Relationships Between Psychopathology and Quality of Life Among Adolescents a Structural Equation Modeling Approach

Purpose: One of the main characteristics of measuring quality of life (QOL) in psychopharmacology is in providing data about the impacts of specific treatments on different aspects of well-being and functioning [1]. Therefore, QOL and other similar patientreported outcome (PRO) measures are recognized by regulatory bodies as important outcome measures in clinical trials, drugs registration, and marketing processes as an important target for intervention. Nevertheless, the aspects of psychopathology and QOL are highly inter-correlated and no clear demarcations were made the concepts [2]. As a useful method for studying complex relationships between various constructs, structural equation modeling (SEM) has not received much attention to study psychopathology and QOL together. This study evaluated the relationships between aspects of QOL and mental health using a SEM approach among adolescents in an international sample. >Methods: In this study, adolescents from an international project participated [2]. Adolescents aged 14−18 years from Serbia, India, Indonesia, Nigeria, Bulgaria, Croatia, and Turkey completed the Pediatric Quality of Life Inventory (PedsQL) for QOL assessments and Strengths and Difficulties Questionnaire (SDQ) for mental health difficulties. Assuming that the aspects of psychopathology and QOL could be highly inter- correlated due to similarities in items, the PedsQL items with similar meaning to the SDQ items measuring psychopathology were omitted. A SEM model was tested for this purpose: one latent QOL variable represented by three indicators − scales derived from the PedsQL (Physical functioning, Social functioning, and School functioning) and two correlated predictors − mental difficulties (derived from the SDQ scores indicating significant psychopathology) and chronic condition/illness (the presence/absence of a chronic health problem). The following statistics was used to assess the adequacy of the model: Tucker Lewis Index − TLI (>0.95 excellent), the Comparative Fit Index − CFI (>0.95 excellent), and Root Mean Square Error of Approximation − RMSEA (