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Record W2106985554 · doi:10.1017/s0317167100001888

Evaluating Migraine Disability: The Headache Impact Test Instrument in Context

2002· review· en· W2106985554 on OpenAlexaffvenue
William Pryse‐Phillips

Bibliographic record

VenueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques · 2002
Typereview
Languageen
FieldMedicine
TopicMigraine and Headache Studies
Canadian institutionsMemorial University of Newfoundland
FundersGlaxoSmithKline
KeywordsMigraineHeadachesContext (archaeology)Test (biology)MedicinePhysical therapyPhysical medicine and rehabilitationPsychologyPsychiatry

Abstract

fetched live from OpenAlex

Migraine impairs physical, social and emotional functioning but the diagnosis is not always made despite the availability of helpful tools. Poor patient-physician communication is one reason cited for this. It is arguable that if the impact that headaches are having on a person's life can be communicated adequately to the physician, the likelihood of appropriate management will increase. The tools currently employed for assessing headache impact are reviewed briefly and the Headache Impact Test (HIT) and HIT-6 described as validated and reliable measures of the effect that headaches are having on patients. The availability of the standard test on the internet, with feedback provided, indicates that this is a potentially useful tool enabling headache sufferers to realize the extent of the burden of migraine and empowering them to seek appropriate management strategies.

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)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0040.005
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
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 head0.207
GPT teacher head0.411
Teacher spread0.204 · 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 designNot applicable
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

Citations53
Published2002
Admission routes2
Has abstractyes

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