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Record W2140576397 · doi:10.1093/her/cyq058

Evaluating the effect of a television public service announcement about epilepsy

2010· article· en· W2140576397 on OpenAlexaff
Alexandra Martiniuk, Mary Secco, L. Yake, Kathy N. Speechley

Bibliographic record

VenueHealth Education Research · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicMisinformation and Its Impacts
Canadian institutionsChildren’s Health Research InstituteUniversity of TorontoWestern UniversitySunnybrook Health Science Centre
Fundersnot available
KeywordsEpilepsyPublic servicePsychologyAdvertisingService (business)BusinessApplied psychologyMarketingPsychiatryPublic relationsPolitical science

Abstract

fetched live from OpenAlex

Public service announcements (PSAs) are non-commercial advertisements aiming to improve knowledge, attitudes and/or behavior. No evaluations of epilepsy PSAs exist. This study sought to evaluate a televised PSA showing first aid for a seizure. A multilevel regression analysis was used to determine the effect of the PSA on epilepsy knowledge and attitudes taking into account school-level clustering as well as individual-level variables, including socioeconomic status, gender, language and familiarity with epilepsy. Of the 803 randomly selected Grade 5 (9-11 years) students, 406 (51%) had seen the epilepsy PSA. Those who saw the PSA scored significantly higher on knowledge (P < 0.001) and had more positive attitudes (P < 0.001) about epilepsy. Those who saw the PSA had even greater knowledge about epilepsy 1 month later, even though the PSA was no longer being televised. Having viewed, the PSA continued to be associated with higher knowledge and more positive attitudes independent of the effects of a school-based epilepsy education program.

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)0.004
metaresearch head score (Gemma)0.027
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 score0.011
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.027
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.607
Teacher spread0.335 · 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

Citations19
Published2010
Admission routes1
Has abstractyes

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