Interactive Relationships in Marital Attachment: A Cross‐Lagged Panel Network Analysis

Attachment theory is one of the key frameworks for understanding close relationships, yet how marital attachment interacts within a dyadic context remains unclear. Using two-wave longitudinal data with a 6-month interval collected from 501 heterosexual spousal pairs, the present study examined interactive relationships in marital attachment within a dyadic context through cross-lagged panel network (CLPN) analysis. Firstly, the results found that wives' attachment components more strongly predicted husbands' attachment components within CLPN. Secondly, wives' attachment avoidance component, not show feel deep down, more strongly predicted other components and husbands' components within CLPN. Finally, bidirectional associations were observed between wives' and husbands' attachment avoidance components. These findings deepen our understanding of marital attachment interactions and offer practical insights for marital and family practices aimed at improving marital relationships.

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Publication Details

Journal
International Journal of Psychology
Published
2026-02-02
DOI
https://doi.org/10.1002/ijop.70180
Primary Topic
Attachment and Relationship Dynamics
Type
article
Field-Weighted Citation Impact
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article

Interactive Relationships in Marital Attachment: A Cross‐Lagged Panel Network Analysis

Menghao Ren, Fan Yang, Xiaohang Luo, Yu Xia et al.
International Journal of Psychology
Attachment and Relationship Dynamics
article

Interactive Relationships in Marital Attachment: A Cross‐Lagged Panel Network Analysis

Menghao Ren, Fan Yang, Xiaohang Luo, Yu Xia, Xinyi Wei
article en

Abstract

Attachment theory is one of the key frameworks for understanding close relationships, yet how marital attachment interacts within a dyadic context remains unclear. Using two-wave longitudinal data with a 6-month interval collected from 501 heterosexual spousal pairs, the present study examined interactive relationships in marital attachment within a dyadic context through cross-lagged panel network (CLPN) analysis. Firstly, the results found that wives' attachment components more strongly predicted husbands' attachment components within CLPN. Secondly, wives' attachment avoidance component, not show feel deep down, more strongly predicted other components and husbands' components within CLPN. Finally, bidirectional associations were observed between wives' and husbands' attachment avoidance components. These findings deepen our understanding of marital attachment interactions and offer practical insights for marital and family practices aimed at improving marital relationships.

International Journal of PsychologyVol. 61(2)
Chongqing Normal University (CN), Waseda University (JP), University of Georgia (US), Hunan Normal University (CN), Harvard University Press (US), Changsha Normal University (CN), Chengdu University (CN), University of Pennsylvania (US)
Openalex Percentile: Top 74%
Attachment and Relationship Dynamics
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