The paper presents data from a study of the psychological state and level of anxiety in 152 elderly people of several megacities of Russia during the COVID-19 pandemic and related restrictions. The data has been obtained through a telephone or online survey. It was found that during the period of restrictive measures associated with coronavirus infection, elderly people showed a wide range of anxiety indicators and options for assessing the situation and behavior in it. To assess the possibility of identifying groups of people with similar characteristics, we used the methods of constructing a dendrogram and "stony talus", the analysis of the results of which showed that it is necessary to use only those signs that are directly related to the objectives of the study, and not all data. The application of the principal component method allowed us to study the data in detail and highlight the most important characteristics for assessing the level of anxiety in the elderly during the COVID-19 pandemic, namely: self-esteem of the patient's mood, general situational ITT, danger of communication and social frustration. These features have been used in the experiments performed. Clusters have been formed using the k-means and ISODATA. The clustering allowed to group the data of the Integrative Anxiety Test and the visual analogue scale of anxiety and well-being into a different number of clusters according to the severity of situational personal anxiety and subjective assessment of one's state in elderly in a situation of an infectious threat. The data obtained allows to conclude that in the event of an infectious threat, a multivariate approach is required not only to providing information about the disease and its prognosis, but also to various options for organizing psychological assistance for the elderly.
|Журнал||CEUR Workshop Proceedings|
|Состояние||Опубликовано - 2020|
|Событие||2020 Big Data Analysis Tasks on the Supercomputer GOVORUN Workshop, SCG 2020 - Dubna, Российская Федерация|
Продолжительность: 16 сен 2020 → …
Предметные области Scopus
- Компьютерные науки (все)