ArticleJournal of athletic training2024
Injury Patterns in Highly Specialized Youth Athletes: A Comparison of 2 Pathways to Specialization.
Article in Journal of athletic training, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
1 citing paper in PubMed, 5 citations in OpenAlex.
- Early Sport Specialization in a Pediatric Population: A Rapid Review of Injury, Function, Performance, and Psychological Outcomes.Clinics and practice · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
contextSport specialization, commonly defined as intensive year-round training in a single sport to the exclusion of other sports, has been associated with an increased risk for overuse injury. Two pathways to becoming highly specialized are recognized: (1) having only ever played 1 sport (exclusive highly specialized) and (2) quitting other sports to focus on a single sport (evolved highly specialized). Understanding the differences in injury patterns between these groups of highly specialized athletes will inform the development of injury-prevention strategies.
objectiveTo compare the distribution of injury types (acute, overuse, serious overuse) among evolved highly specialized athletes, exclusive highly specialized athletes, and low-moderately specialized athletes.
designCross-sectional study.
settingTertiary care pediatric sports medicine clinic between January 2015 and April 2019. PATIENTS OR OTHER
participantsA total of 1171 patients (age = 12.01-17.83 years, 59.8% female) who played ≥1 organized sports, presented with a sport-related injury, and completed a sports participation survey. MAIN OUTCOME MEASURE(S): Distribution of injury types (acute, overuse, serious overuse).
resultsThe percentage of injuries due to overuse was similar between the exclusive and evolved highly specialized athletes (59.2% versus 53.9%; P = .28). Compared with low-moderately specialized athletes, exclusive and evolved highly specialized athletes had a higher percentage of overuse injuries (45.3% versus 59.2% and 53.9%, respectively; P = .001). Multivariate analysis of the highly specialized groups revealed sport type to be a significant predictor of a higher percentage of injuries due to overuse, with individual-sport athletes having increased odds of sustaining an overuse injury compared with team-sport athletes (odds ratio = 1.95; 95% CI = 1.17, 3.24).
conclusionsThe distribution of injury types was similar between evolved and exclusive highly specialized youth athletes, with both groups having a higher percentage of injuries due to overuse compared with low-moderately specialized athletes. Among highly specialized athletes, playing an individual sport was associated with a higher proportion of overuse injuries compared with playing a team sport.
Indexed as
Identifiers
What OpenQuestion holds
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.