Predicting Adolescent Mental Health Outcomes Across Cultures: A Machine Learning Approach

• Main Authors: Rothenberg, W. Andrew, Bizzego, Andrea, Esposito, Gianluca, Lansford, Jennifer E., Al-Hassan, Suha M., Bacchini, Dario, Bornstein, Marc H., Chang, Lei, Deater-Deckard, Kirby, Di Giunta, Laura, Dodge, Kenneth A., Gurdal, Sevtap, Liu, Qin, Long, Qian, Oburu, Paul, Pastorelli, Concetta, Skinner, Ann T., Sorbring, Emma, Tapanya, Sombat, Steinberg, Laurence, Tirado, Liliana Maria Uribe, Yotanyamaneewong, Saengduean, Alampay, Liane Peña
• Format: text
• Published: Archīum Ateneo 2023
• Subjects: Adolescence; Externalizing; Internalizing; Machine learning; Parenting; Prediction; Psychology; Social and Behavioral Sciences
• Online Access: https://archium.ateneo.edu/psychology-faculty-pubs/437; https://doi.org/10.1007/s10964-023-01767-w
• Institution: Ateneo De Manila University

Adolescent mental health problems are rising rapidly around the world. To combat this rise, clinicians and policymakers need to know which risk factors matter most in predicting poor adolescent mental health. Theory-driven research has identified numerous risk factors that predict adolescent mental...