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Record W4404844645 · doi:10.1016/j.yebeh.2024.110156

A practical program for responding to epileptic seizures including buccal midazolam administration in schools: Effectiveness evaluation for Yogo teachers in Japan

2024· article· en· W4404844645 on OpenAlexaff
Etsuko Tomisaki, Hikaru Sou, Shoko Miyagawa, Junki Yoshioka, Hiroko Horie, Ayaka Kandatsu, Naoko Deguchi, Etsuko Soeda

Bibliographic record

VenueEpilepsy & Behavior · 2024
Typearticle
Languageen
FieldMedicine
TopicEpilepsy research and treatment
Canadian institutionsHealth Research Foundation
Fundersnot available
KeywordsMidazolamBuccal administrationEpilepsyMedicinePsychologyAnesthesiaPsychiatryPharmacology

Abstract

fetched live from OpenAlex

Early response to epileptic seizures is critical. In children, epileptic seizures can occur at school, and practical programs are required to enable teachers to respond. In Japan, schoolteachers may administer buccal midazolam orally under certain conditions; however, there are no established training programs for responding to epileptic seizures in schools. In this study, we aimed to develop a training program on how to respond to seizures, including buccal midazolam administration, and evaluate its effectiveness. We conducted a training program for Yogo teachers at special needs schools and evaluated the differences in confidence in responding to epileptic seizures and administering oral buccal midazolam before and after the program. The results demonstrated that confidence in responding to epileptic seizures and administering oral buccal midazolam significantly improved after the program. We concluded that this training program can help special needs Yogo teachers gain confidence in administering buccal midazolam and responding to epileptic seizures in the school setting.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
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 head0.108
GPT teacher head0.493
Teacher spread0.385 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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