Objectives
Self-compassion has gained researchers’ attention in recent years, yet up to now there is no evidence concerning how the six different components of self-compassion interact with mental health, such as depression and anxiety in older people. Network analysis provides approaches to investigate such detailed associations among those variables in a more meticulous way. The current study aimed to model a cross-lagged network of components of self-compassion, depression, and anxiety with longitudinal data to unveil their temporal relationships among seniors.
Method
A sample of 345 community-dwelling elderly individuals (mean age = 83.81, 44.9% male) in Nanjing, China, was assessed with the Self-Compassion Scale and Depression Anxiety Stress Scales-21 three times with an interval of 6 months in between. Two cross-lagged panel networks were examined to model the temporal associations among elements of self-compassion, depression, and anxiety.
Results
The T1–T2 Network yielded two notable cross-lagged edges while the T2–T3 Network yielded five notable edges. Centrality analysis identified depression to be the most influential in both networks, while common humanity and over-identification showed a high inclination of both influencing and being influenced by other variables in the two networks.
Conclusions
The study not only provided some evidence for the tendency for these elements of self-compassion to covary, but also found an unusually positive relationship between the positive components of self-compassion and anxiety, and those relations were rather unstable, highlighting the need for future studies to replicate these findings. The high influence of depression in the two networks and the complicated role of common humanity and over-identification also need further exploration into their mechanisms.
Preregistration
This study is not preregistered.