O-33 Futsal and injuries among recreational sport participants: a prospective field study
Bibliographic record
Abstract
Background Recently, there is an increasing interest in examining sports injuries among participants of recreational sports. However little data is available about injury rate in Futsal as a popular recreation Worldwide.1–4 Objective The purpose of this study was to analyseanalyze the incidence and characteristics of injuries recorded in a large recreational centre over a 1-year period. Methods In a prospective design, all injuries in a total of 88 matches of recreational Futsal in 2014–2015 were recorded. A standard questionnaire on injury characteristics was filled for each injured player. Injury rate was calculated as the total number of injuries divided by total player-time (/hour-player). The average time of each match was 90 minutes in duration. Continuous variables were presented in mean (SD) and countable ones were summarised as numbers (percentage). Results A total of 14 injuries (in 13 individuals) were reported in 1185 player records during 88 matches. The injury rate was estimated 1 in 12500 hour-player. Mean and SD of the age and BMI of injured players were 30.38 (9.1) and 25.09 (4.3) respectively. In total of 13 players, 5 (38.5%) were left leg dominant. On site of injury, 4 (28.6%) of injuries were in upper extremity, 9 (64.3%) in lower extremity and 1 (7.1%) in chest wall. About the type of injury, 5 (35.7%) were abrasion or contusion and the rest were more serious injuries including dislocation, fracture, ligament tearing, sprains and strain. Further analysis showed that 10 (71.4%) did not have a history of previous injury at the same site. To address the mechanisms of injury, 12 (85.7%) of injuries were traumatic while the others were overuse injuries; also 7 (53.8%) were due to player-player and 3 (23.1%) were due to player-ground contact. Finally overall missed playing days due to injury was 16 (17.02) days among injured participants. Conclusion Findings showed that injuries were not uncommon among Futsal recreational sport participants. Expectedly the lower extremity was the most likely site of injury followed by upper extremity and trunk. Unfortunately these injuries may be usually grave in nature. Furthermore, most of recreational sport injuries were related to traumatic contacts with opponent players. Finally our data indicated that recreational sport injuries could lead to missing opportunities for participation in recreational activities. Acknowledgment This study was funded and supported by Tehran University of Medical Sciences & health Services grant [Grant No. 88-03-53-9298]. References Finch C, Cassell E. The public health impact of injury during sport and active recreation. Journal of Science and Medicine in Sport 2006;9:490–497. Grimmer KA, Jones D, Williams J. Prevalence of adolescent injury from recreational exercise: an Australian perspective. Journal of adolescent health 2000;27:266–272. Mummery W, Schofield G, Spence J. The epidemiology of medically attended sport and recreational injuries in Queensland. Journal of Science and Medicine in Sport 2002;5:307–320. Mummery WK, Spence JC, Vincenten JA, et al. A descriptive epidemiology of sport and recreation injuries in a population-based sample: results from the Alberta Sport and Recreation Injury Survey (ASRIS). Canadian journal of public health= Revue canadienne de sante publique 1997;89:53–56.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".