Over the years, mental health challenges, particularly those of students, have increased, so the need to develop targeted diagnostic and treatment tools has increased. In view of substantial research that highlights the massive variation in symptomatic disorders in mental health, the effort to develop an intervention strategy can benefit from personal insight. The study studies the predictive capacity of random forest classification (RFC) to predict mental health risk scores in mental health data from Westborough High School. Our results show differences in mental health outcomes among different student groups and highlight the need for personalized interventions rather than a one-size-fits-all approach.

• This report represents the work of one or more WPI undergraduate students submitted to the faculty as evidence of completion of a degree requirement. WPI routinely publishes these reports on its website without editorial or peer review.

Creator

• Ammartayakun, Aukkawut

Subject

• Health
• Community
• Well-Being

Publisher

• Worcester Polytechnic Institute

Identifier

• 121533
• E-project-042424-145536

Advisor

• Nephew, Benjamin
• Lopez, Richard
• Korkin, Dmitry
• Rodriguez, Angela C Incollingo

Year

• 2024

UN Sustainable Development Goals

• 3 - Good Health and Well-being

Date created

• 2024-04-24

Resource type

• Interactive Qualifying Project

Source

• E-project-042424-145536

Rights statement

• In Copyright