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Record W2124806995 · doi:10.1186/1447-056x-12-3

Alberta family physicians’ willingness to work during an influenza pandemic: a cross-sectional study

2013· article· en· W2124806995 on OpenAlexaffabout
James A. Dickinson, Gisoo Bani-Adam, Tyler Williamson, Sandy Berzins, Craig Pearce, Leah J. Ricketson, Emily Medd

Bibliographic record

VenueAsia Pacific Family Medicine · 2013
Typearticle
Languageen
FieldPsychology
TopicCOVID-19 and Mental Health
Canadian institutionsAlberta Children's HospitalSouth Health CampusQueen's UniversityAlberta Hospital EdmontonHealth Sciences CentreUniversity of Calgary
Fundersnot available
KeywordsMedicinePandemicCross-sectional studyFamily medicineInfluenza pandemicCoronavirus disease 2019 (COVID-19)Work (physics)Environmental healthInternal medicinePathologyInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

OBJECTIVE: Effective pandemic responses rely on frontline healthcare workers continuing to work despite increased risk to themselves. Our objective was to investigate Alberta family physicians willingness to work during an influenza pandemic. DESIGN: Cross-sectional survey. SETTING: Alberta prior to the fall wave of the H1N1 epidemic. PARTICIPANTS: 192 participants from a random sample of 1000 Alberta family physicians stratified by region. MAIN OUTCOME MEASURES: Willingness to work through difficult scenarios created by an influenza epidemic. RESULTS: The corrected response rate was 22%. The most physicians who responded were willing to continue working through some scenarios caused by a pandemic, but in other circumstances less than 50% would continue. Men were more willing to continue working than women. In some situations South African and British trained physicians were more willing to continue working than other groups. CONCLUSIONS: Although many physicians intend to maintain their practices in the event of a pandemic, in some circumstances fewer are willing to work. Pandemic preparation requires ensuring a workforce is available. Healthcare systems must provide frontline healthcare workers with the support and resources they need to enable them to continue providing care.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.030
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.002

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 head0.109
GPT teacher head0.426
Teacher spread0.317 · 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.

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

Citations11
Published2013
Admission routes2
Has abstractyes

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