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Research Topic : Machine learning algorithms
Field of Research : Secondary Education
Australian State/Territory : SA
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  • Active Funded Activity

    Linkage Projects - Grant ID: LP210100166

    Funder
    Australian Research Council
    Funding Amount
    $395,000.00
    Summary
    Reducing self-harm and suicidal behaviours in young people in WA. Aims: reduce self-harm and suicidal behaviours in young people by upskilling teachers and providing resources to respond rapidly to students at risk via an innovative intervention with near real-time measures of changes in vulnerability. Significance: self-harm and suicidal behaviours are increasing at alarming rates in young people. Schools are ideally placed to respond but many struggle to do so. New regular measures and advance .... Reducing self-harm and suicidal behaviours in young people in WA. Aims: reduce self-harm and suicidal behaviours in young people by upskilling teachers and providing resources to respond rapidly to students at risk via an innovative intervention with near real-time measures of changes in vulnerability. Significance: self-harm and suicidal behaviours are increasing at alarming rates in young people. Schools are ideally placed to respond but many struggle to do so. New regular measures and advanced machine learning algorithms measuring change in risk in real time will enable schools to respond in a timely and effective manner and save lives. Expected outcomes: a new intervention to reduce self-harm and suicidal behaviours in young people that measures fluctuations in risk via a Temporal Vulnerability Index.
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