ArticleJournal of athletic training2016
Predicting Injury: Challenges in Prospective Injury Risk Factor Identification.
Article in Journal of athletic training, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- Towards High-Accuracy Athletic Injury Predictions Using a First-Principles Modelling Approach: Theory to (Future) Practice.Sports medicine (Auckland, N.Z.) · 2026Review
- A scoping review of force plates in female soccer: The utility, existing practice and identification of knowledge Gaps.PloS one · 2026Article
- Predictive Utility of the Functional Movement Screen and Y-Balance Test: Current Evidence and Future Directions.Sports (Basel, Switzerland) · 2025Review
- Preseason Neck Mobility Is Associated With Throwing-Related Shoulder and Elbow Injuries, Pain, and Disability in College Baseball Pitchers.Orthopaedic journal of sports medicine · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
contextMusculoskeletal injury-prediction methods vary and may have limitations that affect the accuracy of results and clinical meaningfulness.
backgroundResearch examining injury risk factors is meaningful, but attempting to extrapolate injury risk from studies that do not prospectively assess injury occurrence may limit clinical applications. Injury incidence is a vital outcome measure, which allows for the appropriate interpretation of injury-prediction analyses; a lack of injury-incidence data may decrease the accuracy and increase the uncertainty of injury-risk estimates. Extrapolating results that predict an injury risk factor to predicting actual injuries may lead to inappropriate clinical decision-making models.
conclusionsImproved understanding of the limitations of injury-prediction methods, specifically those that do not prospectively assess injuries, will allow clinicians to better assess the clinical meaningfulness of the results.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.