Studying the Impacts of Higher Taxes and Bans on Electronic Cigarettes to Improve Public Health
6 мая 2026 г. обновлено: Ce Shang, Ohio State University Comprehensive Cancer Center
Design Tiered Tax Rates for Electronic Cigarettes (ECs) Based on Their Appeals to Youth and Young Adults
This clinical trial studies whether imposing higher taxes and bans on electronic cigarettes (EC) with appealing features impacts tobacco use among current and susceptible adolescents and young adults (AYA) EC users and adults who use EC or are open to EC use.
ECs are currently the most popular form of nicotine or tobacco product in the United States.
Compared to burned cigarette products, ECs generally pose fewer short-term harms, making them a promising tool for lowering users' exposure to toxins and cancer-causing chemicals from smoking, promoting better public health outcomes.
However, evidence shows that EC marketing has increased overall initiation into nicotine use among AYAs, and that EC users are at a higher risk of becoming smokers, which could have negative public health outcomes.
Therefore, understanding the public health impact of EC use and regulation remains a major goal in tobacco control research.
This trial studies different scenarios which impose higher taxes or bans on ECs with appealing features.
Researchers hope that by studying participant responses to the different scenarios they may be able to identify which ones best discourage EC use among AYAs while promoting adult EC users to quit smoking, which may improve public health.
Обзор исследования
Статус
Еще не набирают
Условия
Подробное описание
PRIMARY OBJECTIVES:
I. Provide empirical evidence on how tiered EC taxes - imposing higher taxes on ECs with AYA appealing features - impact EC use, combustible tobacco use, and the prevalence of cross-border or illegal purchases.
II. Examine how tiered taxes on AYA-appealing features (flavors, product type, nicotine concentration) impact EC use and combustible tobacco smoking among current and susceptible AYA EC users. (Aim 1) III. Assess how tiered taxes on AYA-appealing features impact EC and combustible tobacco smoking among adult smokers who either use or are open to using ECs. (Aim 2) IV. Compare tiered EC taxes with sales bans on ECs with AYA-appealing features in terms of their impacts on tobacco use, cross-border shopping, and illegal EC purchases. (Aim 3)
OUTLINE: Participants are assigned to 1 of 3 aims.
AIMS 1 & 2: Participants complete volumetric choice experiments (VCEs) over 20 minutes on study with random assignment to: 1) Nicotine levels (low versus [vs.] high); 2) Flavors (fruit/sweet vs. ice vs. menthol/mint vs. tobacco); 3) EC tax bases (by product type vs. by flavor vs. by nicotine concentration), and 4) rate levels (status quo [equal rates] vs. 50% higher vs. 100% higher vs. 200% higher) among six different products (tanks, pods, disposables, cigarettes, cigars, and oral nicotine pouches [ONPs]) and opt-out options (none of the six products or quitting).
AIM 3: Participants are randomized to 1 of 2 groups.
GROUP 1: Participants complete VCEs over 20 minutes on study with random assignment to: 1) nicotine levels (low versus vs. high) and 2) flavors (fruit/sweet vs. ice vs. menthol/mint vs. tobacco) with optimal tiered tax conditions among four different products (preferred EC type, cigarettes, cigars, ONPs) and opt-out options (none of the six products or quitting).
GROUP 2: Participants complete VCEs over 20 minutes on study with random assignment to: 1) nicotine levels (low versus vs. high), 2) flavors (fruit/sweet vs. ice vs. menthol/mint vs. tobacco), and 3) purchasing sources (out-of-state legal vs. local/online illegal, vs. local legal) with banned conditions among four different products (preferred EC type, cigarettes, cigars, ONPs) and opt-out options (none of the six products or quitting).
Тип исследования
Интервенционный
Регистрация (Оцененный)
3400
Фаза
- Непригодный
Контакты и местонахождение
В этом разделе приведены контактные данные лиц, проводящих исследование, и информация о том, где проводится это исследование.
Контакты исследования
- Имя: The Ohio State University Comprehensive Cancer Center
- Номер телефона: 800-293-5066
- Электронная почта: OSUCCCClinicaltrials@osumc.edu
Места учебы
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Ohio
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Columbus, Ohio, Соединенные Штаты, 43210
- Ohio State University Comprehensive Cancer Center
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Контакт:
- Ce Shang, PhD
- Номер телефона: 614-685-3741
- Электронная почта: ce.shang@osumc.edu
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Главный следователь:
- Ce Shang, PhD
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-
Критерии участия
Исследователи ищут людей, которые соответствуют определенному описанию, называемому критериям приемлемости. Некоторыми примерами этих критериев являются общее состояние здоровья человека или предшествующее лечение.
Критерии приемлемости
Возраст, подходящий для обучения
- Ребенок
- Взрослый
- Пожилой взрослый
Принимает здоровых добровольцев
Да
Описание
Inclusion Criteria:
- AYAs aged 15-24 who are daily or nondaily users of ECs and are not smoking in the past 30 days
- AYA tobacco nonusers aged 15-24 who are susceptible to EC or tobacco use (i.e., curiosity about the product, intention to try it in the near future, and likely response if a best friend were to offer them the product)
- Adults aged 18+ who are daily or nondaily users of ECs and combustible tobacco in the past 30 days
- Adults aged 18+ who are daily or nondaily users of combustible tobacco in the past 30 days, not currently using ECs but are open to trying ECs
Учебный план
В этом разделе представлена подробная информация о плане исследования, в том числе о том, как планируется исследование и что оно измеряет.
Как устроено исследование?
Детали дизайна
- Основная цель: Профилактика
- Распределение: Рандомизированный
- Интервенционная модель: Последовательное назначение
- Маскировка: Нет (открытая этикетка)
Оружие и интервенции
Группа участников / Армия |
Вмешательство/лечение |
|---|---|
|
Экспериментальный: Aim 3 group 1 (tiered tax condition VCEs)
Participants complete VCEs over 20 minutes on study with random assignment to: 1) nicotine levels (low versus vs. high) and 2) flavors (fruit/sweet vs. ice vs. menthol/mint vs. tobacco) with optimal tiered tax conditions among four different products (preferred EC type, cigarettes, cigars, ONPs) and opt-out options (none of the six products or quitting).
|
Дополнительные исследования
Complete EC tax base, rate, nicotine level, and flavor VCEs
Другие имена:
Complete tiered tax condition VCEs
Другие имена:
Complete banned condition VCEs
Другие имена:
|
|
Экспериментальный: Aim 3 group 2 (banned condition VCEs)
Participants complete VCEs over 20 minutes on study with random assignment to: 1) nicotine levels (low versus vs. high), 2) flavors (fruit/sweet vs. ice vs. menthol/mint vs. tobacco), and 3) purchasing sources (out-of-state legal vs. local/online illegal, vs. local legal) with banned conditions among four different products (preferred EC type, cigarettes, cigars, ONPs) and opt-out options (none of the six products or quitting).
|
Дополнительные исследования
Complete EC tax base, rate, nicotine level, and flavor VCEs
Другие имена:
Complete tiered tax condition VCEs
Другие имена:
Complete banned condition VCEs
Другие имена:
|
|
Экспериментальный: Aims 1 & 2 (EC tax base and rate VCEs)
Participants complete VCEs over 20 minutes on study with random assignment to: 1) Nicotine levels (low vs. high); 2) Flavors (fruit/sweet vs. ice vs. menthol/mint vs. tobacco); 3) EC tax bases (by product type vs. by flavor vs. by nicotine concentration), and 4) rate levels (status quo [equal rates] vs. 50% higher vs. 100% higher vs. 200% higher) among six different products (tanks, pods, disposables, cigarettes, cigars, and oral nicotine pouches [ONPs]) and opt-out options (none of the six products or quitting).
|
Дополнительные исследования
Complete EC tax base, rate, nicotine level, and flavor VCEs
Другие имена:
Complete tiered tax condition VCEs
Другие имена:
Complete banned condition VCEs
Другие имена:
|
Что измеряет исследование?
Первичные показатели результатов
Мера результата |
Мера Описание |
Временное ограничение |
|---|---|---|
|
Electronic cigarette (EC) use among adolescent and young adult (AYA) current/susceptible users (Aim 1)
Временное ограничение: Up to 2 years
|
Will examine how tiered taxes on AYA-appealing features (flavors, product type, nicotine concentration) impact EC use among current and susceptible AYA EC users.
All hypotheses will be tested using regression analyses.
Will use count data models, such as the Negative Binomial model, the Poisson model, and Multiple Discrete-Continuous Extreme Value (MDCEV) Model.
Will use clustered sandwich estimators and consider mixed effects, random effects, and fixed effects in the modeling to account for the hierarchical structure (participant-choice set-purchase) and correlations among choices made by the same individual (repeated measures).
Analyses will also control for sociodemographic characteristics such as age, sex, race/ethnicity, income, education, tobacco use histories/status, and purchase expenditures.
|
Up to 2 years
|
|
Combustible tobacco smoking among AYA current/susceptible users (Aim 1)
Временное ограничение: Up to 2 years
|
Will examine how tiered taxes on AYA-appealing features (flavors, product type, nicotine concentration) impact combustible tobacco smoking among current and susceptible AYA EC users.
All hypotheses will be tested using regression analyses.
Will use count data models, such as the Negative Binomial model, the Poisson model, and MDCEV Model.
Will use clustered sandwich estimators and consider mixed effects, random effects, and fixed effects in the modeling to account for the hierarchical structure (participant-choice set-purchase) and correlations among choices made by the same individual (repeated measures).
Analyses will also control for sociodemographic characteristics such as age, sex, race/ethnicity, income, education, tobacco use histories/status, and purchase expenditures.
|
Up to 2 years
|
|
EC use among adult smokers who use or are open to ECs (Aim 2)
Временное ограничение: Up to 2 years
|
Will assess how tiered taxes on AYA-appealing features (flavors, product type, nicotine concentration) impact EC smoking among adult smokers who either use or are open to using ECs.
All hypotheses will be tested using regression analyses.
Will use count data models, such as the Negative Binomial model, the Poisson model, and MDCEV Model.
Will use clustered sandwich estimators and consider mixed effects, random effects, and fixed effects in the modeling to account for the hierarchical structure (participant-choice set-purchase) and correlations among choices made by the same individual (repeated measures).
Analyses will also control for sociodemographic characteristics such as age, sex, race/ethnicity, income, education, tobacco use histories/status, and purchase expenditures.
|
Up to 2 years
|
|
Combustible tobacco smoking among adult smokers who use or are open to ECs (Aim 2)
Временное ограничение: Up to 2 years
|
Will assess how tiered taxes on AYA-appealing features (flavors, product type, nicotine concentration) impact combustible tobacco smoking among adult smokers who either use or are open to using ECs.
All hypotheses will be tested using regression analyses.
Will use count data models, such as the Negative Binomial model, the Poisson model, and MDCEV Model.
Will use clustered sandwich estimators and consider mixed effects, random effects, and fixed effects in the modeling to account for the hierarchical structure (participant-choice set-purchase) and correlations among choices made by the same individual (repeated measures).
Analyses will also control for sociodemographic characteristics such as age, sex, race/ethnicity, income, education, tobacco use histories/status, and purchase expenditures.
|
Up to 2 years
|
|
Tobacco use among AYA EC current/susceptible users (Aim 3)
Временное ограничение: Up to 2 years
|
Will compare tiered EC taxes with sales bans on ECs with AYA-appealing features in terms of their impacts on tobacco use.
All hypotheses will be tested using regression analyses.
Will use count data models, such as the Negative Binomial model, the Poisson model, and MDCEV Model.
Will use clustered sandwich estimators and consider mixed effects, random effects, and fixed effects in the modeling to account for the hierarchical structure (participant-choice set-purchase) and correlations among choices made by the same individual (repeated measures).
Analyses will also control for sociodemographic characteristics such as age, sex, race/ethnicity, income, education, tobacco use histories/status, and purchase expenditures.
|
Up to 2 years
|
|
Cross-border shopping among AYA EC current/susceptible users (Aim 3)
Временное ограничение: Up to 2 years
|
Will compare tiered EC taxes with sales bans on ECs with AYA-appealing features in terms of their impacts on cross-border shopping.
In order to assess differences in the proportion of cross-border EC purchases between the two randomization groups, the occurrence of a cross-border EC purchase will be modeled as a binary variable.
All hypotheses will be tested using regression analyses.
Will use count data models, such as the Negative Binomial model, the Poisson model, and MDCEV Model.
Will use clustered sandwich estimators and consider mixed effects, random effects, and fixed effects in the modeling to account for the hierarchical structure (participant-choice set-purchase) and correlations among choices made by the same individual (repeated measures).
Analyses will also control for sociodemographic characteristics such as age, sex, race/ethnicity, income, education, tobacco use histories/status, and purchase expenditures.
|
Up to 2 years
|
|
Illegal EC purchases among AYA EC current/susceptible users (Aim 3)
Временное ограничение: Up to 2 years
|
Will compare tiered EC taxes with sales bans on ECs with AYA-appealing features in terms of their impacts on illegal EC purchases.
In order to assess differences in the proportion of illegal EC purchases between the two randomization groups, the occurrence of an illegal EC purchase will be modeled as a binary variable.
All hypotheses will be tested using regression analyses.
Will use count data models, such as the Negative Binomial model, the Poisson model, and MDCEV Model.
Will use clustered sandwich estimators and consider mixed effects, random effects, and fixed effects in the modeling to account for the hierarchical structure (participant-choice set-purchase) and correlations among choices made by the same individual (repeated measures).
Analyses will also control for sociodemographic characteristics such as age, sex, race/ethnicity, income, education, tobacco use histories/status, and purchase expenditures.
|
Up to 2 years
|
|
Tobacco use among adult smokers who use or are open to ECs (Aim 3)
Временное ограничение: Up to 3 years
|
Will compare tiered EC taxes with sales bans on ECs with AYA-appealing features in terms of their impacts on tobacco use.
All hypotheses will be tested using regression analyses.
Will use count data models, such as the Negative Binomial model, the Poisson model, and MDCEV Model.
Will use clustered sandwich estimators and consider mixed effects, random effects, and fixed effects in the modeling to account for the hierarchical structure (participant-choice set-purchase) and correlations among choices made by the same individual (repeated measures).
Analyses will also control for sociodemographic characteristics such as age, sex, race/ethnicity, income, education, tobacco use histories/status, and purchase expenditures.
|
Up to 3 years
|
|
Cross-border shopping among adult smokers who use or are open to ECs (Aim 3)
Временное ограничение: Up to 2 years
|
Will compare tiered EC taxes with sales bans on ECs with AYA-appealing features in terms of their impacts on cross-border shopping.
In order to assess differences in the proportion of cross-border EC purchases between the two randomization groups, the occurrence of a cross-border EC purchase will be modeled as a binary variable.
All hypotheses will be tested using regression analyses.
Will use count data models, such as the Negative Binomial model, the Poisson model, and MDCEV Model.
Will use clustered sandwich estimators and consider mixed effects, random effects, and fixed effects in the modeling to account for the hierarchical structure (participant-choice set-purchase) and correlations among choices made by the same individual (repeated measures).
Analyses will also control for sociodemographic characteristics such as age, sex, race/ethnicity, income, education, tobacco use histories/status, and purchase expenditures.
|
Up to 2 years
|
|
Illegal EC purchases among adult smokers who use or are open to ECs (Aim 3)
Временное ограничение: Up to 3 years
|
Will compare tiered EC taxes with sales bans on ECs with AYA-appealing features in terms of their impacts on illegal EC purchases.
In order to assess differences in the proportion of illegal EC purchases between the two randomization groups, the occurrence of an illegal EC purchase will be modeled as a binary variable.
All hypotheses will be tested using regression analyses.
Will use count data models, such as the Negative Binomial model, the Poisson model, and MDCEV Model.
Will use clustered sandwich estimators and consider mixed effects, random effects, and fixed effects in the modeling to account for the hierarchical structure (participant-choice set-purchase) and correlations among choices made by the same individual (repeated measures).
Analyses will also control for sociodemographic characteristics such as age, sex, race/ethnicity, income, education, tobacco use histories/status, and purchase expenditures.
|
Up to 3 years
|
Соавторы и исследователи
Здесь вы найдете людей и организации, участвующие в этом исследовании.
Следователи
- Главный следователь: Ce Shang, PhD, Ohio State University Comprehensive Cancer Center
Публикации и полезные ссылки
Лицо, ответственное за внесение сведений об исследовании, добровольно предоставляет эти публикации. Это может быть что угодно, связанное с исследованием.
Полезные ссылки
Даты записи исследования
Эти даты отслеживают ход отправки отчетов об исследованиях и сводных результатов на сайт ClinicalTrials.gov. Записи исследований и сообщаемые результаты проверяются Национальной медицинской библиотекой (NLM), чтобы убедиться, что они соответствуют определенным стандартам контроля качества, прежде чем публиковать их на общедоступном веб-сайте.
Изучение основных дат
Начало исследования (Оцененный)
1 августа 2026 г.
Первичное завершение (Оцененный)
31 декабря 2027 г.
Завершение исследования (Оцененный)
31 декабря 2027 г.
Даты регистрации исследования
Первый отправленный
6 мая 2026 г.
Впервые представлено, что соответствует критериям контроля качества
6 мая 2026 г.
Первый опубликованный (Действительный)
12 мая 2026 г.
Обновления учебных записей
Последнее опубликованное обновление (Действительный)
12 мая 2026 г.
Последнее отправленное обновление, отвечающее критериям контроля качества
6 мая 2026 г.
Последняя проверка
1 апреля 2026 г.
Дополнительная информация
Термины, связанные с этим исследованием
Другие идентификационные номера исследования
- OSU-25157
- NCI-2026-02421 (Идентификатор реестра: CTRP (Clinical Trial Reporting Program))
Информация о лекарствах и устройствах, исследовательские документы
Изучает лекарственный продукт, регулируемый FDA США.
Нет
Изучает продукт устройства, регулируемый Управлением по санитарному надзору за качеством пищевых продуктов и медикаментов США.
Нет
продукт, произведенный в США и экспортированный из США.
Нет
Эта информация была получена непосредственно с веб-сайта clinicaltrials.gov без каких-либо изменений. Если у вас есть запросы на изменение, удаление или обновление сведений об исследовании, обращайтесь по адресу register@clinicaltrials.gov. Как только изменение будет реализовано на clinicaltrials.gov, оно будет автоматически обновлено и на нашем веб-сайте. .