Abstract: Objective To construct and validate a risk predictive model for depression occurrence of navy serviceman during long voyage based on factors such as sleep,fatigue and constitution of traditional Chinese medicine（TCM）. Methods A total of 1 000 navy serviceman during long voyage from June 1 to September 30,2022 were selected as the subjects by random cluster sampling method. All of them were assessed by the self-rating depression scale（SDS）,Pittsburgh sleep quality index（PSQI）,fatigue scale-14（FS-14）,TCM constitution scale to investigate the depressive emotions and influencing factors. The logistic stepwise regression analysis was used to screen risk factors and construct prediction nomogram model. The area under the curve,correction curve and decision curve were used for internal validation and predictive efficacy assessment. Results Totally 949 valid scales were collected,with an effective rate of 94.9%. Before the voyage,15 days and 30 days after voyage,the incidence of depression in navy serviceman was 14.33%,26.34% and 19.18%,respectively. The scores of SDS increased at first and then decreased with the increasing of the voyage time,with statistically significant differences among groups（P<0.05）. There were statistically significant differences compared to the domestic norm（all P<0.01）. There were 11 independent risk factors correlated with depression occurrence of navy serviceman 11 days after voyage,including sex,age,length of work,time from the last long voyage,Qi-deficiency,Phlegm-dampness,Blood-stasis,Qi-stagnation,Special-constitution,sleep disorder and fatigue. A nomogram model was established according to the selected variables,whose area under the curve was 0.871（95%CI：0.840-0.901）. The correction curve showed good fit. The decision curve showed that the model had a positive net benefit when the threshold probability was 5%-87%. Conclusion The predictive model for depression occurrence of navy serviceman during long voyage has good predictive accuracy and efficiency,which provides an effective assessment tool for screening high-risk cases of depression and implementing preventive interventions in navy serviceman during long voyage.

Key words: Navy serviceman, Long voyage, Depression, Predictive model, Nomogram