中国全科医学 ›› 2024, Vol. 27 ›› Issue (07): 843-848.DOI: 10.12114/j.issn.1007-9572.2023.0179

• 论著 • 上一篇    下一篇

北京市医务人员付出回报失衡与工作压力的关系研究

李昂, 郭默宁*(), 谭鹏, 路凤, 王梅   

  1. 100034 北京市卫生健康大数据与政策研究中心
  • 收稿日期:2023-04-06 修回日期:2023-10-04 出版日期:2024-03-05 发布日期:2023-12-19
  • 通讯作者: 郭默宁

  • 作者贡献:李昂负责数据分析、论文撰写;郭默宁负责研究整体规划,指导论文撰写与修改,对文章整体负责;谭鹏、路凤负责数据整理、统计指导;王梅负责质量控制和审校。
  • 基金资助:
    首都卫生发展科研专项(首发2021-1G-3051)

The Relationship between Effort-reward Imbalance and Job Stress among Medical Staff in Beijing

LI Ang, GUO Moning*(), TAN Peng, LU Feng, WANG Mei   

  1. Beijing Municipal Health Big Data and Policy Research Center, Beijing 100034, China
  • Received:2023-04-06 Revised:2023-10-04 Published:2024-03-05 Online:2023-12-19
  • Contact: GUO Moning

摘要: 背景 医务工作具有挑战性高、任务重和压力大的特点。付出-回报失衡(ERI)模型认为,如果组织环境造成了ERI,会对员工产生负面影响。医务人员调查是2018年全国第六次卫生服务调查的重要组成部分,医务人员的良好工作感受和工作状态是居民服务利用和健康改善的重要决定因素,提高医务人员的获得感和满意度也是新医改的重要目标。 目的 探讨北京市医务人员ERI与工作压力的关系,为降低医务人员的工作压力提供参考。 方法 本研究数据来源于2018年全国第六次卫生服务调查中对北京市4 156名医务人员的抽样调查结果。根据医务人员的ERI量表和工作压力量表得分,构建工作压力结构方程预测模型,使用偏最小平方法估计相关参数,分析ERI与工作压力之间的关系。 结果 参与付出回报比(ERI指数)计算的有效记录为4 098条,根据ERI指数计算结果,1 333名(32.53%)医务人员处于付出与回报平衡状态,2 765名(67.47%)医务人员处于付出与回报失衡状态。北京市医务人员46.00%的工作压力可通过ERI模型进行解释。内在付出、外在付出、工作回报对工作压力均具有直接影响(P<0.001),其中内在付出的总效应为0.409(95%CI=0.373~0.443),外在付出的总效应为0.583(95%CI为0.559~0.606),工作回报的总效应为-0.199(95%CI=-0.227~-0.171)。另外,内在付出是外在付出和工作回报对工作压力影响的中介因子(P<0.001)。 结论 研究结果支持ERI是北京市医务人员工作压力重要来源的研究假设。鉴于内在付出对工作压力影响最大,卫生管理部门和医疗机构应针对性地改善相关管理制度,解决ERI问题,降低医务人员的工作压力。

关键词: 医务人员, 工作压力, 付出-回报失衡, 结构方程模型, 偏最小平方法, 北京市

Abstract:

Background

Medical work is characterized as challenging, tasking and stressful. The effort-reward imbalance (ERI) model suggests that if the organizational environment contributes to ERI, it can negatively affect employees. The investigation of medical staff is an important part of the 6th National Health Services Survey in 2018. The good job satisfaction and work conditions of medical staff are important determinants of service utilization and health improvement for the population. The sense of accomplishment and satisfaction of medical staff is also an important goal of the new healthcare reform.

Objective

To explore the relationship between ERI and job stress, and provide a reference for reducing the job stress of medical staff.

Methods

The data for this study were obtained from the results of a sample survey of 4 156 healthcare workers in Beijing during the 6th National Health Services Statistics Survey in 2018. A predictive structural equation model of job stress was constructed and based on ERI questionnaire and job stress questionnaire. Relevant parameters were estimated by using the partial least squares to analyze the relationship between ERI and job stress.

Results

The valid records for participating in the ERI index calculation were 4 098. According to the ERI index calculation results, 1 333 (32.53%) healthcare workers were in a state of balance between effort and reward, and 2 765 (67.47%) health workers were in a state of imbalance between effort and reward. The results of factor analysis showed that 46.00% of the job stress experienced by medical staff in Beijing can be attributed to ERI model. Extrinsic, intrinsic effort and work reward all had a direct impact on job stress (P<0.001) , the total effect of intrinsic effort was 0.409 (95%CI=0.373 to 0.443) ; the total effect of extrinsic effort was 0.583 (95%CI=0.559 to 0.606) ; the total effect of work reward was -0.199 (95%CI=-0.227 to -0.171) . In addition, the intrinsic effort mediated the impact of extrinsic effort and work rewards on job stress.

Conclusion

The results of the study support the hypothesis that ERI is an important source of job stress for medical staff in Beijing. Based on the evidence that the intrinsic effort has the greatest impact on job stress, the relevant management system should be improved by health administration and medical institutions to address ERI and reduce the job stress of medical staff.

Key words: Medical staff, Occupational stress, Effort-reward imbalance, Structural equation model, Partial least square method, Beijing