Показати скорочений опис матеріалу

Prediction of stress-related conditions in students and their prevention through health-enhancing recreational physical activity

dc.contributor.authorBYSHEVETS, NATALIIA
dc.contributor.authorANDRIEIEVA, OLENA
dc.contributor.authorGONCHAROVA, NATALIIA
dc.contributor.authorHAKMAN, ANNA
dc.contributor.authorZAKHARINA, IEVGENIIA
dc.contributor.authorSYNIHOVETS, IHOR
dc.contributor.authorZAITSEV, VOLODYMYR
dc.date.accessioned2023-11-29T17:11:28Z
dc.date.available2023-11-29T17:11:28Z
dc.date.issued2023
dc.identifier.citationByshevets, N., Andrieieva, O., Goncharova, N., Hakman, A., Zakharina, I., Synihovets, I., & Zaitsev, V. (2023). Prediction of stress-related conditions in students and their prevention through health-enhancing recreational physical activity. Journal of Physical Education and Sport, 23(4), 937-943.uk_UA
dc.identifier.urihttps://archer.chnu.edu.ua/xmlui/handle/123456789/8362
dc.description.abstractIntroduction. Persistent negative mental-emotional experiences and the body's responses to stress may have a negative impact on physical condition and mental-emotional status of students and provoke behavioral disorders. Health-enhancing recreational physical activity helps to cope with the negative influence of stress factors. The study was focused on the prediction of stress-related conditions in students and their prevention through healthenhancing recreational physical activity (HRPA). The aim of the study was to develop predictive models for assessing stress-related conditions among students and to identify the opportunities for their prevention through engagement in health-enhancing recreational physical activity based on the assessment of the relationship between physical activity and emotional status. Material & methods. The study involved 573 higher education students from various regions of Ukraine. The following methods were applied: surveying, statistical analysis using non-linear estimation methods and statistical classification methods based on data mining and machine learning methods, such as neural networks. Results. Statistically significant (p<0.05) logistic binary models were developed and scientifically substantiated, which can be used to predict stress-related conditions among higher education students based on data about their HRPA and behavioral characteristics in a long-term stressful situation. According to the survey data, the military conflict on the territory of Ukraine has provoked the emergence of emotional distress in 80.8% of respondents. It was found that regular engagement in HRPA and an active lifestyle allows predicting the maintenance of emotional well-being among students with a probability of 78.0%. Conclusions. The behavioral disorders in higher education students combined with lack of HRPA during the period of armed conflict on the territory of Ukraine significantly increase their risk of anxiety, aggressiveness, depressive states, and mood swings as well as lead to deterioration in physical condition and mental-emotional status. An active lifestyle, regular engagement in health-enhancing recreational physical activity, and cessation of bad habits increase students' adaptability to the impact of stress factors.uk_UA
dc.subjectphysical activity, stress, status, disorders, behavior, correction, well-being, logit modelsuk_UA
dc.titlePrediction of stress-related conditions in students and their prevention through health-enhancing recreational physical activityuk_UA
dc.typeArticleuk_UA


Долучені файли

Thumbnail
Name:
Art117.pdf
Розмір:
210.9Kb
Формат:
PDF
Переглянути

Даний матеріал зустрічається у наступних фондах

Показати скорочений опис матеріалу