MétaCan
Menu
Back to cohort
Record W2907831405 · doi:10.1186/s12889-018-6317-5

Impact of an organization-wide knowledge translation strategy to support evidence-informed public health decision making

2018· article· en· W2907831405 on OpenAlex

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueBMC Public Health · 2018
Typearticle
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsAlberta Health ServicesDalhousie UniversityMcMaster University
FundersInstitute of Population and Public HealthCanadian Institutes of Health Research
KeywordsKnowledge translationBiostatisticsMedicineIntervention (counseling)Public healthEvidence-based practiceDecision aidsMedical educationData collectionBaseline (sea)NursingFamily medicineKnowledge managementAlternative medicine

Abstract

fetched live from OpenAlex

BACKGROUND: The public health sector is moving toward adopting evidence-informed decision making into practice, but effort is still required to effectively develop capacity and promote contextual factors that advance and sustain it. This paper describes the impact of an organization-wide knowledge translation intervention delivered by knowledge brokers on evidence-informed decision making knowledge, skills and behaviour. METHODS: A case study design was implemented with the intervention and data collection tailored to the unique needs of each case (health department). A knowledge broker provided training workshops and mentored small groups through a seven step process of evidence-informed decision making. The intervention was delivered over 22 months; data related to evidence-informed decision making knowledge, skills and behaviour were collected at baseline and follow-up. Mixed effects regression models were developed to assess the impact of involvement in the intervention on the evidence-informed decision making outcomes. RESULTS: Data from a total of 606 health department staff were collected during baseline: 207 (33%) staff from Case A, 304 (28%) from Case B, and 95 (47%) from Case C. There were a total of 804 participants at follow-up: 258 (42%) from Case A, 391 from Case B (37%), and 155 (50%) from Case C. Statistically significant increases in knowledge and skills were observed overall, and in all three health departments. An increase in evidence-informed decision making behaviour was observed among those intensively involved in the intervention from all cases (statistically significant in Case A). The organizational characteristics of strategic priority, leadership, readiness, and choice of staff emerged as important factors in the change process. CONCLUSIONS: Knowledge brokering is a promising organizational knowledge translation intervention to support evidence-informed decision making. The intervention appeared to have the greatest impact on those who became actively engaged with the knowledge broker in the intervention. Active participation in face-to-face training activities with a knowledge broker, focused specifically on evidence-informed decision making skill development, led to the greatest impact on associated behaviours, knowledge, and skills. Several organizational factors emerged as integral to success of the knowledge translation intervention.

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)0.019
metaresearch head score (Gemma)0.022
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.542
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0190.022
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.006
Science and technology studies0.0020.000
Scholarly communication0.0000.003
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.801
GPT teacher head0.701
Teacher spread0.100 · 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