Investigating the differential geographical, sociodemographic and genetic predictors of mental illness and wellbeing using longitudinal survey data

这一奖学金包含一个跨学科的定量研究计划，以检查精神疾病和精神健康的不同模式和预测因素。这两个概念的互换使用在政策和学术研究中很常见，其中一个假设往往是另一个概念的反面，这一假设往往是毋庸置疑的。这导致了许多关于幸福的政策建议被从一篇专门讨论精神疾病预测的文献中概括出来。这一假设虽然可能是直觉的，但越来越多地受到人口测量科学研究的质疑。这一奖学金建立在ESRC资助的高级定量方法论文中调查这两个概念之间(不同)相似性的工作基础上。它使用了一项具有全国代表性的小组研究的数据，该研究在2009至2018年间进行了8次年度扫描，代表每波约45,000人。它将采用先进的量化技术，通过同时回答两份问卷，评估常见精神疾病衡量标准的支撑过程与精神健康衡量标准的支撑过程的不同程度。这使得调查不仅仅是简单地比较反应是否相同，而是比较反应的基础过程是否相同。然后，研究继续调查这两种反应的地理模式是否相似，以及每种反应的人口统计预测因素是否相似。这也同时允许洞察反应最相似的空间尺度，为政策制定者确定一个空间尺度的建议可能最有理由转移到另一个空间尺度。然后，工作方案继续对疾病指标分解的基础过程进行纵向建模，以评估自2009年以来的几年中，哪些人口群体遭受的精神痛苦负担最大。为了补充对精神疾病和精神健康之间关系的人口统计和地理理解，我将调查幸福的基因预测因素与精神疾病的基因预测因素在哪些方面相同。这一点在越来越多的文献中尤其相关，因为文献越来越认识到，精神健康的定义可以关键地影响遗传对心理痛苦影响程度的研究结果。这一奖学金将进一步研究这一问题，并有助于正在进行的学术和政策讨论，讨论积极和消极心理健康之间复杂和未被充分研究的关系，以及如何最有效地设计干预措施以最大限度地发挥积极影响。

This fellowship contains an interdisciplinary programme of quantitative research to examine the differential patterning and predictors of mental ill-health and mental wellbeing. Interchangeable use of the two concepts is common in policy and in academic research with the, often unquestioned, assumption that one is the inverse of the other. This has led to many policy recommendations for wellbeing being generalised from a literature specifically addressing mental illness prediction. This assumption, whilst perhaps intuitive, has been increasingly called into question by scientific studies of population measurement. This fellowship builds upon work undertaken as part of an ESRC funded Advanced Quantitative Methods thesis in investigating the (dis)similarity between the two concepts. It uses data from a nationally representative panel study with 8 annual sweeps representing approximately 45,000 individuals per wave between 2009 and 2018.It will deploy advanced quantitative techniques to evaluate the degree to which the underpinning processes of a common mental illness measure differ from the underpinning processes of a mental wellness measure, using simultaneous responses to two questionnaires. This allows the investigation to go beyond simply comparing whether responses are the same, but whether the underpinning processes patterning the responses are the same. The research then goes on to investigate whether the geographical patterning of the two responses is similar, and whether the demographic predictors of each are similar. This also simultaneously allows insight into what spatial scale the responses behave most similarly, identifying for policymakers at which spatial scale recommendations from one may be most justifiably transferred to the other. The programme of work then goes on to longitudinally model the decomposed underpinning processes of the illness metric in order to assess which demographic groups are suffering the greatest burden of mental distress in the years since 2009.To complement this demographic and geographical understanding of the relationship between mental illness and mental wellbeing, I will investigate the to which the genetic predictors of wellbeing are the same as the genetic predictors of mental illness. This is especially pertinent in a literature which increasingly recognises that how mental health is defined can critically influence findings of the degree to which genetics influence psychological distress. This fellowship will further examine this and contribute to an ongoing academic and policy discussion about the complex and under-examined relationship between positive and negative mental health, and how interventions can be most effectively designed to maximise positive impact.