Establishment and comparison of 3 compassion fatigue risk prediction models for obstetrics and gynaecology nurses based on machine learning
10.3761/j.issn.0254-1769.2025.03.013
- VernacularTitle:基于机器学习的3种妇产科护士共情疲劳风险预测模型的构建与比较
- Author:
Rui ZHAO
1
;
Wenqi FAN
1
;
Xiaoxia LIU
1
;
Lina GE
1
Author Information
1. 110004 沈阳市 中国医科大学附属盛京医院第一妇科病房
- Publication Type:Journal Article
- Keywords:
Machine Learning;
Obstetrics and Gynecology Nurses;
Compassion Fatigue;
Root Cause Analysis;
Nursing Administration Research
- From:
Chinese Journal of Nursing
2025;60(3):347-354
- CountryChina
- Language:Chinese
-
Abstract:
Objective To compare the performance of 3 risk prediction models based on machine learning in predicting the risk of compassion fatigue among obstetrics and gynaecology nurses.Methods Using the convenience sampling method,1 323 obstetrics and gynaecology nurses from 11 tertiary hospitals in 9 cities were selected from December 2022 to March 2023,and were randomly divided into a training set and a test set according to 7∶3 ratio.Compassion Fatigue Scale,Five Facet Mindfulness Questionnaire and Emotional Intelligence Scale were used for the survey.A total of 3 types of risk prediction models were constructed for the factors affecting the compassion fatigue of obstetrics and gynaecology nurses,namely,Logistic Regression,Decision Tree,and Random Forest.The accuracy,precision,specificity,sensitivity,Fl score and AUC were used to compare the predictive performance of the 3 models.Results Finally 1 276 maternity nurses completed the survey.All 3 models showed that nature of employment,years of experience,mindfulness and emotional intelligence were independent risk factors for compassion fatigue in obstetrics and gynaecology nurses(P＜0.05).The results of model comparison showed that the accuracy of Logistic regression,decision tree and random forest were 0.804,0.806,0.796;the precision was 0.821,0.827,0.823;the sensitivity was 0.956,0.949,0.939;the Fl score was 0.883,0.884,0.877;the AUC was 0.704(95％CI:0.701～0.713),0.760(95％CI:0.751～0.771),0.742(95％CI:0.723～0.762)respectively.Conclusion The risk prediction model of factors affecting compassion fatigue among obstetrics and gynaecology nurses constructed by decision tree performed the best,and the predictive performance was better than that of the random forest and logistic regression models.The multi-model effectively predicts the risk of compassion fatigue in obstetrics and gynecology nurses,explores the interaction of influencing factors in multiple dimensions,and it can inform the early identification and prevention of compassion fatigue and the development of related interventions.
