What is expected of people who lead meetings where the goal is to reach consensus? A scoping review with implications for improving the quality of health research grant peer review and clinical guideline development
Bibliographic record
Abstract
Abstract Background The specific roles and responsibilities expected of leaders of consensus-based decision committees, such as grant peer review panels and guideline development panels, are not well-defined, which makes it difficult to train people to lead well. We aimed to explore, describe and define the roles, responsibilities, and leadership characteristics of leaders of meetings where the goal was to reach a consensus decision. Methods We conducted a scoping review with thematic synthesis, guided by the Joanna Briggs Institute Scoping Review Methodology, and Arksey & O’Malley’s framework for scoping reviews as refined by Levac et al. We searched five bibliographic databases from January 2002-2023 in English: Medline (Ovid), Embase (Ovid), CINAHL (EBSCO) and PsycInfo (EBSCO); Proquest Digital Dissertations and ABI-Inform. We searched grey literature in the fields of health science, biomedicine, education, psychology, management, law, ethics and policy. Abstracts and full-text articles were screened in duplicate to identify eligible studies; data were extracted regarding the roles, responsibilities and characteristics of consensus decision committee leaders. Themes were constructed using reflexive thematic analysis. Results From 6732 electronic database records and 126 grey literature records, we included 24 articles and 16 websites. There were 166 unique statements extracted related to roles and responsibilities. We constructed 4 themes to describe the roles for leaders of consensus-based decision meetings: (1) organizer and/or resource manager , (2) facilitator , (3) adjudicator and, (4) administrator . Conclusion Leaders of consensus committees assumed the roles of organiser and/or resource manager, facilitator, adjudicator and administrator. Better clarification of and training for the expected roles and responsibilities of leading consensus decisions are needed. Establishing the roles and responsibilities can inform a systematic process for evaluating the performance of leaders of consensus decision committees.
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.
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 |
|---|---|---|---|
| gemma | Metaresearch Domain: Evaluation · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | high |
| gpt | Metaresearch Domain: Evaluation · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | high |
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 | 0.425 | 0.730 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.008 | 0.006 |
| Bibliometrics | 0.036 | 0.036 |
| Science and technology studies | 0.006 | 0.008 |
| Scholarly communication | 0.020 | 0.035 |
| Open science | 0.005 | 0.008 |
| Research integrity | 0.008 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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 2 models reading the full record.
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".