Assessing the process and outcome of the development of practice guidelines and recommendations: PANELVIEW instrument development
Bibliographic record
Abstract
BACKGROUND: Guideline recommendations may be affected by flaws in the process, inappropriate panel member selection or conduct, conflicts of interest and other factors. To our knowledge, no validated tool exists to evaluate guideline development from the perspective of those directly involved in the process. Our objective was to develop and validate a universal tool, the PANELVIEW instrument, to assess guideline processes, methods and outcomes from the perspective of the participating guideline panellists and group members. METHODS: We performed a systematic literature search and surveys of guideline groups (identified through contacting international organizations and convenience sampling of working panels) to inform item generation. Subsequent groups of guideline methodologists and panellists reviewed items for face validity and missing items. We used surveys, interviews and expert review for item reduction and phrasing. For reliability assessment and feedback, we tested the PANELVIEW tool in 8 international guideline groups. RESULTS: We surveyed 62 members from 13 guideline panels, contacted 19 organizations and reviewed 20 source documents to generate items. Fifty-three additional key informants provided feedback about phrasing of the items and response options. We reduced the number of items from 95 to 34 across domains that included administration, training, conflict of interest, group dynamics, chairing, evidence synthesis, formulating recommendations and publication. The tool takes about 10 minutes to complete and showed acceptable measurement properties. INTERPRETATION: The PANELVIEW instrument fills a gap by enabling guideline organizations to involve clinicians, patients and other participants in evaluating their guideline processes. The tool can inform quality improvement of existing or new guideline programs, focusing on insight into and transparency of the guideline development process, methods and outcomes.
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How this classification was reachedexpand
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 | 0.229 | 0.366 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.009 | 0.007 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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; the direct Gemma label and the distilled Codex classifier 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".