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Record W3183848989 · doi:10.1186/s13063-021-05738-z

Improving peer review of systematic reviews by involving librarians and information specialists: protocol for a randomized controlled trial

2021· article· en· W3183848989 on OpenAlexaff
Melissa L. Rethlefsen, Sara Schroter, L.M. Bouter, David Moher, Ana Patricia Ayala, Jamie J Kirkham, Maurice P. Zeegers

Bibliographic record

VenueTrials · 2021
Typearticle
Languageen
FieldDecision Sciences
TopicMeta-analysis and systematic reviews
Canadian institutionsUniversity of TorontoOttawa Hospital
FundersMedical Research CouncilUniversiteit MaastrichtUniversity College CorkDepartment of Health and Social CareUniversity of BristolNational Institute for Health and Care ResearchUniversity Hospitals Bristol NHS Foundation Trust
KeywordsSystematic reviewRandomized controlled trialProtocol (science)MedicinePeer reviewMEDLINEGrey literatureQuality (philosophy)Medical educationAlternative medicinePathology

Abstract

fetched live from OpenAlex

BACKGROUND: Problems continue to exist with the reporting quality and risk of bias in search methods and strategies in systematic reviews and related review types. Peer reviewers who are not familiar with what is required to transparently and fully report a search may not be prepared to review the search components of systematic reviews, nor may they know what is likely to introduce bias into a search. Librarians and information specialists, who have expertise in searching, may offer specialized knowledge that would help improve systematic review search reporting and lessen risk of bias, but they are underutilized as methodological peer reviewers. METHODS: This study will evaluate the effect of adding librarians and information specialists as methodological peer reviewers on the quality of search reporting and risk of bias in systematic review searches. The study will be a pragmatic randomized controlled trial using 150 systematic review manuscripts submitted to BMJ and BMJ Open as the unit of randomization. Manuscripts that report on completed systematic reviews and related review types and have been sent for peer review are eligible. For each manuscript randomized to the intervention, a librarian/information specialist will be invited as an additional peer reviewer using standard practices for each journal. First revision manuscripts will be assessed in duplicate for reporting quality and risk of bias, using adherence to 4 items from PRISMA-S and assessors' judgements on 4 signaling questions from ROBIS Domain 2, respectively. Identifying information from the manuscripts will be removed prior to assessment. DISCUSSION: The primary outcomes for this study are quality of reporting as indicated by differences in the proportion of adequately reported searches in first revision manuscripts between intervention and control groups and risk of bias as indicated by differences in the proportions of first revision manuscripts with high, low, and unclear bias. If the intervention demonstrates an effect on search reporting or bias, this may indicate a need for journal editors to work with librarians and information specialists as methodological peer reviewers. TRIAL REGISTRATION: Open Science Framework. Registered on June 17, 2021, at https://doi.org/10.17605/OSF.IO/W4CK2 .

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)0.691
metaresearch head score (Gemma)0.916
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (broad), Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.611
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.6910.916
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0380.007
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0020.002
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.748
GPT teacher head0.564
Teacher spread0.184 · 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 designRandomized trial
Domainnot available
GenreProtocol

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

Citations14
Published2021
Admission routes1
Has abstractyes

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