What is it about ACE's? Understanding the relationship between adversity and mental health
What is it about ACE's? Understanding the relationship between adversity and mental health
批准号:
2625989
负责人:
金额:
$0.0万
依托单位:
依托单位国家:
英国
项目类别:
Studentship
财政年份:
2021
资助国家:
英国
项目状态:
未结题
起止时间:
2021 至 --
中文摘要
不良的童年经历(ace),如虐待、欺凌或家庭破裂,越来越被认为是日后心理健康问题的最有力决定因素之一。据估计,在接触过ace的人群中,包括抑郁症和自残在内的精神健康问题至少增加了一倍。尽管人们认识到不良经历对后来的心理健康结果的重要性,但对影响最大的不良经历的特征却知之甚少。首先,许多研究都依赖于累积分数,而ace只是简单地二分和相加。这种方法假定每个ACE对利益结果的贡献都是公平的,并且它们通过相同的机制运作。其他研究关注的是ace个体与心理健康之间的关系。虽然这些研究提供了有用的见解,但众所周知,ace通常是同时发生的,而且大多数都没有考虑到这种聚类。其次,很少有人关注接触时间、慢性性或近期性对心理健康的影响,现有研究的结果也不具有结论性。解开这些影响是具有挑战性的,因为那些在童年时期接触过的人可能接触的时间也更长。以人为中心的方法,如潜在类别分析(LCA)已被用于确定个体之间ACE概况的可变性,但目前尚不清楚ACE概况是否在生命过程的不同阶段有所不同。本博士将解决这些局限性,并对ace与两种心理健康结果(抑郁和自残)之间的关系产生有价值的新见解。抑郁症和自残都是近年来不断上升的主要公共卫生问题。拟议的研究将使用来自雅芳父母和儿童纵向研究(ALSPAC)的数据;这是一项对1991年至1992年出生的14000多名参与者进行的英国出生队列研究。ALSPAC拥有无与伦比的ace数据,在童年和青春期前瞻性地询问了500多个问题,并重复测量了成年后抑郁和自残的数据。该研究还包括生物(如炎症)、社会(如教育成果)和认知(如情感识别)因素的丰富信息,这些因素可以作为将ace与后来的心理健康结果联系起来的潜在机制进行探索。研究问题:在青春期和成年期,特定的不良经历与心理健康结果(抑郁和自残)之间有什么关系?ACE在生命历程的不同阶段是如何聚集在一起的?不同的ACE概况与心理健康有何关系?暴露于ace的时间、慢性性和近期性如何影响心理健康问题的风险?不良经历对心理健康的影响机制是什么?关键方法:结构方程建模、中介分析、缺失数据处理策略(如多次插值)和因果分析方法。
英文摘要
Adverse childhood experiences (ACEs) such as abuse, bullying or family disruption are increasingly recognised as one of the most potent determinants of later mental health problems. Estimates suggest that mental health problems, including depression and self-harm are at least double among those who have been exposed to ACEs. Despite the recognised importance of ACEs to later mental health outcomes, relatively little is known about the characteristics of ACEs that have the greatest impact. Firstly, many studies have relied on cumulative scores, whereby ACEs are simply dichotomised and summed. This approach assumes that each ACE contributes equitably to the outcome of interest and that they operate via the same mechanisms. Other research has focused on the relationship between individual ACEs and mental health. Although such studies have provided useful insights, it is known that ACEs often co-occur and most have failed to take account of this clustering. Secondly, little attention has been paid to the role of timing, chronicity, or recency of exposure in relation to mental health, and findings from existing studies have been inconclusive. Disentangling these effects is challenging as it may be that those who have been exposed earlier in childhood have also been exposed for longer. Person centred approaches such as Latent Class Analysis (LCA) have been used to identify variability in ACE profiles between individuals, however it is not currently known whether ACE profiles differ during different stages of the life-course. This PhD will address these limitations and generate valuable new insights into the relationship between ACEs and two mental health outcomes - depression and self-harm. Both depression and self-harm are major public health concerns which have been rising over recent years. The proposed study will use data from the Avon Longitudinal Study of Parents and Children (ALSPAC); a UK birth cohort study of over 14,000 participants born in 1991-1992. ALSPAC has unrivalled data on ACEs, with over 500 questions asked prospectively across childhood and adolescence, as well as repeated measures data on depression and self-harm into adulthood. The study also includes rich information on biological (e.g. inflammation), social (e.g. educational outcomes), and cognitive (e.g. emotion recognition) factors that could be explored as potential mechanisms linking ACEs with later mental health outcomes.Research questions What is the relationship between specific ACEs and mental health outcomes (depression and self-harm) in adolescence and adulthood? How do ACEs cluster together during different stages of the life course, and how do different ACE profiles relate to mental health? How do timing, chronicity, and recency of exposure to ACEs impact on risk for mental health problems? What are the mechanisms through which ACEs have an impact on mental health? Key Methods: structural equation modelling, mediation analysis, strategies for dealing with missing data (such as multiple imputation) and causal analysis methods.
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