Predictive Models to Estimate Probabilities of Injuries, Poor Physical Fitness, and Attrition Outcomes in Australian Defense Force Army Recruit Training
Abstract
The purpose of this investigation was to assess the predictive potential of variables collected during the Australian Defence Force Recruit Training (n=19,769; 7,692 [28-day reservists course]; 12,077 [80-day standard]. The 28-day incurred 17.6% injury rate, 1 stress fracture, 5.2% attrition, 30.0% fitness test failure. The 80-day: 34.3% injury rate, 44 stress fractures, 5.0% attrition, 12.1% fitness test failure. Separate models were derived to predict injuries, attrition, and failure to pass the final physical fitness tests. Areas under the receiver operating characteristic curves (AUCs) for course-specific predictive models were relatively low (ranging from 0.51 to 0.69) consistent with "failed" to "poor" predictive accuracy. Course-combined models performed somewhat better, with 2 models having AUCs of 0.70 and 0.78; considered "fair" predictive accuracy. Although overall predictive accuracy was poor, accuracy was improved in models that included course length (28 vs. 80 day) as a predictor; suggesting the potential for using duration of training as a proxy for physical activity dosage to help predict injury and physical fitness.
Document Details
- Document Type
- Technical Report
- Publication Date
- Nov 01, 2015
- Accession Number
- AD1000577
Entities
People
- Bruce S. Cohen
- Edward J. Zambraski
- Mark Jaffrey
- Robin Orr
- Stephen C. Allison
Organizations
- United States Army Research Institute of Environmental Medicine