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Record W4407242626 · doi:10.1097/htr.0000000000001038

Cross-Lagged Associations Among Sleep, Headache, and Pain in Pediatric Mild Traumatic Brain Injury: An A-CAP Study

2025· article· en· W4407242626 on OpenAlexaffabout
Safira Dharsee, Mélanie Noël, Amy M. Bender, Miriam H. Beauchamp, William Craig, Quynh Doan, Stephen B. Freedman, Jocelyn Gravel, Roger Zemek, Keith Owen Yeates

Bibliographic record

VenueJournal of Head Trauma Rehabilitation · 2025
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsAlberta Children's Hospital
Fundersnot available
KeywordsMedicineSleep disorderTraumatic brain injurySleep (system call)Physical therapyCohort studyCohortPediatricsPsychiatryInternal medicineInsomnia

Abstract

fetched live from OpenAlex

OBJECTIVE: To test cross-lagged associations among sleep, headache, and pain in pediatric mild traumatic brain injury (mTBI). SETTING, PARTICIPANTS, DESIGN: Children and adolescents aged 8.0 to 16.9 years who sustained a mTBI and presented to 1 of 5 pediatric emergency departments across Canada completed assessments at 1-week, 3 months, and 6 months post-injury as part of a larger prospective cohort study. MAIN MEASURES: Sleep disturbance was measured using 7 sleep items from the Child Behaviour Checklist. Sleep duration was measured using average weekday and weekend sleep from the Healthy Lifestyle Behaviours Questionnaire. Pain intensity was measured using an 11-point numerical rating scale. Headache severity and associated functional impairment were measured using the Headache Impact Test and 1 item from the Health and Behaviour Inventory. Analyses included trivariate-indicator random-intercept cross-lagged panel models. RESULTS: Of 633 recruited children, 563 were included in the current study. Headache showed significant within-person, bidirectional, cross-lagged associations with sleep disturbance and duration, as well as with pain intensity. More specifically, worse headache predicted greater sleep disturbance (1-week to 3 months and 3 months to 6 months: B s = .47, P s ≤ .013) and shorter sleep duration (1-week to 3 months: B = -.21, P = .006), while greater sleep disturbance predicted worse headache (1-week to 3 months: B = .08, P = .001). Worse headache also predicted higher pain intensity (1-week to 3 months & 3 months to 6 months: B s ≥ 1.27, P s < .001), while higher pain intensity predicted worse headache (3 months to 6 months: B s ≥ .03, P s ≤ .042). No cross-lagged associations involving sleep disturbance or duration with pain intensity were significant. CONCLUSIONS: Significant bi-directional, cross-lagged associations exist between headache and both sleep and pain. The findings suggest that early intervention for headaches may help prevent later sleep disturbance and pain after pediatric mTBI.

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)0.003
metaresearch head score (Gemma)0.007
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 score0.031
Threshold uncertainty score0.061

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
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 head0.055
GPT teacher head0.417
Teacher spread0.362 · 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

Citations2
Published2025
Admission routes2
Has abstractyes

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