An investigation on the prediction of nurses' anxiety outcome based on classification regression tree model.

Objective To construct the prediction index of anxiety outcome of nurses in operating room by using classified regression tree model. Methods A total of 284 operating room nurses in 971 th Hospital of Navy of Chinese People's Liberation Army from March 2017 to June 2020 were selected to evaluate the baseline set data by using the classification regression tree model to determine the risk factors inducing anxiety of operating room nurses in military hospitals, and calculate the contribution rate of different risk factors. The prediction set was used as the evaluation method of prediction results to determine the risk factors that induced nurses' self rating Anxiety Scale ( SAS * score to reach the anxiety standard. Results The results of single factor analysis confirmed that the weekly working time, marital status, having children, CD-RISC score, age educational background were statistically significant ( all P < 0. 05 *. The SAS score split regression tree analysis of nurses showed that the weekly working time, marital status, children's situation, CD-RISC score, age entry model, formed 6 nodes, among which there were divorce, weekly working time >45 h and the highest score. Conclusion The risk factors of nurses anxiety in operating room were composed of five items: working hours, marital status, children's condition, psychological elasticity and age. Nursing managers can use the risk factors of nurses anxiety in operating room to predict the anxiety outcome in advance and carry out timely and reasonable intervention, which can help to reduce the anxiety degree of nursing staff. [ABSTRACT FROM AUTHOR]