Illness cognition, dyadic coping, and marital quality networks in young and middle-aged colorectal cancer patients and their spouses: a computer-simulated analysis

This study employed network analysis integrating Gaussian graphical models, Bayesian directed acyclic graphs, and computer-simulated interventions to construct an “illness cognition, dyadic coping, and marital quality” network model for young and middle-aged colorectal cancer (CRC) patients and their spouses, aiming to identify role-specific intervention targets for improving marital quality. A total of 522 patient–spouse dyads were recruited from two tertiary hospitals in Guangzhou, China (May 2023–January 2024). Illness cognition, dyadic coping, and marital quality were assessed using validated self-report instruments. Gaussian graphical models (GGMs) were estimated to characterize the individual patient, individual spouse, and integrated dyadic network structures. Bayesian networks were used to identify conditional dependency patterns, and computer-simulated intervention analyses were performed to identify potential intervention targets. Supportive coping emerged as the most central node across the individual patient, individual spouse, and integrated dyadic networks. Bridge centrality analysis identified spouse and patient negative coping, together with spouse and patient marital satisfaction, as the primary bridge nodes. Bayesian network analysis revealed conditional dependency patterns among illness cognition, dyadic coping, and marital quality. In computer-simulated interventions, spousal consistency was the most influential target for patients (B = 0.843; projected improvement = 19.25%), whereas supportive coping was the most influential target for spouses (projected improvement = 13.97%). This study identified illness cognition as a conditional antecedent of marital quality via dyadic coping, with supportive coping occupying a central position in both partners’ networks. Computer-simulated interventions identified spousal consistency and supportive coping as the optimal targets for improving marital quality in patients and spouses, respectively. These findings provide a data-driven foundation for developing tailored, role-differentiated couple-based psychosocial interventions in young and middle-aged CRC populations.

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Journal
BMC Psychology
Published
2026-10-26
DOI
https://doi.org/10.1186/s40359-026-05701-0
Primary Topic
Cancer survivorship and care
Type
article
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article

Illness cognition, dyadic coping, and marital quality networks in young and middle-aged colorectal cancer patients and their spouses: a computer-simulated analysis

K.C. Ho, Hui Zhao, Qian Sun, Ting Luo et al.
4 links
BMC Psychology
Cancer survivorship and care
article

Illness cognition, dyadic coping, and marital quality networks in young and middle-aged colorectal cancer patients and their spouses: a computer-simulated analysis

K.C. Ho, Hui Zhao, Qian Sun, Ting Luo, Yonghe Chen, Junsheng Peng, Peirong Xu, Lijun Li, Panpan Xiao
article en

Abstract

This study employed network analysis integrating Gaussian graphical models, Bayesian directed acyclic graphs, and computer-simulated interventions to construct an “illness cognition, dyadic coping, and marital quality” network model for young and middle-aged colorectal cancer (CRC) patients and their spouses, aiming to identify role-specific intervention targets for improving marital quality. A total of 522 patient–spouse dyads were recruited from two tertiary hospitals in Guangzhou, China (May 2023–January 2024). Illness cognition, dyadic coping, and marital quality were assessed using validated self-report instruments. Gaussian graphical models (GGMs) were estimated to characterize the individual patient, individual spouse, and integrated dyadic network structures. Bayesian networks were used to identify conditional dependency patterns, and computer-simulated intervention analyses were performed to identify potential intervention targets. Supportive coping emerged as the most central node across the individual patient, individual spouse, and integrated dyadic networks. Bridge centrality analysis identified spouse and patient negative coping, together with spouse and patient marital satisfaction, as the primary bridge nodes. Bayesian network analysis revealed conditional dependency patterns among illness cognition, dyadic coping, and marital quality. In computer-simulated interventions, spousal consistency was the most influential target for patients (B = 0.843; projected improvement = 19.25%), whereas supportive coping was the most influential target for spouses (projected improvement = 13.97%). This study identified illness cognition as a conditional antecedent of marital quality via dyadic coping, with supportive coping occupying a central position in both partners’ networks. Computer-simulated interventions identified spousal consistency and supportive coping as the optimal targets for improving marital quality in patients and spouses, respectively. These findings provide a data-driven foundation for developing tailored, role-differentiated couple-based psychosocial interventions in young and middle-aged CRC populations.

BMC Psychology
Hong Kong Polytechnic University (HK), Sun Yat-sen University (CN), Chinese University of Hong Kong (HK), Sixth Affiliated Hospital of Sun Yat-sen University (CN), Sun Yat-sen University Cancer Center (CN), State Key Laboratory of Oncology in South China (CN), Monash University (AU)
Good health and well-being
Openalex Percentile: Top 17%
Cancer survivorship and care
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