Federated Automated Survey Tool (FAST)

Information

  • Research Project
  • 10382821
  • ApplicationId
    10382821
  • Core Project Number
    R43LM013986
  • Full Project Number
    1R43LM013986-01
  • Serial Number
    013986
  • FOA Number
    PA-20-260
  • Sub Project Id
  • Project Start Date
    9/15/2021 - 3 years ago
  • Project End Date
    8/31/2022 - 2 years ago
  • Program Officer Name
    YE, JANE
  • Budget Start Date
    9/15/2021 - 3 years ago
  • Budget End Date
    8/31/2022 - 2 years ago
  • Fiscal Year
    2021
  • Support Year
    01
  • Suffix
  • Award Notice Date
    9/15/2021 - 3 years ago
Organizations

Federated Automated Survey Tool (FAST)

Summary/Abstract Public health o?cials within both acute and chronic disease realms have relied predominantly on survey data to gather information on disease prevalence, behavioral models, risk populations, risk probability, and disease progression. Conventional surveys are subject to a number of known limitations, such as respondents' reluctance to participate, social desirability biases, lag time between questionnaire design, data collection, and availability of results, and intermittent coverage of important topics due to associated implementation costs. Further, disease control experts and policy makers lack access to real-time data and e?cient tools to provide contextual awareness vis-à-vis surveys that are implemented for disease surveillance and program management. The implications of not having a timely and broader understanding of the environment and community a?ects the representativeness and demographic speci?city of assessments and of the data used to drive policies and interventions. The proposed Federated Automated Survey Tool (FAST) will be developed as a collaboration among Barron Associates, Inc., George Mason University, and University of Virginia researchers. FAST will be an analytics platform that can be used by public health o?cials, clinical care investigators, institutional administrators, and others to more easily survey targeted cohorts regarding acute and chronic diseases (e.g., in?uenza, coronavirus, high blood pressure, etc.) and other indicators (e.g., depression prevalence, tobacco use, substance abuse, etc.) by harnessing social media (e.g., Twitter) or other web/electronic data. Based on both automated and tailorable investigator inputs, the proposed FAST platform will facilitate the construction of appropriate interrogations of social media and web data to yield prospective and longitudinal insights to answer user-initiated questions. The FAST analytics platform will enable local, national, and worldwide surveys on geographically- and demographically-targeted social media and web users based on their Tweets, posts, emails, search, and other web data and metadata. The FAST platform will utilize sophisticated text analytics and novel survey construction and analysis techniques. The survey results will then be analyzed automatically to gain insights and answer a diverse set of questions regarding targeted geographic- and demographic-speci?c prevalence and severity estimates. These can be one-o? surveys, pre- and post-intervention surveys, or online, real-time, longitudinal surveys. As an example of the latter, school administrators could track national or more localized (i.e., geo-tagged) student social media posts in real time regarding issues such as drinking, drug use, stress, depression, or suicide, enabling administrators to better tailor services o?ered to students and/or detect the need for interventions. The FAST platform will employ a consolidated approach that makes it relatively easy for non-experts to create, administer, and survey social network and electronic data of nearly any cohort. With FAST, the full range of probability sampling techniques (e.g., simple random samples, strati?ed random samples, etc.) will be available to end-users, along with the corresponding estimated variance and bound on the error of the estimate.

IC Name
NATIONAL LIBRARY OF MEDICINE
  • Activity
    R43
  • Administering IC
    LM
  • Application Type
    1
  • Direct Cost Amount
  • Indirect Cost Amount
  • Total Cost
    301487
  • Sub Project Total Cost
  • ARRA Funded
    False
  • CFDA Code
    879
  • Ed Inst. Type
  • Funding ICs
    NLM:301487\
  • Funding Mechanism
    SBIR-STTR RPGs
  • Study Section
    ZRG1
  • Study Section Name
    Special Emphasis Panel
  • Organization Name
    BARRON ASSOCIATES, INC.
  • Organization Department
  • Organization DUNS
    120839477
  • Organization City
    CHARLOTTESVILLE
  • Organization State
    VA
  • Organization Country
    UNITED STATES
  • Organization Zip Code
    229012496
  • Organization District
    UNITED STATES