Studying the Impacts of Higher Taxes and Bans on Electronic Cigarettes to Improve Public Health
6 maja 2026 zaktualizowane przez: 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.
Przegląd badań
Status
Jeszcze nie rekrutacja
Warunki
Szczegółowy opis
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).
Typ studiów
Interwencyjne
Zapisy (Szacowany)
3400
Faza
- Nie dotyczy
Kontakty i lokalizacje
Ta sekcja zawiera dane kontaktowe osób prowadzących badanie oraz informacje o tym, gdzie badanie jest przeprowadzane.
Kontakt w sprawie studiów
- Nazwa: The Ohio State University Comprehensive Cancer Center
- Numer telefonu: 800-293-5066
- E-mail: OSUCCCClinicaltrials@osumc.edu
Lokalizacje studiów
-
-
Ohio
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Columbus, Ohio, Stany Zjednoczone, 43210
- Ohio State University Comprehensive Cancer Center
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Kontakt:
- Ce Shang, PhD
- Numer telefonu: 614-685-3741
- E-mail: ce.shang@osumc.edu
-
Główny śledczy:
- Ce Shang, PhD
-
-
Kryteria uczestnictwa
Badacze szukają osób, które pasują do określonego opisu, zwanego kryteriami kwalifikacyjnymi. Niektóre przykłady tych kryteriów to ogólny stan zdrowia danej osoby lub wcześniejsze leczenie.
Kryteria kwalifikacji
Wiek uprawniający do nauki
- Dziecko
- Dorosły
- Starszy dorosły
Akceptuje zdrowych ochotników
Tak
Opis
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
Plan studiów
Ta sekcja zawiera szczegółowe informacje na temat planu badania, w tym sposób zaprojektowania badania i jego pomiary.
Jak projektuje się badanie?
Szczegóły projektu
- Główny cel: Zapobieganie
- Przydział: Randomizowane
- Model interwencyjny: Zadanie sekwencyjne
- Maskowanie: Brak (otwarta etykieta)
Broń i interwencje
Grupa uczestników / Arm |
Interwencja / Leczenie |
|---|---|
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Eksperymentalny: 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).
|
Badania pomocnicze
Complete EC tax base, rate, nicotine level, and flavor VCEs
Inne nazwy:
Complete tiered tax condition VCEs
Inne nazwy:
Complete banned condition VCEs
Inne nazwy:
|
|
Eksperymentalny: 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).
|
Badania pomocnicze
Complete EC tax base, rate, nicotine level, and flavor VCEs
Inne nazwy:
Complete tiered tax condition VCEs
Inne nazwy:
Complete banned condition VCEs
Inne nazwy:
|
|
Eksperymentalny: 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).
|
Badania pomocnicze
Complete EC tax base, rate, nicotine level, and flavor VCEs
Inne nazwy:
Complete tiered tax condition VCEs
Inne nazwy:
Complete banned condition VCEs
Inne nazwy:
|
Co mierzy badanie?
Podstawowe miary wyniku
Miara wyniku |
Opis środka |
Ramy czasowe |
|---|---|---|
|
Electronic cigarette (EC) use among adolescent and young adult (AYA) current/susceptible users (Aim 1)
Ramy czasowe: 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)
Ramy czasowe: 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)
Ramy czasowe: 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)
Ramy czasowe: 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)
Ramy czasowe: 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)
Ramy czasowe: 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)
Ramy czasowe: 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)
Ramy czasowe: 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)
Ramy czasowe: 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)
Ramy czasowe: 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
|
Współpracownicy i badacze
Tutaj znajdziesz osoby i organizacje zaangażowane w to badanie.
Śledczy
- Główny śledczy: Ce Shang, PhD, Ohio State University Comprehensive Cancer Center
Publikacje i pomocne linki
Osoba odpowiedzialna za wprowadzenie informacji o badaniu dobrowolnie udostępnia te publikacje. Mogą one dotyczyć wszystkiego, co jest związane z badaniem.
Przydatne linki
Daty zapisu na studia
Daty te śledzą postęp w przesyłaniu rekordów badań i podsumowań wyników do ClinicalTrials.gov. Zapisy badań i zgłoszone wyniki są przeglądane przez National Library of Medicine (NLM), aby upewnić się, że spełniają określone standardy kontroli jakości, zanim zostaną opublikowane na publicznej stronie internetowej.
Główne daty studiów
Rozpoczęcie studiów (Szacowany)
1 sierpnia 2026
Zakończenie podstawowe (Szacowany)
31 grudnia 2027
Ukończenie studiów (Szacowany)
31 grudnia 2027
Daty rejestracji na studia
Pierwszy przesłany
6 maja 2026
Pierwszy przesłany, który spełnia kryteria kontroli jakości
6 maja 2026
Pierwszy wysłany (Rzeczywisty)
12 maja 2026
Aktualizacje rekordów badań
Ostatnia wysłana aktualizacja (Rzeczywisty)
12 maja 2026
Ostatnia przesłana aktualizacja, która spełniała kryteria kontroli jakości
6 maja 2026
Ostatnia weryfikacja
1 kwietnia 2026
Więcej informacji
Terminy związane z tym badaniem
Inne numery identyfikacyjne badania
- OSU-25157
- NCI-2026-02421 (Identyfikator rejestru: CTRP (Clinical Trial Reporting Program))
Informacje o lekach i urządzeniach, dokumenty badawcze
Bada produkt leczniczy regulowany przez amerykańską FDA
Nie
Bada produkt urządzenia regulowany przez amerykańską FDA
Nie
produkt wyprodukowany i wyeksportowany z USA
Nie
Te informacje zostały pobrane bezpośrednio ze strony internetowej clinicaltrials.gov bez żadnych zmian. Jeśli chcesz zmienić, usunąć lub zaktualizować dane swojego badania, skontaktuj się z register@clinicaltrials.gov. Gdy tylko zmiana zostanie wprowadzona na stronie clinicaltrials.gov, zostanie ona automatycznie zaktualizowana również na naszej stronie internetowej .