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News
October 19, 2026
'Cultural Studies Seeks to Understand What Lies Beneath the Surface of Everyday Things'
Maxim Zhiganov has been exploring different aspects of sound for many years—first in relation to his native Perm and then on a broader, global scale. In this interview for the HSE Young Scientists project, he talks about sound maps, the special issue of the journal Logos, and why it is important to make the familiar less clear and obvious.
October 14, 2026
At HSE University–St Petersburg, Experts Discuss How AI Changes Tourist Routes and Cultural Heritage
Neural networks are no longer simple travel assistants; now they decide what to include on the route and what to skip. Artificial intelligence changes how people perceive a place and shapes the image of tourist centres. At the II International Scientific and Practical Conference ’Information Technologies in the Preservation and Promotion of Cultural Heritage,’ researchers discussed who controls algorithmic solutions and in what ways, and whether authentic traditions get lost in them.
October 12, 2026
Road Injuries Leading Cause of Death Among Men Aged 10 to 39
Worldwide, road injuries are the leading cause of death among males aged 10–39. An international team of researchers reached this conclusion as part of the Global Burden of Disease Study 2023, analysing data from 204 countries between 1990 and 2023. Their findings have been published in The Lancet Public Health, with HSE University Professor Vasily Vlassov listed among the collaborators.

 

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Исследование оценки субъективного благополучия и качества жизни граждан, включенных в систему долговременного ухода, с помощью Telegram-бота

Личность в меняющемся мире: здоровье, адаптация, развитие. 2025. Т. 13. № 2(49). С. 105–120.
Суворова Н. В., Varnavsky A., Оськин Д. Н.

The article presents a rationale for improving the practice of using online questionnaires in the format of a mini-program (Telegram bot) in the Telegram messenger for the needs of social services for the population.

Aim. Identification of the level of subjective well-being of citizens included in the long-term care system; analysis of factors affecting the level of subjective well-being; development of recommendations for improving social and medical support for citizens. Data on the subjective wellbeing of citizens included in the long-term care system were collected through a questionnaire in the Telegram bot. The analysis was carried out using the following models: linear regression, random forest and support vector method (SVM). This allowed for establishing links between factors of emotional state, social activity and satisfaction with services and the overall perception of quality of life. The results obtained provide an accurate and reliable assessment of subjective well-being, minimizing the impact of social and physical barriers, and can be used to further develop programs to support and improve the quality of life in the long-term care system. The study also lays the foundation for further monitoring of the well-being of citizens in long-term care system and improving digital tools for assessing their condition.

Research target: Computer Science Health Studies
Language: Russian
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DOI
Text on another site
Keywords: качество жизнипожилые людиинвалидыquality of lifeопросникelderly peoplequestionnaireсистема долговременного уходаlong-term care systemTelegram botDISABLED PERSONTelegram-бот
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