Alcohol Misuse: Electronic Longitudinal Alcohol Study in Communities (ELAStiC)

现在有一个独特的机会来利用现有的英国数据来更好地了解酒精在整个生命过程中的滥用。该项目的总体目标是1)将数据纳入英国安全电子研究平台(UKSeRP)，并开发设施以实现研究访问；2)利用该平台进行假设驱动的研究，以提供对酒精使用、其影响和危害途径的关键见解；3)利用当前研究小组的专业知识，利用分析方法的最新发展；以及4)明确工作的政策相关性，并利用机会与可能的干预开发进行对接。因此，该项目旨在利用广泛的纵向研究和数据链接设施的价值，在UKSeRP内建立一个分析平台，促进对整个生命过程中有害酒精使用的调查。该提案是平衡的，它结合了广泛的技能、相当多的专业知识和现有数据以及分析这些数据的技术。数据本身涵盖了年轻人，那些处于中年和晚年的人。然后将这些数据与常规行政数据联系起来，包括来自学校(例如教育程度)、国民保健制度(健康)、警察(反社会行为)和其他来源(包括出生和死亡)的数据。然后，这些让我们了解酒精如何影响一般健康、卫生服务使用、精神健康、教育程度和犯罪行为。这些数据的性质也让我们能够了解酒精使用如何影响年轻人晚年的认知能力下降，以及情绪和认知发展。已经有相当多的活动产生了利用纵向数据进行研究的机会，尽管只有有限的工作专门针对酒精。因此，我们能够利用这些正在进行的投资，并与英国痴呆症平台斯旺西大学通过电子记录研究改善人口健康中心(由医学研究理事会领导的财团资助)合作，该中心将为数据链接提供技术和财务支持。此外，该项目将明确审查产出的政策和影响相关性，利用产出调查机会，与(除其他外由经济及社会研究理事会资助的)发展和评价改善公共卫生的复杂干预措施中心一道制定新的干预措施。这些合作带来了这类工作所需的一套独特的技能以及技术支持。该项目的基础是有机会将不同的技能组合在一起。调查人员来自广泛的背景，在分析和解释纵向数据方面有不同的技能。这为特定领域的工作提供了机会，以便为整个项目提供信息。虽然该项目是基于特定的研究假设，但这些假设被提供给工作包，这些工作包使用项目团队的整体技能来开发相关的输出。这种附加值是通过组织资源以最大限度地实现协作工作来实现的，因此超越了对数据提出的基本问题。

There exists a unique opportunity to exploit existing UK data to better understand alcohol misuse across the life course. The overall goals of this project are to 1) incorporate data into the UK Secure eResearch Platform (UKSeRP) and develop facilities to enable research access, 2) undertake hypothesis driven research using this platform to provide critical insights into alcohol use, it's effects and pathways into harm, 3) exploit the current research group's expertise to capitalise on the most recent developments in analytical methodology, and 4) make explicit the policy relevance of the work and exploit opportunities to interface with possible intervention development. This project therefore aims to leverage the value of a broad set of longitudinal studies and data linkage facilities to construct an analytical platform within UKSeRP that facilitates the investigation of harmful alcohol use across the life course. The proposal is balanced, it combines a broad skillset, with considerable expertise with the available data together with techniques in the analysis of such data. The data itself covers youngsters, those in mid- and later-life. These data are then linked to routine administrative data including those from schools (e.g. educational attainment), the NHS (health), the police (anti-social behaviour) and other sources including births and deaths. These then allow us to understand how alcohol affects general health, health service use, mental health, educational attainment and criminality. The nature of these data also allow us to understand how alcohol use affects cognitive decline in later life, and emotional and cognitive development in young people. There has already been considerable activity generating opportunities to use longitudinal data for research, although only limited work has looked at alcohol specifically. We are therefore able to exploit these on-going investments and collaborate with the UK Dementia Platform, Centre for the Improvement of Population Health through e-Records Research (CIPHER) at Swansea University (funded by a consortium led by the Medical Research Council) which will provide technical and financial support for data linkage. In addition, the project will explicitly examine the policy and impact relevance of outputs, use outputs to investigate opportunities to develop novel interventions with, for example, the Centre for the Development and Evaluation of Complex Interventions for Public Health Improvement (funded by the Economic and Social Research Council, amongst others). These collaborations bring together a unique set of skills that are required for such work as well as technical support.Fundamental to the project is the opportunity to bring together a diverse skillset. Investigators come from a broad range of backgrounds and have varying skills in relation to the analysis and interpretation of longitudinal data. This provides opportunities for work in specific areas to inform the project as a whole. Although the project is based on specific research hypotheses, these feed into work packages that use the project team's skills as a whole to develop relevant outputs. This added value is realised through organising resources to maximise collaborative working and therefore go beyond the fundamental questions asked of the data.