ABSTRACT
As global population ages, "Aging in Place" is prioritized as the top aging strategy for many of the older adults worldwide. India, being a nation that is expected to hold the maximum share of the older adult population in the near future, has a huge responsibility vested in it to take care of the needs of older adults. The social structure of the nation has emphasized the importance of older adults to age in place, experiencing all the independence and autonomy at their own dwelling places for as long as possible. This study aims to provide a profound understanding of the meaning, attitude, and perceptions of older adults toward aging in place. Using a qualitative research design, in-depth interviews were conducted among 15 community-dwelling older adults who chose aging in place in Kerala, India. Following the interviews, thematic network analysis was done, inspired by Jennifer Attride-Stirling. Three global themes were derived, which include the older adults' perspectives on (1) determinants of aging in place, (2) challenges of aging in place, and (3) strategies for successful aging in place. The study evokes in-depth exploration of the experiences of older adults aging in place, which inform future evidence-based practices and policy-level implications.
ABSTRACT
Emerging technological tools like Artificial Intelligence-based Chatbots, digital educational alternatives and market-driven educational systems pose a challenge to the fundamental aim of the higher education system; comprehensive education for well-being. Therefore, this research aims to devise and evaluate strategies to impart new-age competencies to innovate socially and morally appropriate solutions in a modern competitive innovative society. The 8-month-long immersive learning framework (ILF), was designed based on the volatility, uncertainty, complexity, and ambiguity (VUCA) paradigm. The framework was evaluated with 133 newly joined postgraduate students doing their science or arts programmes from a higher education institution in Kerala, India. The outcome variables included well-being, depressive symptoms, personality patterns, and sub-domains of philosophy of human nature. The follow-up scores showed a significant improvement in well-being (Mean difference: 1.15, p = 0.005), trustworthiness (Mean difference: 14.74, p = 0.000), strength of will (Mean difference: 10.11, p = 0.000), altruism (Mean difference: 12.85, p = 0.000), and independence (Mean difference: 11.93, p = 0.000). Depression scores did not improve significantly. However, the intervention shielded them from the adjustment issues that often accompany any transition. The ILF framework can help students develop their personal and professional selves if it is implemented collaboratively in a reflective setting. It can also instil moral rectitude and a prosocial mindset.
Subject(s)
Artificial Intelligence , Goals , Humans , Learning , Students , SchoolsABSTRACT
Social networks protect individuals from mental health conditions of depression and anxiety. The association between each social network type and its mental health implications in the Indian population remains unclear. The study aims to determine the association of depression and anxiety with different social network types in the participants of a community cohort. We conducted a cross-sectional household survey among people aged ≥30 years in geographically defined catchment areas of Kerala, India. We used cross-culturally validated assessment tools to measure depression, anxiety and social networks. An educated male belonging to higher income quartiles, without any disability, within a family dependent network has lower odds of depression and anxiety. Furthermore, 28, 26.8, 25.7, 9.8 and 9.7% of participants belonged to private restricted, locally integrated, wider community-focused, family-dependent and locally self-contained networks, respectively. Close ties with family, neighbours, and community had significantly lower odds of anxiety and depression than private restricted networks. The clustering of people to each social network type and its associated mental health conditions can inform social network-based public health interventions to optimize positive health outcomes in the community cohort.
