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

  • W. Andrew Rothenberg
  • , Andrea Bizzego
  • , Gianluca Esposito
  • , Jennifer E. Lansford
  • , Suha M. Al-Hassan
  • , Dario Bacchini
  • , Marc H. Bornstein
  • , Lei Chang
  • , Kirby Deater-Deckard
  • , Laura Di Giunta
  • , Kenneth A. Dodge
  • , Sevtap Gurdal
  • , Qin Liu
  • , Qian Long
  • , Paul Oburu
  • , Concetta Pastorelli
  • , Ann T. Skinner
  • , Emma Sorbring
  • , Sombat Tapanya
  • , Laurence Steinberg
  • Liliana Maria Uribe Tirado, Saengduean Yotanyamaneewong, Liane Peña Alampay
  • Duke University
  • University of Miami
  • Università degli Studi di Trento
  • Hashemite University
  • University of Naples “Federico II”
  • National Institute of Health
  • United Nations Childrens’ Fund (UNICEF)
  • University of Macau
  • University of Massachusetts Amherst
  • Università di Roma
  • University West
  • Chongqing Medical University
  • Duke Kunshan University
  • Maseno University
  • Chiang Mai University
  • Temple University
  • King Abdulaziz University
  • Universidad San Buenaventura

Research output: Contribution to journalArticlepeer-review

Original languageEnglish
Pages (from-to)1595-1619
Number of pages25
JournalJournal of Youth and Adolescence
Volume52
Issue number8
DOIs
StatePublished - Aug 2023

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

ASJC Scopus Subject Areas

  • Social Psychology
  • Education
  • Developmental and Educational Psychology
  • Social Sciences (miscellaneous)

Keywords

  • Adolescence
  • Externalizing
  • Internalizing
  • Machine learning
  • Parenting
  • Prediction

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