What happens when you open up mental health data to the global data science community? In this episode, host Logan Lawler talks with Gregory Kiar and Arianna Zuanazzi from the Child Mind Institute about a recent Kaggle competition that explored how physical health metrics—like sleep and activity—can predict problematic internet use in kids and teens.

Greg, a research scientist and director of the Center for Data Analytics, Innovation, and Rigor, shares how they handle messy, real-world data to generate insights that matter. Arianna, who leads open science and data collaboration efforts, explains why involving people outside of academia leads to better questions and better science. They break down the competition structure, the surprising role of sleep data, and why overfitting results can lead to real-world consequences. They also talk about the challenges of working with human-generated data, and how competitions like this inform future research and care.

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