Improving the Quality of Life of Middle-aged and Older Adults through Mass Sport: The Role of Artificial Intelligence, Infrastructure, and Personal Motivation

Abstract

The relevance of this study stems from population aging and the urgent need to develop effective, personalized models for engaging middle-aged and older adults in mass sport as a means to enhance quality of life and promote active aging. The aim of this paper is to conduct a comprehensive analysis of factors influencing physical activity in this demographic, with a specific focus on personal motivation, adapted infrastructure, and artificial intelligence (AI)-based technologies. The study employed a narrative literature review (21 articles from Scopus and RSCI), a survey (n = 64), and content analysis of official infrastructure data from the Republic of Kazakhstan. The findings reveal that, despite high self-reported engagement (97% participated in some form of physical activity over the past year), only 27% of respondents meet the WHO-recommended activity level (≥150 min/week). Health-related motivation was predominant (72%), while key barriers included chronic health conditions (38%) and a lack of personalized programs. Group-based formats demonstrated significant social efficacy: 77% of respondents reported positive changes in their social relationships. Infrastructure analysis confirmed quantitative growth in sports facilities; however, their alignment with the needs of older adults remains inadequate. The study substantiates the need to transition toward hybrid mass sport models integrating AI-supported guidance, inclusive infrastructure, and social support mechanisms. The practical significance of this research lies in providing a scientific foundation for modernizing public health and sport policies and for developing digital solutions aimed at sustaining physical activity among the 45+ population.