Skip to main content
editor@theusajournals.com | Oscar Publishing Services Journal Home
Login

American Journal of Applied Science and Technology

Peer Reviewed | Open Access | E-ISSN: 2771-2745
Published Article

Emotional Resilience and Social Adaptation in Older Adults Across India: A Descriptive Investigation

Emotional Resilience and Social Adaptation in Older Adults Across India: A Descriptive Investigation

Authors

  • Dr. A. Wanjiku
    Institute of Technology, Kenya

Keywords:

Emotional Resilience Social Adaptation Elderly Population Aging in India

Abstract

The rapid demographic transition toward an aging population in India has intensified the need to understand psychological well-being among older adults, particularly in terms of emotional resilience and social adaptation. This study presents a descriptive investigation into the mechanisms through which elderly individuals maintain emotional stability and adapt to evolving social environments. The research integrates interdisciplinary perspectives, combining psychosocial theories with insights from technological and adaptive system frameworks to construct a multidimensional understanding of resilience.

Grounded in resilience theory and supported by empirical findings from Agarwal et al. (2023), the study conceptualizes emotional resilience as a dynamic capability shaped by cognitive, physiological, and social variables. Social adaptation is examined as a process of behavioral adjustment within shifting familial and societal structures, particularly in the context of urbanization and changing support systems in India.

The methodology employs an observational analytical approach, synthesizing patterns across existing literature to identify key determinants influencing resilience and adaptation. These include cognitive flexibility, emotional regulation, environmental support, and access to technological resources. Additionally, the study explores parallels between adaptive human behavior and technological systems such as neural networks, highlighting how feedback mechanisms enhance learning and adjustment.

Findings indicate that emotional resilience significantly enhances the ability of older adults to navigate social changes, mitigate stress, and maintain psychological equilibrium. The research also reveals that technological and community-based interventions can play a crucial role in strengthening adaptive capacities.

The study concludes by proposing an integrated framework that aligns emotional resilience with social adaptation processes, offering both theoretical and practical implications. It contributes to the discourse on aging by emphasizing the importance of holistic strategies that incorporate psychological, social, and technological dimensions, while identifying areas for future empirical research.

References

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

Aliaksei Severyn and Alessandro Moschitti. Twitter sentiment analysis with deep convolutional neural networks. In Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval, pages 959–962, 2015.

D. Tilman, K. G. Cassman, P. A. Matson, R. Naylor, and S. Polasky, “Agricultural sustainability and intensive production practices,” Nature, vol. 418, no. 6898, pp. 671–677, 2002.

Dat T Nguyen, Ferda Ofli, Muhammad Imran, and Prasenjit Mitra. Damage assessment from social media imagery data during disasters. In Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2017, pages 569–576, 2017.

Dat Tien Nguyen, Kamela Ali Al Mannai, Shafiq Joty, Hassan Sajjad, Muhammad Imran, and Prasenjit Mitra. Rapid classification of crisis-related data on social networks using convolutional neural networks. arXiv preprint arXiv: 1608.03902, 2016.

Dat Tien Nguyen, Kamela Ali Al Mannai, Shafiq Joty, Hassan Sajjad, Muhammad Imran, and Prasenjit Mitra. Robust classification of crisis-related data on social networks using convolutional neural networks. In Eleventh International AAAI Conference on Web and Social Media, pages 632–635, 2017.

L. Rickards and S. M. Howden, “Transformational adaptation: agriculture and climate change,” Crop and Pasture Science, vol. 63, no. 3, pp. 240–250, 2012.

Muhammad Imran, Prasenjit Mitra, and Carlos Castillo. Twitter as a lifeline: Human-annotated twitter corpora for nlp of crisis-related messages. arXiv preprint arXiv: 1605.05894, 2016.

Muhammad Imran, Shady Elbassuoni, Carlos Castillo, Fernando Diaz, and Patrick Meier. Practical extraction of disaster-relevant information from social media. In Proceedings of the 22nd International Conference on World Wide Web, pages 1021–1024, 2013.

R. Few, D. Morchain, D. Spear, A. Mensah, and R. Bendapudi, “Transformation, adaptation and development: relating concepts to practice,” Palgrave Communications, vol. 3, p. 17092, 2017.

R. W. Kates, W. R. Travis, and T. J. Wilbanks, “Transformational adaptation when incremental adaptations to climate change are insufficient,” Proceedings of the National Academy of Sciences, vol. 109, no. 19, pp. 7156–7161, 2012.

Yaqing Wang, Fenglong Ma, Zhiwei Jin, Ye Yuan, Guangxu Xun, Kishlay Jha, Lu Su, and Jing Gao. Eann: Event adversarial neural networks for multi-modal fake news detection. In Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery Data Mining, pages 849–857. ACM, 2018.

Yann LeCun, Yoshua Bengio, and Geoffrey Hinton. Deep learning. Nature, 521 ( 7553 ): 436–444, 2015.