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Predicting states of elevated negative affect in adolescents from smartphone sensors: a novel personalized machine learning approach.

Boyu RenEmma G BalkindBrianna PastroElana S IsraelDiego A PizzagalliHabiballah Rahimi-EichiJustin T BakerChristian A Webb
Published in: Psychological medicine (2022)
To the extent that smartphone data could provide reasonably accurate real-time predictions of states of high negative affect in teens, brief 'just-in-time' interventions could be immediately deployed via smartphone notifications or mental health apps to alleviate these states.
Keyphrases
  • mental health
  • machine learning
  • physical activity
  • young adults
  • big data
  • electronic health record
  • artificial intelligence
  • high resolution
  • data analysis