| Objective:Through the establishment of the cohort,to investigate mental health situation of 172 train drivers in Kunming Railway, study on burnout whether there is a causal association to mental health, explore the influencing fectors of burnout, propose measures to reduce the incidence of burnout and improve mental health level of train drivers, but also provide scientific basis for the relevant departments to prevent mental health problems, ensure traffic safety.Methods:A prospective cohort study of epidemiofogical survey methods were adopted in this study on the basis of the current state of research. Chinese 8-item Short-From Health Survey(SF-8), Chinese Effort-Reward Imbalance Questionnaire(ERI) and Copenhagen Burnout Inventory(CBI) were used to assess their mental health,occupational stress and burnout,occupation health examination and interviews were used to collecte qualitative data, to obtain basic information, mental health status and influencing factors, especially occupational burnout of train drivers. High exposure group selection:in the baseline survey, exclude mental unhealthy, ensure the same type of work, and length of service, age composition (± 3)of the same, burnout score> 75 train drivers as a high-exposure group. Low exposure group selection:In addition to different burnout score(burnout score= 75), other conditions consistent with the high exposure. The follow-up time are two years, follow-up content and manner consistent with the baseline during following-up. As of 2014 terminated, To survey the impact of this population occupational burnout on mental health.Results1. The baseline surveys of two groups of train drivers are comparable. The average age of two groups train drivers was37.04±6.16 years old, the average age of the high burnout group was 36.84 ± 6.14 years old, the average age of the mild burnout group was 37.24 ± 6.22 years old. There was no statistically significant difference in the average age (t=-0.43, P=0.666) and age stratified groups(χ2=0.385, P=0.825) of two groups by test and chi-square test. The average length of service of two train drivers was 17.87 ± 6.88 years, in which the high burnout group, the average length of service for the train driver was 17.99 ± 7.05 years, the average length of service for the mild burnout group was17.76 ± 6.74 years. There was no statistically significant difference in the average length of service (t=-0.22, P= 0.825) and stratified groups(χ2= 0.21, P= 0.901) by test and chi-square test. Two types of train drivers were electric locomotive drivers and diesel drivers,trades constitution where two groups of train drivers posed no statistically significant difference by chi-square test (χ2=0.00,P=1.00). Both groups take the same approach to follow-up, no bst during two years of follo wing-up rate was 100%.2. Train drivers mental health score comparative analysis:from normality test, mental health score was similar to the normal distribution. It found that train drivers mental health (2012 and 2014) score was respectively(44.48 ± 5.23), (40.71 ±0.17).There was statistically significant of mental health disparities between2012 and 2014 by paired samples t-test(P<0.001). The mental health score of 2014 was tower than the score of 2012. It analyzed from various dimensions mental health. There were statistically significant difference about mental health dimensions (t= 4.38, P= 0.001) and role-emotional dimensions (t= 2.12, P= 0.035) of 2012, the mental health and role emotional scores of dimensions of 2014 were lower than the score of 2012. After two years following-up, it found that mental health abnormality detection rate was 27.33%,the high exposure group abnormal detection rate of mental health was 46.51%, the low exposure group detection rate was 8.14%. The danger of highly burnout train drivers occurrence of abnormal mental health is 5.71 times than lower burnout by the chi-square test(RR= 5.71,AR=38.37, AR%=%2.50%,95%RR C.I(2.712-12.04)),PAR=25.26,PAR%=75.63%.3. Train drivers occupational burnout influence factors analysis:using the logistic regression model for multivariate factor analysis, to investigate factors affecting occupational burnout from the individual factors, occupational characteristics, self professional capacity factors, occupational hazards affecting factors of train drivers.It found out that individual factors include fat diet (OR= 1.95), the life pressure (OR= 3.67、drinking (OR= 1.65); occupational factors characteristic only include by shift (OR= 1.97); self-inductance of professional competence factors include working pressure (OR= 3.97), on job satisfaction (OR=3.81); occupational hazards include working pressure (OR= 2.37), domestic work conflict (OR= 2.34).Conclusions Train drivers in Kunming railway locomotive depot are suffered different aspects and levels of mental health problems, mental health abnormal detection rate was 27.33%. The survey found a high degree of occupation burnout associated with mental health abnormalities, occupation burnout is the cause of a train driver mental health exception. There are many factors to effect occupation burnout. fat diet, life stress are factors of train drivers burnout in terms of individual factors; the ability to work, job satisfaction, inductance work stress are factors train drivers burnout in the self-inductance of professional competence factors; work stress and working-family conflict are factors train drivers burnout in occupational harmful factors. Once the burnout factors controlled, the mental health will be improved.Suggestions The survey found a high degree of occupation burnout associated with mental health abnormalities, The higher the degree of burnout is the lower the level of mental health. To improve mental health, the most critical factors is to control burnout. For highly burnout train drivers, to focus on the cause of the proximal end of the chain, take interventions targeted at high risk strategies to reduce burnout and improve mental health. For mild burnout train drivers,should take active measures to reduce burnout to prevent the evolution to highly professional burnout. For no burnout train drivers should take active population-wide strategy to prevent burnout. |
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