{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,28]],"date-time":"2026-10-28T07:57:26Z","timestamp":1793174246585,"version":"4.5.0"},"reference-count":51,"publisher":"SAGE Publications","issue":"6","license":[{"start":{"date-parts":[[2020,3,5]],"date-time":"2020-03-05T00:00:00Z","timestamp":1583366400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Sports Health: A Multidisciplinary Approach"],"published-print":{"date-parts":[[2020,11]]},"abstract":"<jats:sec>\n                    <jats:title>Background:<\/jats:title>\n                    <jats:p>Musculoskeletal injuries are a primary source of disability. Understanding how risk factors predict injury is necessary to individualize and enhance injury reduction programs.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Hypothesis:<\/jats:title>\n                    <jats:p>Because of the multifactorial nature of musculoskeletal injuries, multiple risk factors will provide a useful method of categorizing warrior athletes based on injury risk.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Study Design:<\/jats:title>\n                    <jats:p>Prospective observational cohort study.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Level of Evidence:<\/jats:title>\n                    <jats:p>Level 2.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods:<\/jats:title>\n                    <jats:p>\n                      Baseline data were collected on 922 US Army soldiers\/warrior athletes (mean age, 24.7 \u00b1 5.2 years; mean body mass index, 26.8 \u00b1 3.4 kg\/m\n                      <jats:sup>2<\/jats:sup>\n                      ) using surveys and physical measures. Injury occurrence and health care utilization were collected for 1 year. Variables were compared in healthy versus injured participants using independent\n                      <jats:italic toggle=\"yes\">t<\/jats:italic>\n                      tests or chi-square analysis. Significantly different factors between each group were entered into a logistic regression equation. Receiver operating characteristic curve and accuracy statistics were calculated for regression variables.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results:<\/jats:title>\n                    <jats:p>\n                      Of the 922 warrior athletes, 38.8% suffered a time-loss injury (TLI). Overall, 35 variables had a significant relationship with TLIs. The logistic regression equation, consisting of 11 variables of interest, was significant (adjusted\n                      <jats:italic toggle=\"yes\">R<\/jats:italic>\n                      <jats:sup>2<\/jats:sup>\n                      = 0.21; odds ratio, 5.7 [95% CI, 4.1-7.9]; relative risk, 2.5 [95% CI, 2.1-2.9]; area under the curve, 0.73). Individuals with 2 variables had a sensitivity of 0.89, those with 7 or more variables had a specificity of 0.94.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion:<\/jats:title>\n                    <jats:p>The sum of individual risk factors (prior injury, prior work restrictions, lower perceived recovery from injury, asymmetrical ankle dorsiflexion, decreased or asymmetrical performance on the Lower and Upper Quarter Y-Balance test, pain with movement, slower 2-mile run times, age, and sex) produced a highly sensitive and specific multivariate model for TLI in military servicemembers.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Clinical Relevance:<\/jats:title>\n                    <jats:p>A better understanding of characteristics associated with future injury risk can provide a foundation for prevention programs designed to reduce medical costs and time lost.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/1941738120902991","type":"journal-article","created":{"date-parts":[[2020,3,5]],"date-time":"2020-03-05T12:55:20Z","timestamp":1583412920000},"page":"564-572","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":73,"title":["Identification of Risk Factors Prospectively Associated With Musculoskeletal Injury in a Warrior Athlete Population"],"prefix":"10.1177","volume":"12","author":[{"given":"Deydre S.","family":"Teyhen","sequence":"first","affiliation":[{"name":"Walter Reed Army Institute of Research (WRAIR), Silver Spring, Maryland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Scott W.","family":"Shaffer","sequence":"additional","affiliation":[{"name":"Department of Physical Therapy, Texas State University, Round Rock, Texas"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stephen L.","family":"Goffar","sequence":"additional","affiliation":[{"name":"School of Physical Therapy, University of the Incarnate Word, San Antonio, Texas"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kyle","family":"Kiesel","sequence":"additional","affiliation":[{"name":"Department of Physical Therapy, University of Evansville, Evansville, Indiana"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Robert J.","family":"Butler","sequence":"additional","affiliation":[{"name":"St Louis Cardinals, St Louis, Missouri"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Daniel I.","family":"Rhon","sequence":"additional","affiliation":[{"name":"Doctoral Physical Therapy Programs (DPT and DSc), Baylor University, JBSA Fort Sam Houston, Texas"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Phillip J.","family":"Plisky","sequence":"additional","affiliation":[{"name":"Department of Physical Therapy, University of Evansville, Evansville, Indiana"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2020,3,5]]},"reference":[{"key":"e_1_3_2_2_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jsams.2017.08.001"},{"key":"e_1_3_2_3_2","volume-title":"TB MED 592: Prevention and Control of Musculoskeletal Injury Associated with Physical Training","author":"Alison S","year":"2006","unstructured":"Alison S. 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