MESuRS Laboratory, Conservatoire National des Arts et Métiers, Paris, France
CRESS, Inserm, INRA, Hôpital Hôtel-Dieu de Paris, Paris, France.
BMJ Open. 2022 Dec 30;12(12):e046444. doi: 10.1136/bmjopen-2020-046444.
In modern professional life, mental health prevention and promotion have become a major challenge for decision-makers. Devising appropriate actions requires better understanding the role played by each work-related psychosocial factor (WPSF). The objective of this study was to present a relevant tool to hierarchise WPSFs that jointly takes into account their (impact on mental health) and their (the proportion of the population exposed to WPSF).
A cross-sectional study was conducted in March 2018 among 3200 French workers which are representative of the French working population.
France.
Individuals aged 18-80 years who declared currently having a job (even a part-time job) whatever their occupation or status (employee or self-employed) were eligible. We excluded students, unemployed individuals, housewives/husbands and retired people. The mental health level was assessed using the General Health Questionnaire-28 and 44 items were gathered from theoretical models of WPSFs. We assessed two distinct multivariate methods for calculating WPSF importance: (1) weifila (weighted first last) method in a linear regression context and (2) random forests in a non-linear context. Both methods were adjusted on individual, health and job characteristics.
The WPSF rankings obtained with the two methods to calculate importance are strongly consistent with each other (correlation coefficient=0.88). We highlighted nine WPSFs that are ranked high by both methods. In particular, irrespective of the chosen method, lack of communication, lack of social and hierarchy support and personal-professional life imbalance, emotional demands at work and dissatisfaction with the compensation received came out as top-ranking WPSFs.
A total of nine WPSFs were identified as key for decision-making. The easy-to-use tools we propose can help decision-makers identify priority WPSFs and design effective strategies to promote mental health in the workplace.
在现代职业生活中,心理健康预防和促进已成为决策者面临的一大挑战。制定适当的措施需要更好地了解每个与工作相关的心理社会因素(WPSF)所起的作用。本研究的目的是提出一种相关工具,对 WPSF 进行分层,同时考虑到它们对心理健康的影响以及暴露于 WPSF 的人群比例。
2018 年 3 月,在法国进行了一项横断面研究,共有 3200 名法国工作者参与,这些工作者代表了法国的整个劳动人群。
法国。
符合以下条件的 18-80 岁个体有资格参与:目前正在工作(即使是兼职),无论其职业或身份(受雇或自雇)如何。我们排除了学生、失业者、家庭主妇/丈夫和退休人员。使用一般健康问卷-28 评估心理健康水平,从 WPSF 的理论模型中收集了 44 个项目。我们评估了两种不同的计算 WPSF 重要性的多变量方法:(1)线性回归背景下的 weifila(加权首末)方法和(2)非线性背景下的随机森林。这两种方法都根据个体、健康和工作特征进行了调整。
两种方法计算重要性得到的 WPSF 排名非常一致(相关系数=0.88)。我们突出了九个通过两种方法都排名较高的 WPSF。特别是,无论选择哪种方法,缺乏沟通、缺乏社会和层级支持以及个人-职业生活失衡、工作中的情绪需求和对薪酬的不满都被列为排名靠前的 WPSF。
共确定了九个对决策至关重要的 WPSF。我们提出的易于使用的工具可以帮助决策者识别优先的 WPSF,并设计有效的策略来促进工作场所的心理健康。