The network structure of self-compassion in older adults with different productive engagement patterns

Abstract Self-compassion has gained attention as an important factor for mental health. However, research on self-compassion in older adults is limited. This study aims to reveal the interactions among six self-compassion components in older adults and examine how productive engagement influences th...

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Main Authors: Huinan Hu, Grand H.-L. Cheng, Stephen Cheong Yu Chan, Eddie S. K. Chong, Peiyi Lu, H. N. Cheung
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
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Online Access:https://doi.org/10.1038/s41598-025-08157-1
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Summary:Abstract Self-compassion has gained attention as an important factor for mental health. However, research on self-compassion in older adults is limited. This study aims to reveal the interactions among six self-compassion components in older adults and examine how productive engagement influences these components. A total of 807 older adults aged 55 and older in Hong Kong (67% females) participated in the study. They reported their self-compassion and productive engagement through questionnaires. Latent class analysis (LCA) was used to identify different patterns of productive engagement. The EBICglasso method estimated the self-compassion network for the overall sample and for different productive engagement patterns. The LCA results identified a group with low productive engagement (low productive engagement group) and three groups with engagement in certain productive activities (productive engagement group). The network analysis found that isolation was the central component in the overall sample and in the low productive engagement group. Mindfulness was the central component in the productive engagement group. A dual effect of productive engagement group reported that while it may enhance mindfulness, it might also contribute to the feeling of isolation. Further research is needed to explore these relationships in diverse sociocultural settings.
ISSN:2045-2322