ArticlePloS one2026
Gender differences in the relationship between adult attachment and self-identity: A network analysis research among Chinese college students.
Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
objectiveThis study aims to investigate the relationship between adult attachment and self-identity among Chinese college students using network analysis, with a specific focus on examining gender differences in network structure, global strength. and edge strength.
methodsA convenience sampling method was employed, and a total of 624 university students from China were surveyed using the Experiences in Close Relationships Inventory and the Self-Identity Questionnaire developed by Chinese scholars. Network analysis was conducted to estimate the structure of adult attachment and self-identity, identify central and bridge symptoms, and examine gender differences in network structure, global strength, and edge strength.
resultsThe self-identity items formed a tightly connected cluster. Temporal disintegration constituted the core node bridging adult attachment and self-identity networks, followed by identity diffusion. Attachment anxiety was the strongest bridge node connecting adult attachment to self-identity, primarily associating with temporal disintegration. Network invariance test indicated no significant gender differences. Global strength invariance test was significantly higher in females than in males. Edge strength invariance test revealed that there were significant differences in the strength of some edges between males and females.
conclusionIn the adult attachment and self-identity network, temporal disintegration and identity diffusion serve as core nodes, around which close clusters form. Attachment anxiety serving as the key bridge. Although the network structure is similar across genders, females show significantly stronger overall network connectivity. These findings highlight the importance of examining both local and global metrics when studying group differences in psychological networks.
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