Investigating the Use of Jump Assessments for Firefighters in the London Fire Brigade
Bibliographic record
Abstract
ABSTRACT: Brown, L, Hastings, K, Caufield, S, Haynes, J, McClenaghan, P, and Lenetsky, S. Investigating the use of jump assessments for firefighters in the London Fire Brigade. J Strength Cond Res XX(X): 000-000, 2025-Firefighters must possess requisite muscular strength, power, and endurance to perform operational tasks while handling external loads, such as door breakers and hose lines. When firefighters from the London Fire Brigade (LFB) pass the academy, they are assessed annually using either the Chester Walk Treadmill Test, 1.5-mile, or the bleep test. No strength or power assessments are regularly performed. Therefore, the primary purpose of this study was to identify the feasibility of introducing jump testing for strength and power assessments to be used in the annual fitness test. A total of 41 men (n = 38) and women (n = 3) were recruited (age: 38 ± 9 years; stature: 1.8 ± 0.04 m; mass: 86 ± 10.6), with a minimum of 1-year service. The squat jump (SJ), countermovement jump (CMJ), reactive strength index, and the 1.5-mile treadmill test were used to assess the subjects. Analysis revealed an inverse relationship between SJ, CMJ, and the treadmill run test, indicating that increased jump performance was related to faster run times, with a very large effect size. This study demonstrated that jump tests can be used as an additive to the graded treadmill walking-based test currently being used for annual fitness testing by the LFB.
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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 | 0.005 | 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 | 0.002 | 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".