Studying the Impacts of Higher Taxes and Bans on Electronic Cigarettes to Improve Public Health
2026년 5월 6일 업데이트: 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.
연구 개요
상태
아직 모집하지 않음
정황
상세 설명
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).
연구 유형
중재적
등록 (추정된)
3400
단계
- 해당 없음
연락처 및 위치
이 섹션에서는 연구를 수행하는 사람들의 연락처 정보와 이 연구가 수행되는 장소에 대한 정보를 제공합니다.
연구 연락처
- 이름: The Ohio State University Comprehensive Cancer Center
- 전화번호: 800-293-5066
- 이메일: OSUCCCClinicaltrials@osumc.edu
연구 장소
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Ohio
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Columbus, Ohio, 미국, 43210
- Ohio State University Comprehensive Cancer Center
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연락하다:
- Ce Shang, PhD
- 전화번호: 614-685-3741
- 이메일: ce.shang@osumc.edu
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수석 연구원:
- Ce Shang, PhD
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참여기준
연구원은 적격성 기준이라는 특정 설명에 맞는 사람을 찾습니다. 이러한 기준의 몇 가지 예는 개인의 일반적인 건강 상태 또는 이전 치료입니다.
자격 기준
공부할 수 있는 나이
- 어린이
- 성인
- 고령자
건강한 자원 봉사자를 받아들입니다
예
설명
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
공부 계획
이 섹션에서는 연구 설계 방법과 연구가 측정하는 내용을 포함하여 연구 계획에 대한 세부 정보를 제공합니다.
연구는 어떻게 설계됩니까?
디자인 세부사항
- 주 목적: 방지
- 할당: 무작위
- 중재 모델: 순차적 할당
- 마스킹: 없음(오픈 라벨)
무기와 개입
참가자 그룹 / 팔 |
개입 / 치료 |
|---|---|
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실험적: 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).
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보조 연구
Complete EC tax base, rate, nicotine level, and flavor VCEs
다른 이름들:
Complete tiered tax condition VCEs
다른 이름들:
Complete banned condition VCEs
다른 이름들:
|
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실험적: 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).
|
보조 연구
Complete EC tax base, rate, nicotine level, and flavor VCEs
다른 이름들:
Complete tiered tax condition VCEs
다른 이름들:
Complete banned condition VCEs
다른 이름들:
|
|
실험적: 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).
|
보조 연구
Complete EC tax base, rate, nicotine level, and flavor VCEs
다른 이름들:
Complete tiered tax condition VCEs
다른 이름들:
Complete banned condition VCEs
다른 이름들:
|
연구는 무엇을 측정합니까?
주요 결과 측정
결과 측정 |
측정값 설명 |
기간 |
|---|---|---|
|
Electronic cigarette (EC) use among adolescent and young adult (AYA) current/susceptible users (Aim 1)
기간: 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.
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Up to 2 years
|
|
Combustible tobacco smoking among AYA current/susceptible users (Aim 1)
기간: 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)
기간: 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)
기간: 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)
기간: 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)
기간: 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)
기간: 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)
기간: 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)
기간: 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)
기간: 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
|
공동 작업자 및 조사자
여기에서 이 연구와 관련된 사람과 조직을 찾을 수 있습니다.
수사관
- 수석 연구원: Ce Shang, PhD, Ohio State University Comprehensive Cancer Center
간행물 및 유용한 링크
연구에 대한 정보 입력을 담당하는 사람이 자발적으로 이러한 간행물을 제공합니다. 이것은 연구와 관련된 모든 것에 관한 것일 수 있습니다.
유용한 링크
연구 기록 날짜
이 날짜는 ClinicalTrials.gov에 대한 연구 기록 및 요약 결과 제출의 진행 상황을 추적합니다. 연구 기록 및 보고된 결과는 공개 웹사이트에 게시되기 전에 특정 품질 관리 기준을 충족하는지 확인하기 위해 국립 의학 도서관(NLM)에서 검토합니다.
연구 주요 날짜
연구 시작 (추정된)
2026년 8월 1일
기본 완료 (추정된)
2027년 12월 31일
연구 완료 (추정된)
2027년 12월 31일
연구 등록 날짜
최초 제출
2026년 5월 6일
QC 기준을 충족하는 최초 제출
2026년 5월 6일
처음 게시됨 (실제)
2026년 5월 12일
연구 기록 업데이트
마지막 업데이트 게시됨 (실제)
2026년 5월 12일
QC 기준을 충족하는 마지막 업데이트 제출
2026년 5월 6일
마지막으로 확인됨
2026년 4월 1일
추가 정보
이 연구와 관련된 용어
기타 연구 ID 번호
- OSU-25157
- NCI-2026-02421 (레지스트리 식별자: CTRP (Clinical Trial Reporting Program))
약물 및 장치 정보, 연구 문서
미국 FDA 규제 의약품 연구
아니
미국 FDA 규제 기기 제품 연구
아니
미국에서 제조되어 미국에서 수출되는 제품
아니
이 정보는 변경 없이 clinicaltrials.gov 웹사이트에서 직접 가져온 것입니다. 귀하의 연구 세부 정보를 변경, 제거 또는 업데이트하도록 요청하는 경우 register@clinicaltrials.gov. 문의하십시오. 변경 사항이 clinicaltrials.gov에 구현되는 즉시 저희 웹사이트에도 자동으로 업데이트됩니다. .