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Models to predict injury, physical fitness failure and attrition in recruit training: a retrospective cohort study

Military Medical Research 2020年第4期7卷 391-400页

作者： Robin M.Orr Bruce S.Cohen Stephen C.Allison Lakmini Bulathsinhala Edward J.Zambraski mark jaffrey Tactical Research Unit Bond University2 Promethean WayGold CoastRobinaQLD 4226Australia United States Army Research Institute for Environmental Medicine NatickMA 01760USA Defence Science and Technology Group Port MelbourneVIC 3207Australia

Background:Attrition rate in new army recruits is higher than in incumbent *** the current study,we identified the risk factors for attrition due to injuries and physical fitness failure in recruit training.A variety of predictive models were ***:This retrospective cohort included 19,769 Army soldiers of the Australian Defence Force receiving recruit training during a period from 2006 to *** them,7692 reserve soldiers received a 28-day training course,and the remaining 12,077 full-time soldiers received an 80-day training *** data included anthropometric measures,course-specific variables,injury,and physical fitness *** regression was used to develop a variety of models to predict the rate of attrition due to injuries and physical fitness *** area under the receiver operating characteristic curve was used to compare the performance of the ***:In the overall analysis that included both the 28-day and 80-day courses,the incidence of injury of any type was 27.8%.The 80-day course had a higher rate of injury if calculated per course(34.3%vs.17.6%in the 28-day course),but lower number of injuries per person-year(1.56 vs.2.29).Fitness test failure rate was significantly higher in the 28-day course(30.0%vs.12.1%).The overall attrition rate was 5.2%and 5.0%in the 28-day and 80-day courses,*** fracture was common in the 80-day course(n=44)and rare in the 28-day course(n=1).The areas under the receiver operating characteristic curves for the course-specific predictive models were relatively low(ranging from 0.51 to 0.69),consistent with"failed"to"poor"predictive *** course-combined models performed somewhat better than the course-specific models,with two models having AUC of 0.70 and 0.78,which are considered"fair"predictive ***:Attrition rate was similar between 28-day and 80-day *** comparison to the 80-day full course,the 28-day course had a lower rat

关键词： Military training Predictive modelling Risk management Soldier

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