Physical Tests to Predict Combat Task Performance Among Brazilian Air Force Infantry Cadets

Mil Med. 2023 Aug 29;188(9-10):3095-3101. doi: 10.1093/milmed/usac111.

Abstract

Introduction: The Brazilian Air Force (BAF) personnel must be prepared to perform their professional activities under the worst conditions. This preparation goes beyond habits of practicing physical activity, since it is necessary to perform specific physical tasks, referred to as "combat tasks" (CTs). This study aimed to investigate a combination of specific physical tests (SPTs) for predicting physical performance on simulated tasks (STs) that mimicked the performance of CTs.

Materials and methods: Thirty infantry cadets from the BAF took part in anthropometric assessments, 11 SPTs, and 3 STs, during 7 testing days. Bivariate Pearson's correlation was used to determine linear relationships between SPT and ST results, and multiple linear regression models were used to identify test batteries that significantly predicted performance on STs. The level of significance was set at 5%. The study was conducted according to the guidelines of the Declaration of Helsinki and approved by the Ethics Committee of the BAF (protocol code 15796819.4.0000.5250, date of approval September 25, 2019).

Results: The greatest predictive power was obtained by the test battery that consisted of sprint-drag-carry, leg tucks, and handgrip strength (R2 = 0.56, P < .01). Conversely, the test battery comprised of push-ups, sit-ups, and 12-minute run (which represents the conventional physical test of the BAF), which presented the lowest predictive power (R2 = 0.14, P < .05).

Conclusions: In conclusion, this study identified a test battery for predicting performance on the following STs: foot march, casualty drag, and move under direct fire. This finding represents the first step to improve the reliability of the BAF physical assessments, focusing on combat readiness levels.

MeSH terms

  • Brazil
  • Exercise Test / methods
  • Hand Strength
  • Humans
  • Military Personnel*
  • Physical Fitness*
  • Reproducibility of Results
  • Task Performance and Analysis