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Grant: Fellowship - Priority Announcement: Pandemic Preparedness and Health Emergencies

Unity Health Toronto

$140,000.00

Understanding the Impact of the COVID-19 Pandemic: A Population-Level Natural Language Processing Study of Youth Mental Health

EF 2025-26

Résumé
Young people in Canada are struggling with mental health at unprecedented levels. About one in five youth face a mental health disorder, and the COVID-19 pandemic made this crisis even worse. Many youth cannot access the help they need due to long waitlists, their geographical location, or the stigma surrounding seeking support. Kids Help Phone (KHP), a free national mental health service, has recorded over 1.5 million text and chat sessions from young people since 2018 seeking mental health support. While these conversations contain invaluable insight into what youth are experiencing, KHP currently lacks the tools to fully understand patterns in this data, such as who is reaching out, how their needs change over time, and what strategies from responders make the most difference. Our project will use natural language processing (NLP), a type of artificial intelligence that enables computers to understand human language, to analyze KHP's de-identified text and chat records from 2018-2025. This approach will allow us to track important mental health features, such as signs of anxiety, sadness, anger, and overall mood, before, during, and after the COVID-19 pandemic. We will also examine whether these patterns vary across youth from diverse backgrounds, including different age groups, racial identities, and sexual orientations, to support equitable decision-making and care for youth from diverse backgrounds. By uncovering how youth mental health changed during the pandemic and what kinds of support work best, this research will provide KHP with direct guidance to strengthen their counseling practices. Ultimately, my work aims to make sure that young people across Canada receive faster, more effective, and more equitable mental health support when they need it most.
Programme
Fellowship - Priority Announcement: Pandemic Preparedness and Health Emergencies
Bénéficiaire
Emplacement
Ontario, Canada
Type de bénéficiaire
Other
Type
Grant
Source
CIHR Funding Decisions Database

Tel que publié

Id
538189
Name
Li Yutong
Region
Ontario
Country
Canada
Orgtype
Institution Paid; Research Institution
Instname2
Neurosciences, Mental Health and Addiction
Theme2
Social / Cultural / Environmental / Population Health
Prcname2
Canada Postdoctoral Research Award - B
Projecttitle
Understanding the Impact of the COVID-19 Pandemic: A Population-Level Natural Language Processing Study of Youth Mental Health
Programtype2
Fellowship Programs
Orgnameinp2
Unity Health Toronto
Cihramount2
$140,000
Cihrequipment2
$0
Programname2
Fellowship - Priority Announcement: Pandemic Preparedness and Health Emergencies
Keyworddelim
Covid-19; Longitudinal Outcomes; Machine Learning; Natural Language Processing; Populational Mental Health; Youth Mental Health
Abstract
Young people in Canada are struggling with mental health at unprecedented levels. About one in five youth face a mental health disorder, and the COVID-19 pandemic made this crisis even worse. Many youth cannot access the help they need due to long waitlists, their geographical location, or the stigma surrounding seeking support. Kids Help Phone (KHP), a free national mental health service, has recorded over 1.5 million text and chat sessions from young people since 2018 seeking mental health support. While these conversations contain invaluable insight into what youth are experiencing, KHP currently lacks the tools to fully understand patterns in this data, such as who is reaching out, how their needs change over time, and what strategies from responders make the most difference. Our project will use natural language processing (NLP), a type of artificial intelligence that enables computers to understand human language, to analyze KHP's de-identified text and chat records from 2018-2025. This approach will allow us to track important mental health features, such as signs of anxiety, sadness, anger, and overall mood, before, during, and after the COVID-19 pandemic. We will also examine whether these patterns vary across youth from diverse backgrounds, including different age groups, racial identities, and sexual orientations, to support equitable decision-making and care for youth from diverse backgrounds. By uncovering how youth mental health changed during the pandemic and what kinds of support work best, this research will provide KHP with direct guidance to strengthen their counseling practices. Ultimately, my work aims to make sure that young people across Canada receive faster, more effective, and more equitable mental health support when they need it most.
Competitiondate
202509
Approvedterm2
2 yrs 0 mth
Pinamesdelim
Li, Yutong
Approvedterm
2 ans 0 mois
Cihrcontribution2
~ $140,000~ $0~