The longitudinal relationship between the achievement of successful aging and its influencing factors: a cross-lagged panel network analysis
As the population ages rapidly, the concept of successful aging has emerged as a significant subject of discussion. However, the multidimensional nature of its connotation, the complexity of its influencing factors, and the challenges in comparing the relative impact of each factor present significa...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-07-01
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| Series: | Acta Psychologica |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S0001691825004597 |
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| Summary: | As the population ages rapidly, the concept of successful aging has emerged as a significant subject of discussion. However, the multidimensional nature of its connotation, the complexity of its influencing factors, and the challenges in comparing the relative impact of each factor present significant obstacles to the development of effective interventions. Meanwhile, the interaction mechanism between the influencing factors and the elements of successful aging needs to be further clarified. Grounded in the ecosystem theory, this study utilizes the China Health and Retirement Longitudinal Study (CHARLS) data from 2018 and 2020, and for the first time adopts the cross-lagged panel network analysis method to explore in-depth the dynamic relationship between influencing factors and successful aging. The findings indicate that various influencing factors impact successful aging through distinct contexts and mechanisms. Among them, health insurance is a key factor influencing the realization of successful aging, with positive predictive effects, especially on life satisfaction and self-rated health among older adults. These findings offer valuable insights into the intricate mechanisms underpinning the achievement of successful aging and provide a robust scientific foundation for the development and implementation of effective, targeted interventions. |
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| ISSN: | 0001-6918 |