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Mental Health Predicts Better Academic Outcomes: A Longitudinal Study of Elementary School Students in Chile

Abstract

The world’s largest school-based mental health program, Habilidades para la Vida [Skills for Life (SFL)], has been operating on a national scale in Chile for 15 years. SFL’s activities include using standardized measures to screen elementary school students and providing preventive workshops to students at risk for mental health problems. This paper used SFL’s data on 37,397 students who were in first grade in 2009 and third grade in 2011 to ascertain whether first grade mental health predicted subsequent academic achievement and whether remission of mental health problems predicted improved academic outcomes. Results showed that mental health was a significant predictor of future academic performance and that, overall, students whose mental health improved between first and third grade made better academic progress than students whose mental health did not improve or worsened. Our findings suggest that school-based mental health programs like SFL may help improve students’ academic outcomes.

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Notes

  1. 1.

    Covariates were first grade variables of percent attendance, gender, family participation in welfare, school identification number, whether the mother was a teenager when the child was born, whether the father was living with the child, whether the child had a chronic illness leading to one or more school absences a month, whether the child was living with a relative disabled by mental illness, and whether the family participated in organized social activities These covariates were included in all of the other analyses reported below.

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Correspondence to J. Michael Murphy.

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Murphy, J.M., Guzmán, J., McCarthy, A.E. et al. Mental Health Predicts Better Academic Outcomes: A Longitudinal Study of Elementary School Students in Chile. Child Psychiatry Hum Dev 46, 245–256 (2015). https://doi.org/10.1007/s10578-014-0464-4

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Keywords

  • Children
  • Mental health
  • Screening
  • School-based services
  • Low-income population