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Record W2156129418 · doi:10.1161/strokeaha.107.484071

Can Mass Media Influence Emergency Department Visits for Stroke?

2007· article· en· W2156129418 on OpenAlexafffundabout
Corinne Hodgson, Patrice Lindsay, Frank Rubini

Bibliographic record

VenueStroke · 2007
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsHeart and Stroke Foundation
FundersCanadian Stroke Network
KeywordsMedicineEmergency departmentStroke (engine)Medical emergencyEmergency medicinePsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND AND PURPOSE: Television advertising has been associated with significant increases in the knowledge of the warning signs of stroke among Ontarians aged 45 and older. However, to date there has been little data on the relationship between knowledge of the warning signs of stroke and behavior. METHODS: Data on presentation to regional and enhanced district stroke center emergency departments were obtained from the Registry of the Canadian Stroke Network for a 31-month period between mid 2003 and the beginning of 2006. Public opinion polling was used to track knowledge of the warning signs of stroke among Ontarians aged 45 and older. RESULTS: The public's awareness of the warning signs of stroke increased during 2003 to 2005, decreasing in 2006 after a 5-month advertising blackout. There was a significant increase in the mean number of emergency department visits for stroke over the study period. A campaign effect independent of year was observed for total presentations, presentation within 5 hours of last seen normal, and presentation within 2.5 hours. For TIAs there was a strong campaign effect but no change in the number of presentations by year. CONCLUSIONS: Continuous advertising may be required to build and sustain public awareness of the warning signs of stroke. There are many factors that may influence presentation for stroke and awareness of the warning signs may be only one. However, results of this study suggest there may be an important correlation between the advertising and emergency department presentations with stroke, particularly for TIAs.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.223
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.013
GPT teacher head0.282
Teacher spread0.269 · 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

Citations180
Published2007
Admission routes3
Has abstractyes

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