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A Decision Tree Model for Breast Reconstruction of Women with Breast Cancer: A Mixed Method Approach
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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8036358/ https://www.ncbi.nlm.nih.gov/pubmed/33808263 http://dx.doi.org/10.3390/ijerph18073579 |
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author | Park, Eun Young Yi, Myungsun Kim, Hye Sook Kim, Haejin |
author_facet | Park, Eun Young Yi, Myungsun Kim, Hye Sook Kim, Haejin |
author_sort | Park, Eun Young |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-8036358 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-80363582021-04-12 A Decision Tree Model for Breast Reconstruction of Women with Breast Cancer: A Mixed Method Approach Park, Eun Young Yi, Myungsun Kim, Hye Sook Kim, Haejin Int J Environ Res Public Health Article 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. MDPI 2021-03-30 /pmc/articles/PMC8036358/ /pubmed/33808263 http://dx.doi.org/10.3390/ijerph18073579 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Park, Eun Young Yi, Myungsun Kim, Hye Sook Kim, Haejin A Decision Tree Model for Breast Reconstruction of Women with Breast Cancer: A Mixed Method Approach |
title | A Decision Tree Model for Breast Reconstruction of Women with Breast Cancer: A Mixed Method Approach |
title_full | A Decision Tree Model for Breast Reconstruction of Women with Breast Cancer: A Mixed Method Approach |
title_fullStr | A Decision Tree Model for Breast Reconstruction of Women with Breast Cancer: A Mixed Method Approach |
title_full_unstemmed | A Decision Tree Model for Breast Reconstruction of Women with Breast Cancer: A Mixed Method Approach |
title_short | A Decision Tree Model for Breast Reconstruction of Women with Breast Cancer: A Mixed Method Approach |
title_sort | decision tree model for breast reconstruction of women with breast cancer: a mixed method approach |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8036358/ https://www.ncbi.nlm.nih.gov/pubmed/33808263 http://dx.doi.org/10.3390/ijerph18073579 |
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