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Towards early identification of adolescent mental health problems

Towards early identification of adolescent mental health problems
尽早发现青少年心理健康问题
批准号:
MR/T046430/1
负责人:
Anna Moore
金额:
$12.82万
依托单位:
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
项目状态:
已结题
起止时间:
2020 至 --

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中文摘要
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英文摘要
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.
期刊论文(9)
专著(0)
科研奖励(0)
会议论文
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: --
作者: [Cardinal R]
通讯作者: Cardinal R
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。
DOI: 10.17863/cam.86012
发表时间: 2022
期刊:
影响因子: --
作者: [Moorthie S]
通讯作者: Moorthie S
DOI: 10.1186/s12911-023-02176-6
发表时间: 2023-05-05
期刊: BMC medical informatics and decision making
影响因子: 3.5
作者: []
通讯作者:
Transforming child mental health: co-designing, building and evaluating a digitally enabled, personalised, prevention pathway
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    MR/X034917/1
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    2022
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    1043282
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    2011
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    2009
  • 负责人:
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