Epidemiology and Risk Factors of Table-Tennis-Related Injuries: Findings from a Scoping Review of the Literature
Bibliographic record
Abstract
Background and Objectives: Table tennis represents one of the fastest ball games in the world and, as such, is characterized by unique physiological demands. Despite its popularity, there is a dearth of data related to table-tennis-related risk factors and injuries. Therefore, the present review was conducted to fill in this gap of knowledge. Material and Methods: The present review was designed as a scoping review. Eleven online databases were searched with no language/date limitations. Results: Forty-two investigations were retained in the present review. These studies indicated that tenosynovitis, benign muscle injuries, strains, and sprains were the most common injury types. In order, the most commonly affected anatomical regions were the lower limb, shoulder, spine, knee, upper limb, and trunk. When comparing the injury occurrence between training and competition, the results were contradictory. National/international athletes had higher indices of injury than regional players, even though other investigations failed to replicate such findings. According to some scholars, there was a difference between female and male athletes: in females, more injuries involved the upper limbs when compared to men who had more injuries to the lower limbs, while other studies did not find differences in terms of gender. Conclusions: Table tennis is generally considered at lower risk for injuries than other sports. However, the present scoping review showed that injuries can occur and affect a variety of anatomic regions. Sports scientists/physicians could utilize the information contained in the current review for devising ad hoc programs to adopt an effective/appropriate prevention strategy and to monitor table tennis players’ training load and to achieve maximal fitness, as these will reduce the risk of injuries. However, most of the studies included in our scoping review are methodologically weak or of low-to-moderate evidence, being anecdotal or clinical case reports/case series, warranting caution when interpreting our findings and, above all, further high-quality research in the field is urgently needed.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".