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Towards early identification of adolescent mental health problems

尽早发现青少年心理健康问题

基本信息

批准号：
MR/T046430/1
负责人：
Anna Moore
金额：
$ 12.82万
依托单位：
University of Cambridge
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2020
资助国家：
英国
起止时间：
2020 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=MR%2FT046430%2F1
关键词：
Towards early identification adolescent mental

项目摘要

Many aspects of a child or young person's life can affect their mental health. If someone has a serious mental health problem their general practitioner (GP) may refer them to mental health (psychiatry) services for assessment and treatment by professionals. Mental health services are stretched so often intervene late, leaving people to suffer unnecessarily with problems that therefore may last longer, be more severe, or be harder to treat.Early warning signs of mental health problems may be noticed by the person themselves or by others (e.g. school staff, social workers). Many things can suggest a mental health problem, such as difficult early experiences, bullying, changes in behaviour, poor school attendance or grades, or risk-taking. Not all who experience one or more of these will have a mental health problem, so we need to take them together to spot patterns that show who is developing problems and may need professional help. However, this information (data) is stored in different places, e.g. by schools, GPs and social workers and so it may be impossible to spot problems early.Some researchers have joined data from two or more sources to find patterns suggesting mental health problems. Their success indicates good potential in this approach, but they have not made a practical difference for two main reasons: 1) the models are not yet accurate enough, probably because they omit many factors that can lead to problems; 2) the results cannot be used directly to help young people as they are based on anonymous data.We will develop a system that can be used by health, education, or social workers to identify adolescents showing early signs of mental health problems, to offer them help sooner. At the same time we want to provide better anonymous data for research into predicting mental health problems.Data must be held securely (most likely in the NHS), and only people involved in a person's care should be able to see it, but we need to understand how best to do this. To use data for research while protecting privacy it will be anonymised, removing anything that directly identifies a person (e.g. name, address, date of birth, NHS number) and access will be restricted to approved researchers. But we do not yet know what technical problems there may be in linking the databases, or what data the system will need in order to detect people showing early signs of a problem. The final challenge is how to make this work within the NHS, schools, and social care settings to enable earlier identification of young sufferers of mental health problems.Over the next year, we want to tackle these challenges by creating a group including mental health researchers, psychologists, schools, the NHS, councils, computer scientists, security experts, mathematicians, people who provide services, and policy makers, many of whom are doing ground-breaking work in other areas. We want to turn their attention to jointly solving these problems. We must involve young people, their carers, and people with lived experience: it is their data and we need to understand their views. We would like their help thinking about which professionals can see their data, and what should happen when a young person is thought to be developing mental health problems.We will hold workshops about these questions. We also have permission to create an initial data set with data from health, social services, and education. We will anonymise these, and practise linking and analysing them. These will help us understand the challenges, so that our final plan will be more detailed and likely to succeed.In the future we want to test if a computer program makes it easier to identify mental health problems and offer young people treatments earlier, and if they get better quicker because of this. This might have a range of benefits including helping with school, relationships, home life, and getting jobs or into university, and we want to test this theory.

儿童或青少年生活的许多方面都会影响他们的心理健康。如果某人有严重的心理健康问题，他们的全科医生 (GP) 可能会将他们转介至心理健康（精神病学）服务机构，由专业人员进行评估和治疗。心理健康服务捉襟见肘，干预往往较晚，使人们遭受不必要的痛苦，因此可能持续更长时间、更严重或更难治疗。心理健康问题的早期预警信号可能会被人自己或其他人（例如学校工作人员、社会工作者）注意到。许多事情都可能表明存在心理健康问题，例如困难的早期经历、欺凌、行为改变、出勤率或成绩不佳或冒险行为。并非所有经历过其中一种或多种的人都会出现心理健康问题，因此我们需要将他们放在一起，以发现表明谁正在出现问题并可能需要专业帮助的模式。然而，这些信息（数据）存储在不同的地方，例如一些研究人员将来自两个或多个来源的数据结合起来，以寻找表明心理健康问题的模式。他们的成功表明了这种方法的良好潜力，但由于两个主要原因，他们还没有产生实际影响：1）模型还不够准确，可能是因为它们忽略了许多可能导致问题的因素； 2）结果不能直接用来帮助年轻人，因为它们基于匿名数据。我们将开发一个系统，可供卫生、教育或社会工作者使用，以识别出现心理健康问题早期迹象的青少年，以便更快地为他们提供帮助。与此同时，我们希望为预测心理健康问题的研究提供更好的匿名数据。数据必须安全保存（最有可能在 NHS 中），并且只有参与个人护理的人员才能看到它，但我们需要了解如何最好地做到这一点。为了在保护隐私的同时将数据用于研究，数据将被匿名化，删除任何直接识别个人身份的信息（例如姓名、地址、出生日期、NHS号码），并且访问将仅限于经批准的研究人员。但我们还不知道连接数据库时可能存在哪些技术问题，也不知道系统需要哪些数据才能检测到出现问题的早期迹象。最后的挑战是如何在 NHS、学校和社会护理机构中开展这项工作，以便更早识别患有心理健康问题的年轻患者。在接下来的一年里，我们希望通过创建一个包括心理健康研究人员、心理学家、学校、NHS、理事会、计算机科学家、安全专家、数学家、提供服务的人员和政策制定者的团队来应对这些挑战，其中许多人正在其他领域开展开创性的工作。我们希望引起他们的注意，共同解决这些问题。我们必须让年轻人、他们的照顾者和有生活经验的人参与进来：这是他们的数据，我们需要了解他们的观点。我们希望他们帮助思考哪些专业人士可以看到他们的数据，以及当年轻人被认为出现心理健康问题时应该采取什么措施。我们将举办有关这些问题的研讨会。我们还有权使用来自健康、社会服务和教育的数据创建初始数据集。我们将对这些进行匿名化，并练习链接和分析它们。这些将帮助我们了解挑战，以便我们的最终计划更加详细并可能成功。将来我们想测试计算机程序是否可以更容易地识别心理健康问题并更早地为年轻人提供治疗，以及他们是否因此而更快地好起来。这可能有一系列好处，包括帮助学校、人际关系、家庭生活、找到工作或进入大学，我们想测试这个理论。

项目成果

期刊论文数量（9）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Additional file 1 of De-identified Bayesian personal identity matching for privacy-preserving record linkage despite errors: development and validation

尽管存在错误，但用于隐私保护记录链接的去识别贝叶斯个人身份匹配的附加文件 1：开发和验证

DOI：
10.6084/m9.figshare.22774184
发表时间：
2023
期刊：
影响因子：
0
作者：
Cardinal R
通讯作者：
Cardinal R

Leveraging Administrative Data to Better Understand and Address Child Maltreatment: A Scoping Review of Data Linkage Studies.

DOI：
10.1177/10775595221079308
发表时间：
2023-03
期刊：
CHILD MALTREATMENT
影响因子：
5.1
作者：
Soneson, Emma;Das, Shruti;Burn, Anne-Marie;van Melle, Marije;Anderson, Joanna K.;Fazel, Mina;Fonagy, Peter;Ford, Tamsin;Gilbert, Ruth;Harron, Katie;Howarth, Emma;Humphrey, Ayla;Jones, Peter B.;Moore, Anna
通讯作者：
Moore, Anna

Rapid systematic review to identify key barriers to access, linkage, and use of local authority administrative data for population health research, practice, and policy in the United Kingdom.

快速系统审查，以确定英国人口健康研究、实践和政策中获取、链接和使用地方当局行政数据的主要障碍。