Prevention of sport injury II: a systematic review of clinical science research
Bibliographic record
Abstract
OBJECTIVE: To characterise the nature of the sport injury prevention literature by reviewing published articles that evaluate specific clinical interventions designed to reduce sport injury risks. DATA SOURCES: PubMed, Cinahl, Web of Science and Embase. MAIN RESULTS: Only 139 of 2525 articles retrieved met the inclusion criteria. Almost 40% were randomised controlled trials and 30.2% were cohort studies. The focus of the study was protective equipment in 41%, training in 32.4%, education in 7.9%, rules and regulations in 4.3%, and 13.3% involved a combination of the above. Equipment research studied stability devices (42.1%), head and face protectors (33.3%), attenuating devices (17.5%) as well as other devices (7%). Training studies often used a combination of interventions (eg, balance and stretching); most included balance and coordination (63.3%), with strength and power (36.7%) and stretching (22.5%) being less common. Almost 70% of the studies examined lower extremity injuries, and a majority of these were joint (non-bone)-ligament injuries. Contact sports were most frequently studied (41.5%), followed by collision (39.8%) and non-contact (20.3%). CONCLUSION: The authors found only 139 publications in the existing literature that examined interventions designed to prevent sports injury. Of these, the majority investigated equipment or training interventions whereas only 4% focused on changes to the rules and regulations that govern sport. The focus of intervention research is on acute injuries in collision and contact sports whereas only 20% of the studies focused on non-contact sports.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.051 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.010 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".