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The Science of Decision-Making: Connecting People and Policy

The Science of Decision-Making: Connecting People and Policy. Enhancing the Economic Impact Analysis Used in FDA’s Rules for Tobacco Products Frank J. Chaloupka. Aim 1. Aim 2. Aim 3. Impact of FDA regulatory actions and other tobacco control policies on tobacco use and related outcomes.

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The Science of Decision-Making: Connecting People and Policy

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  1. The Science of Decision-Making: Connecting People and Policy Enhancing the Economic Impact Analysis Used in FDA’s Rules for Tobacco Products Frank J. Chaloupka Aim 1 Aim 2 Aim 3 Impact of FDA regulatory actions and other tobacco control policies on tobacco use and related outcomes • Impact of FDA regulatory actions and other tobacco control policies on the consumer surplus obtained by tobacco users • Approach: Conduct an RCT to estimate the costs of behavioral biases neglected in past cost-benefit analyses of tobacco use • We will recruit 900 adult daily smokers from 10 cities through web-based panel. • Range of costs and benefits including in assessing the economic impact of FDA regulatory actions • Approach: • Conduct cost benefit analysis of reductions in secondhand smoke exposure • Incorporate benefits of reductions in maternal smoking during/after pregnancy • Assess long term benefits from reduced prevalence from tobacco use • Incorporate additional economic benefits Policies Bans on the Display of Tobacco Products Comprehensive Point-of-Sale Marketing Restrictions Graphic Warning Labels Bans on the Use of Flavoring in Cigarettes Bans of the Use of Descriptors Policies on Specifying Minimum Pack Sizes Smoking Status Quitting Initiation Substitution/Switching Consumption Approach: Estimate the impact of existing, possible, and future FDA regulatory actions and other tobacco control policies on tobacco use and related outcomes Aim 1 Aim 2 Acknowledgements • Randomized Control Trial: • Recruit 900 adult daily smokers from 10 cities through web-based panel. • Subjects will get cash incentives to be smoke-free in certain weeks, and will predict response to different-sized incentives. • The difference between predictions and quit behavior will be used to estimate parameters from a behavioral economics model. • Focus on present bias and projection bias Co-Investigators: Aim 1: Jidong Huang, Roy Wada, Ce Shang, UIC Aim 2: Justin White, Stanford, & Matt Levy, LSE Aim 3: Richard Peck & John Tauras, UIC A • Analyses (using a variety of data sources): • The impact on trajectories of tobacco use among young people and adults. • The differential impact of these actions on disparate populations. • The differential impact of regulatory actions and control policies on the use of traditional and emerging tobacco products, purchase behaviors, and related outcomes.

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