This article analyses the complex factors contributing to rising medical expenses, focusing on the senior citizen demographic in Malaysia. With the global aging population, notably in lower and middle-income countries, the study highlights the escalating medical and health insurance costs, driven by age, income source, modern healthcare, and geographical residence. The research draws on an extensive literature review, demographic analysis, and quantitative methods to examine these determinants. It critically analyzes Malaysia’s healthcare system, which operates on a dual-tier model, and the financial burden placed on senior citizens. The findings indicate that age, source of income, and geographical residence significantly influence medical expenses, whereas modern healthcare’s impact is not statistically significant. The study calls for government intervention, insurance industry adjustments, and private sector support to mitigate the financial strain on senior citizens. Recommendations include tax relief adjustments, National Health Insurance Scheme implementation, and employment sustainability for seniors. This research provides some recommendations to policymaking, the insurance industry, and academia by providing insights into managing the healthcare needs of an aging population sustainably.

The purpose of the study was to examine the role of personalization in motivating senior citizens to use AI driven fitness apps. Vroom’s expectancy theory of motivation was applied to examine the motivation of senior citizens. The responses from participants were collected through structured interviews. The participants belonged to South Asian origin belonging to India, Bangladesh, Nepal and Bhutan. The authors adopted a content analysis approach where the gathered interview responses were coded in the context of elements of Vroom’s theory. The findings of the study indicated that a highly personalized approach in the context of motivation, expectancy, instrumentality and valence will motivate senior citizens to use AI based fitness apps. The study contributes to the personalization of AI fitness apps for senior citizens.