The Impact of Formal Strength and Conditioning on the Fitness of Law Enforcement Recruits: A Retrospective Cohort Study
Bibliographic record
Abstract
International Journal of Exercise Science 13(4): 1615-1629, 2020. Research involving law enforcement populations has suggested better fitness could enhance job task performance and reduce injuries. Academy training should lead to improvements in recruit fitness. The aim of this study was to investigate the impact of a strength and conditioning program on fitness among law enforcement recruits. Twenty-six recruits (23 males, three females) completed a 27-week academy, which incorporated 3-4 physical training sessions per week. Fitness assessment occurred during pre- (week 0), mid- (week 14), and post-testing (week 27) time points. The fitness assessments included: vertical jump, one-minute push-ups, one-minute sit-ups, posterior chain strength measured by a leg/back dynamometer, grip strength, and aerobic fitness measured by the 20-m multistage shuttle run (MSR). A repeated measures ANOVA with Bonferroni post hoc tests determined any significant changes in fitness between time points, with alpha set at p < .05. Due to the small sample size of females, statistical analysis was only conducted on male recruits. Overall, significant main effects (p < .001) were observed in all fitness assessments except for grip strength. The results detailed general improvements in fitness. However, push-up and MSR scores decreased from mid- to post-test, while sit-ups did not change. Posterior chain strength and the vertical jump improved from mid- to post-test. The data indicated that the strength and conditioning program positively influenced the fitness of recruits. An increased focus on skill-specific work in the second-half of academy may have contributed to the plateaus in muscular endurance and aerobic fitness, and improvement of lower-body strength and power.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".