Indicators to evaluate organisational knowledge brokers: a scoping review
Bibliographic record
Abstract
BACKGROUND: Knowledge translation (KT) is currently endorsed by global health policy actors as a means to improve outcomes by institutionalising evidence-informed policy-making. Organisational knowledge brokers, comprised of researchers, policy-makers and other stakeholders, are increasingly being used to undertake and promote KT at all levels of health policy-making, though few resources exist to guide the evaluation of these efforts. Using a scoping review methodology, we identified, synthesised and assessed indicators that have been used to evaluate KT infrastructure and capacity-building activities in a health policy context in order to inform the evaluation of organisational knowledge brokers. METHODS: A scoping review methodology was used. This included the search of Medline, Global Health and the WHO Library databases for studies regarding the evaluation of KT infrastructure and capacity-building activities between health research and policy, published in English from 2005 to 2016. Data on study characteristics, outputs and outcomes measured, related indicators, mode of verification, duration and/or frequency of collection, indicator methods, KT model, and targeted capacity level were extracted and charted for analysis. RESULTS: A total of 1073 unique articles were obtained and 176 articles were qualified to be screened in full-text; 32 articles were included in the analysis. Of a total 213 indicators extracted, we identified 174 (174/213; 81.7%) indicators to evaluate the KT infrastructure and capacity-building that have been developed using methods beyond expert opinion. Four validated instruments were identified. The 174 indicators are presented in 8 domains based on an adaptation of the domains of the Lavis et al. framework of linking research to action - general climate, production of research, push efforts, pull efforts, exchange efforts, integrated efforts, evaluation and capacity-building. CONCLUSION: This review presents a total of 174 method-based indicators to evaluate KT infrastructure and capacity-building. The presented indicators can be used or adapted globally by organisational knowledge brokers and other stakeholders in their monitoring and evaluation work.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.055 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.000 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 0.007 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".