Zeng Jie Ye1, Chao Hua Peng2, Hao Wei Zhang3, Mu Zi Liang4, Jing Jing Zhao5, Zhe Sun6, Guang Yun Hu7, Yuan Liang Yu8. 1. Guangzhou University of Chinese Medicine, Guangzhou, Guangdong Province, 510006, China. Electronic address: zengjieye@qq.com. 2. School of Nursing, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong Province, 510006, China. 3. Harbin Medical University-Daqing, Daqing, Heilongjiang Province, 163319, China. 4. Guangzhou University of Chinese Medicine, Guangzhou, Guangdong Province, 510006, China. Electronic address: 1047052548@qq.com. 5. Department of Nursing, Chongqing Medical and Pharmaceutical College, Chongqing, Sichuan Province, 401331, China. 6. The First Affiliated Hospital, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong Province, 510405, China. 7. Guangdong Second Provincial Traditional Chinese Medicine Hospital, Guangzhou, Guangdong Province, 510095, China. 8. South China University of Technology, Guangzhou, Guangdong Province, 510641, China.
Abstract
PURPOSE: Patients diagnosed with breast cancer exhibited critical biopsychosocial functions following surgery or adjuvant treatment; therefore, it is important that they exhibit resilience. A Resilience Model for Breast Cancer (RM-BC) was developed using Chinese breast cancer patients to increase our understanding of how resilience outcomes are positively and negatively affected by protective and risk factors, respectively. METHODS: Chinese women with breast cancer completed the questionnaires within 1 week of beginning treatment. Exploratory Structural Equation Modeling was used to evaluate the RM-BC using a sample size of 342 patients. RESULTS: RM-BC suggested satisfactory goodness-of-fit indices and 67 percents of variance for resilience was explained. The Fit Indices for the measurement model were as follows: CFI = 0.909, GFI = 0.911, IFI = 0.897, NFI = 0.922, PNFI = 0.896, PCFI = 0.884, and RMSEA = 0.031. Three risk factors - emotional distress, physical distress, and intrusive thoughts - and four protective factors - self-efficacy, social support, courage-related strategy, and hope - were recognized. CONCLUSION: The resilience model allows for a better understanding of Chinese breast cancer patients' resilience integration while undergoing treatment and provides an effective structure for the development of resilience-focused interventions that are grounded in their experiences. A randomized trial has provided evidences of feasibility in Chinese women with breast cancer and the resilience model could be used as a useful framework for more resilience intervention in the future.
PURPOSE:Patients diagnosed with breast cancer exhibited critical biopsychosocial functions following surgery or adjuvant treatment; therefore, it is important that they exhibit resilience. A Resilience Model for Breast Cancer (RM-BC) was developed using Chinese breast cancerpatients to increase our understanding of how resilience outcomes are positively and negatively affected by protective and risk factors, respectively. METHODS: Chinese women with breast cancer completed the questionnaires within 1 week of beginning treatment. Exploratory Structural Equation Modeling was used to evaluate the RM-BC using a sample size of 342 patients. RESULTS: RM-BC suggested satisfactory goodness-of-fit indices and 67 percents of variance for resilience was explained. The Fit Indices for the measurement model were as follows: CFI = 0.909, GFI = 0.911, IFI = 0.897, NFI = 0.922, PNFI = 0.896, PCFI = 0.884, and RMSEA = 0.031. Three risk factors - emotional distress, physical distress, and intrusive thoughts - and four protective factors - self-efficacy, social support, courage-related strategy, and hope - were recognized. CONCLUSION: The resilience model allows for a better understanding of Chinese breast cancerpatients' resilience integration while undergoing treatment and provides an effective structure for the development of resilience-focused interventions that are grounded in their experiences. A randomized trial has provided evidences of feasibility in Chinese women with breast cancer and the resilience model could be used as a useful framework for more resilience intervention in the future.
Authors: Mu Zi Liang; Ying Tang; M Tish Knobf; Alex Molassiotis; Peng Chen; Guang Yun Hu; Zhe Sun; Yuan Liang Yu; Zeng Jie Ye Journal: J Cancer Surviv Date: 2022-08-06 Impact factor: 4.062
Authors: Francesca Chiesi; Deborah Vizza; Moira Valente; Rosy Bruno; Chloe Lau; Maria Rosita Campagna; Melania Lo Iacono; Francesco Bruno Journal: Support Care Cancer Date: 2022-05-17 Impact factor: 3.359