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Record W4220722251 · doi:10.31222/osf.io/82wau

Reporting guideline for overviews of reviews of healthcare interventions: The Preferred Reporting Items for Overviews of Reviews (PRIOR) statement

2022· preprint· en· W4220722251 on OpenAlexfundno aff
Michelle Gates, Allison Gates, Dawid Pieper, Ricardo J. Fernandes, Andrea C. Tricco, David Moher, Sue Brennan, Tianjing Li, Michelle Pollock, Carole Lunny, Dino Sepúlveda, Joanne E. McKenzie, Karen A. Robinson, Katja Matthias, Konstantinos I. Bougioukas, Paolo Fusar‐Poli, Penny Whiting, Stephana J. Moss, Lisa Hartling

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicDelphi Technique in Research
Canadian institutionsnot available
FundersNational Eye InstituteNational Health and Medical Research CouncilCanadian Institutes of Health ResearchNational Institutes of Health
KeywordsChecklistGuidelineSystematic reviewHealth carePsychological interventionStakeholderDelphi methodStatement (logic)DelphiPsychologyEvidence-based medicineMedical educationEvidence-based practicePublic relationsMedicineMEDLINEPolitical scienceComputer scienceAlternative medicineNursing

Abstract

fetched live from OpenAlex

The publication of systematic reviews has rapidly increased making it challenging to remain apprised of and interpret evidence from their growing number. A newer form of evidence synthesis, overview of reviews, synthesizes evidence from multiple systematic reviews. Authors would benefit from evidence- and consensus-based guidance for the complete and transparent reporting of overviews of reviews; in turn this will improve their reproducibility, trustworthiness, and usefulness for readers and end users (e.g., healthcare providers, healthcare decision-makers, policy-makers, patients/public).The PRIOR statement provides an evidence-based reporting guideline developed using established, rigorous methods that involved a four-stage process (project launch, evidence reviews, modified Delphi exercise, development of the reporting guideline) and an international stakeholder group representing varied experiences (e.g., authors, peer reviewers, editors, readers) and roles (e.g., patients/public, researchers, statisticians, librarians, healthcare professionals, policymakers). The PRIOR statement includes: a checklist with 27 main items that cover all steps and considerations involved in planning and conducting an overview of reviews of healthcare interventions; an explanation and elaboration document with rationale, essential elements, additional elements, and example for each item; and a flow diagram.

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)0.191
metaresearch head score (Gemma)0.110
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.570
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.1910.110
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.004
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0020.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.727
GPT teacher head0.639
Teacher spread0.089 · 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
GenreReview

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

Citations15
Published2022
Admission routes1
Has abstractyes

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