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Record W3212030091 · doi:10.1177/19417381211056301

Age of Early Specialization, Competitive Volume, Injury, and Sleep Habits in Youth Sport: A Preliminary Study of US Youth Basketball

2021· article· en· W3212030091 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSports Health A Multidisciplinary Approach · 2021
Typearticle
Languageen
FieldPsychology
TopicSport Psychology and Performance
Canadian institutionsQueen's University
FundersNational Center for Advancing Translational SciencesNational Center for Research Resources
KeywordsBasketballPsychologyFeelingClubYouth sportsAthletesElitePhysical therapyMedicineSocial psychologyGeographyPolitical sciencePolitics

Abstract

fetched live from OpenAlex

BACKGROUND: Concerns for youth sports in the United States often focus on early sport specialization, overemphasis on competition, injuries, and burnout. Little research has addressed relationships among the preceding and other concerns, including time away from organized sport, sleep, and perceptions of physical and psychological well-being. HYPOTHESIS: There is an association between reported competitive gameplay volume and specialization, injury, and fatigue among elite youth basketball players. STUDY DESIGN: Cross-sectional study; convenience sample. LEVEL OF EVIDENCE: Level 4. METHODS: An anonymous questionnaire was administered to a convenience sample of youth basketball players between 13 and 18 years of age from across the United States. Participants were queried about multiple factors, including the extent of their participation in organized basketball and other sports, time away from organized basketball, injury, sleep, and feelings of exhaustion related to basketball participation. RESULTS: A total of 772 participants (145 girls, 627 boys) completed a survey. All participants played for a select or elite club basketball team and/or a high school basketball team. Overall, 49% played more than 50 games within the past year. A total of 73% were specialized in basketball, 58% prior to age 14 years, and 35% prior to age 11 years. In all, 70% reported less than 1 month away from organized basketball within the past year, and 28% reported no time away. A total of 54% reported sleeping less than the recommended 8 hours each night during the school year. Within the prior year, 55% reported feeling physically exhausted and 45% reported feeling mentally exhausted from basketball. Regression analysis did not find any significant relationships between early specialization prior to age 14 years and basketball-related injury or feelings of mental or physical exhaustion. CONCLUSION: In this select group of youth basketball players, the majority specialized in basketball prior to age 14 years and reported a large number of competitive events with little time away from organized basketball. CLINICAL RELEVANCE: The results from a sample of highly competitive youth basketball players indicate issues that warrant further attention and research regarding the potential impact of specialization, frequent competitions, lack of time away from organized sport, and perceptions of well-being in young athletes.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.099
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.034
GPT teacher head0.325
Teacher spread0.291 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it