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Record W2767459374 · doi:10.1111/head.13194

Headache Education Active‐Waiting Directive: A Program to Enhance Well‐Being During Long Referral Wait Times

2017· article· en· W2767459374 on OpenAlexaffabout
Ana Marissa Lagman‐Bartolome, Valerie Lawler, Christine Lay

Bibliographic record

VenueHeadache The Journal of Head and Face Pain · 2017
Typearticle
Languageen
FieldMedicine
TopicMigraine and Headache Studies
Canadian institutionsWomen's College HospitalUniversity of Toronto
Fundersnot available
KeywordsMedicineMigraineReferralSpecialtyHeadachesEmergency departmentFamily medicineAnxietyPhysical therapyPediatricsEmergency medicineNursingPsychiatry

Abstract

fetched live from OpenAlex

OBJECTIVE: The aim of this initiative was to evaluate the clinical impact, patient acceptability, and sustainability of implementing a newly developed evidence-guided migraine education program in an academic headache center. BACKGROUND: Headache is the fifth most common reason for emergency department (ED) visits and accounts for more than 10 million physician visits annually. Successful management of headaches presents a challenge to both primary care providers and neurologists. The catchment area for an academic headache specialty center in a large metropolitan area is over 6 million with an average wait time of over 15 months. This delays diagnosis and impacts patients, thus a Headache Education Active-Waiting Directive (HEAD) was developed to improve patient knowledge and self-care skills among migraine patients awaiting an initial appointment. METHODS: This was a prospective pre- and post-intervention study. English-speaking adults, aged 18-65 years, referred to the Center for Headache at the University of Toronto for headache consultation between May and December 2012, who had not previously been assessed by a headache specialist, were consented and enrolled. Data on Migraine Disability Assessment (MIDAS) with additional questions on emergency visits, lifestyle, and self-efficacy were collected premigraine and postmigraine education program session. RESULTS: Two hundred and forty-eight patients attended the HEAD program and 177 (71%) consented to the study. Detailed predata and postdata were available for 152 participants (mean age 42.5 ± 11.9 years, 86% females); 117/150 (78%) presented with depressive symptoms and 90/146 (62%) presented with anxiety symptoms. One hundred and thirty-seven of 143 (96%) were using headache treatment. Eighty of 137 (58%) were overusing over-the-counter medications and only 21/137 (15%) were on preventative treatment. There was a decrease in the MIDAS scores of participants at postsession testing prior to neurological consultation (pre-MIDAS mean 50.0 ± 64.6 vs post-MIDAS mean 43.2 ± 50.8, P = .046), as well as a decrease in the number of patients requiring ED visit (presession 33 [22%] vs postsession 17 [11%], P = .001). A significant decrease in medication and narcotic overuse after the HEAD program was also observed. Hydration (water intake), morning protein intake, and routine sleep frequency also significantly improved postsession. Controlling for pre-MIDAS score, poor outcome defined as higher post-MIDAS score was statistically associated with lower education level [F(2,149) = 10.88, P = .001]. The majority (144/167, 86%) of the participants found the HEAD program helpful, with 70/167 (42%) very satisfied and 74/167 (44%) somewhat satisfied. One hundred and thirty-two of 167 (79%) felt empowered after attending the education session, and 152/167 (91%) felt that other patients with headache would benefit from this program. CONCLUSIONS: The HEAD program, created to help manage lengthy appointment wait times, was associated with lowering migraine-associated disability, decreasing ED visits, reducing medication and narcotic use and overuse. Education empowers patients to take an active role in their care, especially in regards to improving treatment timing and modifiable lifestyle behaviors. This education program can potentially play a role in early intervention for headache patients especially with chronic migraine and medication overuse headache.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.680
Threshold uncertainty score0.892

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.022
GPT teacher head0.363
Teacher spread0.340 · 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 teacher head, 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

Citations32
Published2017
Admission routes2
Has abstractyes

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