Using random forest to identify correlates of depression symptoms among adolescents.

Mahmoodreza GohariAmanda DoggettKaren A PatteMark A FerroJoel A DubinCarla HilarioScott T Leatherdale

Published in: Social psychiatry and psychiatric epidemiology (2024)

This study highlights RF's utility in identifying important correlates of adolescent depressive symptoms. RF's natural hierarchy offers an advantage over traditional methods. The findings underscore the importance and additional potential of sleep health promotion and school belonging initiatives in preventing adolescent depression.

Keyphrases

depressive symptoms
sleep quality
health promotion
mental health
young adults
physical activity
social support
climate change
quality improvement
risk assessment
human health
high school