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. 2023 Aug;38(4):1277-1285.
doi: 10.1007/s13187-022-02260-x. Epub 2023 Jan 11.

The Characteristics of Asian American Breast Cancer Survivors with Low Quality of Life: a Decision Tree Analysis

Eun-Ok Im  1 , Jee-Seon Yi  2   3 , Wonshik Chee  2
Affiliations

The Characteristics of Asian American Breast Cancer Survivors with Low Quality of Life: a Decision Tree Analysis

Eun-Ok Im et al. J Cancer Educ. 2023 Aug.

Abstract

To provide appropriate and adequate information and support for Asian American breast cancer survivors, it would be essential to identify risk groups among them to target in future cancer education interventions. In this secondary analysis, the characteristics of risk groups within Asian American breast cancer survivors who had low quality of life were identified using a decision tree analysis. For this analysis, only the pre-test data of 185 women from a parent study were selected. Multiple instruments including the Functional Assessment of Cancer Therapy Scale-Breast Cancer (FACT-B) were used in the parent study. The data were analyzed using descriptive and inferential statistics and decision tree analyses. The decision tree analyses showed six combined characteristics associated with lower quality of life scores than the total mean quality of life scores. For instance, the women with lower quality of life scores (than the total mean quality of life scores) had high perceived barriers (cut point = 1.84), low self-efficacy for coping (cut point = 81.50), and high global symptom distress (cut point = 2.27). Also, the characteristics linked to the lowest quality life scores were different depending on the dimensions of the quality of life. The characteristics associated with the quality of life of Asian American breast cancer survivors need to be considered in future education programs for this specific population.

Keywords: Asian American; Breast Cancer; Decision Tree; Quality of Life; Survivors.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
The decision tree on the quality of life of the participants
See this image and copyright information in PMC

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