A structural equation modeling analysis of successful aging in older adults with osteoarthritis: A cross-sectional descriptive study
Year: 2025
Type: article
Study design: Observational Study
Abstract: Purpose: This study was designed to construct and test a structural model of successful aging in older adults with osteoarthritis using the selection, optimization, and compensation (SOC) strategy, and to identify the direct and indirect effects of various influencing factors. Methods: Physical factors, depression, healthcare provider, and family support were set as exogenous variables. Endogenous outcomes were the SOC strategy and successful aging. The 220 study participants were older adults (aged ≥65 years) and had degenerative osteoarthritis. Data were collected with a structured questionnaire administered between December 2019 and February 2020. Subsequently, the data were analyzed, and a hypothetical model was tested. The data were analyzed using SPSS Ver. 25.0 and AMOS Ver. 20. Results: Nine paths of the hypothetical model were changed to six modified routes, and a simple modified model was defined as this study’s final modified model, including increasing the goodness-of-fit. Variables influencing successful aging were depression (β=-.70, p=.002), healthcare provider support (β=.20, p=.002), family support (β=.14, p=.041), and the SOC strategy (β=.21, p=.020). For depression, the direct effect (β=-.70, p=.002), the indirect effect (β=-.07, p=.001), and the total effect (β=-.77, p=.006) on successful aging were statistically significant. For healthcare provider support, it was noted that the direct effect (β=.20, p=.002), the indirect effect (β=.02, p=.044), and the total effect (β=.23, p=.022) on successful aging were statistically significant. Conclusion: It is important to reduce depression and promote healthcare provider support for successful aging in older adults with osteoarthritis using the SOC strategy.
Author: Jeong Hwa Kum
Institution: Gimcheon University
Language: English
Field: Psychology
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W4410873289