New AI method for public health analysis shows trends in substance use among high schoolers

Credit: Unsplash/CC0 Public Domain

High school students who have a large weekly allowance, friends who smoke and low levels of physical activity are more likely to use multiple substances over time. Conversely, being older, being Black and eating breakfast daily were factors associated with a smaller chance of transitioning to multiple use.

These conclusions were reached by a team of researchers at the University of Waterloo who used artificial intelligence to analyze a large, complex public health dataset—a novel way to approach public health analysis.

The study used machine learning instead of traditional statistical methods, allowing researchers to thoroughly assess multiple factors related to alcohol and other substance use patterns and transitions among Canadian high-school students over three time periods between 2016-19.

“Machine learning has advantages over traditional statistical methods,” said Helen Chen, a public health professor at…

Continue reading at MedicalExpress.com

About Medical Express

Medical Xpress is a web-based medical and health news service that is part of the renowned Science X network. Based on the years of experience as a Phys.org medical research channel, started in April 2011, Medical Xpress became a separate website. Branching out with Phys.org's monthly 2.5 million readership, Medical Xpress features the most comprehensive coverage in medical research and health news in the fields of neuroscience, cardiology, cancer, HIV/AIDS, psychology, psychiatry, dentistry, genetics, diseases and conditions, medications and more.

Leave a Reply

Your email address will not be published. Required fields are marked *