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西部某大型国企员工心理健康水平及其影响因素 被引量:5

Mental health level and its influencing factors of employees in a large state-owned enterprise in Western China
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摘要 目的了解西部某大型国企员工的心理健康水平和工作状况,并在此基础上探讨国企员工心理健康的影响因素。方法采用普查的方法,用90项症状自评量表(SCL-90)对西部某大型国企7099名员工进行心理健康调查。结果该国企员工SCL-90筛查阳性率为28.7%,除躯体化因子得分高于全国常模外,总均分和其他因子得分均低于全国常模,差异有统计学意义(P〈0.001)。经聚类分析,7099名国企员工分为3类,这3个类别因子分差异均有统计学意义(P〈0.01)。第1类各因子分均值为1.0~1.3,心理状况良好;第Ⅱ类除恐怖因子外其他各因子分均值为1.5~2.1,心理状况一般;第Ⅲ类因子分均大于2.0,心理状况较差。单因素分析显示,性别、年龄、文化程度、经济状况、岗位类型、工作地点、工作时长、加班频率是该人群心理健康水平的影响因素(P〈0.001)。结论该国企员工心理健康水平整体良好,应针对其影响因素开展基于工作场所的心理健康促进。 [Objective] To understand the mental health level and work conditions of employees in a large state-owned enterprise in Western China, explore the influencing factors based on these researches.[Methods]The census sampling method was used and 7 099 employees were interviewed by 90 Symptom Check List(SCL-90).[Results] The SCL-90 positive rate of the employees was 28.7%, and the total average scores and other factor scores were lower than the national norm (P〈0.001) except somatization score which was higher than the national norm. According to cluster analysis, 7 099 employees were divided into three subgroups with significant differences in factor scores(P〈0.01 ): grade I of good mental health status(factor scores from 1.0-1.3), grade II of general mental health status (factor scores from 1.5-2.1, except for horror) and grade III of poor mental health status (scores greater than 2.0). Single factor analysis showed that gender, age, educational level, income, job type, work location, work time, and work overtime frequency were the main influencing factors of mental health level among the targeted population(P〈0.001 ). [Conclusion] The mental health status of the employees in this large state-owned enterprise is good, and it is necessary to carry out the mental health promotion activities based on working sites according to the influencing factors.
出处 《职业与健康》 CAS 2016年第5期595-598,602,共5页 Occupation and Health
关键词 大型国有国企 员工 SCL-90 心理状况 聚类分析中国图书资料 Large state-owned enterprise Employees SCL-90 Mental health status Cluster analysis
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