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Record W2951786096 · doi:10.1186/s12961-019-0460-z

A description of a tailored knowledge translation intervention delivered by knowledge brokers within public health departments in Canada

2019· article· en· W2951786096 on OpenAlex
Maureen Dobbins, Lori Greco, Jennifer Yost, Robyn Traynor, Kara DeCorby-Watson, Reza Yousefi‐Nooraie

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueHealth Research Policy and Systems · 2019
Typearticle
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsDalhousie UniversityRegional Municipality of OttawaMcMaster University
FundersInstitute of Population and Public Health
KeywordsKnowledge translationEnthusiasmIntervention (counseling)Health administrationPsychological interventionHealth services researchKnowledge managementPublic healthMedical educationMedicinePsychologyNursingComputer scienceSocial psychology

Abstract

fetched live from OpenAlex

BACKGROUND: While there is an expectation to demonstrate evidence-informed public health there is an ongoing need for capacity development. The purpose of this paper is to provide a description of a tailored knowledge translation intervention implemented by knowledge brokers (KBs), and reflections on the factors that facilitated or hindered its implementation. METHODS: The 22-month knowledge translation intervention, implemented by two KBs, sought to facilitate evidence-informed public health decision-making. Data on outcomes were collected using a knowledge, skills and behavioural assessment survey. In addition, the KBs maintained reflective journals noting which activities appeared successful or not, as well as factors related to the individual or the organisation that facilitated or hindered evidence-informed decision-making. RESULTS: Tailoring of the knowledge translation intervention to address the needs, preferences and structure of each organisation resulted in three unique interventions being implemented. A consistent finding across organisations was that each site needed to determine where evidence-informed decision-making 'fit' within pre-existing organisational processes. Components of the intervention consistent across the three organisations included one-to-one mentoring of teams through rapid evidence reviews, large group workshops and regular meetings with senior management. Components that varied included the frequency of the KB being physically onsite, the amount of time staff spent with the KB and proportion of time spent one-to-one with a KB versus in workshops. Key facilitating factors for implementation included strong leadership, influential power of champions, supportive infrastructure, committed resources and staff enthusiasm. CONCLUSIONS: The results of this study illustrate the importance of working collaboratively with organisations to tailor knowledge translation interventions to best meet unique needs, preferences, organisational structures and contexts. Organisational factors such as leadership, champions and supportive infrastructure play a key role in determining the impact of the knowledge translation interventions. Future studies should explore how these factors can be fostered and/or developed within organisations. While KBs implemented the knowledge translation intervention in this study, more research is needed to understand the impact of all change agent roles including KBs, as well as how these roles can be maintained in the long-term if proven effective.

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)0.025
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.232
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0250.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
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 head0.857
GPT teacher head0.677
Teacher spread0.180 · 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