The Impact Of Different Types Of Core Training In Stable And Unstable Environments On Markers Of Athletic Performance
Bibliographic record
Abstract
"Background: Research suggests that core stability and strength is important in facilitating athletes to effectively transfer force to the lower and upper extremities of the body. The purpose of the current research was to evaluate the impact of an eight week intervention of core training on stable and unstable surfaces, and in vertical and horizontal alignments, on markers of athletic performance relevant to team sports. Methods: The athletic performance markers selected were bounce depth jump, countermovement Jump, agility (T-test), 10 meter sprint, 30 meter sprints, and IRM leg strength as identified by Cressey (2007). Core stability and strength were measured using the McGill (2001) core stability tests, composed of combined time for trunk flexion, trunk extension, lateral right bridge and lateral left bridge. Participants, (N=89), were assigned to cither an intervention group or control group. Intervention groups were divided based on their classification, i.e. exercising in (i) stable vertical, (ii) unstable vertical, (iii) stable horizontal and, (iv) unstable horizontal. Paired sample t tests and analyses of variance were used to assess the magnitude of change from pre to post intervention across each of the five groups. Results: Significant changes occurred in core stability, post intervention across all groups with the greatest magnitude of change in the intervention groups. There was no significant difference across groups on the combined dependent variables, (F24, 276) = 1.02, p = .44; Wilks Lambda = .74, partial eta squared = .07. Data from a mixed between-within subject’s analysis of variance revealed significant improvements in markers of athletic performance over time. No clear improvement was found in markers of athletic performance across each of the participating groups. Conclusion: The study concluded that the 8 week intervention was effective at eliciting greater improvements in core stability. No difference in improvement was found however in markers of athletic performance between different participating intervention groups. "
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".