To explore the categories of decision fatigue in young and middle-aged breast cancer patients,analyze their influencing factors,and construct a Nomogram model.

A total of 188 young and middle-aged breast cancer patients admitting to our hospital were selected as the study subjects by a convenience sample method from June 2023 to January 2025.The patients were surveyed using a general information questionnaire,the Decision Fatigue Scale,the Chinese version of the Decision Self-Efficacy Scale,the Decision Preparation Scale,and the Family Care Index.A latent class growth model was used to identify the categories of decision fatigue among patients. Logistic regression analysis was employed to screen for factors influencing decision fatigue categories.The R 4.2.1 software was used to construct a Nomogram model.The predictive performance of the Nomogram model was evaluated.

The decision fatigue score of young and middle-aged breast cancer patients was 17.74±2.63.Two categories were identified,namely a low decision fatigue group(70.2%) and a high decision fatigue group(29.8%).Age,education level,average monthly household income,awareness of specific tumor stage,whether radiotherapy or chemotherapy had been received,family care index,decision preparation score,and decision self-efficacy score were all influencing factors for decision fatigue categories in young and middle-aged breast cancer patients(P<0.05).A Nomogram model for predicting the risk of high decision fatigue in young and middle-aged breast cancer patients was constructed based on the influencing factors.The area under the receiver operating characteristic curve was 0.864,with a sensitivity of 87.50% and a specificity of 77.42%.The calibration curve approached the ideal curve.The net benefit value of the model was positive when the threshold probability ranged from 2% to 97%.

The level of decision fatigue in young and middle-aged breast cancer patients is relatively higher.Decision preparation and decision self-efficacy could influence decision fatigue categories.The Nomogram constructed in this study is beneficial for identifying patients with high decision fatigue.