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Record W4415992224 · doi:10.1136/bjsports-2025-110067

Optimal movement behaviours for postconcussion symptom recovery in children and adolescents: a compositional analysis of the PedCARE cohort

2025· article· en· W4415992224 on OpenAlexafffund
Nicholas Kuzik, Veronik Sicard, Mark S. Tremblay, Adrienne L. Davis, Gurinder Sangha, Keith Owen Yeates, Roger Zemek, Andrée‐Anne Ledoux

Bibliographic record

VenueBritish Journal of Sports Medicine · 2025
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsUniversity of CalgaryLondon Health Sciences CentreHospital for Sick ChildrenUniversity of OttawaChildren's Hospital of Eastern Ontario
FundersPhysicians' Services Incorporated FoundationOntario SPOR SUPPORT Unit
KeywordsConcussionCohortBalance (ability)Movement (music)Cohort studyPoison controlMotor activityInjury prevention

Abstract

fetched live from OpenAlex

OBJECTIVE: Optimal balances of sedentary behaviour, physical activity and sleep (collectively termed movement behaviours) for concussion management remain unknown. We sought to determine the optimal daily distribution of movement behaviours for reducing postconcussion symptom burden in children and adolescents. METHODS: This secondary analysis of the Paediatric Concussion Assessment of Rest and Exertion (PedCARE) study included participants aged 10 to <18 years with an acute concussion (>48 hours of presenting to emergency department). Health and Behaviour Inventory (HBI) concussion symptoms were measured at a 2-week post-emergency department follow-up. Persisting symptoms after concussion (PSAC) were classified through reliable change in total HBI scores. Movement behaviours were measured with accelerometers over 13 days. For each day of movement behaviours, compositional regression models were built to determine the optimal daily movement behaviours for predicting HBI scores and PSAC probability. RESULTS: Analyses included 259 participants (45% female, mean age 13.3 years). Compared with the average, movement behaviours associated with optimal postconcussion outcomes followed a trend of initially more rest (eg, day 2: 11.5 (95% CI 8.8 to 12.7) hours/day of sleep and 8.5 (95% CI 6.5 to 11.3) hours/day sedentary). Optimal patterns also included above-average moderate-to-vigorous physical activity across the 13 days (eg, days 2, 7, 13:0.6 (95% CI 0.2 to 1.2), 1.5 (95% CI 1.2 to 1.7), 1.1 (95% CI 0.2 to 1.7) hours/day, respectively), with increased light physical activity emerging as optimal later in recovery (eg, day 10:5.5 (95% CI 5.0 to 5.8) hours/day). CONCLUSIONS: This is the first study to use compositional data analyses to identify an optimal distribution of movement behaviours for concussion symptom recovery in children and adolescents. Our results can inform concussion management protocols that balance rest and activity throughout recovery.

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)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.032
Threshold uncertainty score0.065

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.002
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 head0.009
GPT teacher head0.296
Teacher spread0.287 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations0
Published2025
Admission routes2
Has abstractyes

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