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作者

Shuyun Yang Ying Wang Guijie Guo Haiyang Chu Dong Kong Liping Chen

作者单位

Road, Huaiyin District, Jinan, 250000, China ³The Affiliated Hospital of Qingdao University, 16 Jiangsu Road, Shinan District, Qingdao, 266000, China We ²co-first author ¹School of Nursing, Shandong First Medical University & Shandong Academy of Medical Sciences, 619 Changcheng Road, Daiyue District, Taian, 271000, China ⁴Nursing Department, Affiliated Provincial Hospital of Shandong First Medical University, 324 Jin

刊名

European Journal of Oncology Nursing

年份

2026

卷号

Vol.81

页码

103165

ISSN

1462-3889

关键词

Back propagation neural network Body image Breast cancer Emotion Latent profile analysis.

摘要

Purpose This study uses latent profile analysis to explore the latent characteristics of body image and emotional response in postoperative breast cancer patients and its influencing factors. Methods From November 2023 to April 2024, a convenience sampling method was used to select 338 postoperative breast cancer patients for the study. A general information section, Chinese version of the Body Image and Relationships Scale, Positive and Negative Affect Scale, Impact on Participation and Autonom...更多

Purpose This study uses latent profile analysis to explore the latent characteristics of body image and emotional response in postoperative breast cancer patients and its influencing factors. Methods From November 2023 to April 2024, a convenience sampling method was used to select 338 postoperative breast cancer patients for the study. A general information section, Chinese version of the Body Image and Relationships Scale, Positive and Negative Affect Scale, Impact on Participation and Autonomy, Social Support Rating Scale, and Medical Coping Mode Questionnaire were used to conduct the survey. Conducted latent profile analysis of body image and emotional response characteristics of postoperative breast cancer patients identified the influencing factors of their latent profiles through univariate and multivariate logistic stepwise regression analyses and combined with back propagation neural network. Results Three latent categories were identified: mild body image concerns with emotion stability group , social-physical distress with emotion containment group , and pronounced appearance-social barriers and affect ambivalence group . The results of multivariate logistic stepwise regression and BPNN showed that the factors influencing the body image and emotional response patterns of postoperative breast cancer patients were, in descending order of importance: confrontation, resignation, social participation, social support, and chemotherapy. Conclusions Most postoperative breast cancer patients belonged to the social-physical distress with emotion containment group. Clinical staff should focus on the patients in the pronounced appearance-social barriers and affect ambivalence group, strengthening the core coping patterns of “Confrontation” and “Resignation”.收起

文献类型

期刊