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Studying the Impacts of Higher Taxes and Bans on Electronic Cigarettes to Improve Public Health

6. maj 2026 opdateret af: 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.

Studieoversigt

Status

Ikke rekrutterer endnu

Betingelser

Intervention / Behandling

Detaljeret beskrivelse

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).

Undersøgelsestype

Interventionel

Tilmelding (Anslået)

3400

Fase

  • Ikke anvendelig

Kontakter og lokationer

Dette afsnit indeholder kontaktoplysninger for dem, der udfører undersøgelsen, og oplysninger om, hvor denne undersøgelse udføres.

Studiekontakt

Studiesteder

  • Forenede Stater
    • Ohio
      • Columbus, Ohio, Forenede Stater, 43210
        • Ohio State University Comprehensive Cancer Center
        • Kontakt:
        • Ledende efterforsker:
          • Ce Shang, PhD

Deltagelseskriterier

Forskere leder efter personer, der passer til en bestemt beskrivelse, kaldet berettigelseskriterier. Nogle eksempler på disse kriterier er en persons generelle helbredstilstand eller tidligere behandlinger.

Berettigelseskriterier

Aldre berettiget til at studere

  • Barn
  • Voksen
  • Ældre voksen

Tager imod sunde frivillige

Ja

Beskrivelse

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

Studieplan

Dette afsnit indeholder detaljer om studieplanen, herunder hvordan undersøgelsen er designet, og hvad undersøgelsen måler.

Hvordan er undersøgelsen tilrettelagt?

Design detaljer

  • Primært formål: Forebyggelse
  • Tildeling: Randomiseret
  • Interventionel model: Sekventiel tildeling
  • Maskning: Ingen (Åben etiket)

Våben og indgreb

Deltagergruppe / Arm
Intervention / Behandling
Eksperimentel: 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).
Andet: Undersøgelsesadministration
Hjælpestudier
Andet: Discrete Choice Study
Complete EC tax base, rate, nicotine level, and flavor VCEs
Andre navne:
  • DCE
  • Discrete Choice Experiment
  • Discrete Choice Task
Andet: Discrete Choice Study
Complete tiered tax condition VCEs
Andre navne:
  • DCE
  • Discrete Choice Experiment
  • Discrete Choice Task
Andet: Discrete Choice Study
Complete banned condition VCEs
Andre navne:
  • DCE
  • Discrete Choice Experiment
  • Discrete Choice Task
Eksperimentel: 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).
Andet: Undersøgelsesadministration
Hjælpestudier
Andet: Discrete Choice Study
Complete EC tax base, rate, nicotine level, and flavor VCEs
Andre navne:
  • DCE
  • Discrete Choice Experiment
  • Discrete Choice Task
Andet: Discrete Choice Study
Complete tiered tax condition VCEs
Andre navne:
  • DCE
  • Discrete Choice Experiment
  • Discrete Choice Task
Andet: Discrete Choice Study
Complete banned condition VCEs
Andre navne:
  • DCE
  • Discrete Choice Experiment
  • Discrete Choice Task
Eksperimentel: 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).
Andet: Undersøgelsesadministration
Hjælpestudier
Andet: Discrete Choice Study
Complete EC tax base, rate, nicotine level, and flavor VCEs
Andre navne:
  • DCE
  • Discrete Choice Experiment
  • Discrete Choice Task
Andet: Discrete Choice Study
Complete tiered tax condition VCEs
Andre navne:
  • DCE
  • Discrete Choice Experiment
  • Discrete Choice Task
Andet: Discrete Choice Study
Complete banned condition VCEs
Andre navne:
  • DCE
  • Discrete Choice Experiment
  • Discrete Choice Task

Hvad måler undersøgelsen?

Primære resultatmål

Resultatmål
Foranstaltningsbeskrivelse
Tidsramme
Electronic cigarette (EC) use among adolescent and young adult (AYA) current/susceptible users (Aim 1)
Tidsramme: 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)
Tidsramme: 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)
Tidsramme: 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)
Tidsramme: 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)
Tidsramme: 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)
Tidsramme: 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)
Tidsramme: 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)
Tidsramme: 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)
Tidsramme: 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)
Tidsramme: 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

Samarbejdspartnere og efterforskere

Det er her, du vil finde personer og organisationer, der er involveret i denne undersøgelse.

Sponsor

Ohio State University Comprehensive Cancer Center

Efterforskere

  • Ledende efterforsker: Ce Shang, PhD, Ohio State University Comprehensive Cancer Center

Publikationer og nyttige links

Den person, der er ansvarlig for at indtaste oplysninger om undersøgelsen, leverer frivilligt disse publikationer. Disse kan handle om alt relateret til undersøgelsen.

Hjælpsomme links

Datoer for undersøgelser

Disse datoer sporer fremskridtene for indsendelser af undersøgelsesrekord og resumeresultater til ClinicalTrials.gov. Studieregistreringer og rapporterede resultater gennemgås af National Library of Medicine (NLM) for at sikre, at de opfylder specifikke kvalitetskontrolstandarder, før de offentliggøres på den offentlige hjemmeside.

Studer store datoer

Studiestart (Anslået)

1. august 2026

Primær færdiggørelse (Anslået)

31. december 2027

Studieafslutning (Anslået)

31. december 2027

Datoer for studieregistrering

Først indsendt

6. maj 2026

Først indsendt, der opfyldte QC-kriterier

6. maj 2026

Først opslået (Faktiske)

12. maj 2026

Opdateringer af undersøgelsesjournaler

Sidste opdatering sendt (Faktiske)

12. maj 2026

Sidste opdatering indsendt, der opfyldte kvalitetskontrolkriterier

6. maj 2026

Sidst verificeret

1. april 2026

Mere information

Begreber relateret til denne undersøgelse

Andre undersøgelses-id-numre

  • OSU-25157
  • NCI-2026-02421 (Registry Identifier: CTRP (Clinical Trial Reporting Program))

Lægemiddel- og udstyrsoplysninger, undersøgelsesdokumenter

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Betingelser

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