The present study tested a novel, person-specific method for identifying discrete mood profiles from time-series data, and examined the degree to which these profiles could be predicted by lagged mood and anxiety variables and time-based variables, i...
OBJECTIVE: To employ machine learning algorithms to examine patterns of rumination from RDoC perspective and to determine which variables predict high levels of maladaptive rumination across a transdiagnostic sample.
Smartphone addiction (SA) significantly impacts the physical and mental health of adolescents, and can further exacerbate existing mental health issues in those with depression. However, fewer studies have focused on the predictors of SA in adolescen...
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