{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,19]],"date-time":"2026-09-19T13:24:41Z","timestamp":1789824281045,"version":"4.0.1"},"reference-count":0,"publisher":"Human Kinetics","issue":"2","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2016,5]]},"abstract":"<jats:sec sec-type=\"context\"><jats:title>Context:<\/jats:title><jats:p>The Balance Error Scoring System (BESS) is the current standard for assessing postural stability in concussed athletes on the sideline. However, research has questioned the objectivity and validity of the BESS, suggesting that while certain subcategories of the BESS have sufficient reliability to be used in evaluation of postural stability, the total score is not reliable, demonstrating limited interrater and intrarater reliability. Recently, a computerized BESS test was developed to automate scoring.<\/jats:p><\/jats:sec><jats:sec sec-type=\"objective\"><jats:title>Objective:<\/jats:title><jats:p>To compare computerderived BESS scores with those taken from 3 trained human scorers.<\/jats:p><\/jats:sec><jats:sec sec-type=\"design\"><jats:title>Design:<\/jats:title><jats:p>Interrater reliability study.<\/jats:p><\/jats:sec><jats:sec sec-type=\"setting\"><jats:title>Setting:<\/jats:title><jats:p>Athletic training room.<\/jats:p><\/jats:sec><jats:sec sec-type=\"patients\"><jats:title>Patients:<\/jats:title><jats:p>NCAA Division I student athletes (53 male, 58 female; 19 \u00b1 2 y, 168 \u00b1 41 cm, 69 \u00b1 4 kg).<\/jats:p><\/jats:sec><jats:sec sec-type=\"interventions\"><jats:title>Interventions:<\/jats:title><jats:p>Subjects were asked to perform the BESS while standing on the Tekscan (Boston, MA) MobileMat\u00ae BESS. The MobileMat BESS software displayed an error score at the end of each trial. Simultaneously, errors were recorded by 3 separate examiners. Errors were counted using the standard BESS scoring criteria.<\/jats:p><\/jats:sec><jats:sec sec-type=\"main outcome measures\"><jats:title>Main Outcome Measures:<\/jats:title><jats:p>The number of BESS errors was computed for the 6 stances from the software and each of the 3 human scorers. Interclass correlation coefficients (ICCs) were used to compare errors for each stance scored by the MobileMat BESS software with each of 3 raters individually. The ICC values were converted to Fisher Z scores, averaged, and converted back into ICC values.<\/jats:p><\/jats:sec><jats:sec sec-type=\"results\"><jats:title>Results:<\/jats:title><jats:p>The double-leg, single-leg, and tandem-firm stances resulted in good agreement with human scorers (ICC = .999, .731, and .648). All foam stances resulted in fair agreement.<\/jats:p><\/jats:sec><jats:sec sec-type=\"conclusions\"><jats:title>Conclusions:<\/jats:title><jats:p>Our results suggest that the MobileMat BESS is suitable for identifying BESS errors involving each of the 6 stances of the BESS protocol. Because the MobileMat BESS scores consistently and reliably, this system can be used with confidence by clinicians as an effective alternative to scoring the BESS.<\/jats:p><\/jats:sec>","DOI":"10.1123\/jsr.2014-0281","type":"journal-article","created":{"date-parts":[[2014,10,30]],"date-time":"2014-10-30T20:47:52Z","timestamp":1414702072000},"page":"133-136","source":"Crossref","is-referenced-by-count":15,"title":["Comparing Computer-Derived and Human-Observed Scores for the Balance Error Scoring System"],"prefix":"10.1123","volume":"25","author":[{"given":"Jaclyn B.","family":"Caccese","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Thomas W.","family":"Kaminski","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"100","container-title":["Journal of Sport Rehabilitation"],"original-title":[],"link":[{"URL":"https:\/\/journals.humankinetics.com\/view\/journals\/jsr\/25\/2\/article-p133.xml","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.humankinetics.com\/downloadpdf\/journals\/jsr\/25\/2\/article-p133.xml","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,19]],"date-time":"2022-05-19T23:00:16Z","timestamp":1653001216000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.humankinetics.com\/view\/journals\/jsr\/25\/2\/article-p133.xml"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,5]]},"references-count":0,"journal-issue":{"issue":"2"},"URL":"https:\/\/doi.org\/10.1123\/jsr.2014-0281","relation":{},"ISSN":["1056-6716","1543-3072"],"issn-type":[{"value":"1056-6716","type":"print"},{"value":"1543-3072","type":"electronic"}],"subject":[],"published":{"date-parts":[[2016,5]]}}}