A Field Investigation Exploring the Effect of Load and Load Distribution on Performance during Team-Based Military Tasks
Bibliographic record
Abstract
INTRODUCTION: Heavy load carriage has negative health and performance implications for military personnel, such as links to musculoskeletal injuries and longer completion times of military tasks. There is a need to understand performance-related factors as they interact with equipment in a simulated military task, completed in teams and in an outdoor environment. The purpose of this study was to determine the effect of load condition on the performance of a simulated high-intensity military task completed in an outdoor environment in a 2-person team. MATERIALS AND METHODS: A total of 14 male participants (average ± standard deviation 27.7 ± 7.5 years, 180.2 ± 7.1 cm, and 79.2 ± 7.4 kg) were recruited from the Canadian Army reserve force population. In pairs, participants completed eight simulated bounding rush tasks over 30 m in an outdoor field environment while wearing four randomized equipment conditions, including, (i) Slick (5 kg); (ii) Medium (23 kg); (iii) Heavy Pockets (37 kg), Medium with additional load concentrated anterior and posteriorly close to the torso; and (iv) Heavy Backpack (37 kg), Medium with additional load distributed posteriorly in a day pack. Each participant began one of the bounding rush trials (e.g., moved first) for each equipment condition (two trials per condition) and self-selected the distance travelled in each individual bound and speed during each task. Inertial measurement units (Movella, Henderson, NV, United States) captured the movements of both participants continuously, and surveys assessed the acceptability of aspects of the equipment conditions and performance of each task. RESULTS: There was a main effect of equipment condition on the total team completion time of the bounding rush task (P = .0006) and the individual prone-to-run transition (P = .0343), where the Heavy Pocket and Heavy Backpack conditions took significantly longer to complete compared to the Slick condition. Subjective ratings of speed performance demonstrated a significant difference between equipment conditions (P = .0008), where significant differences were detected between the Slick, Medium, and Heavy Backpack conditions, while there was no significant difference between the Heavy Pockets, Medium, and Heavy Backpack conditions. CONCLUSIONS: Equivalent weight carried in a posterior location (e.g., a backpack) compared to closer to the midline of the body does not improve subjective, survey-based perceived ratings of overall performance, agility speed, or mobility during the tasks evaluated in the current investigation. Future investigations examining team dynamics would improve external validity by including the full team in the scenario.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".