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Record W4413901452 · doi:10.1111/head.15039

Exploring the relationship between pain catastrophizing and migraine in youth: A longitudinal clinical cohort study

2025· article· en· W4413901452 on OpenAlexafffund
Alexis Espanioli, Nynke J. van den Hoogen, Jonathan Kuziek, Kirsten Sjonnesen, Mélanie Noël, Serena L. Orr

Bibliographic record

VenueHeadache The Journal of Head and Face Pain · 2025
Typearticle
Languageen
FieldMedicine
TopicMigraine and Headache Studies
Canadian institutionsHotchkiss Brain InstituteOntario Brain InstituteAlberta Children's HospitalUniversity of Calgary
FundersCanadian Institutes of Health ResearchCumming School of Medicine, University of CalgaryAmerican Headache SocietyAlberta Children's Hospital Research InstituteUniversity of CambridgeUniversité de Sherbrooke
KeywordsMigrainePain catastrophizingMedicinePhysical therapyCohortConfidence intervalCohort studyPopulationProspective cohort studyLongitudinal studyChronic painPsychiatryInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: This study explored the relationship between pain catastrophizing and migraine-related outcomes (i.e., migraine-related disability and headache frequency) between visits with a neurologist in a clinical population of children and adolescents with migraine. BACKGROUND: Evidence from adult populations suggests that pain catastrophizing, the tendency to magnify the threat value of, and ruminate and feel helpless about, pain may be associated with migraine-related outcomes, but the association in children and adolescents is less clear. METHODS: In this prospective longitudinal clinical cohort study, children and adolescents aged 8-18 years with migraine completed headache questionnaires and a validated measure of pain catastrophizing (Pain Catastrophizing Scale for Children) at baseline and initial follow-up visits with a neurologist. Recruitment spanned from May 2019 to July 2023. Headache frequency and migraine-related disability (Pediatric Migraine Disability Assessment) were assessed at both visits. Migraine outcomes at follow-up were examined in relation to baseline pain catastrophizing scores in models that controlled for sex, age, preventive treatment use, baseline headache frequency, and baseline disability. RESULTS: For this study, 121 consenting participants were included. In models adjusted for age, sex, baseline headache frequency, baseline disability, and preventive treatment use, baseline pain catastrophizing scores were significantly associated with disability scores at follow-up (β = 0.81, 95% confidence interval [CI] = 0.13-1.48, p = 0.020), but not with headache frequency at follow-up (β = 0.04, 95% CI = -0.10 to 0.19, p = 0.575). When examining the specific subscales of pain catastrophizing in an adjusted model, only baseline pain magnification (β = 6.73, 95% CI = 2.95-10.51, p = 0.001) had a significant association with disability at follow-up, while feelings of helplessness (β = 0.08, 95% CI = -2.11 to 2.27, p = 0.944) and rumination did not (β = -1.83, 95% CI = -4.22 to 0.56, p = 0.133). In a subset of participants with pain catastrophizing measured at both visits (n = 65), pain catastrophizing total and subscale scores did not significantly differ between visits. CONCLUSION: Baseline pain catastrophizing scores were associated with migraine-related disability, but not headache frequency, at follow-up in a clinical population of children and adolescents with migraine. Pain magnification specifically appeared to drive this association. Future studies should aim to replicate our results and to investigate if interventions aimed specifically at reducing pain magnification may help to mitigate migraine-related disability in children and adolescents.

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)0.004
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 score0.015
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.272
GPT teacher head0.397
Teacher spread0.125 · 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

Citations3
Published2025
Admission routes2
Has abstractyes

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