TY - JOUR
T1 - The application of latent class analysis for investigating population child mental health
T2 - a systematic review
AU - Petersen, Kimberly J.
AU - Qualter, Pamela
AU - Humphrey, Neil
N1 - Publisher Copyright:
© 2019 Petersen, Qualter and Humphrey.
Copyright:
Copyright 2019 Elsevier B.V., All rights reserved.
PY - 2019/5/29
Y1 - 2019/5/29
N2 - Background: Latent class analysis (LCA) can be used to identify subgroups of children with similar patterns of mental health symptoms and/or strengths. The method is becoming more commonly used in child mental health research, but there are reservations about the replicability, reliability, and validity of findings. Objective: A systematic literature review was conducted to investigate the extent to which LCA has been used to study population mental health in children, and whether replicable, reliable and valid findings have been demonstrated. Methods: Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed. A search of literature, published between January 1998 and December 2017, was carried out using MEDLINE, EMBASE, PsycInfo, Scopus, ERIC, ASSIA, and Google Scholar. A total of 2,748 studies were initially identified, of which 23 were eligible for review. The review examined the methods which studies had used to choose the number of mental health classes, the classes that they found, and whether there was evidence for the validity and reliability of the classes. Results: Reviewed studies used LCA to investigate both disparate mental health symptoms, and those associated with specific disorders. The corpus of studies using similar indicators was small. Differences in the criteria used to select the final LCA model were found between studies. All studies found meaningful or useful subgroups, but there were differences in the extent to which the validity and reliability of classes were explicitly demonstrated. Conclusions: LCA is a useful tool for studying and classifying child mental health at the population level. Recommendations are made to improve the application and reporting of LCA and to increase confidence in findings in the future, including use of a range of indices and criteria when enumerating classes, clear reporting of methods for replicability, and making efforts to establish the validity and reliability of identified classes.
AB - Background: Latent class analysis (LCA) can be used to identify subgroups of children with similar patterns of mental health symptoms and/or strengths. The method is becoming more commonly used in child mental health research, but there are reservations about the replicability, reliability, and validity of findings. Objective: A systematic literature review was conducted to investigate the extent to which LCA has been used to study population mental health in children, and whether replicable, reliable and valid findings have been demonstrated. Methods: Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed. A search of literature, published between January 1998 and December 2017, was carried out using MEDLINE, EMBASE, PsycInfo, Scopus, ERIC, ASSIA, and Google Scholar. A total of 2,748 studies were initially identified, of which 23 were eligible for review. The review examined the methods which studies had used to choose the number of mental health classes, the classes that they found, and whether there was evidence for the validity and reliability of the classes. Results: Reviewed studies used LCA to investigate both disparate mental health symptoms, and those associated with specific disorders. The corpus of studies using similar indicators was small. Differences in the criteria used to select the final LCA model were found between studies. All studies found meaningful or useful subgroups, but there were differences in the extent to which the validity and reliability of classes were explicitly demonstrated. Conclusions: LCA is a useful tool for studying and classifying child mental health at the population level. Recommendations are made to improve the application and reporting of LCA and to increase confidence in findings in the future, including use of a range of indices and criteria when enumerating classes, clear reporting of methods for replicability, and making efforts to establish the validity and reliability of identified classes.
KW - Child
KW - Latent class analysis
KW - Latent profile analysis
KW - LCA
KW - LPA
KW - Mental health
KW - Systematic review
UR - http://www.scopus.com/inward/record.url?scp=85068330876&partnerID=8YFLogxK
U2 - 10.3389/fpsyg.2019.01214
DO - 10.3389/fpsyg.2019.01214
M3 - Review article
AN - SCOPUS:85068330876
VL - 10
JO - Frontiers in Psychology
JF - Frontiers in Psychology
M1 - 1214
ER -