- ICH GCP
- Registr klinických studií v USA
- Klinická studie NCT07581041
Studying the Impacts of Higher Taxes and Bans on Electronic Cigarettes to Improve Public Health
Design Tiered Tax Rates for Electronic Cigarettes (ECs) Based on Their Appeals to Youth and Young Adults
Přehled studie
Postavení
Podmínky
Detailní popis
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 studie
Zápis (Odhadovaný)
Fáze
- Nelze použít
Kontakty a umístění
Studijní kontakt
- Jméno: The Ohio State University Comprehensive Cancer Center
- Telefonní číslo: 800-293-5066
- E-mail: OSUCCCClinicaltrials@osumc.edu
Studijní místa
-
-
Ohio
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Columbus, Ohio, Spojené státy, 43210
- Ohio State University Comprehensive Cancer Center
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Kontakt:
- Ce Shang, PhD
- Telefonní číslo: 614-685-3741
- E-mail: ce.shang@osumc.edu
-
Vrchní vyšetřovatel:
- Ce Shang, PhD
-
-
Kritéria účasti
Kritéria způsobilosti
Věk způsobilý ke studiu
- Dítě
- Dospělý
- Starší dospělý
Přijímá zdravé dobrovolníky
Popis
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
Studijní plán
Jak je studie koncipována?
Detaily designu
- Primární účel: Prevence
- Přidělení: Randomizované
- Intervenční model: Sekvenční přiřazení
- Maskování: Žádné (otevřený štítek)
Zbraně a zásahy
Skupina účastníků / Arm |
Intervence / Léčba |
|---|---|
|
Experimentální: 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).
|
Pomocná studia
Complete EC tax base, rate, nicotine level, and flavor VCEs
Ostatní jména:
Complete tiered tax condition VCEs
Ostatní jména:
Complete banned condition VCEs
Ostatní jména:
|
|
Experimentální: 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).
|
Pomocná studia
Complete EC tax base, rate, nicotine level, and flavor VCEs
Ostatní jména:
Complete tiered tax condition VCEs
Ostatní jména:
Complete banned condition VCEs
Ostatní jména:
|
|
Experimentální: 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).
|
Pomocná studia
Complete EC tax base, rate, nicotine level, and flavor VCEs
Ostatní jména:
Complete tiered tax condition VCEs
Ostatní jména:
Complete banned condition VCEs
Ostatní jména:
|
Co je měření studie?
Primární výstupní opatření
Měření výsledku |
Popis opatření |
Časové okno |
|---|---|---|
|
Electronic cigarette (EC) use among adolescent and young adult (AYA) current/susceptible users (Aim 1)
Časové okno: 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)
Časové okno: 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)
Časové okno: 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)
Časové okno: 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)
Časové okno: 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)
Časové okno: 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)
Časové okno: 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)
Časové okno: 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)
Časové okno: 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)
Časové okno: 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
|
Spolupracovníci a vyšetřovatelé
Vyšetřovatelé
- Vrchní vyšetřovatel: Ce Shang, PhD, Ohio State University Comprehensive Cancer Center
Publikace a užitečné odkazy
Užitečné odkazy
Termíny studijních záznamů
Hlavní termíny studia
Začátek studia (Odhadovaný)
Primární dokončení (Odhadovaný)
Dokončení studie (Odhadovaný)
Termíny zápisu do studia
První předloženo
První předloženo, které splnilo kritéria kontroly kvality
První zveřejněno (Aktuální)
Aktualizace studijních záznamů
Poslední zveřejněná aktualizace (Aktuální)
Odeslaná poslední aktualizace, která splnila kritéria kontroly kvality
Naposledy ověřeno
Více informací
Termíny související s touto studií
Další identifikační čísla studie
- OSU-25157
- NCI-2026-02421 (Identifikátor registru: CTRP (Clinical Trial Reporting Program))
Informace o lécích a zařízeních, studijní dokumenty
Studuje lékový produkt regulovaný americkým FDA
Studuje produkt zařízení regulovaný americkým úřadem FDA
produkt vyrobený a vyvážený z USA
Tyto informace byly beze změn načteny přímo z webu clinicaltrials.gov. Máte-li jakékoli požadavky na změnu, odstranění nebo aktualizaci podrobností studie, kontaktujte prosím register@clinicaltrials.gov. Jakmile bude změna implementována na clinicaltrials.gov, bude automaticky aktualizována i na našem webu .
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