Rapid reviews methods series: assessing the appropriateness of conducting a rapid 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
This paper, part of the Cochrane Rapid Review Methods Group series, offers guidance on determining when to conduct a rapid review (RR) instead of a full systematic review (SR). While both review types aim to comprehensively synthesise evidence, RRs, conducted within a shorter time frame of typically 6 months or less, involve streamlined methods to expedite the process. The decision to opt for an RR depends on the urgency of the research question, resource availability and the impact on decision outcomes. The paper categorises scenarios where RRs are appropriate, including urgent decision-making, informing guidelines, assessing new technologies and identifying evidence gaps. It also outlines instances when RRs may be inappropriate, cautioning against conducting them solely for ease, quick publication or only cost-saving motives.When deciding on an RR, it is crucial to consider both conceptual and practical factors. These factors encompass the urgency of needing timely evidence, the consequences of waiting for a full SR, the potential risks associated with incomplete evidence, and the risk of not using synthesised evidence in decision-making, among other considerations. Key factors to weigh also include having a clearly defined need, a manageable scope and access to the necessary expertise. Overall, this paper aims to guide informed judgements about whether to choose an RR over an SR based on the specific research question and context. Researchers and decision-makers are encouraged to carefully weigh potential trade-offs when opting for RRs.
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 |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Methods About the Canadian research system: no · About a Canadian topic: no | Not applicable | high |
| gpt | Metaresearch Domain: Methods · Genre: Methods About the Canadian research system: no · About a Canadian topic: no | Not applicable | high |
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 | 0.678 | 0.468 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.045 | 0.012 |
| Bibliometrics | 0.001 | 0.012 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.008 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.022 | 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 it