Stress Management Ability and Psychosocial Wellbeing in Indian Senior Citizens: A Descriptive Research
Keywords:
Stress Management, Psychosocial Wellbeing, Elderly Population, Aging in IndiaAbstract
The rapid demographic aging in India has intensified the importance of understanding stress management abilities and psychosocial wellbeing among senior citizens. This research presents a descriptive analysis of how elderly individuals cope with stress and maintain psychological balance within evolving socio-economic and familial contexts. The study conceptualizes stress management as a dynamic, adaptive process influenced by cognitive, emotional, environmental, and systemic factors, while psychosocial wellbeing is framed as a composite outcome of mental health, social integration, and life satisfaction.
Drawing upon resilience theory and supported by Agarwal et al. (2023), the research examines how coping mechanisms, emotional regulation, and social support structures contribute to effective stress management. The study also integrates interdisciplinary insights from systems engineering and adaptive control models, using analogies from microgrid optimization and feedback-based control systems to conceptualize human stress regulation processes.
The methodology adopts a descriptive and analytical framework based on synthesis of existing literature. It identifies key determinants of stress management, including cognitive flexibility, social connectivity, environmental stability, and access to technological resources. The research further explores how adaptive feedback mechanisms—similar to those used in energy systems optimization—can enhance psychological resilience in elderly populations.
Findings indicate that individuals with strong emotional resilience and structured coping strategies demonstrate higher levels of psychosocial wellbeing. Social support and community engagement emerge as critical factors, while technological interventions show potential in bridging gaps in social connectivity. The study also identifies systemic vulnerabilities, such as isolation and lack of adaptive resources, which negatively impact stress management capacity.
The research concludes by proposing an integrated adaptive framework linking stress management abilities with psychosocial outcomes. It contributes to academic discourse by combining psychological theories with systems-based analogies, offering novel insights for policy design and intervention strategies aimed at improving the quality of life among Indian senior citizens.
References
1. Agarwal, R., Usha Rani, B., & V, S. . (2023). RESILIENCE TO STRESS AND PSYCOSOCIAL ADJUSTMENTS AMONG ELDERS IN INDIA: a DESCRIPTIVE STUDY. European Chemical Bulletin, 12(05), 510–527. https://doi.org/10.48047/ecb/2023.12.si5.051
2. A. Narasimhan, “Simulation of Microgrid Technology by modelling Solar Plant and Battery System,” 2020 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT), 2020, pp. 1–6, doi: 10.1109/CONECCT50063.2020.9198581.
3. A. Ouammi, H. Dagdougui and R. Sacile, “Optimal Control of Power Flows and Energy Local Storages in a Network of Microgrids Modeled as a System of Systems,” in IEEE Transactions on Control Systems Technology, vol. 23, no. 1, pp. 128–138, Jan. 2015, doi: 10.1109/TCST.2014.2314474.
4. Bersani, C., Dagdougui, H., Ouammi, A. and Sacile, R. ( 2020 ), Stochastic constrained linear quadratic control in a network of smart microgrids. IET Renewable Power Generation, 14 : 1193–1200. https://doi.org/10.1049/iet-rpg.2019.0992.
5. D. Kotin and I. Ivanov, “New Type Single-Phase Generator for Autonomous Consumer,” 2020 International Conference on Industrial Engineering, Applications and Manufacturing (ICIEAM), 2020, pp. 1–5, doi: 10.1109/ICIEAM48468.2020.9112062.
6. D. Kotin, L. Tolstobrova and I. Ivanov, “Mathematical modeling of multi -winding synchronous generators with permanent magnets for autonomous consumers,” 2021 XVIII International Scientific Technical Conference Alternating Current Electric Drives (ACED), 2021, pp. 1–6, doi: 10.1109/ACED50605.2021.9462302.
7. I. Sami, N. Ullah, S. M. Muyeen, K. Techato, M. S. Chowdhury and J. -S. Ro, “Control Methods for Standalone and Grid Connected Micro-Hydro Power Plants With Synthetic Inertia Frequency Support: A Comprehensive Review,” in IEEE Access, vol. 8, pp. 176313–176329, 2020, doi: 10.1109/ACCESS.2020.3026492.
8. Junfei Chen, Hongbin Wu, Ming Sun, Weinan Jiang, Liang Cai and Caiyun Guo, “Modeling and simulation of directly driven wind turbine with permanent magnet synchronous generator,” IEEE PES Innovative Smart Grid Technologies, 2012, pp. 1–5, doi: 10.11 09/ISGT -Asia.20 12.6303300.
9. L. Jia, Y. Zhu and Y. Wang, “Architecture design for new AC- DC hybrid micro-grid,” 2015 IEEE First International Conference on DC Microgrids (ICDCM), 2015, pp. 113–118, doi: 10.1109/ICDCM.2015.7152020.
10. M. A. Michael, A. G. Petoussis, S. M. Stavrinos and A. Polycarpou, “The impact of load modeling on power flow studies for the cyprus power system,” 2014 49th International Universities Power Engineering Conference (UPEC), 2014, pp. 1–6, doi: 10.1109/UPEC.2014.6934744.
11. T. Halina, I. Ivanov and M. Stalnaya, “Sine-cosine Generator,” 2019 International Multi-Conference on Industrial Engineering and Modern Technologies (FarEastCon), 2019, pp. 1–4, doi: 10.11 09/FarEastCon.20 19.8934028.
12. V. Yaramasu, B. Wu, P. C. Sen, S. Kouro and M. Narimani, “High-power wind energy conversion systems: State-of-the-art and emerging technologies,” in Proceedings of the IEEE, vol. 103, no. 5, pp. 740–788, May 2015, doi: 10.1109/JPROC.2014.2378692.
13. X. Liu, P. Wang and P. C. Loh, “A Hybrid AC/DC Microgrid and Its Coordination Control,” in IEEE Transactions on Smart Grid, vol. 2, no. 2, pp. 278–286, June 2011, doi: 10.11 09/TSG.20 11.2116162.
14. X. Liu, P. Wang and P. C. Loh, “A Hybrid AC/DC Microgrid and Its Coordination Control,” in IEEE Transactions on Smart Grid, vol. 2, no. 2, pp. 278–286, June 2011, doi: 10.11 09/TSG.20 11.2116162.
15. Y. M. Atwa, E. F. El-Saadany, M. M. A. Salama and R. Seethapathy, “Optimal Renewable Resources Mix for Distribution System Energy Loss Minimization,” in IEEE Transactions on Power Systems, vol., no. 1, pp. 360–370, Feb. 2010, doi: 10.1109/TPWRS.2009.2030276.
16. “Load representation for dynamic performance analysis (of power systems),” in IEEE Transactions on Power Systems, vol. 8, no. 2, pp. 472–482, May 1993, doi: 10.1109/59.260837.
