OBJECTIVETo investigate the occurrence and associated factors for posttraumatic stress disorder (PTSD) in rescuers and firefighters.

METHODSThe PTSD of 264 rescuers and firefighters who had participated in rescue was evaluated using the self-designed fireman general situation questionnaire and PTSD Checklist-Civilian Version (PCL-C). The factors associated with the occurrence of PTSD were also analyzed.

RESULTSThe incidence rate of PTSD in the subjects was 8.3%. The PTSD rate of special service corps (12%) was significantly higher than that of other subjects (P<0.05). The incidence of PTSD was highest in the rescuers and firefighters above the third rank, but without significant differences (P>0.05). The PTSD rate of married rescuers and firefighters was significantly higher than that of unmarried subjects (P<0.05). The PTSD rate of subjects addicted to drinking was significantly higher than that of non-drinking subjects (P<0.05). Subjects with more frequent attendance were more susceptible to PTSD compared with those with less attendance.

CONCLUSIONThe incidence rate of PTSD is high in rescuers and firefighters who have attended rescues. It is necessary to implement both short-term and long-term counseling programs for stress management and intervention in order to reduce the psychological trauma after rescue and improve the mental health of rescuers and firefighters.

Firefighters ; psychology ; Humans ; Incidence ; Stress Disorders, Post-Traumatic ; diagnosis ; Surveys and Questionnaires

OBJECTIVETo explore the effect of signal strength indictor (SSI) in improving sensitivity of China Infectious Diseases Automated-alert and Response System (CIDARS).

METHODSDiarrhea cases in 2007-2011 and early warning signals in 2010-2011 were selected by using random digital table method. Then, SSI and event-related ratio (ER) were calculated. The relationship between ER and SSI was analyzed, and the effect of SSI on ER was explored by using multiple logistic regression analysis.

RESULTS9 620 early warning signals in 2010-2011 were generated in two years. Of these, 74, or 0.77% were defined as suspected outbreak signal. The median of SSI related with suspected outbreak signal was 4.0, which was much higher than non-suspected outbreak signal (1.7). ER was significantly correlated with SSI (r=0.917). SSI classification has a good correlation between the ER, ER exceeded 20 after SSI reached 20. The multivariate logistic regression analysis showed OR of SSI related with suspected outbreak signal was 2.52 (95% CI 2.04-3.12). Compared with non-epidemic season, the relationship of SSI and ER in epidemic season was much higher.

CONCLUSIONSSI was closely related with ER. The relationship was much closer in large scale outbreak and epidemic season, and compared to non-epidemic,the effect of epidemic season is more obvious.

China ; Communicable Diseases ; diagnosis ; epidemiology ; Diarrhea ; diagnosis ; epidemiology ; Disease Outbreaks ; Humans ; Population Surveillance

OBJECTIVETo investigate the current status and characteristics of work-related fatigue among scientific and technical personnel and its associated factors, and to provide a scientific basis for further interventions.

METHODSA cross-sectional survey was conducted in the staff from a single scientific institution, using a self-administered questionnaire. Basic information of participants, Fatigue Scale-14, and Job Content Questionnaire were collected.

RESULTSThe prevalence of work-related fatigue among the scientific and technical personnel was 54.6%; work-related fatigue was positively correlated with occupational stress (rs = 0.384, P < 0.05). Significant differences in the scores, proportions, and types of fatigue were found between different types of occupational stress. The associated factors of work-related fatigue included occupational stress profiles, social support, and educational status. A higher risk of work-related fatigue was found in the staff under high stress, compared with those under low stress (OR = 8.5, 95%CI = 3.9∼18.7). Social support served as a protective factor for work-related fatigue, while a higher level of education was correlated with more severe work-related fatigue.

CONCLUSIONWork-related fatigue is common and serious among scientific and technical personnel, especially in those under high stress. Effective interventions according to occupational stress are of great importance to reduce work-related fatigue.

Cross-Sectional Studies ; Fatigue ; epidemiology ; Humans ; Occupational Diseases ; epidemiology ; Prevalence ; Research Personnel ; psychology ; Risk Factors ; Social Support ; Stress, Psychological ; epidemiology ; Surveys and Questionnaires

OBJECTIVETo analyze the job burnout and mental health status of clinicians and the relationship of personality with job burnout and psychological stress, and to investigate the direct or indirect effects of personality on psychological stress.

METHODSMaslach Burnout Inventory-General Survey (MBI-GS), Eysenck Personality Questionnaire-Revised Short Scale (EPQ-RSC), and Kessler 10 Scale were administered to 775 clinicians.

RESULTSOf all clinicians, 29.5% had mild burnout, with a score of 22.7 ± 8.18 for psychological stress risk. The effect of personality on emotional exhaustion and cynicism was greater than that on personal accomplishment. Clinicians with a personality of introversion, neuroticism, and psychoticism suffered a higher risk of psychological stress. Personality had both direct and indirect effects on psychological stress. Neuroticism had the strongest effect on psychological stress, with an effect size of 0.55.

CONCLUSIONClinicians have a high level of both job burnout and mental psychological stress risk. Personality is significantly correlated with job burnout and psychological stress risk. Measures depending on personality should be taken for effective intervention.

Anxiety Disorders ; Burnout, Professional ; epidemiology ; psychology ; Fatigue ; Humans ; Neuroticism ; Personality ; Physicians ; psychology ; Risk ; Stress, Psychological ; epidemiology ; psychology ; Surveys and Questionnaires

Objective:To explore the application of the first ventilatory threshold (VT1) and the second ventilatory threshold (VT2) in the classification of physical workload for plateau workers, to provide reference for formulating the classification in plateau.Methods:In August 2018, 88 male workers from substations at different altitudes (500 m, 2000 m, 3000 m and 4000 m) of a company were selected as study subjects by cluster sampling. They were divided into plain group and plateau groups.The intensities of workload were simulated by power bicycle, and physiologic parameters, including VO 2, heart rate (HR) and energy metabolic rate per body surface area (E/BSA) , were recorded in test system when reaching VT1, VT2 and peak oxygen uptake (VO 2Peak) . The ratios of VT1, VT2 and VO 2Peak to the quiet and work potential at different altitudes were compared. Results:In a quiet state, compared with the plain group, the HR and E/BSA of the workers in the 2000 m and 3000 m groups increased, and the differences were statistically significant ( P<0.05) . At VT2, compared with the plain group, the HR of the workers in the 4000 m group decreased, the difference was statistically significant ( P<0.05) . VO 2 and E/BSA of workers in each plateau group were lower than those in the plain group at VO 2Peak, and the differences were statistically significant ( P<0.05) . At VT2 and VO 2Peak, the ratios of VO 2, HR, and E/BSA relative to the quiet state of the workers in each plateau group were lower than those of the plain group, and the differences were statistically significant ( P<0.05) . In the quiet state and VT1, compared with the plain group, the remaining percentages of VO 2 and E/BSA of workers in each plateau group decreased, and the differences were statistically significant ( P<0.05) . Taking VT1, VT2 and VO 2Peak as cut-off points and VO 2, HR and E/BSA as indicators, the physical workload in plateau could be divided into four levels, namely medium, heavy, extremely heavy and extreme physical workload. Conclusion:It is practicable to use ventilatory threshold to classification of physical workload. VT1 and VT2 can be applied to the classification in plateau to supplement and optimize current national standard of physical workload.

Objective:To explore the application of the first ventilatory threshold (VT1) and the second ventilatory threshold (VT2) in the classification of physical workload for plateau workers, to provide reference for formulating the classification in plateau.Methods:In August 2018, 88 male workers from substations at different altitudes (500 m, 2000 m, 3000 m and 4000 m) of a company were selected as study subjects by cluster sampling. They were divided into plain group and plateau groups.The intensities of workload were simulated by power bicycle, and physiologic parameters, including VO 2, heart rate (HR) and energy metabolic rate per body surface area (E/BSA) , were recorded in test system when reaching VT1, VT2 and peak oxygen uptake (VO 2Peak) . The ratios of VT1, VT2 and VO 2Peak to the quiet and work potential at different altitudes were compared. Results:In a quiet state, compared with the plain group, the HR and E/BSA of the workers in the 2000 m and 3000 m groups increased, and the differences were statistically significant ( P<0.05) . At VT2, compared with the plain group, the HR of the workers in the 4000 m group decreased, the difference was statistically significant ( P<0.05) . VO 2 and E/BSA of workers in each plateau group were lower than those in the plain group at VO 2Peak, and the differences were statistically significant ( P<0.05) . At VT2 and VO 2Peak, the ratios of VO 2, HR, and E/BSA relative to the quiet state of the workers in each plateau group were lower than those of the plain group, and the differences were statistically significant ( P<0.05) . In the quiet state and VT1, compared with the plain group, the remaining percentages of VO 2 and E/BSA of workers in each plateau group decreased, and the differences were statistically significant ( P<0.05) . Taking VT1, VT2 and VO 2Peak as cut-off points and VO 2, HR and E/BSA as indicators, the physical workload in plateau could be divided into four levels, namely medium, heavy, extremely heavy and extreme physical workload. Conclusion:It is practicable to use ventilatory threshold to classification of physical workload. VT1 and VT2 can be applied to the classification in plateau to supplement and optimize current national standard of physical workload.

OBJECTIVEProviding evidences for further modification of China Infectious Diseases Automated-alert and Response System (CIDARS) via analyzing the outbreak detection performance of Moving Percentile Method (MPM) by optimizing thresholds in different provinces.

METHODSWe collected the amount of MPM signals, response results of signals in CIDARS, cases data in nationwide Notifiable Infectious Diseases Reporting Information System, and outbreaks data in Public Health Emergency Reporting System of 16 infectious diseases in 31 provinces in Chinese mainland from January 2011 to October 2013. The threshold with the optimal sensitivity, the shortest time to detect outbreak and the least number of signals was considered as the best threshold of each disease in Chinese mainland and in each province.

RESULTSAmong all the 16 diseases, the optimal thresholds of 10 diseases, including dysentery, dengue, hepatitis A, typhoid and paratyphoid, meningococcal meningitis, Japanese encephalitis, scarlet fever, leptospirosis, hepatitis, typhus in country level were the 90(th) percentile (P90), which was the same as provincial level for those diseases.For the other 6 diseases, including other infectious diarrhea, influenza, acute hemorrhagic conjunctivitis, mumps, rubella and epidemic hemorrhagic fever, the nationwide optimal thresholds were the 80th percentile (P80), which was different from that by provinces for each disease. For these 6 diseases, the number of signals generated by MPM with the optimal threshold for each province was decreased by 23.71% (45 557), 15.59% (6 124), 14.07% (1 870), 9.44% (13 881), 8.65% (1 294) and 6.03% (313) respectively, comparing to the national optimal threshold, while the sensitivity and time to detection of CIDARS were still the same.

CONCLUSIONOptimizing the threshold by different diseases and provinces for MPM in CIDARS could reduce the number of signals while maintaining the same sensitivity and time to detection.

China ; Communicable Diseases ; Disease Notification ; Disease Outbreaks ; prevention & control ; Humans ; Population Surveillance ; methods