RESUMO
BackgroundThe mental health of employees in railway enterprises is related to the safety and stability of railway transportation. As an important factor affecting occupational mental health， job characteristics have attracted the attention of researchers. However， there exists a lack of job characteristic scales with occupational specificity in current researches relevant to the railway industry. ObjectiveTo develop a job characteristics questionnaire oriented to railway employees that takes both Job Demands-Resources Model （JD-R） and Chinese actual conditions into essential consideration， so as provide guidance for the research on the mental health of railway employees. MethodsPurposive and theoretical samplings were used to select 77 employees across 9 railway units as research objects， and interview method was used to conduct qualitative research in order to determine the structural dimensions and items of the questionnaire. The 612 subjects randomly selected from the railway maintenance system went through the preliminary test， then exploratory factor analysis and confirmatory factor analysis were employed to test the questionnaire. After forming a formal questionnaire on the job characteristics of railway employees， it is extended to the other four main industry systems of railway enterprises， responsible for locomotive maintenance， vehicle depot， signal and communication maintenance， and power supply respectively， to verify the stability and effectiveness. Results①Exploratory factor analysis showed that the questionnaire included two factors， job demands and job resources， with a total of 14 items. The factor loading of each item ranged from 0.761 to 0.916， and the two factors accounted for 71.02% of the total variance. The results of confirmatory factor analysis indicated good fitting of the two-factor model （χ2/df=3.310， RMSEA=0.087， GFI=0.892， CFI=0.932， NFI=0.905， IFI=0.932）. ② Confirmatory factor analysis was carried out in four extended samples of locomotive maintenance， vehicle depot， signal and communication maintenance， and power supply， and each result indicated a satisfactory model fit（χ2/df=2.678， 4.741， 4.868， 3.502， RMSEA=0.109， 0.096， 0.093， 0.084，GFI=0.832， 0.878， 0.894， 0.904，NFI=0.874， 0.935， 0.902， 0.928，IFI=0.917， 0.948， 0.920， 0.947）. ③Job demands in five sub-samples can positively predict job burnout and turnover intention （β=0.564~0.686， 0.425~0.554， P<0.01）. Job resources in five sub-samples can positively predict job performance and job satisfaction （β=0.594~0.752， 0.731~0.807， P<0.01）， and it can also negatively predict job burnout and turnover intention （β=-0.247~-0.186， -0.357~-0.175，P<0.05 or 0.01）.In sub-samples of locomotive maintenance and power supply， job demands can positively predict job performance （β=0.242，0.261， P<0.01）.In sub-samples of railway maintenance and signal and communication maintenance， job demands can negatively predict job satisfaction （β=-0.065， -0.091， P<0.01）. ConclusionThe questionnaire has good reliability and validity， and is applicable for the study of occupational mental health research on railway employees. ［Funded by Major Projects of the National Social Science Foundation of China （number， 19ZDA3580）， Scientific Research and Development Program of China Railway Chengdu Group Co.， Ltd （number， CX21099）］