Work

Educational differences in anxiety–depression symptom networks among Chinese women with breast cancer: A network comparison with simulation-guided intervention targets

Year: 2025

Type: article

Abstract: To examine whether anxiety-depression symptom networks differ by education levels among Chinese women with breast cancer and to identify subgroup-specific intervention targets. Using cross-sectional data from 414 patients with breast cancer, we estimated Gaussian graphical models (GGMs) separately for lower- and higher-education groups. We evaluated central and bridge symptoms, compared networks using permutation-based Network Comparison Tests, and conducted simulation-based intervention analyses to identify symptoms whose hypothetical improvement would most reduce overall symptoms. “ Cheerful” (H6) was the most central symptom in both education groups. Bridge symptoms diverged: the lower-education network was bridged primarily by “worried” (H5), whereas in the higher-education network “cheerful” (H6) served a dual core-bridge role. Global network strength did not differ significantly between groups, yet 11 individual edges did, including 8 cross-construct (anxiety-depression) connections. Simulation analyses suggested different leverage points by education: improving “optimistic” (H12) produced the largest downstream symptom reductions in the lower-education group, while targeting “frightened” (H3) was most effective in the higher-education group. Although core anxiety-depression architecture is similar across education levels, bridge structure and optimal intervention targets differ. Tailoring psychosocial care by educational backgrounds, emphasizing optimism-building in lower-education patients and fear-reduction in higher-education patients, may enhance treatment efficacy.

Source: Measurement and Evaluations in Cancer Care

DOI: 10.1016/j.ymecc.2025.100021

Authors: Ying Xiong, Hongman Li, Miao Yu, Jiaying Li, Zengjie Ye

Institutions: Guangzhou University of Chinese Medicine, Johns Hopkins University, Chinese University of Hong Kong, Guangzhou Medical University

Language: English

Topic: Cancer survivorship and care

Subfield: Oncology

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: hybrid

Estimated APC paid: $1,740