Early predictors of child depression in at-risk families : latent profile analysis of risk factors occurring in ecological systems of young children
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[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] In this study, we identified patterns of risk factors across developmental contexts during the third year of life using latent profile analysis (LPA). We then examined whether these risk patterns differentially predicted child depression during middle childhood as well as the socioeconomic characters of each identified class. Participants included 688 families. The mean age for the mother participants was 23.4 (SD= 5.8). Over 60% of the sample had household incomes below the poverty line. The racial/ethnic characteristics were 33.5% Pacific Islander, 28% Asian, 12% Caucasian, and 26.5% unknown. The data was collected by the Hawaii's Healthy Start Program (HSP; Duggan et al., 2004). The following variables are included to describe the early environment: infant temperament, child externalizing problems, home educational resources, parent-child attachment, exposure to spouse violence, maternal depression, parenting stress, and insufficient community resources. Research results supported a five-class (i.e. adverse home environment class, low risk class, distressed parents and adverse community class, struggling children and violent spouse class and high risk class) solution. Children's depression scores varied significantly across classes. Results also indicated distinguished demographic factors associated with each class. The results offer important findings to establish a sophisticated model for capturing risk factors across the various ecological systems targeting specific developmental periods. Such findings could guide future prevention efforts by identifying children most at risk for adverse outcomes.
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