A Decision Tree Model for Breast Reconstruction of Women with Breast Cancer: A Mixed Method Approach

Eun Young Park, Myungsun Yi, Hye Sook Kim and Haejin Kim
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Eun Young Park: College of Nursing, Gachon University, Incheon 21936, Korea
Myungsun Yi: College of Nursing, Seoul National University, Seoul 03080, Korea
Hye Sook Kim: Department of Nursing, Suwon Science College, Suwon 18516, Korea
Haejin Kim: Department of Nursing, Suwon Women’s University, Suwon 16632, Korea

IJERPH, 2021, vol. 18, issue 7, 1-13

Abstract: The number of breast reconstructions following mastectomy has increased significantly during the last decades, but women are experiencing a number of conflicts with breast reconstruction decisions. The aim of this study was to develop a decision tree model of breast reconstruction and to examine its predictability. Mixed method design using ethnographic decision tree modeling was used. In the qualitative stage, data were collected using individual and focus group interviews and analyzed to construct a decision tree model. In the quantitative stage, the questionnaire was developed questions based on the criteria identified in the qualitative stage. A total of 61 women with breast cancer participated in 2017. Five major criteria: recovery of body image; impact on recurrence; recommendations from others; financial resources; and confirmation by physicians. The model also included nine predictive pathways. It turns out that the model predicted 90% of decisions concerning whether or not to have breast reconstruction. The findings indicate that the five criteria play a key role in decision-making about whether or not to have breast reconstruction. Thus, more comprehensive issues, including these five criteria, need to be integrated into an intervention for women with breast cancer to make their best decision on breast reconstruction.

Keywords: breast cancer; decision-making; ethnography; mixed method design; breast reconstruction; decision tree model (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2021
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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