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Record W4394011289 · doi:10.1111/head.14701

Anxiety and depressive symptoms and migraine‐related outcomes in children and adolescents

2024· article· en· W4394011289 on OpenAlexafffund
Bilal Rizvi, Jonathan Kuziek, Lydia Y. Cho, Paul E. Ronksley, Melanie N. Noel, Serena L. Orr

Bibliographic record

VenueHeadache The Journal of Head and Face Pain · 2024
Typearticle
Languageen
FieldMedicine
TopicMigraine and Headache Studies
Canadian institutionsHotchkiss Brain InstituteAlberta Children's HospitalUniversity of Calgary
FundersResearch Committee, Aristotle University of ThessalonikiCanadian Institutes of Health ResearchDepartment of Pediatrics, School of Medicine, University of VirginiaAlberta Children's Hospital Research InstituteUniversity of Cambridge
KeywordsMigraineAnxietyMedicineDepression (economics)CohortConfidence intervalCohort studyProspective cohort studyPsychiatryPhysical therapyPediatricsInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: The objective of this study was to explore the longitudinal relationship between anxiety and depressive symptoms and migraine outcomes in children and adolescents. BACKGROUND: Children and adolescents with migraine experience more anxiety and depressive symptoms than their peers without migraine, but it is unknown if these symptoms are associated with differential migraine outcomes. METHODS: In this prospective clinical cohort study, children and adolescents aged 8.0-18.0 years with migraine completed headache questionnaires and validated measures of anxiety and depressive symptoms (Patient-Reported Outcomes Measurement Information System) at an initial consultation and at their first follow-up visit with a neurologist. Changes in monthly headache frequency and changes in migraine-related disability (Pediatric Migraine Disability Assessment) were tracked at each time point. The relationships between these migraine outcomes and anxiety and depressive symptoms were estimated using models controlling for sex, age, headache frequency, and treatment type. RESULTS: There were 123 consenting participants. In models adjusted for age, sex, baseline disability score, and treatment type, baseline anxiety and depressive symptom levels were not significantly associated with change in headache frequency (for anxiety symptoms: β = -0.05, 95% confidence interval [CI] = -0.268 to 0.166, p = 0.639; for depressive symptoms: β = 0.14, 95% CI = -0.079 to 0.359, p = 0.209). Similarly, in models adjusted for age, sex, baseline headache frequency, and treatment type, the change in disability was not associated with baseline anxiety (β = -0.45, 95% CI = -1.69 to 0.78, p = 0.470), nor with baseline depressive symptom scores (β = 0.16, 95% CI = -1.07 to 1.40, p = 0.796). In post hoc exploratory analyses (N = 84 with anxiety and N = 82 with depressive symptom data at both visits), there were also no significant associations between change in mental health symptoms and change in headache frequency (for anxiety symptoms: β = -0.084, 95% CI = -0.246 to 0.078, p = 0.306; for depressive symptoms: β = -0.013, 95% CI = -0.164 to 0.138, p = 0.865). Similarly, the change in disability scores between visits was not related to the change in anxiety (β = 0.85, 95% CI = -0.095 to 1.78, p = 0.077) nor depressive symptom scores (β = 0.32, 95% CI = -0.51 to 1.15, p = 0.446). CONCLUSION: Baseline anxiety and depressive symptom levels were not associated with longitudinal migraine outcomes and neither were longitudinal changes in anxiety and depressive symptom levels; this contradicts popular clinical belief that mental health symptoms predict or consistently change in tandem with migraine outcomes.

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)0.003
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 score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.008
GPT teacher head0.268
Teacher spread0.261 · 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

Citations14
Published2024
Admission routes2
Has abstractyes

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