I Corps: A Psychologically-Informed Contact Tracing Tool

  • Funded by National Science Foundation (NSF)
  • Total publications:0 publications

Grant number: 2311182

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Key facts

  • Disease

    Disease X
  • Start & end year

    2023
    2025
  • Known Financial Commitments (USD)

    $50,000
  • Funder

    National Science Foundation (NSF)
  • Principal Investigator

    Deborah; Jacqueline Goldfarb; Evans
  • Research Location

    United States of America
  • Lead Research Institution

    Florida International University
  • Research Priority Alignment

    N/A
  • Research Category

    Infection prevention and control

  • Research Subcategory

    N/A

  • Special Interest Tags

    Digital Health

  • Study Type

    Non-Clinical

  • Clinical Trial Details

    N/A

  • Broad Policy Alignment

    Pending

  • Age Group

    Unspecified

  • Vulnerable Population

    Unspecified

  • Occupations of Interest

    Unspecified

Abstract

The broader impact/commercial potential of this I-Corps project is the development of an interactive, online platform that conducts patient-led, interviewer-free, contact tracing interviews (CTI). Contact tracing is a well-established public health measure used to contain the spread of contagious diseases such as HIV, Ebola, and COVID. In its current state, interviewer-led contact tracing is costly, inefficient, and results in the omission of potentially infectious contacts, allowing the continued spread of disease. The proposed technology takes well-established, empirically validated psychological approaches from cognitive and social psychology that bolster recall and applies them to public health. This new application of existing psychological approaches to CTIs may increase interview yield by 50%. In addition, the proposed tool may be used to span multiple infectious diseases and may quickly conform to the parameters of any infectious disease and any language. This I-Corps project is based on the development of a digital platform that applies cognitive psychological techniques to improve contact tracing to combat the spread of contagious disease. The proposed digital platform removes the interviewer from the contact tracing interview without a loss of efficiency. Self-led interviews empower patients to choose the time, place, and pace of the interview. The result is fewer contacts forgotten, rapid results, and cost savings as the technology facilitates data collection through technologically driven distribution channels without hiring, training, and compensating contact tracers. In addition, the proposed platform also uses natural language processing and artificial intelligence to aggregate the data and detect patterns in contagious outbreaks. Prior research reveals that the psychological methods utilized in the proposed technology help increase the amount of information that interviewees may recall, thus helping better inform decision-making by businesses and government entities. 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.