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 作为评估消费者对新产品偏好的最新方法，离散选择实验 （DCE）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（例如警告和运动）。 与观察性调查数据相比，DCE的优点是提供有关新兴的敏捷证据 患病率低并预测潜在政策对行为的影响 在现实世界中实施。但是，它们在指导和捍卫FDA政策方面的潜力尚未完全 由于几个方法上的挑战而意识到。第一个挑战是烟草DCE缺乏一致性 设计和报告。研究人员通常采用不同的设计功能（例如，是否包括选择退出 选项）并在报告中采取不同的措施，例如支付意愿（WTP）与相对重要性得分。 因此，重要的是要审查当前实践，探索如何综合现有的DCE证据以及 未来DCE设计和报告的建议指南。第二个挑战是假设偏见 - 偏见 在陈述的偏好（SP）或“人们声称自己会做的事情”之间，并揭示了偏好（RP）或 “人们在现实世界中实际做的事情。”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）以减轻假设的偏见，为我们提供了重新审视现有DCE的独特机会 并提高其政策影响预测的准确性。该项目的总体目标是通知 FDA监管政策对使用现有DCE证据的烟草使用行为的影响。我们将进行 通过评估产品标准和消息传递开发的系统评价，以综合证据 政策重要性和WTP的排名。此外，我们将将现有DCE与Nielsen零售扫描仪相结合 数据和全国代表调查以减轻DCE中假设偏见的调查，这改善了 使用现有数据预测潜在监管政策的影响的准确性 实施了。具体目的是1）对操纵烟草DCE进行系统审查 产品属性。 2）对操纵产品消息的烟草DCE进行系统审查。 3） 结合陈述的偏见DCE，并揭示了Preference Real-World零售和调查数据，以预测 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的系统审查，进一步改善 DCE在预测政策影响方面的准确性。总而言之，该项目使用现有数据来解决优先级 RFA-OD-21-003的科学领域，包括烟草产品特征，通信实践和 烟草使用模式。