Prediction of Distress Tolerance in Patients with Breast Cancer based on Anger Rumination and Physical Health: Using an Artificial Neural Network

Abstract

Background: Breast cancer is a common cancer in women, causing significant psychological consequences. Traditionally, researchers have relied on statistical methods to predict factors influencing distress in cancer patients. However, this study explores the potential of artificial neural networks (ANNs) as a novel approach for predicting distress tolerance in women with breast cancer. This study aims to explore the use of ANNs in predicting distress tolerance in women with breast cancer, based on anger rumination and physical health. Methods: The research method was descriptive and correlational. The statistical population of this study consisted of 207 women with breast cancer admitted to the hematology oncology department of Shafa Hospital in Ahvaz in 2023, selected using convenience sampling. Data were collected using Distress Tolerance Scale (DTS), Anger Rumination Scale (ARS), and Physical Health Questionnaire (PHQ). Data analysis involved Pearson correlation coefficient and ANN. SPSS-27 was used for initial analyses and MATLAB-2019 was used for ANN modeling. Results: The results showed a negative relationship between anger rumination and distress tolerance, and a positive one between physical health and distress tolerance in women with breast cancer (P < 0.001). Furthermore, a significant correlation was found among anger rumination, physical health, and distress tolerance in these women (P < 0.001). The ANN analysis also highlighted that anger rumination had the most significant connection with distress tolerance in the patients, with physical health following in the next stage. Conclusion: This study identified significant associations between anger rumination, physical health, and distress tolerance in women with breast cancer. These findings add to understanding distress tolerance in women with breast cancer, emphasizing the need to address psychological and physical health in interventions to improve well-being.