Media exposure and the trajectory of depression in older adults: An analysis based on latent variable growth models

This study aims to understand the developmental trajectory of media exposure and depression in the older adults Chinese population and explore the associated influencing factors. This research seeks to establish a scientific basis for preventing and treating depression in older adults.

Data were sourced from the Chinese Longitudinal Aging Social Survey (CLASS) database. We selected survey data from 2016, 2018, and 2020, focusing on participants who fully completed the depression status panel and three interviews, totaling 5,496 older adults. First, demographic variables were analyzed for descriptive statistics using SPSS 27.0, and Pearson correlation analyses of media exposure, marital status, and depression were conducted at the three time points. Second, using unconditional least squares, we estimated parameters for potential change trajectories in media exposure, marital status, and depression status among older adults, excluding covariates. Finally, latent variable growth models were constructed using Mplus 8.0 to test the developmental trajectories of media exposure and depression status among older adults, and we reported cross-sectional and prospective cross-lag correlations and ran baseline-adjusted two-wave lagged regressions in both directions as sensitivity analyses.

The unconditional least squares analysis revealed significant differences in initial media exposure (Ψ₁ = 3.655) and its growth rate (Ψ₂ = 1.504, p < 0.001), initial marital status (Ψ₁ = 0.123) and its growth rate (Ψ₂ = 0.009, p < 0.001), as well as in initial depression levels (Ψ₁ = 4.852) and their growth rate (Ψ₂ = 2.655, p < 0.001) among older adults. The latent variable growth model indicated a negative correlation between the intercept and slope of depression (β = -0.227, p < 0.001) and media exposure (β = -0.423, p < 0.001) in older adults. Regarding demographic characteristics, age, residence, and marital status significantly influenced the initial level of depression (p < 0.001), while gender, age, education, and residence significantly affected the slope of depression levels (p < 0.05). Additionally, the regression analysis showed that the intercept of media exposure significantly influenced the depression intercept in older adults (β = -0.373, p < 0.001), and the slope of media exposure significantly affected the slope of depression (β = -0.319, p < 0.001). Cross-lag zero-order correlations were small and mixed, baseline-adjusted two-wave lagged tests yielded similarly small effects in both directions, consistent with the parallel-process growth findings.

Over time, media exposure in the older adults gradually decreases while their level of depression gradually increases. Therefore, it is crucial for society to monitor the media exposure and depression levels of the older adults, utilizing various media forms to prevent and alleviate their depression. For instance, creating new media platforms can enhance the older adults's media exposure, and balanced publicity should be maintained to ensure equitable information acquisition and communication during their media engagement. Additionally, considering the varied depression levels among different groups of the older adults, interventions should specifically target those who are older, live in rural areas, are without partners, and have lower education levels. Implementing these measures is vital for improving depression in older individuals and promoting healthy aging.