乳腺癌
医学
社会认知理论
健康信念模型
认知
临床心理学
乳腺癌筛查
结构方程建模
癌症
肿瘤科
内科学
心理学
精神科
乳腺摄影术
健康教育
发展心理学
公共卫生
病理
统计
数学
作者
Ningning Lu,Chi Zhang,Hua You,Zhuyue Ma,Ping Zhu,Cheng Fang
出处
期刊:Cancer Nursing
[Lippincott Williams & Wilkins]
日期:2022-12-08
卷期号:47 (4): 271-280
被引量:3
标识
DOI:10.1097/ncc.0000000000001176
摘要
Background Breast cancer is the most common cancer in women, and first-degree relatives (FDRs) of breast cancer patients have a significantly higher risk of developing breast cancer. However, the factors affecting breast cancer screening behavior of FDRs in China remain unclear. Objective The aim of this study was to determine the social cognitive theory factors influencing screening behaviors of FDRs. Methods A cross-sectional survey was conducted, and 430 FDRs were recruited. Data were collected using demographic information and self-reported questionnaire based on the social cognitive theory. The structural equation modeling method was used to analyze the influence of social cognitive factors on breast cancer screening behavior. Results The model showed a good fit (goodness of fit = 0.462). Goal setting and self-regulation (β = 0.631, P < .001) and positive outcome expectation (β = 0.098, P = .042) were positively related to breast cancer screening behavior. Negative outcome expectation was negatively related to breast cancer screening behavior (β = −0.102, P = .024). In addition, positive outcome expectation, negative outcome expectation, and goal setting and self-regulation are mediators of self-efficacy (β = 0.475, P < .001) to breast cancer screening behavior. Conclusion Goal setting and self-regulation are important influences on breast cancer screening behavior. The social cognitive theory is both applicable to and effective in explaining and predicting breast cancer screening behavior. Implications for Practice Health professionals can develop appropriate intervention strategies based on the social cognitive theory among FDRs. It is necessary to focus on the people who influence women, such as spouses, mothers, or daughters.
科研通智能强力驱动
Strongly Powered by AbleSci AI