Determinants that influence knowledge brokers' and opinion leaders' role to close knowledge practice gaps in rehabilitation: A realist review
Bibliographic record
Abstract
RATIONALE: Despite the available evidence to support optimal practices in rehabilitation, significant knowledge practice gaps persist. Opinion leaders (OLs) and knowledge brokers (KBs) can enhance the success of knowledge translation (KT) interventions and improve uptake of best practices among clinicians. However, the literature on the mechanisms underpinning OLs'/KBs' activities, and guidance on the type of support needed for successful implementation of these roles in rehabilitation contexts is scarce. This research aimed to highlight the differences and similarities between OLs and KBs with respect to context, mechanism, and outcomes as well as describe the common patterns of OLs and KBs by creating a context-mechanism-outcomes configuration. METHODS: We conducted a realist review to synthesize the available evidence on OLs/KBs as active KT strategies. A search was conducted across five databases up to November 2019. Two independent reviewers extracted the data using a structured form. A context-mechanism-outcome configuration was used to conceptualize a cumulative portrait of the features of OLs/KBs roles. RESULTS: The search identified 3282 titles after removing duplicates. Seventeen studies (reported in 20 articles) were included in the review. Findings suggest a number of desirable features of OLs/KBs roles that may maximize the achievement of targeted outcomes namely being (a) embedded within their organization as "insiders"; (b) adequately skilled to perform their role; (c) identified as able to fulfil the role; (d) appropriately trained; and (e) able to use different KT interventions. CONCLUSION: Findings of this realist review converge to create a context-mechanism-outcomes configuration with suggestions to optimally utilize OLs/KBs in rehabilitation. The configurations suggest desirable features that can lead to a greater potential to achieve targeted goals. It is preferable that OLs/KBs be embedded in the organization and that they are adequately skilful and well-trained. Also, OLs/KBs should perform the required roles using KT interventions adapted to the local context.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gpt | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | high |
| grok | Meta-epidemiology (broad) Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | high |
| opus | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | medium |
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.058 | 0.254 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.006 |
| Bibliometrics | 0.014 | 0.013 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
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, unvalidatedLabeled directly by 3 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".