This study used a machine learning framework in conjunction with a large battery of measures from 9,718 school-age children (ages 9–11) from the Adolescent Brain Cognitive Development℠ (ABCD) Study to identify factors associated with fluid cognitive functioning (FCF), or the capacity to learn, solve problems, and adapt to novel situations.
The identified algorithm explained 14.74% of the variance in FCF, replicating previously reported socioeconomic and mental health contributors to FCF, and adding novel and potentially modifiable contributors, including extracurricular involvement, screen media activity, and sleep duration. Pragmatic interventions targeting these contributors may enhance cognitive performance and protect against their negative impact on FCF in children. (Publisher Abstract)
Downloads
Similar Publications
- The Possible Backfire Effects of Hot Spots Policing: An Experimental Assessment of Impacts on Legitimacy, Fear and Collective Efficacy
- Long-Term Memory in Adults Exposed to Childhood Violence: Remembering Genital Contact Nearly 20 Years Later
- Raman spectroscopic signature of vaginal fluid and its potential application in forensic body fluid identification