DEFINING RAPID REVIEWS: A MODIFIED DELPHI CONSENSUS APPROACH
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
OBJECTIVES: Rapid reviews are characterized as an accelerated evidence synthesis approach with no universally accepted methodology or definition. This modified Delphi consensus study aimed to develop a comprehensive set of defining characteristics for rapid reviews that may be used as a functional definition. METHODS: Expert panelists with knowledge in rapid reviews and evidence synthesis were identified. In the first round, panelists were asked to answer a seventeen-item survey addressing a variety of rapid review topics. Results led to the development of statements describing the characteristics of rapid reviews that were circulated to experts for agreement in a second survey round and further revised in a third round. Consensus was reached if ≥70 percent of experts agreed and there was stability in free-text comments. RESULTS: A panel of sixty-six experts participated. Consensus was reached on ten of eleven statements describing the characteristics of rapid reviews. According to the panel, rapid reviews aim to meet the requirements and timelines of a decision maker and should be conducted in less time than a systematic review. They use a variety of approaches to accelerate the evidence synthesis process, tailor the methods conventionally used to carry out systematic reviews, and use the most rigorous methods that the delivery time frame will allow. CONCLUSIONS: This study achieved consensus on ten statements describing the defining characteristics of rapid reviews based on the opinion of a panel of knowledgeable experts. Areas of disagreement were also highlighted. Findings emphasize the role of the decision maker and stress the importance of transparent reporting.
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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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