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ABSTRACT
Recently, there has been growing concern regarding social capital, one of the social factors predicting depression in the older adults. However, previous studies related to the relationship between social capital and depression have focused only on one-way causal relationships, making it difficult to identify cause and effect variables clearly, and there have been insufficient studies validating the mutual causal relationship between the two types of variables. Therefore, this study analyzed the mutual causal relationship between social capital and depression in the older adults using an autoregressive cross-lagged model. We analyzed data from the Korea Welfare Panel Study (KoWePS), including 1,907 people (698 males and 1,209 females) aged 65 or over. As a result of the analysis, we found that social capital and depression in the older adults had a reciprocal causal relationship. In other words, a decrease in social capital in the older adults increased depression, while an increase in depression led to a decrease in social capital. Based on the results, we suggest several practical implications.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Notes
1. Verification of metric invariance is conducted to verify whether the concepts measured at each time point are the same or change over time in longitudinal studies. If metric invariance is established, it means that the respondents have identical interpretations of the contents of the measurement variables over time.
2. Verification of path invariance consists of verification of autoregressive coefficients measuring the same concept and verification of cross-lagged coefficients between variables measuring different concepts. Verification of path invariance is to verify that the regression coefficients are the same over time, verifying that the variables at a previous point in time have the same effect on the variables at the next point in time.
3. In a longitudinal study, by fixing the covariance with the error set at each time point, it is possible to verify whether the relevance of the variable is coincidental or truly meaningful as time changes.
4. The competitive model is established to verify metric invariance, path invariance, and error covariance equality, which are verified by comparing the previous assumptions with the goodness of fit of the satisfied model.