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.