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

6 maggio 2026 aggiornato da: 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.

Panoramica dello studio

Stato

Non ancora reclutamento

Condizioni

Intervento / Trattamento

Descrizione dettagliata

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).

Tipo di studio

Interventistico

Iscrizione (Stimato)

3400

Fase

  • Non applicabile

Contatti e Sedi

Questa sezione fornisce i recapiti di coloro che conducono lo studio e informazioni su dove viene condotto lo studio.

Contatto studio

Luoghi di studio

  • Stati Uniti
    • Ohio
      • Columbus, Ohio, Stati Uniti, 43210
        • Ohio State University Comprehensive Cancer Center
        • Contatto:
        • Investigatore principale:
          • Ce Shang, PhD

Criteri di partecipazione

I ricercatori cercano persone che corrispondano a una certa descrizione, chiamata criteri di ammissibilità. Alcuni esempi di questi criteri sono le condizioni generali di salute di una persona o trattamenti precedenti.

Criteri di ammissibilità

Età idonea allo studio

  • Bambino
  • Adulto
  • Adulto più anziano

Accetta volontari sani

Sì

Descrizione

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

Piano di studio

Questa sezione fornisce i dettagli del piano di studio, compreso il modo in cui lo studio è progettato e ciò che lo studio sta misurando.

Come è strutturato lo studio?

Dettagli di progettazione

  • Scopo principale: Prevenzione
  • Assegnazione: Randomizzato
  • Modello interventistico: Assegnazione sequenziale
  • Mascheramento: Nessuno (etichetta aperta)

Armi e interventi

Gruppo di partecipanti / Arm
Intervento / Trattamento
Sperimentale: 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).
Altro: Amministrazione del sondaggio
Studi accessori
Altro: Discrete Choice Study
Complete EC tax base, rate, nicotine level, and flavor VCEs
Altri nomi:
  • DCE
  • Discrete Choice Experiment
  • Discrete Choice Task
Altro: Discrete Choice Study
Complete tiered tax condition VCEs
Altri nomi:
  • DCE
  • Discrete Choice Experiment
  • Discrete Choice Task
Altro: Discrete Choice Study
Complete banned condition VCEs
Altri nomi:
  • DCE
  • Discrete Choice Experiment
  • Discrete Choice Task
Sperimentale: 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).
Altro: Amministrazione del sondaggio
Studi accessori
Altro: Discrete Choice Study
Complete EC tax base, rate, nicotine level, and flavor VCEs
Altri nomi:
  • DCE
  • Discrete Choice Experiment
  • Discrete Choice Task
Altro: Discrete Choice Study
Complete tiered tax condition VCEs
Altri nomi:
  • DCE
  • Discrete Choice Experiment
  • Discrete Choice Task
Altro: Discrete Choice Study
Complete banned condition VCEs
Altri nomi:
  • DCE
  • Discrete Choice Experiment
  • Discrete Choice Task
Sperimentale: 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).
Altro: Amministrazione del sondaggio
Studi accessori
Altro: Discrete Choice Study
Complete EC tax base, rate, nicotine level, and flavor VCEs
Altri nomi:
  • DCE
  • Discrete Choice Experiment
  • Discrete Choice Task
Altro: Discrete Choice Study
Complete tiered tax condition VCEs
Altri nomi:
  • DCE
  • Discrete Choice Experiment
  • Discrete Choice Task
Altro: Discrete Choice Study
Complete banned condition VCEs
Altri nomi:
  • DCE
  • Discrete Choice Experiment
  • Discrete Choice Task

Cosa sta misurando lo studio?

Misure di risultato primarie

Misura del risultato
Misura Descrizione
Lasso di tempo
Electronic cigarette (EC) use among adolescent and young adult (AYA) current/susceptible users (Aim 1)
Lasso di tempo: 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)
Lasso di tempo: 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)
Lasso di tempo: 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)
Lasso di tempo: 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)
Lasso di tempo: 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)
Lasso di tempo: 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)
Lasso di tempo: 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)
Lasso di tempo: 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)
Lasso di tempo: 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)
Lasso di tempo: 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

Collaboratori e investigatori

Qui è dove troverai le persone e le organizzazioni coinvolte in questo studio.

Sponsor

Ohio State University Comprehensive Cancer Center

Investigatori

  • Investigatore principale: Ce Shang, PhD, Ohio State University Comprehensive Cancer Center

Pubblicazioni e link utili

La persona responsabile dell'inserimento delle informazioni sullo studio fornisce volontariamente queste pubblicazioni. Questi possono riguardare qualsiasi cosa relativa allo studio.

Collegamenti utili

Studiare le date dei record

Queste date tengono traccia dell'avanzamento della registrazione dello studio e dell'invio dei risultati di sintesi a ClinicalTrials.gov. I record degli studi e i risultati riportati vengono esaminati dalla National Library of Medicine (NLM) per assicurarsi che soddisfino specifici standard di controllo della qualità prima di essere pubblicati sul sito Web pubblico.

Studia le date principali

Inizio studio (Stimato)

1 agosto 2026

Completamento primario (Stimato)

31 dicembre 2027

Completamento dello studio (Stimato)

31 dicembre 2027

Date di iscrizione allo studio

Primo inviato

6 maggio 2026

Primo inviato che soddisfa i criteri di controllo qualità

6 maggio 2026

Primo Inserito (Effettivo)

12 maggio 2026

Aggiornamenti dei record di studio

Ultimo aggiornamento pubblicato (Effettivo)

12 maggio 2026

Ultimo aggiornamento inviato che soddisfa i criteri QC

6 maggio 2026

Ultimo verificato

1 aprile 2026

Maggiori informazioni

Termini relativi a questo studio

Altri numeri di identificazione dello studio

  • OSU-25157
  • NCI-2026-02421 (Identificatore di registro: CTRP (Clinical Trial Reporting Program))

Informazioni su farmaci e dispositivi, documenti di studio

Studia un prodotto farmaceutico regolamentato dalla FDA degli Stati Uniti

No

Studia un dispositivo regolamentato dalla FDA degli Stati Uniti

No

prodotto fabbricato ed esportato dagli Stati Uniti

No

Queste informazioni sono state recuperate direttamente dal sito web clinicaltrials.gov senza alcuna modifica. In caso di richieste di modifica, rimozione o aggiornamento dei dettagli dello studio, contattare register@clinicaltrials.gov. Non appena verrà implementata una modifica su clinicaltrials.gov, questa verrà aggiornata automaticamente anche sul nostro sito web .

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Condizioni

Malattie rare

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Supplementi dietetici

Sponsor / Collaboratori

Sedi

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