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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 conseque...

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Autores principales: Hardesty, Jeffrey J, Crespi, Elizabeth, Nian, Qinghua, Sinamo, Joshua K, Breland, Alison B, Eissenberg, Thomas, Welding, Kevin, Kennedy, Ryan David, Cohen, Joanna E
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10020901/
https://www.ncbi.nlm.nih.gov/pubmed/36862467
http://dx.doi.org/10.2196/38732
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author Hardesty, Jeffrey J
Crespi, Elizabeth
Nian, Qinghua
Sinamo, Joshua K
Breland, Alison B
Eissenberg, Thomas
Welding, Kevin
Kennedy, Ryan David
Cohen, Joanna E
author_facet Hardesty, Jeffrey J
Crespi, Elizabeth
Nian, Qinghua
Sinamo, Joshua K
Breland, Alison B
Eissenberg, Thomas
Welding, Kevin
Kennedy, Ryan David
Cohen, Joanna E
author_sort Hardesty, Jeffrey J
collection PubMed
description 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
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spelling pubmed-100209012023-03-18 The Vaping and Patterns of e-Cigarette Use Research Study: Protocol for a Web-Based Cohort Study Hardesty, Jeffrey J Crespi, Elizabeth Nian, Qinghua Sinamo, Joshua K Breland, Alison B Eissenberg, Thomas Welding, Kevin Kennedy, Ryan David Cohen, Joanna E JMIR Res Protoc Protocol 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 JMIR Publications 2023-03-02 /pmc/articles/PMC10020901/ /pubmed/36862467 http://dx.doi.org/10.2196/38732 Text en ©Jeffrey J Hardesty, Elizabeth Crespi, Qinghua Nian, Joshua K Sinamo, Alison B Breland, Thomas Eissenberg, Kevin Welding, Ryan David Kennedy, Joanna E Cohen. Originally published in JMIR Research Protocols (https://www.researchprotocols.org), 02.03.2023. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Research Protocols, is properly cited. The complete bibliographic information, a link to the original publication on https://www.researchprotocols.org, as well as this copyright and license information must be included.
spellingShingle Protocol
Hardesty, Jeffrey J
Crespi, Elizabeth
Nian, Qinghua
Sinamo, Joshua K
Breland, Alison B
Eissenberg, Thomas
Welding, Kevin
Kennedy, Ryan David
Cohen, Joanna E
The Vaping and Patterns of e-Cigarette Use Research Study: Protocol for a Web-Based Cohort Study
title The Vaping and Patterns of e-Cigarette Use Research Study: Protocol for a Web-Based Cohort Study
title_full The Vaping and Patterns of e-Cigarette Use Research Study: Protocol for a Web-Based Cohort Study
title_fullStr The Vaping and Patterns of e-Cigarette Use Research Study: Protocol for a Web-Based Cohort Study
title_full_unstemmed The Vaping and Patterns of e-Cigarette Use Research Study: Protocol for a Web-Based Cohort Study
title_short The Vaping and Patterns of e-Cigarette Use Research Study: Protocol for a Web-Based Cohort Study
title_sort vaping and patterns of e-cigarette use research study: protocol for a web-based cohort study
topic Protocol
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10020901/
https://www.ncbi.nlm.nih.gov/pubmed/36862467
http://dx.doi.org/10.2196/38732
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