Objective To identify effective strategies to motivate medical staff in private hospitals to engage in health science popularization by analyzing the current situation and influencing factors.Methods A general descriptive analysis was conducted to evaluate the basic information and status of health science popularization among the subjects.The factors influencing the willingness of medical staff in private hospitals to engage in health science popularization were examined using single-factor a-nalysis and a multi-factor logistic regression model.Results A total of 88.61％of medical staff expressed willingness to partici-pate in health science popularization,while 56.39％engaged in such activities.Factors such as interest in health science popu-larization,availability of resources,training,and dissemination channels significantly influenced participation(P＜0.05).Con-clusion Similar to public hospitals,most medical staff in private hospitals are willing to disseminate health science,but actual participation rate remains low.To enhance engagement,hospitals should improve performance incentive mechanisms and develop a diversified training system and comprehensive media platforms for science popularization.

Objective To identify effective strategies to motivate medical staff in private hospitals to engage in health science popularization by analyzing the current situation and influencing factors.Methods A general descriptive analysis was conducted to evaluate the basic information and status of health science popularization among the subjects.The factors influencing the willingness of medical staff in private hospitals to engage in health science popularization were examined using single-factor a-nalysis and a multi-factor logistic regression model.Results A total of 88.61％of medical staff expressed willingness to partici-pate in health science popularization,while 56.39％engaged in such activities.Factors such as interest in health science popu-larization,availability of resources,training,and dissemination channels significantly influenced participation(P＜0.05).Con-clusion Similar to public hospitals,most medical staff in private hospitals are willing to disseminate health science,but actual participation rate remains low.To enhance engagement,hospitals should improve performance incentive mechanisms and develop a diversified training system and comprehensive media platforms for science popularization.

Objective:To analyze risk factors for deep vein thrombosis(DVT)in patients with severe cerebral infarction and to find early and sensitive indicators for the prediction and intervention of DVT.Methods:A total of 226 patients with severe cerebral infarction aged 62.5±12.9 years in our department from January 2017 to May 2020 were enrolled.Clinical data, biochemical examinations and color Doppler ultrasound results were collected.Risk factors for DVT were analyzed.The receiver operating characteristic curve(ROC)was used to determine the cut-off value, area under the curve, sensitivity and specificity.Results:Age, reaction(R)time of blood coagulation factors on thromboelastography(TEG)and fibrinogen degradation products(FDP)were risk factors for DVT with no adjustment of the overall effect of time on coagulation mechanisms.According to time stratified analysis, decreased R time( OR=0.58, 95% CI: 0.40-0.84)and increased FDP( OR=1.17, 95% CI: 1.02-1.33)within 3 days of onset were risk factors for DVT, and the cut-off values were 5.35 min and 0.39 mg/L, respectively; 3 and 7 days after onset, increased D-dimer was a risk factor for DVT( OR=2.73, 95% CI: 1.53-4.86; OR=2.57, 95% CI: 1.32-5.03), and the cut-off values were 0.39 mg/L and 0.76 mg/L, respectively.Excluding the effects of FDP primary and D-Dimer secondary fibrinolysis, risk factors for DVT within 3 days of onset were decreased R time on TEG and increased age, and all risk factors were not statistically significant 3 days and 7 days after onset( P<0.05). Conclusions:The key factors affecting DVT in patients with severe cerebral infarction are different at different stages.Decreased R time within 3 days of onset is a predictive indicator of DVT.FDP and D-dimer can be used to assess thrombosis, but may not be appropriate as predictive indicators.