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

Autor: Saleh M; School of Social Work, Virginia Commonwealth University, Richmond, Virginia, United States of America., Amona E; Department of Statistical Sciences and Operations Research, Virginia Commonwealth University, Richmond, Virginia, United States of America., Kuttikat M; School of Social Work, Virginia Commonwealth University, Richmond, Virginia, United States of America., Sahoo I; Department of Statistical Sciences and Operations Research, Virginia Commonwealth University, Richmond, Virginia, United States of America., Chan D; Department of Applied Mathematics, Virginia Commonwealth University, Richmond, Virginia, United States of America., Murphy J; School of Social Work, University of Texas at Arlington, Arlington, TX, United States of America., Kim K; School of Social Work, Virginia Commonwealth University, Richmond, Virginia, United States of America., George H; Department of Anthropology, George Washington University, Washington, DC, United States of America., Lund M; School of Social Work, Virginia Commonwealth University, Richmond, Virginia, United States of America.
Jazyk: angličtina
Zdroj: PloS one [PLoS One] 2024 Sep 16; Vol. 19 (9), pp. e0303632. Date of Electronic Publication: 2024 Sep 16 (Print Publication: 2024).
DOI: 10.1371/journal.pone.0303632
Abstrakt: 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.
Competing Interests: This does not alter our adherence to PLOS ONE policies on sharing data and materials.
(Copyright: © 2024 Saleh et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)
Databáze: MEDLINE
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