American journal of preventive medicine
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Over 40,000 people die by suicide annually in the U.S., and firearms are the most lethal suicide method. There is limited evidence on the effectiveness of many state-level policies on reducing firearm suicide. The objective of this study was to identify public policies that best predict state-level firearm suicide rates. ⋯ On average, firearm suicide rates were lower in state-years that had each influential policy active. Notably, these analyses were ecological and noncausal. However, this study was able to use a supervised machine learning approach with inherent feature selection and many policy types to make predictions using unseen data (i.e., balancing Lasso and Ridge regularization penalties).