The guideline implementability research and application network (GIRAnet): an international collaborative to support knowledge exchange: study protocol
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: Modifying the format and content of guidelines may facilitate their use and lead to improved quality of care. We reviewed the medical literature to identify features desired by different users and associated with guideline use to develop a framework of implementability and found that most guidelines do not contain these elements. Further research is needed to develop and evaluate implementability tools. METHODS: We are launching the Guideline Implementability Research and Application Network (GIRAnet) to enable the development and testing of implementability tools in three domains: Resource Implications, Implementation, and Evaluation. Partners include the Guidelines International Network (G-I-N) and its member guideline developers, implementers, and researchers. In phase one, international guidelines will be examined to identify and describe exemplar tools. Indication-specific and generic tools will populate a searchable repository. In phase two, qualitative analysis of cognitive interviews will be used to understand how developers can best integrate implementability tools in guidelines and how health professionals use them for interpreting and applying guidelines. In phase three, a small-scale pilot test will assess the impact of implementability tools based on quantitative analysis of chart-based behavioural outcomes and qualitative analysis of interviews with participants. The findings will be used to plan a more comprehensive future evaluation of implementability tools. DISCUSSION: Infrastructure funding to establish GIRAnet will be leveraged with the in-kind contributions of collaborating national and international guideline developers to advance our knowledge of implementation practice and science. Needs assessment and evaluation of GIRAnet will provide a greater understanding of how to develop and sustain such knowledge-exchange networks. Ultimately, by facilitating use of guidelines, this research may lead to improved delivery and outcomes of patient care.
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.
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: Protocol About the Canadian research system: no · About a Canadian topic: no | Not applicable | high |
| grok | no category Domain: not available · Genre: Protocol About the Canadian research system: no · About a Canadian topic: no | Other design | high |
| opus | no category Domain: not available · Genre: Protocol About the Canadian research system: no · About a Canadian topic: no | Other design | low |
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 | 0.066 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.004 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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