TY - JOUR
T1 - Psychosis Symptom Trajectories Across Childhood and Adolescence in Three Longitudinal Studies
T2 - An Integrative Data Analysis with Mixture Modeling
AU - Musci, Rashelle J.
AU - Kush, Joseph M.
AU - Masyn, Katherine E.
AU - Esmaeili, Masoumeh Amin
AU - Susukida, Ryoko
AU - Goulter, Natalie
AU - McMahon, Robert J.
AU - Eddy, J. Mark
AU - Ialongo, Nicholas S.
AU - Tolan, Patrick
AU - Godwin, Jennifer
AU - the Conduct Problems Prevention Research Group6
AU - Bierman, Karen L.
AU - Coie, John D.
AU - Crowley, D. Max
AU - Dodge, Kenneth A.
AU - Greenberg, Mark T.
AU - Lochman, John E.
AU - McMahon, Robert J.
AU - Pinderhughes, Ellen E.
AU - Wilcox, Holly C.
PY - 2023/11
Y1 - 2023/11
N2 - Psychotic-like experiences (PLEs) are common throughout childhood, and the presence of these experiences is a significant risk factor for poor mental health later in development. Given the association of PLEs with a broad number of mental health diagnoses, these experiences serve as an important malleable target for early preventive interventions. However, little is known about these experiences across childhood. While these experiences may be common, longitudinal measurement in non-clinical settings is not. Therefore, in order to explore longitudinal trajectories of PLEs in childhood, we harmonized three school-based randomized control trials with longitudinal follow-up to identify heterogeneity in trajectories of these experiences. In an integrative data analysis (IDA) using growth mixture modeling, we identified three latent trajectory classes. One trajectory class was characterized by persistent PLEs, one was characterized by high initial probabilities but improving across the analytic period, and one was characterized by no reports of PLEs. Compared to the class without PLEs, those in the improving class were more likely to be male and have higher levels of aggressive and disruptive behavior at baseline. In addition to the substantive impact this work has on PLE research, we also discuss the methodological innovation as it relates to IDA. This IDA demonstrates the complexity of pooling data across multiple studies to estimate longitudinal mixture models.
AB - Psychotic-like experiences (PLEs) are common throughout childhood, and the presence of these experiences is a significant risk factor for poor mental health later in development. Given the association of PLEs with a broad number of mental health diagnoses, these experiences serve as an important malleable target for early preventive interventions. However, little is known about these experiences across childhood. While these experiences may be common, longitudinal measurement in non-clinical settings is not. Therefore, in order to explore longitudinal trajectories of PLEs in childhood, we harmonized three school-based randomized control trials with longitudinal follow-up to identify heterogeneity in trajectories of these experiences. In an integrative data analysis (IDA) using growth mixture modeling, we identified three latent trajectory classes. One trajectory class was characterized by persistent PLEs, one was characterized by high initial probabilities but improving across the analytic period, and one was characterized by no reports of PLEs. Compared to the class without PLEs, those in the improving class were more likely to be male and have higher levels of aggressive and disruptive behavior at baseline. In addition to the substantive impact this work has on PLE research, we also discuss the methodological innovation as it relates to IDA. This IDA demonstrates the complexity of pooling data across multiple studies to estimate longitudinal mixture models.
KW - Integrative data analysis
KW - Mixture modeling
KW - Psychotic-like experiences
UR - http://www.scopus.com/inward/record.url?scp=85173817530&partnerID=8YFLogxK
U2 - 10.1007/s11121-023-01581-7
DO - 10.1007/s11121-023-01581-7
M3 - Article
C2 - 37615885
AN - SCOPUS:85173817530
SN - 1389-4986
VL - 24
SP - 1636
EP - 1647
JO - PREVENTION SCIENCE
JF - PREVENTION SCIENCE
IS - 8
ER -