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Machine learning based individual treatment optimization of online notice delivery for behavioral change

Grant number: unknown

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Key facts

  • Disease

    COVID-19

  • Funder

    RIKEN

  • Principal Investigator

    N/A

  • Research Location

    Japan

  • Lead Research Institution

    N/A

  • Research Priority Alignment

    N/A

  • Research Category

    Secondary impacts of disease, response & control measures

  • Research Subcategory

    Indirect health impacts

  • Special Interest Tags

    N/A

  • Study Type

    Non-Clinical

  • Clinical Trial Details

    N/A

  • Broad Policy Alignment

    Pending

  • Age Group

    Not Applicable

  • Vulnerable Population

    Not applicable

  • Occupations of Interest

    Not applicable

Abstract

It is well known in preventive medicine and behavioral economics that traditional information delivery is not effective for behavioral change. To aid effective information delivery for infection prevention of COVID-19 such as keeping away from high-risk behaviors, we are developing methods for machine learning-based individual treatment optimization of online notice delivery based on various studies in preventive medicine and behavioral economics and carrying out experiments based on the methods developed.