Objective To investigate the mental health status and related personality type of psychological clinic adoleScent in general hospital and provide data for psychology treatment and intervention.Methods 219 adolescence consulters in 2006 were tested by symptom checklist(SCL-90) and eysenck personality questionnaire(EPQ).The caseswere separatedthree age groups,A group(16～20 years old),B group(21～25 years old),C group(26～30 years old)and disposed by SPSS 13.0.Results All factor scores of SCL-90 in psychological clinic adolescents were higher than those of youth norm in China(P＜0.01).The scores of female consulters were significant higher than those of male in depression(P＜0.05).The incident rate of mild mental obstacle(factor score＞2)in 3 age groups were significant different.The incidence rate of B and C groups were higher A group(P＜0.01).The factor scores were positive associated with P in EPQ and negative associated with L in EPQ.The obsession score of SCL-90 was negative associated with E in EPQ.Conclusions The mental health status of psychological clinic adolescents was not as good as norm adolescents.In psychological consulting and psychological health service,measures in different age and different personality could help build up healthy personality and effectively promote the development of mental health.

Objective To analyze the situation of table tennis competitions in emergency public health events, find the possible weak links in the emergency rescue and care work, put forward the hospital in response to emergency public health emergency preparedness plan, health emergency drills and emergency rescue personnel training and so on targeted reference views. Methods A total of four public health emergencies such as traffic accident, mass food poisoning, fire and bird flu were selected as the theme of the competition to simulate the emergency rescue process after the emergency,the examination of each team is divided into pre-hospital disposal and hospital disposal links. Results The score of Crash in Batches was 225.13 ± 8.38, followed by Fire accident 222.78 ± 16.57, Avian Influenza 210.32 ± 11.19, Group Food poisoning 204.80 ± 6.77, the difference was statistically significant (F=8.706,P=0.000). The scores of pre-hospital treatment in all four subjects were109.04±4.80, 108.62±10.12, 98.24±6.95, 101.14± 8.85,lower than those in hospital, which were 116.09±4.79, 114.16±7.61, 106.56±5.31, 109.18±4.24, the difference was statistically significant (t=-6.130--2.338,P＜0.01 or 0.05). Conclusions On the different topics exposed in the desktop exercise competition and the differences between the pre-hospital treatment and the hospital disposal, the nursing managers should strengthen the training and practice of public health emergencies with different themes, and pay attention to the pre-hospital emergency public health emergencies training and rehearsal,the emergency response plans for public health emergencies were revised and improved through the health emergency drills.

Objective:To explore the application of effect of healthcare failure mode and effect analysis (HFMEA) in emergency waiting risk management.Methods:From May 2020 to April 2021, totally 87 902 emergency waiting patients from the First Affiliated Hospital of Anhui Medical University were assigned to control group by cluster sampling method. From May 2021 to April 2022, 80 594 emergency waiting patients were assigned to observed group. The patients in the control group received routine emergency waiting of itinerant management mode. In contrast, the patients in the observed group received emergency waiting risk management mode based on HFMEA. The process risk priority number (RPN) and waiting risk management index between two groups were compared.Results:The mean RPN of the observed group was (98.48 ± 8.27) points, significantly lower than that of the control group (251.27 ± 16.95) points. The nurses′ pre-identification rates of changes in the condition and adverse reaction in the observed group were 10.77%(8680/80 594) and 13.37%(10 775/80 594), which were higher than those in the control group, 5.77%(5072/87 902) and 8.12%(7134/87 902), the differences were statistically significant ( χ2 values were 1402.32 and 1221.66, all P<0.05). Conclusions:The application of HFMEA to optimize the emergency waiting management process can effectively reduce the risk of emergency waiting and improve the quality of emergency waiting management.