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STTR Phase I: Digital Mental Health for Children and Adolescents

STTR Phase I: Digital Mental Health for Children and Adolescents
STTR 第一阶段:儿童和青少年的数字心理健康
批准号:
2110953
负责人:
Tamara Fyke
金额:
$25.59万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2022
资助国家:
美国
项目状态:
已结题
起止时间:
2022-07-15 至 2023-06-30

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英文摘要
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is improved children’s mental and behavioral health via the creation of a platform that unifies the silos of healthcare and education to put children and families first. Due in part to the current pandemic, there is an increased need to support children’s mental and behavioral health. The end-users are the 28 million children between 8-12 years old in America. The team is advancing patient-centered care and personalized education. After the platform is tested for an initial age group of 8-12-year-olds, the plan is to expand the platform across the age-span, including early childhood through senior adults. The platform promises engaging, self-contained, adaptable, safe, and research-based support and learning. The team expects to grow their market share through strategic partnerships with healthcare, education, industry, and non-profit partners. This Small Business Innovation Research Phase I project focuses on leveraging technology, including natural language processing, machine learning, and chatbots, to provide information to students, families, and educators about mental and behavioral health and to get feedback from these groups through their web-based computing devices. This project seeks to develop an online platform that will engage students and allow them to leverage personal care resources aimed at building resilience and providing them access to support and information customized to their individual needs. This Phase I project focuses on building a proof-of-concept platform that provides precision mental health solutions by combining interactive health and wellness methods with engaging content personalized and delivered by machine learning technologies and tools.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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