Facilitation roles and characteristics associated with research use by healthcare professionals: a scoping review
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.
Bibliographic record
Abstract
BACKGROUND: Implementing research findings into practice is a complex process that is not well understood. Facilitation has been described as a key component of getting research findings into practice. The literature on facilitation as a practice innovation is growing. This review aimed to identify facilitator roles and to describe characteristics of facilitation that may be associated with successful research use by healthcare professionals. METHODS: We searched 10 electronic databases up to December 2016 and used predefined criteria to select articles. We included conceptual papers and empirical studies that described facilitator roles, facilitation processes or interventions, and that focused on healthcare professionals and research use. We used content and thematic analysis to summarise data. Rogers' five main attributes of an innovation guided our synthesis of facilitation characteristics. RESULTS: Of the 38 488 articles identified from our online and manual search, we included 195 predominantly research studies. We identified nine facilitator roles: opinion leaders, coaches, champions, research facilitators, clinical/practice facilitators, outreach facilitators, linking agents, knowledge brokers and external-internal facilitators. Fifteen facilitation characteristics were associated with research use, which we grouped into five categories using Rogers' innovation attributes: relative advantage, compatibility, complexity, trialability and observability. CONCLUSIONS: We found a diverse and broad literature on the concept of facilitation that can expand our current thinking about facilitation as an innovation and its potential to support an integrated, collaborative approach to improving healthcare delivery.
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 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 | 0.034 | 0.040 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it