Utilizing tobacco discrete choice experiments to predict the population impacts of FDA regulatory policies

利用烟草离散选择实验来预测 FDA 监管政策对人群的影响

• 批准号: 10679412
• 负责人: Ce Shang
• 金额: $ 22.68万
• 依托单位: OHIO STATE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-04-07 至 2025-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10679412
• 关键词: Address; Adopted; Adult; Area; Authorization documentation; Behavior; Calibration; Characteristics; Communication; Consumer Preferences; Data; Development; Elasticity; Electronic cigarette; Experimental Designs; Future; Goals; Guidelines; Health; Literature; Low Prevalence; Marketing; Measures; Meta-Analysis; Methodology; Methods; Motion; Nicotine; Oral; Pattern; Persons; Policies; Population; Price; Protocols documentation; Public Health; Regulation; Reporting; Research Personnel; Risk; Shapes; Smoking; Surveys; Tobacco; Tobacco use; United States Food and Drug Administration; Variant; Visit; Youth; addiction; authority; behavior prediction; combustible tobacco; design; electronic cigarette user; experimental study; heated tobacco products; improved; method development; non-smoker; preference; response; risk perception; systematic review; tobacco advertising; tobacco products; tobacco regulation; tobacco smokers; tool; willingness to pay; young adult

PROJECT SUMMARY As the state-of-the-art method to assess consumers’ preferences for new products, discrete choice experiments (DCEs) have been increasingly applied to study the impacts of potential policies on tobacco use behaviors, particularly in the areas of product standards and messaging development (e.g., warnings and campaigns). Compared to observational survey data, DCEs have the advantage of providing nimble evidence on emerging products with low prevalence and predicting the impacts of potential policies on behaviors before they are implemented in the real world. However, their potential in guiding and defending FDA policies has not been fully realized due to several methodological challenges. The first challenge is the lack of consistency in tobacco DCE design and reporting. Researchers often adopt different design features (e.g., whether to include an opt-out option) and use different measures in reporting, such as willingness to pay (WTP) vs. relative importance scores. Therefore, it is important to review current practices, explore how to synthesize existing DCE evidence, and propose guidelines for future DCE design and reporting. The second challenge is hypothetical bias – the bias between stated preferences (SP) or “what people claim that they would do” and revealed preferences (RP) or “what people actually do in the real world.” Recent method development has combined DCEs and RP data (e.g., retail and survey data) to mitigate hypothetical bias, providing us a unique opportunity to revisit existing DCEs and improve their accuracy in policy impact prediction. The overarching goal of this project is to inform the impact of FDA regulatory policies on tobacco use behaviors using existing DCE evidence. We will conduct systematic reviews to synthesize evidence on product standards and messaging development by assessing the ranking of policy importance and WTP. Moreover, we will combine existing DCEs with Nielsen Retail Scanner data and nationally representative surveys to mitigate the hypothetical bias in DCEs, which improves the accuracy of using existing data to predict the impact of potential regulatory policies that have not been implemented yet. The specific aims are to 1) Conduct a systematic review of tobacco DCEs manipulating product attributes. 2) Conduct a systematic review of tobacco DCEs manipulating product messaging. 3) Combine stated-preference DCEs and revealed-preference real-world retail and survey data to predict the impacts of FDA regulatory policies on product market shares and tobacco use. This project will provide the first systematic review of tobacco DCEs in the context of informing FDA regulatory policies, further improving the accuracy of DCE in predicting policy impacts. In summary, this project uses existing data to address priority scientific domains of RFA-OD-21-003, including tobacco product characteristics, communication practices, and tobacco use patterns.

项目摘要 离散选择实验作为评估消费者对新产品偏好的最新方法， （DCEs）已越来越多地用于研究潜在政策对烟草使用行为的影响， 特别是在产品标准和消息传递开发领域（例如，警告和活动）。 与观测调查数据相比，DCEs的优势在于为新兴的 低流行率的产品，并预测潜在政策对行为的影响， 在真实的世界中实现。然而，他们在指导和捍卫FDA政策方面的潜力尚未得到充分发挥。 这是由于一些方法上的挑战。第一个挑战是烟草DCE缺乏一致性 设计和报告。研究人员经常采用不同的设计特征（例如，是否包括选择退出 选项），并在报告中使用不同的措施，如支付意愿（WTP）与相对重要性分数。 因此，重要的是要审查目前的做法，探讨如何综合现有的DCE证据， 为未来的DCE设计和报告提出指导方针。第二个挑战是假设性偏见--偏见 在陈述偏好（SP）或“人们声称他们会做什么”和显示偏好（RP）之间， “人们在真实的世界中的所作所为”最近的方法开发已经结合了DCE和RP数据（例如， 零售和调查数据），以减轻假设性偏见，为我们提供了一个独特的机会，重新审视现有的DCE 提高政策影响预测的准确性。该项目的总体目标是告知 FDA监管政策对烟草使用行为的影响，使用现有的DCE证据。我们会进行 系统性审查，通过评估 政策重要性和支付意愿的排名。此外，我们还将联合收割机与尼尔森零售扫描仪相结合 数据和全国代表性的调查，以减轻假设偏差的DCE，这提高了 使用现有数据预测尚未实施的潜在监管政策的影响的准确性 尚未实施。具体目的是：1）对烟草DCE操作进行系统回顾 产品属性。2)对操纵产品信息的烟草DCE进行系统性审查。第三章 结合联合收割机的陈述偏好DCE和显示偏好的真实世界的零售和调查数据， FDA监管政策对产品市场份额和烟草使用的影响。该项目将提供第一个 在告知FDA监管政策的背景下对烟草DCE进行系统性审查，进一步改善 预测政策影响的准确性。总之，本项目利用现有数据， RFA-OD-21-003的科学领域，包括烟草产品特性、传播实践，以及 烟草使用模式