{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,18]],"date-time":"2026-08-18T17:30:34Z","timestamp":1787074234841,"version":"build-2736575974"},"reference-count":27,"publisher":"BMJ","funder":[{"DOI":"10.13039\/100012676","name":"National Collegiate Athletic Association","doi-asserted-by":"publisher","award":["N\/A"],"award-info":[{"award-number":["N\/A"]}],"id":[{"id":"10.13039\/100012676","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["bmj.com"],"crossmark-restriction":true},"short-container-title":["Inj Prev"],"accepted":{"date-parts":[[2026,8,4]]},"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>The National Collegiate Athletic Association Injury Surveillance Program (NCAA ISP) is among the longest-standing sport injury surveillance systems in the world. The NCAA ISP relies on a convenience sample of reporting institutions to estimate population-level injury metrics by scaling reported counts by an inverse school-reporting fraction and a fixed under-reporting correction. We propose a new method for improving population estimates of injury incidence obtained in the NCAA ISP, through a quasi-bootstrapping algorithm that capitalises on the historically archived NCAA ISP data.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We employed a phased approach including both a simulation study and a practical application, grounded in the operational methods of the NCAA ISP.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Across a range of simulated conditions, the proposed method approximated true population values with near-zero bias, produced more stable estimates than the current method and generated valid uncertainty intervals for both injuries and exposures. We also noted that when applied to real-world data, the proposed method produced plausible and credible estimates of injury and exposure counts.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Discussion<\/jats:title>\n                    <jats:p>By incorporating real-world variability from archived data, this approach improves point and interval estimation even under conditions of low or biased reporting.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>The proposed method demonstrates strong potential as a scalable and statistically robust alternative to current population estimation practices in injury surveillance systems that rely on convenience samples.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1136\/ip-2025-046042","type":"journal-article","created":{"date-parts":[[2026,8,18]],"date-time":"2026-08-18T17:20:23Z","timestamp":1787073623000},"page":"ip-2025-046042","update-policy":"https:\/\/doi.org\/10.1136\/crossmarkpolicy","source":"Crossref","is-referenced-by-count":0,"title":["Population estimation in injury surveillance using a quasi-bootstrapping approach with convenience sample data"],"prefix":"10.1136","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2949-3668","authenticated-orcid":false,"given":"Avinash","family":"Chandran","sequence":"first","affiliation":[{"name":"Datalys Center for Sports Injury Research and Prevention, Indianapolis, Indiana, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Derek W.","family":"Brown","sequence":"additional","affiliation":[{"name":"Datalys Center for Sports Injury Research and Prevention, Indianapolis, Indiana, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"239","published-online":{"date-parts":[[2026,8,18]]},"reference":[{"key":"2026081810201644000_ip-2025-046042v1.1","doi-asserted-by":"crossref","DOI":"10.26633\/RPSP.2024.9","article-title":"Public health surveillance and the data, information, knowledge, intelligence and wisdom paradigm","volume":"48","author":"Choi","year":"2024","journal-title":"Rev Panam Salud Publica"},{"key":"2026081810201644000_ip-2025-046042v1.2","doi-asserted-by":"publisher","DOI":"10.2471\/BLT.08.055798"},{"key":"2026081810201644000_ip-2025-046042v1.3","doi-asserted-by":"publisher","DOI":"10.1093\/oxfordjournals.epirev.a036021"},{"key":"2026081810201644000_ip-2025-046042v1.4","unstructured":"World Health Organization . Injury surveillance guidelines \/ edited by: Y. Holder\u2026 [et al.], (WHO\/NMH\/VIP\/01.02), 2001. 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