rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: In the trenches of military epidemiological research
    sub title: lessons learned from large-scale archival data projects
  name:
    name part: Belding, Jennifer
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: Koenig, Hannah G.
    role:
      role term: author.
  name:
    name part: McAnany, Jennifer
    role:
      role term: author.
  name:
    name part: Del Re, A. C.
    role:
      role term: author.
  name:
    name part: Bonkowski, James F.
    role:
      role term: author.
  name:
    name part: Thomsen, Cynthia J.
    role:
      role term: author.
  type of resource: text
  genre: bibliography
  genre: Case studies.
  origin info:
    place:
      place term: enk
    date issued: 2020
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource.
  abstract: Using two ongoing epidemiological research projects in which data are drawn from the medical and career records of members of the U.S. Armed Forces as context, this case study provides insights into the benefits and challenges of using large-scale archival data to understand factors impacting health and wellbeing. We describe the process involved in preparing a "big" database for analysis, including obtaining approval of an institutional review board protocol and data sharing agreements, accessing the data, and cleaning and preparing a database specifically designed to address study goals. We describe inherent challenges and resources required to effectively work with this type of data in addition to research decisions often not discussed in peer-reviewed articles. We cover four lessons learned, including the importance of (1) keeping the purpose of the project and any associated deliverables in mind at all times; (2) having a clear idea of the research question and resisting the urge to expand upon it too much; (3) maintaining a specific, written data analysis plan; and (4) being aware of potential confounds and limitations of your findings. We strongly encourage others to consider using large-scale archival data (such as healthcare reimbursement data) in epidemiological and medical research, and we urge interested researchers to enlist a mentor to assist them as they develop their own skills working with this type of data.
  target audience: specialized
  note: Jennifer N. Belding, Hannah G. Koenig, Jennifer McAnany, A.C. Del Re, James F. Bonkowski, Cynthia J. Thomsen.
  note: Includes bibliographical references and index.
  subject:
    topic: Medicine, Military
    topic: Databases
    genre: Case studies
  subject:
    topic: Epidemiology
    genre: Case studies
  subject:
    topic: Médecine militaire
    topic: Bases de données
    genre: Études de cas
  subject:
    topic: Épidémiologie
    genre: Études de cas
  subject:
    topic: Epidemiology
  classification: RA652.2.D38 B45 2020
  classification: 614.4
  related item:
    title info:
      title: SAGE Research Methods Cases: Medicine and Health
  identifier: 9781529720235
  identifier: 1529720230
  identifier: http://proxy.library.tamu.edu/login
  record info:
    record content source: SGPBL
    record creation date: 200123
    record change date: 20240923170123.8
    record identifier: in00005492687
    language of cataloging:
      language term: eng