Construction and validation of predictive model for fatigue in soldiers during long voyage
10.3969/j.issn.1009-0754.2025.02.007
- VernacularTitle:长航官兵疲劳发生风险预测模型的构建及验证
- Author:
Xiuzhong QI
1
;
Lei YU
;
Jian WANG
;
Huixin WU
;
Fengbao ZHOU
Author Information
1. 266071 山东 青岛,海军青岛特勤疗养中心中医科
- Keywords:
Soldier during long voyage;
Fatigue;
Influencing factors;
Predictive model;
Nomogram
- From:
Journal of Navy Medicine
2025;46(2):138-143
- CountryChina
- Language:Chinese
-
Abstract:
Objective To construct and validate a risk predictive model for fatigue in soldiers during long voyage based on sleep,mood and constitution.Methods One thousand soldiers during long voyage were selected as research objects by random cluster sampling.The fatigue scale-14(FS-14),Pittsburgh sleep quality index(PSQI),self-rating anxiety scale(SAS),self-rating depression scale(SDS),and TCM constitution scale were used to assess the occurrence of fatigue and its influence factors.Logistic stepwise regression analysis was used to screen variables,and the prediction nomogram model was constructed based on the risk factors of fatigue.The area under the receiver operator characteristic curve(AUC),calibration curve,Hosmer-Lemeshow test and decision curve were used for internal validation and predictive efficacy assessment.Results A total of 935 effective scales were collected,with an effective rate of 93.5%.Excluding 306 soldiers who were already fatigued before voyage,the fatigue incidence rate of 629 soldiers after 15 days and 30 days of voyage were 26.39%and 42.13%,respectively.The total score of FS-14 and the scores of physical fatigue and mental fatigue were significantly proportional to the voyage time(P<0.01).Eight variables including Qi-deficiency,Yang-deficiency,Yin-deficiency,Qi-stagnation,Special-constitution,anxiety,depression,and sleep disorder might be the independent risk factors for the occurrence of fatigue 30 days after voyage.A nomogram model was established according to the selected variables,and the AUC of the model was 0.828(95%CI:0.797-0.858).Calibration curve and Hosmer-Lemeshow test showed that the goodness of fit of the model was good(χ2=15.384,P=0.052).Decision curve showed that the model had a positive net benefit when the threshold probability was 10%-95%.Conclusion The predictive model for fatigue in soldiers during long voyage has good predictive accuracy and efficiency.It is an effective assessment tool for screening high-risk cases of fatigue and implementing preventive interventions in soldiers during long voyage.
