wave 5.5 is not analyzed in detail due to incomparability with other waves (i.e. 0% self-administered).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003ePrevalence of youth ENDS use\u003c/h3\u003e\n\u003cp\u003eFigure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows the na\u0026iuml;ve vs. methodologically-comparable estimates of youth ENDS use prevalence and use patterns over Waves 5\u0026ndash;7. Results showed a statistically-significant decline in P30D youth ENDS use over the prior 3 years for both the na\u0026iuml;ve (8.6\u0026ndash;5.4%, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) and comparable-subgroup analyses (12.2\u0026ndash;7.5%, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001); we also previously reported a significant decline between Waves 5\u0026ndash;6.\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e In the prior 1-year period (Waves 6\u0026ndash;7), ENDS use prevalence declined, but not significantly, according to both analyses (na\u0026iuml;ve analysis: 5.9\u0026ndash;5.4%, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.1886; comparable-subgroup analysis: 8.5\u0026ndash;7.5%, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.1337). However, point estimates were considerably higher in the comparable-subgroup analysis at all time points.\u003c/p\u003e \u003cp\u003eFor the prevalence of ENDS use, the interaction between age and wave over the prior 3 years was significant (p\u0026thinsp;\u0026lt;\u0026thinsp;.0001). Specifically, youth aged 14\u0026ndash;17 (vs. 12\u0026ndash;13) had higher prevalence overall (Wave 5: 12.2% vs 1.2; Wave 7: 7.5% vs. 1.7%, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.0001) and decreased their ENDS use over the prior 3 years (12.2\u0026ndash;7.5%), while youth aged 12\u0026ndash;13 showed a modest increase. Controlling for this interaction resulted in a net non-significant main effect of wave, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.3214).\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003ePatterns of ENDS use\u003c/h2\u003e \u003cp\u003eFrequency of ENDS use did not significantly change over the prior 1-year or 3-year periods in either analysis and point estimates were generally similar across the na\u0026iuml;ve vs. comparable-subgroup analyses (differences of ~\u0026thinsp;5.0 percentage points or less; same rank order of frequency groups). With respect to device type, there was a large shift over the prior 3 years away from pod/cartridge and tank devices and towards disposable devices, which largely occurred during the first of those 3 years (i.e. Waves 5\u0026ndash;6), as previously reported.\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e Device type patterns were approximately stable over the prior 1 year in both the na\u0026iuml;ve and comparable-subgroup analyses (differences\u0026thinsp;\u0026lt;\u0026thinsp;2.0 percentage points). Use of fruit- and candy/sweet-flavored ENDS were fairly consistent across all waves analyzed, reported by 70% and 33% of youth reporting P30D ENDS use, in both na\u0026iuml;ve and comparable-subgroup analyses. However, there were significant changes in the use of other flavors over the prior 3 years: use of menthol/mint significantly decreased (from ~\u0026thinsp;55% to ~\u0026thinsp;44%, in both na\u0026iuml;ve and comparable-subgroup analyses) and the use of tobacco flavor, which was uncommon, fell by approximately half (from ~\u0026thinsp;10% to ~\u0026thinsp;5%, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.0001). These declines in use of menthol/mint and tobacco flavors appear to have continued over the prior 1 year, though the comparisons did not reach statistical significance, possibly due to lower sample size in Wave 6 (see Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWith respect to usual/last-used brand (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), JUUL declined over the prior 3 years as reported previously\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e as Vuse, Hyde, and Puff Bar increased; brand use was similar over the 1 year prior to Wave 7. Neither brand prevalence nor changes over time were materially different across na\u0026iuml;ve vs. comparable-subgroup analyses.\u003c/p\u003e \u003cp\u003eAdditional interaction analyses examined how age-range differences may be associated with trends in patterns of use over the prior 3 years. For most flavors, there was no interaction between age range and wave, with the sole exception of tobacco flavor where the mean effects of age group and wave were significant as was their interaction (p\u0026thinsp;\u0026lt;\u0026thinsp;.05 for all with a Bonferroni correction of 5 flavor comparisons), reflecting the fact that the effect of age on use of tobacco-flavored ENDS varied by wave, while the effects on use of other flavors use did not.\u003c/p\u003e \u003cp\u003eWith respect to device type, an interaction of age range and wave was found only with trends in pod/cartridge ENDS products: while there was no main effect on use of cartridges overall (i.e. across waves), there was an interaction between age and wave (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0055) such that youth aged 14\u0026ndash;17 showed larger declines in use of cartridges over the prior 3 years (55.6\u0026ndash;17.5%) than youth aged 12\u0026ndash;13 (30.8% vs. 24.8%, respectively). Age was not significantly associated with prevalence or trends in other device types.\u003c/p\u003e \u003cp\u003eFinally, with respect to JUUL as usual/last-used brand, there were strongly significant main effects of both age and wave as well as their interaction (p\u0026thinsp;\u0026lt;\u0026thinsp;.0001 for al) on estimates of JUUL as usual/last-used ENDS brand. Specifically, at Wave 5, youth aged 12\u0026ndash;13 (vs. 14\u0026ndash;17) were more likely to report JUUL as their usual/last-used brand (29.2% vs. 23.7%, respectively). However, in addition to an overall decline in use of JUUL as usual/last-used brand over the prior 3 years (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), this age difference reversed in Wave 7 (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001 for interaction between age and wave), when \u003cem\u003eno\u003c/em\u003e 12\u0026ndash;13 year-olds reported JUUL use (vs. 5.4% of 14\u0026ndash;17 year-olds).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eUsual/last-used ENDS brand, naively and within comparable subgroups, PATH Waves 5\u0026ndash;7.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWave 5\u003c/p\u003e \u003cp\u003e(~\u0026thinsp;2019)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eWave 6\u003c/p\u003e \u003cp\u003e(~\u0026thinsp;2021)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eWave 7\u003c/p\u003e \u003cp\u003e(~\u0026thinsp;2022)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003csup\u003ec,d\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(W5\u0026agrave;7)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003csup\u003ec,d\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(W6\u0026agrave;7)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eNa\u0026iuml;ve analysis\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo regular brand\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e62.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e45.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e44.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eNA\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eNA\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMost common named brands\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eJUUL: 23.9%\u003c/p\u003e \u003cp\u003eBlu: 3.0%\u003c/p\u003e \u003cp\u003eSMOK: 1.8%\u003c/p\u003e \u003cp\u003eE-Swisher: 1.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHyde: 10.0%\u003c/p\u003e \u003cp\u003eVuse: 7.8%\u003c/p\u003e \u003cp\u003eJUUL: 6.5%\u003c/p\u003e \u003cp\u003ePuff: 9.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHyde: 12.1%\u003c/p\u003e \u003cp\u003eVuse: 6.1%\u003c/p\u003e \u003cp\u003eJUUL: 4.8%\u003c/p\u003e \u003cp\u003ePuff: 4.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eHyde: \u003cem\u003eNA\u003c/em\u003e\u003c/p\u003e \u003cp\u003eVuse: \u0026lt;0.0001\u003c/p\u003e \u003cp\u003eJUUL: \u0026lt;0.0001\u003c/p\u003e \u003cp\u003ePuff: \u003cem\u003eNA\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eHyde: 0.4041\u003c/p\u003e \u003cp\u003eVuse: 0.2746\u003c/p\u003e \u003cp\u003eJUUL: 0.2924\u003c/p\u003e \u003cp\u003ePuff: 0.0126\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAll other listed brands\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eNA\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eNA\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOther brand (not listed)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.6954\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eComparable subgroup\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo regular brand\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e62.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e51.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e43.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eNA\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eNA\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMost common named brands\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eJUUL: 23.7%\u003c/p\u003e \u003cp\u003eblu: 3.1%\u003c/p\u003e \u003cp\u003eSmok: 1.9%\u003c/p\u003e \u003cp\u003eVuse: 0.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHyde: 12.5%\u003c/p\u003e \u003cp\u003eVuse: 9.4%\u003c/p\u003e \u003cp\u003eJUUL: 7.8%\u003c/p\u003e \u003cp\u003ePuff: 6.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHyde: 13.0%\u003c/p\u003e \u003cp\u003eVuse: 6.2%\u003c/p\u003e \u003cp\u003eJUUL: 5.5%\u003c/p\u003e \u003cp\u003ePuff: 5.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eHyde: \u003cem\u003eNA\u003c/em\u003e\u003c/p\u003e \u003cp\u003eVuse: \u0026lt;0.0001\u003c/p\u003e \u003cp\u003eJUUL: \u0026lt;0.0001\u003c/p\u003e \u003cp\u003ePuff: \u003cem\u003eNA\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eHyde: 0.8863\u003c/p\u003e \u003cp\u003eVuse: 0.2338\u003c/p\u003e \u003cp\u003eJUUL: 0.3579\u003c/p\u003e \u003cp\u003ePuff: 0.5216\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAll other listed brands\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eNA\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eNA\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOther brand (not listed)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.0128\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003cem\u003eNotes\u003c/em\u003e: Gray cells indicate that Wave 5.5 is not analyzed due to incomparability with other waves (i.e. 0% self-administered).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003ea: Na\u0026iuml;ve analysis includes all youth participants, regardless of methodological differences between waves.\u003c/p\u003e \u003cp\u003eb: Comparable subgroup analysis includes only youth participants aged 14\u0026ndash;17 who self-administered the survey.\u003c/p\u003e \u003cp\u003ec: An overall significance test was not possible due to different lists of most common brands across waves; thus, separate significance tests were performed for each brand vs. all others.\u003c/p\u003e \u003cp\u003ed: The alpha level for brand comparisons is 0.01, using a Bonferroni correction for 5 tests.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis analysis extends previous analyses\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e documenting methodological artifacts in PATH that impact estimates of youth ENDS use prevalence, here focusing on the impact of Wave 6 youth being older than usual (14\u0026ndash;17 vs. 12\u0026ndash;17), in combination with the previously-reported survey-mode difference. Prevalence estimates of P30D ENDS use differ substantially between na\u0026iuml;ve analyses and comparable-subset analyses, with higher prevalence among self-interviewed and older (14\u0026ndash;17) youth. In addition to age group having an effect on estimates of ENDS use prevalence, it also had an effect on age-specific trends (i.e., an interaction between age and wave) such that older youth showed larger declines over the prior 3 years. Methodological differences generally impacted \u003cem\u003epatterns\u003c/em\u003e of ENDS use (including frequency of use, device type, flavors, and usual brand) to a lesser degree, in that both patterns of use and trends over time were similar across na\u0026iuml;ve vs. comparable-subgroup analyses. Age range did, however, impact both prevalence and trends in use of tobacco-flavored ENDS, use of JUUL as usual/last-used brand (such that 12-13-year-olds had larger declines in JUUL use over the prior 3 years), and use of pod/cartridge device types (such that 14-17-year-olds had larger declines in pod/cartridge use).\u003c/p\u003e \u003cp\u003eThese analyses are consistent with prior work in PATH\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e and NYTS\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e showing that COVID-related changes in survey methodology introduce artifacts that complicate comparisons across waves. The survey-mode artifact seems to be at least partly explained by social desirability bias,\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e as youth who interact with a live person to give their responses are less likely to report on sensitive behaviors including ENDS use.\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e The current analysis extends this work to highlight the impact of an age-range difference which further complicates prevalence comparisons, as Wave 6\u0026rsquo;s relative absence of younger participants (~\u0026thinsp;12\u0026ndash;13 years) who are less likely to use ENDS, may result in higher apparent prevalence, all else (including survey mode) being equal.\u003c/p\u003e \u003cp\u003eOn the other hand, patterns of ENDS use are not substantially impacted by methodological changes across waves, suggesting that among youth who use ENDS, those who are willing to disclose that behavior in the survey also go on to also report their detailed patterns of use in similar fashion. That is, social desirability may impact the initial reporting of ENDS use but does usually appear to bias responses to more detailed questions on patterns of use once the participant has initially disclosed ENDS use.\u003c/p\u003e \u003cp\u003eA similar phenomenon may apply to age, whereby older youth (14\u0026ndash;17 vs. 12\u0026ndash;17) are more likely to use ENDS, but among those who do use ENDS, patterns of use are similar. There were some exceptions, notably use of tobacco flavor (but no other flavors), use of JUUL as usual/last-used brand (though other brands could not be evaluated), and use of pod/cartridge ENDS (but not other device types). The reason why age impacted prevalence and trends of these specific patterns of use is unclear, but could be due to the diversification of the ENDS market: younger youth (12\u0026ndash;13) may have initiated after the proliferation of non-tobacco flavors and disposable devices, explaining their lower use of tobacco flavor and pod/cartridge ENDS (and accordingly, use of JUUL, a brand that sells pod/cartridge products) over the prior year. Similarly, migrating to flavors also explains the steeper decline in use of tobacco flavor and pod/cartridge devices among older youth (14\u0026ndash;17).\u003c/p\u003e \u003cp\u003eTrends in patterns of use over time are consistent with other sources. In particular, there has been a large shift away from pod/cartridge devices and towards disposable device types since 2020,\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e and the current analysis shows that this trend continues in PATH W7. Use of common brands has changed accordingly, i.e. away from JUUL in Wave 5 to Puff and Hyde in Waves 6 and 7 (brands that sell disposables). Use of fruit and candy/sweet flavors remains consistently high. Frequency continues to be bimodally distributed\u0026mdash;with approximately 33\u0026ndash;40% (across analyses) using frequently (i.e. 20\u0026thinsp;+\u0026thinsp;days in P30D), just under half using on only 1\u0026ndash;5 days per week, and few using on an intermediate number of days\u0026mdash;consistent with youth use of nicotine/tobacco products in general.\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eLimitations include the self-reported nature of data, which may be inaccurate due to recall bias and (as discussed above) social desirability bias. Additionally, there is the possibility of a self-selection bias in the survey mode in Wave 6, as some participants who were eligible for in-person self-administered survey completion nevertheless elected a telephone interview. Unfortunately, there are no data indicating which telephone-interviewed participants elected vs. were assigned a telephone interview. Regardless of this possible self-selection, however, there remains a significant difference in ENDS use prevalence by survey mode that future research should take into account.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eMethodological differences in survey mode and age range complicate comparisons of youth ENDS use prevalence in PATH Waves affected by COVID-related changes and, generally to a lesser extent, \u003cem\u003epatterns\u003c/em\u003e of ENDS use (i.e., frequency of use, usual device type, flavors, and brands). Future analyses of PATH prevalence trends that include Waves 5.5 and 6 must account for survey mode and age; or alternatively, only directly compare Waves 5 and Wave 7, which are approximately equivalent.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cspan\u003e\u003cstrong\u003eIRB\u003c/strong\u003e: The corresponding author has confirmed the study was reviewed by the appropriate committee and the need for IRB was waived.\u003c/span\u003e\u003c/p\u003e\n\u003cstrong\u003eDisclosures\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAS, SK, and MH are employes of Pinney Associates, Inc. (PA) and SS is an advisor to PA. Since October 2019, PA has been and continues to consult to Juul Labs on nicotine vapor products to advance tobacco harm reduction. JLI funded the preparation of this manuscript and reviewed a near-final copy.\u003c/p\u003e\n\u003cp\u003eIn addition, as of October 2024, PA consults to Philip Morris International (PMI) solely on US regulatory pathways for non-combustible, non-tobacco, nicotine products. PA does not consult on combustible tobacco products. AS also individually consults on behavioral science to \u0026nbsp;the Center of Excellence for the Acceleration of Harm Reduction (CoEHAR) through ECLAT Srl, which received funding from the Foundation for a Smoke-Free World (FSFW; now the Global Action to End Smoking (GA)). Neither PMI, CoEHAR, nor FSFW/GA had any role in, or oversight of, this manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003ePark-Lee E, Jamal A, Cowan H, et al. Notes from the Field: E-Cigarette and Nicotine Pouch Use Among Middle and High School Students\u0026mdash;United States, 2024. \u003cem\u003eMMWR Morbidity and Mortality Weekly Report\u003c/em\u003e. 2024;73(35):774-778. doi:10.15585/mmwr.mm7335a3\u003c/li\u003e\n\u003cli\u003eHealth USDo, Abuse HSNIoHNIoD, Health USDo, Food HS, Products DACfT. Data from: Population Assessment of Tobacco and Health (PATH) Study [United States] Restricted-Use Files. 2024. doi:10.3886/ICPSR36231.v40\u003c/li\u003e\n\u003cli\u003eBrouwer AF, Jeon J, Jimenez-Mendoza E, et al. Changing patterns of cigarette and ENDS transitions in the USA: a multistate transition analysis of youth and adults in the PATH Study in 2015\u0026ndash;2017 vs 2017\u0026ndash;2019. \u003cem\u003eTobacco Control\u003c/em\u003e. 2023:tc-2022-057905. doi:10.1136/tc-2022-057905\u003c/li\u003e\n\u003cli\u003eStanton CA, Bansal-Travers M, Johnson AL, et al. Longitudinal e-Cigarette and Cigarette Use Among US Youth in the PATH Study (2013-2015). \u003cem\u003eJ Natl Cancer Inst\u003c/em\u003e. Oct 1 2019;111(10):1088-1096. doi:10.1093/jnci/djz006\u003c/li\u003e\n\u003cli\u003eSun R, Mendez D, Warner KE. Can PATH Study susceptibility measures predict e-cigarette and cigarette use among American youth 1 year later? \u003cem\u003eAddiction\u003c/em\u003e. Jul 2022;117(7):2067-2074. doi:10.1111/add.15808\u003c/li\u003e\n\u003cli\u003eSelya A, Hannon MJ, Shiffman S. Youth use of electronic nicotine delivery systems (ENDS) in the Population Assessment of Tobacco and Health (PATH) Wave 6: Impact of survey mode. \u003cem\u003eAddict Behav\u003c/em\u003e. Nov 2024;158:108124. doi:10.1016/j.addbeh.2024.108124\u003c/li\u003e\n\u003cli\u003eHealth USDo, Abuse HSNIoHNIoD, Health USDo, Food HS, Products DACfT. \u003cem\u003ePopulation Assessment of Tobacco and Health (PATH) Study [United States] Restricted-Use Files User Guide\u003c/em\u003e. 2024. \u003c/li\u003e\n\u003cli\u003eSelya A, Shiffman S, Hannon MJ. Youth patterns of use of electronic nicotine delivery systems (ENDS), Population Assessment of Tobacco and Health (PATH) waves 4-5.5. \u003cem\u003eAddict Behav\u003c/em\u003e. Oct 2023;145:107783. doi:10.1016/j.addbeh.2023.107783\u003c/li\u003e\n\u003cli\u003eChen-Sankey J, Bover Manderski MT, Young WJ, Delnevo CD. Examining the Survey Setting Effect on Current E-Cigarette Use Estimates among High School Students in the 2021 National Youth Tobacco Survey. \u003cem\u003eInt J Environ Res Public Health\u003c/em\u003e. May 26 2022;19(11)doi:10.3390/ijerph19116468\u003c/li\u003e\n\u003cli\u003ePark-Lee E, Gentzke AS, Ren C, et al. Impact of Survey Setting on Current Tobacco Product Use: National Youth Tobacco Survey, 2021. \u003cem\u003eJournal of Adolescent Health\u003c/em\u003e. 2023;72(3):365-374. \u003c/li\u003e\n\u003cli\u003eTourangeau R, Yan T. Sensitive questions in surveys. \u003cem\u003ePsychol Bull\u003c/em\u003e. Sep 2007;133(5):859-83. doi:10.1037/0033-2909.133.5.859\u003c/li\u003e\n\u003cli\u003eYan T. Consequences of asking sensitive questions in surveys. \u003cem\u003eAnnual Review of Statistics and Its Application\u003c/em\u003e. 2021;8:109-127. \u003c/li\u003e\n\u003cli\u003eKasza KA, Hammond D, Reid JL, Rivard C, Hyland A. Youth Use of e-Cigarette Flavor and Device Combinations and Brands Before vs After FDA Enforcement. \u003cem\u003eJAMA Netw Open\u003c/em\u003e. Aug 1 2023;6(8):e2328805. doi:10.1001/jamanetworkopen.2023.28805\u003c/li\u003e\n\u003cli\u003eMcCauley DM, Gaiha SM, Lempert LK, Halpern-Felsher B. Adolescents, Young Adults, and Adults Continue to Use E-Cigarette Devices and Flavors Two Years after FDA Discretionary Enforcement. \u003cem\u003eInt J Environ Res Public Health\u003c/em\u003e. Jul 18 2022;19(14)doi:10.3390/ijerph19148747\u003c/li\u003e\n\u003cli\u003eVillanti AC, Pearson JL, Glasser AM, et al. Frequency of Youth E-Cigarette and Tobacco Use Patterns in the United States: Measurement Precision Is Critical to Inform Public Health. \u003cem\u003eNicotine Tob Res\u003c/em\u003e. Nov 1 2017;19(11):1345-1350. doi:10.1093/ntr/ntw388\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Juul Labs, Inc.","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Behavior, electronic cigarettes, nicotine, prevalence, surveillance, youth","lastPublishedDoi":"10.21203/rs.3.rs-6264312/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6264312/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cu\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/u\u003e\u003cu\u003e:\u003c/u\u003eThe Population Assessment of Tobacco and Health (PATH) is a commonly-used longitudinal survey on nicotine/tobacco product use. Accurate surveillance to prevent youth use of electronic nicotine delivery systems (ENDS) requires understanding the impact of methodological differences in Wave 6 (~2021), specifically older ages (14–17 vs. usual 12–17) and survey mode (some telephone interviews vs. usual self-completed).\u003c/p\u003e\n\u003cp\u003e\u003cu\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/u\u003e\u003cu\u003e:\u003c/u\u003eChanges in past-30-day (P30D) youth ENDS prevalence and patterns of use (i.e., frequency, device type, flavors, and brand) were examined year-over-year and for the 3-year period (2019–2022) . Analyses compared combined age groups and survey modes (i.e. among all youth in each wave regardless of survey mode) with methodologically-comparable subgroups (i.e. same age range and survey mode). The impact of age on point estimates and trends (i.e. interaction with wave) was examined.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/u\u003e\u003cu\u003e:\u003c/u\u003eYouth P30D ENDS prevalence significantly declined over the prior 3 years, but not over the prior 1 year in either the naïve or methodologically-comparable analyses. However, 14-17-year olds reported higher prevalence and steeper declines (age-wave interaction \u003cem\u003ep\u003c/em\u003e\u0026lt;0.0001) over the past 3 years (12.2% to 7.5%) than 12-13-year olds (1.7% to 1.2%). Age differences had more modest impacts on \u003cem\u003epatterns\u003c/em\u003e of ENDS use.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003e\u003cstrong\u003eDiscussion\u003c/strong\u003e\u003c/u\u003e\u003cu\u003e:\u003c/u\u003eMethodological differences in PATH Wave 6 introduced artifacts in estimates of prevalence, and to a lesser extent, \u003cem\u003epatterns\u003c/em\u003e of youth ENDS use. Waves 5 and 7 are approximately comparable with respect to these differences. Future research examining prevalence trends over these waves should account for differences in survey mode and age range.\u003c/p\u003e","manuscriptTitle":"Methodology Differences Impacting Prevalence Estimates of Youth Use of Electronic Nicotine Delivery Systems (ENDS) across Waves 5-7 of the Population Assessment of Tobacco and Health","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-03-27 05:39:32","doi":"10.21203/rs.3.rs-6264312/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ebbef7b7-ed35-4005-a114-08de9c7a2c7e","owner":[],"postedDate":"March 27th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":46146168,"name":"Epidemiology"}],"tags":[],"updatedAt":"2025-03-27T05:39:32+00:00","versionOfRecord":[],"versionCreatedAt":"2025-03-27 05:39:32","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6264312","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6264312","identity":"rs-6264312","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}