2.4 Statistical analyses
IBM SPSS version 22.0 software was used. Clinical case profiles, coping styles, together with self-esteem were assessed through Pearson chi-square analyses or one-way analyses of variance (ANOVAs) as deemed fit, having least-significant difference (LSD) or Tamhane’s T2 corrections for multiple comparisons. Analyses of covariance (ANCOVAs) additionally evaluated coping style together with self-esteem interactions across all study groups, controlling for demographic variables. In addition, the correlations of SIPS, MADRS, PANSS, and GAF scores with coping styles together with self-esteem within UHR, ReSch together with FEP groups were examined using Spearman’s correlation analysis.
Moreover, binary logistic regression assessments probed risk parameters linked to prodromal psychosis or psychiatric conditions, through ReSch, FEP, UHR, and HC status as dependent variable and highly varying socio-demographic profiles (such as marital status, age, education level and employment status) as independent variables for univariate assessments. Meanwhile MARDS was divided into the presence or absence of depression as an independent variable into the model with a cut-off score of 12. Furthermore, coping styles and self-esteem were also incorporated within such assessments, irrespective of influence upon revealing major associations during univariate assessment, due to being deemed vital parameters for this investigation. A two-tailed P<0.05 conferred statistical significance.