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Rapid report on using data to make standardized decisions about enrollment during the COVID-19 pandemic: perspectives from the MoTrPAC study.
George, Stephanie M; Chen, Haiying; Miller, Michael E; Rejeski, W Jack; Stowe, Cynthia L; Webb, Christopher; Kraus, William E; Musi, Nicolas; Jakicic, John M.
  • George SM; Division of Extramural Research, National Institute of Arthritis and Musculoskeletal and Skin Diseases, National Institutes of Health, Bethesda, MD. Electronic address: Stephanie.george@nih.gov.
  • Chen H; Department of Biostatistics and Data Science, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC.
  • Miller ME; Department of Biostatistics and Data Science, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC.
  • Rejeski WJ; Department of Health and Exercise Science, Wake Forest University, Winston-Salem, NC.
  • Stowe CL; Department of Biostatistics and Data Science, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC.
  • Webb C; Department of Biostatistics and Data Science, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC.
  • Kraus WE; Duke Molecular Physiology Institute and Division of Cardiology, Duke University School of Medicine, Durham, NC.
  • Musi N; Barshop Institute for Longevity and Aging Studies, University of Texas Health San Antonio, San Antonio, TX.
  • Jakicic JM; University of Pittsburgh, Healthy Lifestyle Institute, Pittsburgh, PA.
Ann Epidemiol ; 62: 19-21, 2021 10.
Article in English | MEDLINE | ID: covidwho-1213034
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Pandemics / COVID-19 Limits: Humans Language: English Journal: Ann Epidemiol Journal subject: Epidemiology Year: 2021 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Pandemics / COVID-19 Limits: Humans Language: English Journal: Ann Epidemiol Journal subject: Epidemiology Year: 2021 Document Type: Article