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Record W4388796355 · doi:10.1080/17430437.2023.2282159

The impact of competitive youth athlete injury on parents: a narrative review

2023· review· en· W4388796355 on OpenAlexaff
Leslie Podlog, Stefan Wagnsson, Ross Wadey

Bibliographic record

VenueSport in Society · 2023
Typereview
Languageen
FieldMedicine
TopicSports injuries and prevention
Canadian institutionsUniversité de MontréalCentre Hospitalier Universitaire Sainte-Justine
Fundersnot available
KeywordsConceptualizationAthletesPsychologyNarrativeInjury preventionSuicide preventionInterpersonal communicationPoison controlApplied psychologySocial psychologyMedicinePhysical therapy

Abstract

fetched live from OpenAlex

Athletic injuries are common in youth sports, and much research has focused on the injury experience of athletes.However, less attention has been given to the impact of adolescent injury on relevant others within athletes' recovery orbit, particularly parents.This narrative review examines the impact of adolescent injury on parents using the Multilevel Model of Sport Injury (MMSI).Results revealed that parents' experience of their adolescent's injury is influenced by intra-and interpersonal factors (e.g., thoughts, emotions, behaviors, and interactions with coaches, and sport medicine providers), as well as institutional, cultural, and policylevel factors (e.g., lack of organizational support, internalization of sport norms about playing with pain, and sport injury policies and guidelines).The review provides a more nuanced understanding of the factors and interactions that parents have following adolescent sport injury.Further research using the MMSI can extend current conceptualization and theorizing regarding parents' experiences following adolescent injury.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.004
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.063
GPT teacher head0.429
Teacher spread0.366 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations5
Published2023
Admission routes1
Has abstractyes

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