A systematic review of the effectiveness of eccentric strength training in the prevention of hamstring muscle strains in otherwise healthy individuals.
Bibliographic record
Abstract
BACKGROUND: Hamstring strains are the most common soft-tissue injury observed in recreational and athletic activities, yet no consensus exists regarding appropriate primary and secondary strategies to prevent these strains. Eccentric exercise has been reported to reduce the incidence of ham-string strains but its role has not been clearly defined. OBJECTIVE: The objective of this systematic review was to determine the effectiveness of eccentric exercise in preventing hamstring strains. DATA SOURCES: Online databases, including MED-LINE, PubMed, CINAHL, PEDro, SPORTDiscus, EMBASE, Cochrane Database of Systematic Reviews, Cochrane Central Register of Controlled Trials, and Web of Science were searched for relevant articles. Each database was searched from the earliest date to July 2007. STUDY SELECTION: Selection criteria included diagnosis of hamstring strain, otherwise healthy individuals, and at least one group receiving an eccentric exercise intervention. Seven articles {three randomized controlled trials (RCTs) and four cohort studies} met the inclusion criteria. DATA EXTRACTION: Data were extracted using a customized form. Methodological rigor of included studies was assessed using the PEDro scale and Oxford Centre for Evidence-based Medicine Levels of Evidence. DATA SYNTHESIS: STUDIES WERE GROUPED BY ECCENTRIC EXERCISE INTERVENTION PROTOCOL: hamstring lowers, isokinetic strengthening, and other strengthening. A best-evidence synthesis of pooled data was qualitatively summarized. CONCLUSIONS: Findings suggest that eccentric training is effective in primary and secondary prevention of hamstring strains. Study heterogeneity and poor methodological rigor limit the ability to provide clinical recommendations. Further RCTs are needed to support the use of eccentric training protocols in the prevention of hamstring strains.
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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 | 0.017 | 0.067 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.008 |
| Bibliometrics | 0.013 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".