杨金凤, 尉敏淇, 赵秋雯, 孙艺璇, 胡真, 戴俊明. 上海市闵行区企业员工职业倦怠与健康生产力受损的关系[J]. 环境与职业医学, 2023, 40(3): 273-280. DOI: 10.11836/JEOM22379
引用本文: 杨金凤, 尉敏淇, 赵秋雯, 孙艺璇, 胡真, 戴俊明. 上海市闵行区企业员工职业倦怠与健康生产力受损的关系[J]. 环境与职业医学, 2023, 40(3): 273-280. DOI: 10.11836/JEOM22379
YANG Jinfeng, WEI Minqi, ZHAO Qiuwen, SUN Yixuan, HU Zhen, DAI Junming. Association between job burnout and health-related productivity loss among enterprise staff in Minhang District of Shanghai[J]. Journal of Environmental and Occupational Medicine, 2023, 40(3): 273-280. DOI: 10.11836/JEOM22379
Citation: YANG Jinfeng, WEI Minqi, ZHAO Qiuwen, SUN Yixuan, HU Zhen, DAI Junming. Association between job burnout and health-related productivity loss among enterprise staff in Minhang District of Shanghai[J]. Journal of Environmental and Occupational Medicine, 2023, 40(3): 273-280. DOI: 10.11836/JEOM22379

上海市闵行区企业员工职业倦怠与健康生产力受损的关系

Association between job burnout and health-related productivity loss among enterprise staff in Minhang District of Shanghai

  • 摘要: 背景

    目前国内职业倦怠与健康生产力相关研究局限在医务群体,企业员工职业倦怠对健康生产力的影响值得关注。

    目的

    以企业员工作为调查对象,分析企业员工职业倦怠对健康生产力受损的影响。

    方法

    采用现况调查研究方法,采用方便抽样方式选定上海市闵行区的7家企业,对企业员工展开横断面电子问卷调查。运用职业倦怠通用版量表(MBI-GS)中文版评估职业倦怠,借鉴并修改世界卫生组织健康与工作绩效问卷评估健康生产力损失。采用logistic回归分析的方法,分析在控制人口学特征、社会经济因素和职业相关因素的情况下职业倦怠对健康生产力的影响。

    结果

    共回收问卷3489份,纳入统计分析的有效问卷3156份。其中,有2228名(70.8%)研究对象表现出不同程度的职业倦怠,其中轻中度职业倦怠者1858名(59.0%),重度职业倦怠者370名(11.7%);研究对象的职业倦怠总分中位数(四分位数间距)为2.18(2.69),缺勤率为0.00%(0.00%),隐性缺勤率为20.00%(50.00%)。不同性别、文化程度、婚姻状况、工龄、工作性质、职业倦怠各维度和职业倦怠程度间,隐性缺勤程度不同,差异有统计学意义(P<0.05);不同文化程度、婚姻状况、工龄、工作性质、职业倦怠各维度和职业倦怠程度间,缺勤程度不同,差异有统计学意义(P<0.05)。职业倦怠与缺勤率(r=0.157)和隐性缺勤率(r=0.412)均存在正相关关系(P<0.01)。在控制了人口学特征因素、社会经济因素和职业相关因素后,logistic回归分析显示职业倦怠程度与健康生产力受损的关联关系依然存在,且OR值相对稳定,参照职业倦怠阴性,重度职业倦怠的OR(95%CI)为6.35(4.52~8.92)。

    结论

    企业员工职业倦怠对健康生产力有负面影响,职业倦怠越重,健康生产力受损越严重。企业宜关注职业倦怠防控,以降低健康生产力损失。

     

    Abstract: Background

    At present, domestic research on job burnout and health-related productivity is limited to medical workers, and the impact of job burnout on health-related productivity of enterprise staff deserves attention.

    Objective

    To explore the association between job burnout and health-related productivity loss among enterprise staff.

    Methods

    A cross-sectional online questionnaire survey was conducted among enterprise staff who were selected from seven enterprises in Minhang District of Shanghai. The Chinese version of Maslach Burnout Inventory-General Survey (MBI-GS) was used to assess job burnout, and a questionnaire based on and modified from the WHO Health and Work Performance Questionnaire was used to assess the loss of health-related productivity. Logistic regression was used to analyze the impact of job burnout on health-related productivity under the control of selected demographic characteristics, socio-economic factors, and occupational factors.

    Results

    A total of 3489 questionnaires were recovered, and 3156 valid questionnaires were included in the statistical analysis. Among the 3156 valid questionnaires, 2228 (70.8%) respondents were assessed as suffering from job burnout, in which 1858 (59.0%) were mild to moderate job burnout, and 370 (11.7%) were severe job burnout; the median score (interquartile range) of MBI-GS was 2.18(2.69), the median rates (interquartile range) of absenteeism and presenteeism were 0.00% (0.00%) and 20.00% (50.00%), respectively. The prevalence of presenteeism significantly varied by gender, education, marital status, working years, job category, exhaustion, cynicism, professional efficacy, and job burnout (P<0.05). The prevalence of absenteeism significantly varied by education, marital status, working years, job category, exhaustion, cynicism, professional efficacy, and job burnout (P<0.05). Job burnout was positively correlated with absenteeism (r=0.157) and presenteeism (r=0.412) (P<0.01). After controlling for selected demographic characteristics, social economic factors, and occupational factors, the logistic regression showed that job burnout was associated with health-related productivity loss, the OR value remained relatively stable, and referring to negative job burnout, the OR (95%CI) of severe job burnout was 6.35 (4.52-8.92).

    Conclusion

    Job burnout of enterprise staff has a negative impact on health-related productivity. Severer job burnout associates with higher health-related productivity loss. Enterprises should pay attention to the prevention and control of job burnout to reduce health-related productivity loss.

     

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