Scalable TRansdiagnostic Early Assessment of Mental Health (STREAM)

可扩展的心理健康跨诊断早期评估 (STREAM)

• 批准号: MR/S036423/1
• 负责人: Bhismadev Chakrabarti
• 金额: $ 502.51万
• 依托单位: University of Reading
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2019
• 资助国家: 英国
• 起止时间: 2019 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=MR%2FS036423%2F1
• 关键词: Scalable; TRansdiagnostic; Early; Assessment; Mental

Worldwide, over 250 million children are at risk of not obtaining their developmental potential due to exposure to adverse circumstances. India and Malawi house some of the most disadvantaged populations in the world, with over 10% of all children aged 2 to 9 years estimated to have neurodevelopmental disorders. However, social and economic barriers to access qualified health personnel mean that most of these children do not receive any assessment of neurodevelopment or a clinical diagnosis when needed. Moreover, many parents are unaware of developmental milestones, so clinical opinion is sought only when symptoms become more pronounced and begin to impact daily life with a lost opportunity for early interventions. This avoidable delay is an unfolding tragedy in light of evidence showing that frontline worker delivered interventions can lead to better behavioural and social outcomes and improve long term developmental trajectories. Scalable methods to assess child neurodevelopment and mental health would promote early referral to specialist facilities, ultimately connecting families with affordable, community-based interventions. Directly measuring neurodevelopment allows us to identify the most vulnerable children as early as possible, allowing limited resources to be focused on those most likely to benefit from preventive approaches. Taken together, focusing on brain development in early childhood is critical to revolutionising global mental health of young children.We will realise this goal by developing a Scalable Transdiagnostic Assessment of Mental Health (STREAM), a mobile platform usable in the home or in a routine health facility by non-specialist workers. STREAM will be delivered on a tablet PC and will collect different types of data from 4000 children in India and Malawi. First, parents will be asked simple questions about their child's everyday behaviour, based on established questionnaires that have been validated in low income settings. Second, gamified tasks designed to measure motor, social, and cognitive abilities will be administered on the tablet. Additionally, novel low-cost eye-tracking technology on the same tablet PC will be used to monitor the child's eye movements in simple tasks, such as those assessing preference for social versus non-social images, and measuring how quickly attention shifts to new objects appearing on the screen. Finally, a segment of parent and child interaction will be recorded using the inbuilt camera, and used to code for signs of atypical behaviour. This combination of multiple measures will provide independent channels of data collected on a single platform, significantly improving on current assessment methods that often rely on one technique and expensive, highly skilled but scarce human resources. STREAM will be designed such that it will require minimal training to be administered by non-specialist workers in low and middle income countries, thereby promoting task-sharing, a concept endorsed by the World Health Organization to reach wider populations. This task-sharing approach reduces the burden on the small number of highly-skilled mental-health and child development professionals in these low resource settings. STREAM can also help develop community awareness and, in the longer term, address the barrier of low demand for services in these areas. The development and application of the STREAM platform involves collaborations across the breadth of basic and applied sciences. Our network comprising clinicians, neuroscientists, public health specialists and data scientists spread across UK, India and Malawi is optimally suited to leading this challenge because of our combined expertise deploying novel technologies to measure early childhood neurodevelopment in low-resource settings.

在世界范围内，超过2.5亿儿童由于暴露于不利环境而面临无法获得其发展潜力的风险。印度和马拉维是世界上处境最不利的人口之一，据估计，2至9岁的儿童中有10%以上患有神经发育障碍。然而，在获得合格的保健人员方面存在社会和经济障碍，这意味着这些儿童中的大多数在需要时得不到任何神经发育评估或临床诊断。此外，许多父母不知道发育的里程碑，因此只有当症状变得更加明显，开始影响日常生活，失去了早期干预的机会时，才寻求临床意见。有证据表明，一线工作人员提供的干预措施可以带来更好的行为和社会结果，并改善长期发展轨迹，因此这种可以避免的延误是一场正在上演的悲剧。评估儿童神经发育和心理健康的可扩展方法将促进早期转诊到专业设施，最终将家庭与负担得起的社区干预措施联系起来。直接测量神经发育使我们能够尽早识别最脆弱的儿童，使有限的资源集中在那些最有可能从预防措施中受益的儿童身上。综上所述，关注幼儿期的大脑发育对于彻底改变全球幼儿心理健康至关重要。我们将通过开发一个可扩展的心理健康跨诊断评估（STREAM）来实现这一目标，这是一个移动的平台，可供非专业工作人员在家庭或常规卫生设施中使用。STREAM将在平板电脑上提供，并将从印度和马拉维的4000名儿童中收集不同类型的数据。首先，根据在低收入环境中得到验证的既定问卷，父母将被问到关于孩子日常行为的简单问题。其次，旨在测量运动、社交和认知能力的游戏化任务将在平板电脑上执行。此外，同一台平板电脑上的新型低成本眼动追踪技术将用于监测儿童在简单任务中的眼动，例如评估对社交图像和非社交图像的偏好，以及测量注意力转移到屏幕上出现的新物体的速度。最后，一段父母和孩子的互动将使用内置的摄像头记录，并用于编码的非典型行为的迹象。这种多种措施的结合将为在单一平台上收集的数据提供独立的渠道，大大改善目前往往依赖一种技术和昂贵、高技能但稀缺的人力资源的评估方法。STREAM的设计将使中低收入国家的非专业工作人员只需接受最低限度的培训，从而促进任务分担，这是世界卫生组织赞同的一个覆盖更广泛人群的概念。这种任务分担的方法减轻了在这些低资源环境中少数高技能心理健康和儿童发展专业人员的负担。STREAM还可以帮助提高社区意识，并从长远来看，解决这些地区服务需求低的障碍。STREAM平台的开发和应用涉及基础科学和应用科学的广泛合作。我们的网络由遍布英国，印度和马拉维的临床医生，神经科学家，公共卫生专家和数据科学家组成，最适合领导这一挑战，因为我们的综合专业知识部署了新技术来衡量低资源环境中的儿童早期神经发育。

项目成果

Autism community priorities in diverse low-resource settings: A country-wide scoping exercise in India.

• DOI: 10.1177/13623613231154067
• 发表时间: 2024-01
• 期刊: AUTISM
• 影响因子: 5.2
• 作者: Dey, Ipsita;Chakrabarty, Sreerupa;Nandi, Rajanya;Shekhar, Rakshita;Singhi, Sakhi;Nayar, Shoba;Ram, Jai Ranjan;Mukerji, Shaneel;Chakrabarti, Bhismadev
• 通讯作者: Chakrabarti, Bhismadev

Self-Face Recognition and the Brain - How the Neuroscience of Mirror Recognition Has Changed Psychology, Psychiatry, and Evolution

自我面部识别和大脑——镜子识别的神经科学如何改变了心理学、精神病学和进化论

• DOI: 10.4324/9781003181156-9
• 发表时间: 2023
• 作者: Chakraborty A

Quantifying preference for social stimuli in young children using two tasks on a mobile platform.

• DOI: 10.1371/journal.pone.0265587
• 发表时间: 2022
• 期刊: PLOS ONE
• 影响因子: 3.7
• 作者: Dubey, Indu;Brett, Simon;Ruta, Liliana;Bishain, Rahul;Chandran, Sharat;Bhavnani, Supriya;Belmonte, Matthew K.;Estrin, Georgia Lockwood;Johnson, Mark;Gliga, Teodora;Chakrabarti, Bhismadev
• 通讯作者: Chakrabarti, Bhismadev

EEG signatures of cognitive and social development of preschool children-a systematic review.

• DOI: 10.1371/journal.pone.0247223
• 发表时间: 2021
• 期刊: PloS one
• 影响因子: 3.7
• 作者: Bhavnani S;Lockwood Estrin G;Haartsen R;Jensen SKG;Gliga T;Patel V;Johnson MH
• 通讯作者: Johnson MH

EEG signatures of cognitive and social development of preschool children-a systematic review

学龄前儿童认知和社会发展的脑电图特征——系统评价

• DOI: 10.17863/cam.65054
• 发表时间: 2021
• 作者: Bhavnani S