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Child mental health predictors among camp Tamil refugees: Utilizing linear and XGBOOST models.

Authors :
Saleh, Muna
Amona, Elizabeth
Kuttikat, Miriam
Sahoo, Indranil
Chan, David
Murphy, Jennifer
Kim, Kyeongmo
George, Hannah
Lund, Marianne
Source :
PLoS ONE; 9/16/2024, Vol. 19 Issue 9, p1-18, 18p
Publication Year :
2024

Abstract

While the association between migration and deteriorated refugee mental health is well-documented, existing research overwhelmingly centers on adult populations, leaving a discernible gap in our understanding of the factors influencing mental health for forcibly displaced children. This focus is particularly noteworthy considering the estimated 43.3 million children who are forcibly displaced globally. Little is known regarding the association between family processes, parental and child wellbeing for this population. This study addresses these gaps by examining the relationship between parental mental health and child mental health among refugees experiencing transmigration. We conducted in-person structured survey interviews with 120 parent-adolescent dyads living in the Trichy refugee camp in Tamil Nadu, India. Descriptive, multivariate analysis (hierarchical regression), and Machine Learning Algorithm (XGBOOST) were conducted to determine the best predictors and their importance for child depressive symptoms. The results confirm parental mental health and child behavioral and emotional factors are significant predictors of child depressive symptoms. While our linear model did not reveal a statistically significant association between child mental health and family functioning, results from XGBOOST highlight the substantial importance of family functioning in contributing to child depressive symptoms. The study's findings amplify the critical need for mental health resources for both parents and children, as well as parenting interventions inside refugee camps. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
19326203
Volume :
19
Issue :
9
Database :
Complementary Index
Journal :
PLoS ONE
Publication Type :
Academic Journal
Accession number :
179663929
Full Text :
https://doi.org/10.1371/journal.pone.0303632