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

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...

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Publicado en:	Journal of Youth & Adolescence Vol. 52; no. 8; pp. 1595 - 1620
Autores principales:	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
Formato:	Artículo
Publicado:	Springer Nature Aug2023
Materias:	Mental illness risk factors Culture Adolescent health Teenagers' conduct of life Adolescence Machine learning Risk assessment Research funding Descriptive statistics Prediction models
Acceso en línea:	Ver este registro en EBSCOhost