关键词: 无尿意排尿行为, 护士, 职业紧张, 预测模型

Abstract: Objective: To explore the status quo of female nurses′ unintentional urination behavior, analyze the influencing factors, and establish a line graph model for predicting female nurses′ unintentional urination behavior. Methods: A total of 170 female nurses (training set) in a class A hospital in Tianjin were included and divided into urinary incontinence group and non-urinary incontinence group according to whether there was no intention to urinate. Single and multiple logistic regression models were used to analyze the risk factors, and R software was used to establish the prediction line graph model. Another fifty female nurses in the hospital were selected as the validation set, and the ROC curve was used to analyze the efficacy of the model in predicting the non-urination behavior of the training set and the validation set. Results: There were 83 cases (48.82%) in the incontinence group and 87 cases (51.18%) in the non-incontinence group. Logistic regression analysis showed that age over 35, the number of labor, the behavior of holding urine, sedentary or standing for a long time, irregular pelvic floor muscle training, negative urination behavior, and high occupational tension were all independent factors influencing the behavior of urination without intention (P<0.05). ROC curve analysis showed that the AUC of the line graph model was 0.965 (95%CI 0.940~0.989) for the training set and the C-index of the validation set was 0.968 (95%CI 0.946~0.990). Conclusion: The nomogram model established based on the above independent risk factors has good predictive efficacy. Medical staff can develop relevant measures based on influencing factors to decrease female nurses′ unintentional urination behavior and enhance their quality of life.

Key words: Unintentional urination, Nurse, Occupational stress, Prediction model