Artificial Intelligence for Mental Health: A Review Based Analysis of Early Detection and Management of Depression in Elderly Citizens

Abstract

Depression among the elderly in India is increasingly concerning due to socio-economic, health, and cultural factors. The elderly population is projected to rise significantly, highlighting the need to address mental health issues like depression. Social isolation is a major factor, exacerbated by the shift from traditional joint families to nuclear families, leaving many elderly individuals lonely and with reduced familial support. Additionally, the erosion of social networks and community ties further isolates them.

Health issues also significantly contribute to depression among the elderly. Chronic illnesses, physical disabilities, and general health decline with aging impact mental well-being. The lack of adequate healthcare infrastructure, especially in rural areas, leaves many elderly without necessary medical and psychological care. Financial insecurity, due to inadequate pension systems and rising living costs, adds stress and anxiety.

Cultural stigmas around mental health prevent many from seeking help. Depression is often misunderstood or dismissed, leading to underreporting and insufficient care. Societal expectations for stoicism and resilience in the elderly further discourage them from expressing their struggles.

A multi-faceted approach is needed to address this issue, including expanding accessible mental health services, community-based support systems, awareness campaigns to destigmatize mental health issues, and integrating mental health care into primary health services. Utilizing AI for prevention and mental well-being among senior citizens can be a potential solution. This paper is an attempt to understand how effectively AI can be used to address the issue.