Work, Welfare and Mental Health: a longitudinal analysis of trends in working conditions, welfare provision and inequalities in mental health

英国的工作强度远高于法国和德国等其他欧洲国家，但生产率却低了约20%，而且在过去十年中几乎没有提高。与欧洲同行相比，英国公司对新技术的投资不足，这意味着工人需要更努力、更快地工作来弥补这一点[1]。这可能会给工人带来巨大的压力，影响他们的心理健康。工作中的心理健康问题每年为英国每个工人花费约1300英镑。使人们在工作中承受压力和紧张的代价对人们的家园、健康和家庭产生了溢出效应。在极端情况下，心理健康状况不佳的人可能不再能够工作。2016年，超过50%的丧失工作能力相关福利申请人报告心理健康状况不佳（焦虑，抑郁，压力或焦虑）是他们的主要健康状况，而2000年只有33%的申请人。在与工作有关的心理健康状况方面，还存在着严重的地理、社会经济和性别不平等。这个博士项目的目的是使用先进的纵向定量方法和二级数据源，以更好地了解工作条件，福利制度，社会地位和地理位置对心理健康的影响。了解这一点将有助于制定工作中的健康和福利政策以及有利于心理健康的福利政策。具体而言，本博士论文将集中在以下研究问题：1）工作类型，工作时间，工作时间长度，工作期限和通勤时间如何影响心理健康？2)他们在心理健康方面的不平等是否受年龄、性别、教育程度或地理位置的影响？3)随着时间的推移，（1）和（2）是否发生了变化，特别是与经济衰退和紧缩政策相关的变化？4)福利性质的变化是否对工作条件和心理健康之间的关系产生了影响？为了解决这些研究问题，将使用一些英国数据集。用于获取个人信息的主要数据集将来自英国家庭小组调查和理解社会调查，涵盖1991-2016年期间，以了解心理健康与工作之间关系的演变。NOMIS关于福利津贴支付和邻里特征的其他数据将附在这一数据之后。此外，我们还将利用英国犯罪统计数据来捕捉可能影响心理健康的邻里因素。分析将采用一些计量经济学技术的面板数据。博士生将熟悉应用标准估计技术，如随机广义最小二乘法和固定效应模型。此外，她将应用更多新颖的方法来识别使用看似无关的回归和分解相关系数的方差/协方差矩阵的途径。因果模型也将估计，以确定福利状态和心理健康之间的关系。总的来说，该项目将为学生提供必要的技能，以在目前技能短缺的领域从事定量社会科学发展能力的职业。

Work intensity in the UK is much higher than other European countries such as France and Germany but productivity is approximately 20% lower and has barely improved over the last decade. Compared to their European counterparts, UK companies have underinvested in new technologies meaning that workers need to work harder and faster to make up for it [1]. This can put significant strain on workers impacting on their mental health. Mental health problems at work cost approximately £1300 per year for every worker in the UK. The cost of putting people under stress and strain at work has spillover effects to people's homes, health and families. In the extreme, people with poor mental health may no longer be able to work. In 2016, over 50% of people claiming incapacity-related benefits reported poor mental health (anxiety, depression, stress or anxiety) as their main health condition compared to only 33% of claimants in 2000. There are also significant geographical, socio-economic and gender inequalities in work-related mental health conditions. The aim of this PhD project is to use advanced longitudinal quantitative methods and secondary data sources to better understand how working conditions, the welfare system, social position, and geography impact on mental health. Understanding this will help contribute to the development of health and well-being policy at work and mental health friendly welfare policy. Specifically, this PhD dissertation will focus on the following research questions:1) How does job type, working hours, length of time in the job, job tenure, and commuting time impact on mental health? 2) Are their inequalities in the mental health effects of (1) by age, gender, educational attainment, or geography? 3) Have (1) and (2) been changing over time particularly in relation to recession and austerity?4) Does the changing nature of welfare provision have any impact on the relationship between working conditions and mental health?To address these research questions, a number of UK datasets will be used. The main dataset used to obtain information on individuals would come from the British Household Panel Survey and Understanding Society Survey covering the period 1991-2016 to look at the evolution of the relationship between mental health and work over time. Additional data from NOMIS on welfare benefits payments and neighbourhood characteristics will be appended to this data. In addition, we will also utilise data from UK Crime Statistics to capture neighbourhood factors that are likely to impact on mental health. The analysis will employ a number of econometric techniques for panel data. The PhD student will gain familiarity with applying standard estimation techniques such as randomised generalised least squares and fixed effects models. In addition, she will apply more novel methods for identifying pathways using seemingly unrelated regressions and decomposing the variance/covariance matrix of the correlation coefficient. Causal models will also be estimated to identify the relationship between the welfare state and mental health. Overall, this project will provide the student with the necessary skills to pursue a career in quantitative social sciences developing capacity in an area which currently has a skills shortage.