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Record W2131627463 · doi:10.1071/ah050469

Enhancing evidence-based practice in population health: staff views, barriers and strategies for change

2005· article· en· W2131627463 on OpenAlex
Armita Adily, Jeanette Ward

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAustralian Health Review · 2005
Typearticle
Languageen
FieldHealth Professions
TopicHealth Sciences Research and Education
Canadian institutionsInstitute of Population and Public Health
FundersUniversity of New South WalesCancer Council NSWRoyal Australasian College of Physicians
KeywordsPopulation healthHealth economicsPublic healthHealth carePublic relationsPopulationNursingGovernment (linguistics)Health services researchMedicineBusinessEnvironmental healthPolitical scienceEconomic growthEconomics

Abstract

fetched live from OpenAlex

STUDY OBJECTIVE: To determine barriers and enablers for evidence-based practice (EBP) in population health and potential strategies for change. DESIGN: Self-administered survey of 104 professional staff (response rate, 73%) in the Division of Population Health, South Western Sydney Area Health Service in NSW serving a disadvantaged urban population. MAIN RESULTS: Most respondents (80%) "strongly agreed" or "agreed" that EBP would improve the effectiveness of their efforts in a disadvantaged region. However, more than half of respondents (56%) "strongly agreed" or "agreed" that there is lack of evidence for interventions in population health. Eighty two per cent of respondents "strongly agreed" or "agreed" that training in EBP is important for all population health workers. Those who used evidence also needed a greater capacity to discriminate "good" from "bad" research (85% in agreement). Contradictory policy was cited by one third of respondents as acting against EBP.

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.

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)0.014
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.666
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0140.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.002
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 head0.505
GPT teacher head0.610
Teacher spread0.105 · 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