Omar Alsayyed, Tareq Hamadneh, Hassan Al-Tarawneh, Mohammad Alqudah, Saikat Gochhait, Irina Leonova, Om Parkash Malik, Mohammad Dehghani
Giant Armadillo Optimization: A New Bio-Inspired Metaheuristic Algorithm for Solving Optimization Problems
Biomimetics (Basel, Switzerland)
little known underlying relationships selfreported mental health items measuring positive negative emotional behavioural symptoms population level young people improved measurement full range mental wellbeing mental illness may aid understanding aetiological substrates underlying development mental wellness well specific psychiatric diagnoses general population sample aged 14 24 years completed selfreport questionnaires anxiety depression psychoticlike symptoms obsessionality wellbeing exploratory confirmatory factor models categorical data latent profile analyses used evaluate structure mental wellness illness items first order second order bifactor structures evaluated 118 selfreported items obtained 2228 participants bifactor solution best fitting latent variable model one general latent factor termed distress five distress independent specific factors defined selfconfidence antisocial behaviour worry aberrant thinking mood next six distinct subgroups derived personcentred latent profile analysis factor scores finally concurrent validity assessed using information hazardous behaviours alcohol use substance misuse selfharm treatment mental ill health discriminated latent traits latent profile subgroups findings suggest complex multidimensional mental health structure youth population rather previously assumed first second order factor structure additionally analysis revealed low hazardous behaviourlow mental illness risk subgroup previously described population subgroups show greater validity single variable factors revealing mental illness risks conclusion findings indicate structure self reported mental health multidimensional nature uniquely finds improved prediction mental illness risk within personcentred subgroups derived multidimensional latent traits