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Record W4391563803 · doi:10.1136/bmj-2023-076335

Updated recommendations for the Cochrane rapid review methods guidance for rapid reviews of effectiveness

2024· article· en· W4391563803 on OpenAlexaff
Chantelle Garritty, Candyce Hamel, Marialena Trivella, Gerald Gartlehner, Barbara Nußbaumer-Streit, Declan Devane, Chris Kamel, Ursula Griebler, Valerie King

Bibliographic record

VenueBMJ · 2024
Typearticle
Languageen
FieldDecision Sciences
TopicMeta-analysis and systematic reviews
Canadian institutionsPublic Health Agency of CanadaCanadian Agency for Drugs and Technologies in HealthUniversity of Ottawa
Fundersnot available
KeywordsSystematic reviewScope (computer science)InterimTimelineMedicineCochrane collaborationProcess (computing)Computer scienceManagement scienceHealth careMEDLINEProcess managementRisk analysis (engineering)EngineeringPolitical science

Abstract

fetched live from OpenAlex

This article provides updated guidance on methods for conducting rapid reviews of effectiveness, targeted at Cochrane and other stakeholders interested in the methodology of rapid reviews. The guidance, developed by the Cochrane Rapid Reviews Methods Group, builds upon previous interim guidance, and incorporates changes based on an evaluation of its application, a scope of the literature on rapid review methodology, and input from a diverse group of experts in rapid review methods. The guidance consists of 24 specific recommendations supporting the conduct of rapid reviews, applicable both within and outside Cochrane. It underscores the importance of considering the appropriateness of undertaking rapid reviews and advocates for a tailored, iterative approach to each review. Key defining features of rapid reviews, such as restricted methods, how the dimension of timelines factors into rapid reviews, and the involvement of knowledge users (eg, patient and public partners, healthcare providers, policy makers), are outlined. The paper presents a definition of a Cochrane rapid review and additional considerations for rapid reviews of effectiveness to enhance the efficiency of the review process. In conclusion, the Cochrane Rapid Review Methods Group’s updated guidance, complemented by examples, seeks to guide methodological decisions in the design and conduct of rapid reviews, facilitating timely decision making in healthcare.

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

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.433
metaresearch head score (Gemma)0.103
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.430
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.4330.103
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0090.000

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.

Opus teacher head0.762
GPT teacher head0.650
Teacher spread0.112 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreMethods

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".

Quick stats

Citations207
Published2024
Admission routes1
Has abstractyes

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