유방암 생존자의 우울예측요인
Predictive Factors for Depression in Breast Cancer Survivors
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초록
Purpose: This study was to identify the predictive factors for depression in breast cancer survivors. Methods: The participants were 180 female survivors who visited outpatient clinics after mastectomy or partial resection for breast cancer and had completed adjuvant treatment such as chemotherapy and/or radiation therapy at a university hospital and a general hospital. Data were collected utilizing the Zung depression scale, the Mishel uncertainty scale, the Fitts & Osgoods body image scale, and the Zimet social support scale. Results: The level of depression in the participants was moderate. There were significant correlations among depression, body image, uncertainty, and social support. There were significant differences in depression by education, economic state, perceived health status, fatigue, and pain. In regression analysis, the most powerful predictor of depression was body image (40%). Overall, body image, fatigue, social support, and uncertainty explained 62% of the variance of depression in the participants. Conclusion: Body image, fatigue, social support, and uncertainty were important predictors of depression. These results demonstrate the need for interventions to manage depression in breast cancer survivors.
Abstract
Purpose: This study was to identify the predictive factors for depression in breast cancer survivors. Methods: The participants were 180 female survivors who visited outpatient clinics after mastectomy or partial resection for breast cancer and had completed adjuvant treatment such as chemotherapy and/or radiation therapy at a university hospital and a general hospital. Data were collected utilizing the Zung depression scale, the Mishel uncertainty scale, the Fitts & Osgoods body image scale, and the Zimet social support scale. Results: The level of depression in the participants was moderate. There were significant correlations among depression, body image, uncertainty, and social support. There were significant differences in depression by education, economic state, perceived health status, fatigue, and pain. In regression analysis, the most powerful predictor of depression was body image (40%). Overall, body image, fatigue, social support, and uncertainty explained 62% of the variance of depression in the participants. Conclusion: Body image, fatigue, social support, and uncertainty were important predictors of depression. These results demonstrate the need for interventions to manage depression in breast cancer survivors.
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