Efficiency of technology for restoring the quality of life of young people with metabolic syndrome and chronic pain using physical therapy

Authors

  • Yuliya Kalmykova Department of Propaedeutics of internal medicine and physical reahabilitation, V.N. Karazin Kharkiv National University, Kharkiv, Ukraine; Municipal Non-Profit Enterprise Сітy Children's Hospital №5 Of Khariv City Council, Kharkiv, Ukraine https://orcid.org/0000-0002-6227-8046
  • Olha Svierchkova Department of physical therapy, Kharkiv State Academy of Physical Culture, Kharkiv, Ukraine https://orcid.org/0000-0001-9987-6405
  • Sergey Kalmykov Dean of the faculty of physical therapy and human health, Kharkiv State Academy of Physical Culture, Kharkiv, Department of physical therapy, Kharkiv State Academy of Physical Culture, Kharkiv, Ukraine https://orcid.org/0000-0002-6837-2826
  • Sviatoslava Pashkevych Department of physical therapy, Kharkiv State Academy of Physical Culture, Kharkiv, Ukraine https://orcid.org/0000-0002-4842-4350

DOI:

https://doi.org/10.15391/prrht.2024-9(5).07

Keywords:

system for restoring quality of life, technology, physical therapy, metabolic syndrome, chronic pain, efficiency criteria.

Abstract

Purpose: substantiation of criteria for the effectiveness of technology for restoring the quality of life of young people with metabolic syndrome and chronic pain by means of physical therapy.

Material and methods: The study involved 97 young women with metabolic syndrome and chronic pain in the musculoskeletal system. The study used general scientific methods - the method of a systemic approach and systemic analysis, bibliosemantic, content analysis, the method of conceptual modeling and empirical methods - anthropometric, physiological, clinical, sociological, the method of expert assessments, mathematical and statistical research methods. The information base of the study was sources of professional scientific, reference, directive information and the results of our own research, the representativeness and reliability of which are proven by medical and statistical calculations.

Results: Based on the results of factor analysis and taking into account the results of correlation analysis, the criteria for the effectiveness of the proposed technology were developed. In the process of developing the criteria, the machine learning method was used - modeling with multidimensional adaptive regression splines MARSplines. This method made it possible to find mutually agreed indicators and, according to the criterion, select those of them that are more convenient to diagnose.

Conclusions: based on determining the ratio of body length and weight and waist to hip circumference, the dynamics of the BMI index and static back strength, as well as the results of the dynamics of quality of life indicators, it is possible to determine the degree of influence of the means and methods of the author's technology on the quality of life and pain syndrome of women with MS, and also to establish the degree of effect.

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2024-09-12

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