国际护理科学（英文）2025，Vol.12Issue(3)：253-260,8.DOI:10.1016/j.ijnss.2025.04.008
基于可解释性机器学习的初产妇分娩心理创伤的影响因素分析
Identifying the key influencing factors of psychological birth trauma in primiparous women with interpretable machine learning
摘要
Abstract
Objective:Accurately identifying the key influencing factors of psychological birth trauma in primiparous women is crucial for implementing effective preventive and intervention measures.This study aimed to develop and validate an interpretable machine learning prediction model for identifying the key influ-encing factors of psychological birth trauma in primiparous women. Methods:A multicenter cross-sectional study was conducted on primiparous women in four tertiary hospitals in Sichuan Province,southwestern China,from December 2023 to March 2024.The Childbirth Trauma Index was used in assessing psychological birth trauma in primiparous women.Data were collected and randomly divided into a training set(80％,n=289)and a testing set(20％,n=73).Six different machine learning models were trained and tested.Training and prediction were conducted using six machine learning models included Linear Regression,Support Vector Regression,Multilayer Perceptron Regression,eXtreme Gradient Boosting Regression,Random Forest Regression,and Adaptive Boosting Regression.The optimal model was selected based on various performance metrics,and its predictive results were interpreted using SHapley Additive exPlanations(SHAP)and accumulated local effects(ALE). Results:Among the six machine learning models,the Multilayer Perceptron Regression model exhibited the best overall performance in the testing set(MAE=3.977,MSE=24.832,R2=0.507,EVS=0.524,RMSE=4.983).In the testing set,the R2 and EVS of the Multilayer Perceptron Regression model increased by 8.3％and 1.2％,respectively,compared to the traditional linear regression model.Mean-while,the MAE,MSE,and RMSE decreased by 0.4％,7.3％,and 3.7％,respectively,compared to the traditional linear regression model.The SHAP analysis indicated that intrapartum pain,anxiety,post-partum pain,resilience,and planned pregnancy are the most critical influencing factors of psychological birth trauma in primiparous women.The ALE analysis indicated that higher intrapartum pain,anxiety,and postpartum pain scores are risk factors,while higher resilience scores are protective factors. Conclusions:Interpretable machine learning prediction models can identify the key influencing factors of psychological birth trauma in primiparous women.SHAP and ALE analyses based on the Multilayer Perceptron Regression model can help healthcare providers understand the complex decision-making logic within a prediction model.This study provides a scientific basis for the early prevention and personalized intervention of psychological birth trauma in primiparous women.关键词
影响因素/机器学习/初产妇/分娩心理创伤Key words
Influencing factor/Machine learning/Primiparous women/Psychological birth trauma引用本文复制引用
吴雨泽,李奉玲,舒慧兰,李思媛,崔丽君,谭敏,罗澜峻,魏雪梅..基于可解释性机器学习的初产妇分娩心理创伤的影响因素分析[J].国际护理科学（英文）,2025,12(3):253-260,8.基金项目
This study was supported by the Sichuan Province Nursing Scientific Research Project Plan(H23022)and the 2022 Municipal-University Science and Technology Strategic Cooperation Special Fund of Nanchong Science and Technology Bureau(22SXQT0222). （H23022）
