RESUMO
Objectives: The bipolar spectrum concept has resulted in a paradigm shift that has affected both the diagnosis and therapy of mood disorders, with bipolarity becoming an indicator of treatment resistance in depression. Evening circadian preference has also been linked to affective disorders. The aim of our study was to confirm the relationship between the severity of depressive symptoms, bipolar features, chronotype, and sleep quality among patients with major depressive disorder. Methods: A group of 55 individuals who were recruited from a mental health outpatient clinic completed the following psychometric tools: a Chronotype Questionnaire comprising morningness-eveningness (ME) and subjective amplitude of the rhythm (AM) scales, the Hypomania Checklist 32 (HCL-32), the Beck Depression Inventory (BDI) and the Pittsburgh Sleep Quality Index (PSQI). Results: Factor analysis identified two latent components, accounting cumulatively for 58% of variables: depressive symptoms (BDI and PSQI) and bipolarity (ME, AM, and HCL-32). After rotation, ME loading in the first factor increased the result to a significant level. The correlation between the two components was very low. Conclusions: Evening chronotype appears to be a bipolarity-related marker, with this relationship being independent of its link to depressive symptoms and sleep quality. Eveningness and high circadian rhythm amplitude may offer promise as diagnostic, prognostic, and therapeutic predictors.
RESUMO
The main purpose of this study was to explore the latent relations of the selected morphometric, physiological and biochemical parameters. Thirty-six variables (12 morphometric, 9 physiological and 15 biochemical variables) were measured on 317 male-entities aged 17 - 35 y/o. The obtained data were analysed through the factor analysis of the first and second order. The statistical analyses were performed with the IBM SPSS Statistics software package, version 20. The factorization of the first order enabled extraction of 12 latent factors that explain 74.8 % of the total variance, while the factorization of the second order enabled extraction of five latent components that explain 51.39 % of the total variance. The final results of this study confirm the main hypothesis that there exist the numbers of latent variables that explain the latent structure of selected biometric measures. The nature of the extracted latent factors/ components in both orders of factorization is relatively clear, understandable, and easy to interpret. The higher projections of the manifest biometric variables on the extracted latent factors of the first and second order were accordingly with the nature of the measured variables. The results of this research might be considered as one step more in the holistic approach to the biometric measures.
El objetivo principal de este estudio fue explorar las relaciones latentes de parámetros morfométricos, fisiológicos y bioquímicos seleccionados. Treinta y seis variables (12 morfométricas, 9 fisiológicas y 15 bioquímicas) se midieron en 317 hombres de 17 a 35 años. Los datos obtenidos fueron analizados a través del análisis factorial de primer y segundo orden. Los análisis estadísticos se realizaron con el software IBM SPSS Statistics, versión 20. La factorización del primer orden permitió la extracción de 12 factores latentes que explican el 74,8 % de la varianza total, mientras que la factorización del segundo orden permitió la extracción de cinco componentes latentes que determinaron el 51,39 % de la varianza total. Los resultados finales de este estudio confirmaron la hipótesis principal de que existen números de variables latentes que explican la estructura latente de las medidas biométricas seleccionadas. La naturaleza de los factores/componentes latentes extraídos en ambos órdenes de factorización es relativamente clara, comprensible y fácil de interpretar. Las proyecciones superiores de las variables biométricas manifiestas en los factores latentes extraídos del primer y segundo orden correspondieron a la naturaleza de las variables medidas. Los resultados de esta investigación podrían considerarse como un paso más en el enfoque holístico de las medidas biométricas.