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An effective, data driven, interoperable, early intervention to tackle the covid related decline in youth mental health

An effective, data driven, interoperable, early intervention to tackle the covid related decline in youth mental health
一种有效的、数据驱动的、可互操作的早期干预措施,以解决与新冠病毒相关的青少年心理健康下降问题
批准号:
79504
负责人:
金额:
$33.68万
依托单位:
依托单位国家:
英国
项目类别:
Collaborative R&D
财政年份:
2020
资助国家:
英国
项目状态:
已结题
起止时间:
2020 至 --

项目摘要

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中文摘要
翻译
在2019冠状病毒病爆发之前,全球的青年心理健康服务已经不堪重负,资金不足(WHO\_2018)。年轻人的精神疾病花费公共钱包高达每人63,878英镑,pa(Suhrcke_2008)。在COVID-19期间,对支持的需求增加,而获得支持的机会减少(Young\_Minds\_2020)。已有证据表明,在封锁期间儿童抑郁症增加([Bignardi\_2020][0]\_[Cortina\_2020][1])。自3月20日以来,MeeTwo的参与度增加了30%,高风险职位增加了65%。COVID产生了多种并发的风险因素,增加了心理健康困难的可能性(例如,父母失业、婚姻冲突、丧亲之痛)。这种风险的聚集只会随着时间的推移而显现,因此早期干预至关重要[(Wade,2020)][2]。早期干预有助于防止年轻人达到危机点,并降低成年后长期精神疾病的可能性(RCON 2017)。在COVID-19之后,英国开发创新的预防、干预和服务提供方法至关重要。MeeTwo是一款屡获殊荣的同龄人支持应用程序,适用于11-25岁的人群。它已经支持了35,000名年轻人,并在NHS应用程序库中有特色。MeeTwo Connect是一项在封锁期间推出的新服务,它使年轻人能够从应用程序中连接到他们的学校,大学或NHS心理健康提供者。MeeTwo和MeeTwo Connect是创新的,因为它们提供了随时随地访问多种可互操作的心理支持选项。MeeTwo数据集于2017年推出,现在已经足够大,可以纵向深入了解疫情的影响。我们迫切需要开发一套数据报告工具,并进行独立的影响评估,以便我们能够充分利用我们数据的价值。机器学习和先进的数据分析技术的整合将提高对COVID-19后青少年心理健康的理解,并提高我们帮助用户获得适当服务的能力。该项目直接解决COVID-19引起的心理健康问题。通过更好地了解我们的数据,我们可以确定COVID-19如何损害青少年的心理健康,并按问题、地点、性别和年龄提供有针对性的支持。早期干预的37%的年轻人提到CAMHS,但出院后的评估将削减CAMHS等待名单。在2017/18年度,69%的被转介到CAMHS的年轻人在一年内没有接受治疗(儿童专员2018)。为所有年轻人提供易于获得的,高质量的,基于证据的心理帮助将减轻学校和大学辅导员,CAMHS和IAPT的负担;释放辅导员和临床医生,专注于最需要的人。与本研究一起开发的数据报告工具将使与机构共享数据更容易,以告知和改善其服务。这个为期9个月的实验/工业研究项目与安娜弗洛伊德中心和Oxleas NHS基金会信托合作,将确保MeeTwo Connect完全具备在COVID-19后复苏中发挥主导作用。[0]:https://osf.io/v7f3q/[1]:https://www.ucl.ac.uk/evidence-based-practice-unit/sites/evidence-based-practice-unit/files/coronavirus_emerging_evidence_issue_2.pdf [2]:https://ucl-new-primo.hosted.exlibrisgroup.com/primo-explore/fulldisplay? docid=TN_elsevier_sdoi_10_1016_j_psychres_2020_113143&context=PC&vid=UCL_VU2?= en_US&search_scope=CSCOP_UCL& adapter =primo_central_multiple_fe&tab=local&query= any,contains,mental%20health%20youth%20covid&offset =0
英文摘要
Prior to the outbreak of COVID-19 youth mental health services globally were already overstretched and unfunded (WHO\_2018). Mental illness in young people costs the public purse up to £63,878 per person, pa (Suhrcke\_2008). During COVID-19 the need for support has increased, whilst access to support has declined (Young\_Minds\_2020). There is already evidence of increased childhood depression during lockdown ([Bignardi\_2020][0]\_[Cortina\_2020][1]). Since March 20th, engagement on MeeTwo has increased by 30% and high risk posts have increased by 65%. COVID has created multiple co-occurring risk factors that increase the likelihood of mental health difficulties (e.g., parental job loss, marital conflict, bereavement). The aggregation of this risk will only unfold over time so early intervention is crucial [(Wade, 2020)][2]. Early intervention helps prevent young people reaching crisis point and decreases the likelihood of long-term mental ill health in adulthood (RCON 2017). Post COVID-19 it is critical that the UK exploit innovative methods of prevention, intervention and service delivery.MeeTwo is a multi-award winning peer support app for people aged 11-25\. It already supports 35k young people and is featured on the NHS Apps Library. MeeTwo Connect is a new service, launched during lockdown, which enables young people to connect to their school, university or NHS mental health provider from within the app. MeeTwo and MeeTwo Connect are innovative because they provide anytime, anywhere access to multiple interoperable psychological support options.Launched in 2017, the MeeTwo data set is now big enough to provide longitudinal insights into the impact of the pandemic. We urgently need to develop a suite of data reporting tools and undertake independent impact evaluation so that we can fully exploit the value of our data. The integration of Machine Learning and advanced data analytics techniques will improve understanding of youth mental health following COVID-19 and increase our capacity to help users access appropriate services.This project directly addresses the mental health issues arising from COVID-19\. With a better understanding of our data we can identify how COVID-19 has damaged youth mental health and deliver targeted support by issue, location, gender and age. Early intervention for the 37% of young people referred to CAMHS but discharged following assessment would slash CAMHS waiting lists. In 2017/18, 69% of young people referred to CAMHS did not receive treatment within a year (Children's Commissioner 2018). The provision of easily accessible, high quality, evidence based mental help for all young people will reduce the burden on school and university counsellors, CAMHS and IAPT; freeing up counsellors and clinicians to focus on those with greatest need. Data reporting tools developed with this research will make it easier to share data with institutions to inform and improve their services.This 9-month Experimental/Industrial Research project, run in partnership with The Anna Freud Centre and Oxleas NHS Foundation Trust will ensure that MeeTwo Connect is fully equipped to play a leading role in the post COVID-19 recovery.[0]: https://osf.io/v7f3q/[1]: https://www.ucl.ac.uk/evidence-based-practice-unit/sites/evidence-based-practice-unit/files/coronavirus_emerging_evidence_issue_2.pdf[2]: https://ucl-new-primo.hosted.exlibrisgroup.com/primo-explore/fulldisplay?docid=TN_elsevier_sdoi_10_1016_j_psychres_2020_113143&context=PC&vid=UCL_VU2?=en_US&search_scope=CSCOP_UCL&adaptor=primo_central_multiple_fe&tab=local&query=any,contains,mental%20health%20youth%20covid&offset=0
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国内基金
海外基金
Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis
Data-driven Recommendation System Construction of an Online Medical Platform Based on the Fusion of Information
复杂数据下半参数转换模型及其在老年慢性病发展中的应用研究
  • 批准号:
    72101261
  • 项目类别:
    青年科学基金项目(C类)
  • 资助金额:
    30.0万元
  • 批准年份:
    2021
  • 负责人:
    孙韬
  • 依托单位:
Development of a Linear Stochastic Model for Wind Field Reconstruction from Limited Measurement Data
  • 批准号:
    --
  • 项目类别:
    --
  • 资助金额:
    40万元
  • 批准年份:
    2020
  • 负责人:
    Vikrant Gupta
  • 依托单位: