Could firearm suicide risk be predicted at the time of firearm purchase, creating an opportunity to help those at risk? 

In this issue: Could firearm suicide risk be predicted at the time of firearm purchase, creating an opportunity to help those at risk? 
 
Led by Dr. Hannah Laqueur, our colleagues set out to answer that question using machine learning, a type of artificial intelligence that uses mathematical models to identify patterns in data and make predictions. The resulting algorithm was able to forecast the likelihood of firearm suicide using handgun purchasing data. While the study was largely “proof of concept,” the results suggest the potential of utilizing firearm transaction records in identifying high-risk individuals to aid suicide prevention. 
 
September is Suicide Prevention month, and it’s an important time to recognize how preventable suicide is. Firearms are the most lethal means when it comes to suicide. Putting time and space between a suicidal person and guns through everyday safer storage practices and precautionary steps like temporary transfers can be the difference between life and death. Learn more about suicide and firearms on BulletPointsProject.org. 
 
In a crisis and for more resources, the 988 Suicide & Crisis Lifeline is available by calling or texting 988. Please save the number in your phone and share it with anyone who may need it.  

Other topics covered:

• New research on firearm purchasing characteristics, machine learning analysis of transaction records, gun-free zones, political violence, suicide prevention, racial capitalism, expections and perceived need for civil war, and extreme risk protection orders. 
• VPRP research featured by the CDC
• The BulletPoints Project's 2024 Train the Trainer Event: a virtual workshop on clinical firearm injury prevention

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