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

该研究金包含一个跨学科的定量研究方案，以研究精神疾病和精神健康的差异模式和预测因素。这两个概念的互换使用在政策和学术研究中很常见，通常毫无疑问，假设一个是另一个的反面。这导致了许多从专门针对精神疾病预测的文献中概括出的福利政策建议。这一假设虽然可能是直观的，但越来越多地受到人口测量科学研究的质疑。该奖学金建立在作为ESRC资助的高级定量方法论文的一部分所进行的工作的基础上，该论文调查了两个概念之间的（不）相似性。它使用的数据来自一项全国代表性的小组研究，在2009年至2018年期间，每年进行8次扫描，每波约有45，000人。它将采用先进的定量技术来评估一种常见精神疾病措施的基础过程与一种精神健康措施的基础过程的不同程度，同时回答两份问卷。这使得调查不仅仅是比较反应是否相同，而是比较反应模式化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预测因素是否相似。这也同时允许洞察什么样的空间尺度的反应行为最相似，为决策者确定在哪个空间尺度的建议，从一个可能最容易转移到另一个。然后，工作计划继续对疾病指标的分解基础过程进行纵向建模，以评估自2009年以来哪些人口群体遭受了最大的精神痛苦负担。我将研究哪些健康的遗传预测因子与精神疾病的遗传预测因子相同。这是特别相关的文献，越来越多地认识到，如何定义心理健康可以严重影响遗传学影响心理困扰的程度的结果。该奖学金将进一步研究这一点，并有助于正在进行的学术和政策讨论，探讨积极和消极的心理健康之间复杂而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.