Regularities of the patterns of interdependence between characteristics of the functional state of the organism and indicators of the health status of students and their comprehensive assessment
An essential component of adequate prognostic assessment of the interdependence of the leading correlates of adaptive capacity and functional resources of the human organism is the use of factor analysis procedures. The purpose of the work is to establish the patterns of interdependence of the characteristics of the functional state of the organism and indicators of the health status of students and their complex assessment based on the use of factor analysis procedures. In the course of scientific researches were studied indicators of functional features of higher nervous activity, visual sensory system and somatosensory analyzer. Data on the communication and interdependence characteristics of the level of development of psychophysiological functions and indicators of the health status of students were subjected to statistical processing using the licensed standardized package “Statistica 6.1 for Windows” (license number ВXXR901E245722FA) based on the factor analysis procedures. During the complex assessment of the patterns of interdependence between the characteristics of health status and indicators of the development of psychophysiological functions of the organism of students, who were at different stages of higher medical education, it was determined that young man had the most significant influence on health characteristics of the level of health factors such as “functional features of the visual sensory system”, “functional features of motion coordination” and “functional features speed of visual-motor speed and stability of attention”, young woman – factors such as “functional features of the visual sensory system”, “functional features of motion coordination” and “functional features speed of visual-motor reaction”. The results obtained are the basis for the development of methods for the prognostic evaluation of the characteristics of the formation of health characteristics in the context of determining indicators of the development of psychophysiological functions of young men and young women, as well as the development of effective health-saving technologies to create a preventive educational environment in higher education.
 Baranov, A. A., Kuchma, V. R., & Suhareva, L. M. (2008). Medical and social aspects of adaptation of modern adolescents to conditions of education, training and labor activity. Moscow: GOETAR-Media.
 Borovikov, V. P., & Borovikov, I. P. (1998). STATISTICA: Statistical analysis and data processing in Windows. Moscow: Publishing House “Filin”.
 Byuyul, A., & Cefel, P. (2005). SPSS: the art of information processing. Analysis of statistical data and restoration of hidden patterns. St-Petersburg: LLC “DiaSoftYuP”.
 Castro, M. A., Baltar, V. T., Selem, S. S. C., Marchioni, D. M. L., & Fisberg, R. M. (2015). Empirically derived dietary patterns: interpretability and construct validity according to different factor rotation methods. Cad Saúde Pública, 31(2), 298-310. doi: 10.1590/0102-311X00070814
 Floyd, F. J., & Widaman, K. F. (1995). Factor analysis in the development and refinement of clinical assessment instruments. Psychol Assess, 7(3), 286-299. doi: 10.1037/1040-35188.8.131.526
 Hair, Jr. J. F., Black W. C., Babin B. J., Anderson R. E., & Tatham R. L. (2006). Multivariate Data Analysis. 6ª ed. Upper Saddle River: Pearson Prentice Hall.
 Johnson, R. A, & Wichern, D. W. (1998). Applied Multivariate Statistical Analysis. 6ª ed. Upper Saddle River: Pearson Prentice Hall.
 Kalnish, V. V. (2008). Psychophysiological aspects of studying the reliability of operator activity. Ukrainian Journal of Medicine, 3(15), 81-89.
 Kuchma, V. R., & Suhareva, L. M. (2006). Scientific and methodological foundations for studying the adaptation of children and adolescents to living conditions. Moscow: [wp].
 Meyers, L. S, Gamst, G., & Guarino, A. J. (2006). Applied multivariate research: design and interpretation. California: Sage.
 Nasledov, A. D. (2005). SPSS: Computer Data Analysis in Psychology and Social Sciences. St-Petersburg: Piter.
 Nasledov, A. D. (2006) Mathematical methods of psychological research. Analysis and interpretation of data. St-Petersburg: Rech.
 Park, H. S., Dailey, R., & Lemus, D. (2002). The use of exploratory factor analysis and principal components analysis in communication research. Hum. Commun. Res., 28(4), 562-577. doi: 10.1111/j.1468-2958.2002.tb00824.x
 Polka, N. S., & Serheta, I. V. (2012). Actual problems of psychohygiene of children and adolescents: ways and perspectives of their solution (review of literature and own research). Journal of the Academy of Medical Sciences of Ukraine, 18(2), 223-236.
 Rebrova, O. Yu. (2006). Statistical analysis of medical data. Application package Statistica. Moscow: MediaSfera.
 Rencher, A. C. (2002). Methods of multivariate analysis. 2ª ed. New York: John Wiley & Sons.
 Sass, D. A. (2010). Factor loading estimation error and stability using exploratory factor analysis. Education Psychology Measurement, 70(4), 557-577. doi: 10.1177%2F0013164409355695
 Schneeweiss, H., & Mathes, H. (1995). Factor analysis and principal components. J Multivar Anal, 55(1), 105-124. doi: 10.1006/jmva.1995.1069
 Serheta, I. V., & Bardov,V. G. (1998). Perspectives on using the level of physical performance as a quantitative indicator of the health of children and adolescents. Environment and health, 1(4), 14-17.
 Serheta, I. V., & Mostova, O. P. (2013). Medical and social aspects of educational adaptation and health status of schoolchildren. Topical issues of pediatrics, obstetrics and gynecology, 2, 20-22.
 Serheta, I. V., Bratkova, O. Y., Mostova, O. P., Panchuk, O. Y., & Dudarenko, O. B. (2012). Scientific principles of psychohygienic diagnostics of the health of children, adolescents and youth. Environment and health, 4(64), 21-25.
 Serheta, I. V., Grigorchuk, L. I., & Molchanova, O. P. (2002). Ways of optimization of professional adaptation of students to the conditions of study at a medical higher educational institution and their predictive value. Environment and health, 4(23), 57-61.
 Serheta, I. V., Panchuk, O. Y., Stoyan, N. V., Drezhenkova, I. L., & Makarov, S. Y. (2016). University hygiene in the context of implementation of the “Law on Higher Education”: physiological and hygienic bases, realities and ways of development. Dovkillya ta zdorov’ya, 4(80), 46-52.
 Suharev, A. G., & Serheta, I. V. (1996). Personal features of the body of modern teenagers and the ways of their correction. Higiene and sanitation, 1, 29-31.
 Suhr, D. (2005). Principal component analysis vs. exploratory factor analysis. In: SUGI 30 Proceedings [Internet]. Available from: http://www2.sas.com/proceedings/sugi30/Leadrs30.pdf
 Yerina, A. M. (2001). Statistical modeling and forecastin. Kiev: KNEU.
 Yong, A. G., & Pearce, S. (2013). A beginner’s guide to factor analysis: focusing on exploratory factor analysis. Tutor Quant Methods Psychol, 9(2), 79-94. doi: 10.20982/tqmp.09.2.p079
 Zygmont, C., & Smith, M. R. (2014). Robust factor analysis in the presence of normality violations, missing data, and outliers: Empirical questions and possible solutions. Quantitative Method for Psychology, 10(1), 40-55. doi: 10.20982/tqmp.10.1.p040
This work is licensed under a Creative Commons Attribution 4.0 International License.