Predicting the development trend of job burnout in editors of Chinese science and technology journal based on artificial intelligence algorithms
Objective To construct and preliminarily validate an artificial intelligence algorithm to predict the development trend of job burnout in editors of Chinese science and technology journal.Methods A simple random sampling method was used to investigate the job burnout in editors of Chinese science and technology journals based on"questionnaire stars"from March 1 to May 1,2023.Firstly,seven machine learning algorithms,including random forest,simple Bayes,K-nearest neighbor,support vector machine,artificial neural network,logistic regression and gradient enhancement algorithm,were used to construct the prediction model,and then a new fusion model was constructed based on the above seven algorithms by weighted voting method.Finally,receiver operating characteristic(ROC)curve,calibration curve and decision curve were used to evaluate the efficacy of the model,and SHAP value was used to evaluate the importance of predictive variables.The model application software was constructed based on R shiny APP.Results A total of 341 editors were included in the analysis.The incidence of job burnout was 402％(137/341).The area under the ROC curve of the fusion model was 0.807(95％CI:0.761-0.853),the sensitivity was 0.774(95％CI:0.709-0.839),and the specificity was 0.772(95％CI:0.709-0.836).The calibration curve showed that the fusion model had good calibration(Hosmer-Lemeshow x2=5.036,P＞0.05).The top five importance of prediction characteristics were personal monthly income level,weekly working hours,weekly overtime,whether there had been honors or rewards in the past year,and whether the division of responsibilities is clear.The decision curve showed that when the prediction probability of job burnout was between 20％and 90％,taking certain intervention measures can achieve maximum benefit.Conclusion A prediction model for the development trend of job burnout in Chinese science and technology journal editors has been preliminarily established based on the artificial intelligence algorithm,which has certain reference value for taking timely measures to alleviate the job burnout of editors.
Science and technology journalsEditorsJob burnoutArtificial intelligenceMachine learningPrediction
NETL
NSTL
万方数据
