Predictors of Self Assessed Support Needs in Women with Breast Cancer: A Classification Tree Model

Introduction: Evaluating predictors of the self-assessed support needs of women with breast cancer may guide care planning, counselling and education of the women. Therefore, this research was planned and studied. The researcher aimed to determine predictors of self-assessed support needs by classification tree in women with breast cancer. Methods: The sample consisted of 282 women with breast cancer. Data were collected by treatment characteristics and the self-assessed support needs of women with breast cancer scale in 2014. The researcher visited the oncology clinic two days (Monday and Saturday) in every week and conducted interviews with the patients. The participants read the questionnaire and they marked their answers on the sheets. The questionnaire took approximately 20 minutes to complete and could be understood by people with minimal reading ability. All of the participants completed the questionnaire. Results: The participants perceived the need for support needs in all categories; they expressed the highest support need in category of after care. Age of the women was important predictor for femininity and body image, and indirect effective on total support need in this study. Education level was an important predictor for information support need. Treatment characteristic was an important predictor for total support needs. Total demographic and disease/ treatment characteristics were predictor in 10% level for total support needs. Conclusions: The results of this study should increase awareness among cancer care professionals about a range of psychosocial needs.