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Record W2396846174 · doi:10.1371/journal.pmed.1002028

Epidemiology and Reporting Characteristics of Systematic Reviews of Biomedical Research: A Cross-Sectional Study

2016· article· en· W2396846174 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenuePLoS Medicine · 2016
Typearticle
Languageen
FieldDecision Sciences
TopicMeta-analysis and systematic reviews
Canadian institutionsVancouver General HospitalPublic Health OntarioUniversity of TorontoSt. Michael's HospitalChildren's Hospital of Eastern OntarioOttawa HospitalUniversity of Ottawa
FundersNational Health and Medical Research CouncilMedical Research CouncilNational Institute for Health and Care ResearchCoordenação de Aperfeiçoamento de Pessoal de Nível SuperiorCanadian Institutes of Health ResearchGeneralitat ValencianaGoverno Brasil
KeywordsMedicineMEDLINESystematic reviewEpidemiologyCross-sectional studySample size determinationMeta-analysisFamily medicinePathologyStatistics

Abstract

fetched live from OpenAlex

BACKGROUND: Systematic reviews (SRs) can help decision makers interpret the deluge of published biomedical literature. However, a SR may be of limited use if the methods used to conduct the SR are flawed, and reporting of the SR is incomplete. To our knowledge, since 2004 there has been no cross-sectional study of the prevalence, focus, and completeness of reporting of SRs across different specialties. Therefore, the aim of our study was to investigate the epidemiological and reporting characteristics of a more recent cross-section of SRs. METHODS AND FINDINGS: We searched MEDLINE to identify potentially eligible SRs indexed during the month of February 2014. Citations were screened using prespecified eligibility criteria. Epidemiological and reporting characteristics of a random sample of 300 SRs were extracted by one reviewer, with a 10% sample extracted in duplicate. We compared characteristics of Cochrane versus non-Cochrane reviews, and the 2014 sample of SRs versus a 2004 sample of SRs. We identified 682 SRs, suggesting that more than 8,000 SRs are being indexed in MEDLINE annually, corresponding to a 3-fold increase over the last decade. The majority of SRs addressed a therapeutic question and were conducted by authors based in China, the UK, or the US; they included a median of 15 studies involving 2,072 participants. Meta-analysis was performed in 63% of SRs, mostly using standard pairwise methods. Study risk of bias/quality assessment was performed in 70% of SRs but was rarely incorporated into the analysis (16%). Few SRs (7%) searched sources of unpublished data, and the risk of publication bias was considered in less than half of SRs. Reporting quality was highly variable; at least a third of SRs did not report use of a SR protocol, eligibility criteria relating to publication status, years of coverage of the search, a full Boolean search logic for at least one database, methods for data extraction, methods for study risk of bias assessment, a primary outcome, an abstract conclusion that incorporated study limitations, or the funding source of the SR. Cochrane SRs, which accounted for 15% of the sample, had more complete reporting than all other types of SRs. Reporting has generally improved since 2004, but remains suboptimal for many characteristics. CONCLUSIONS: An increasing number of SRs are being published, and many are poorly conducted and reported. Strategies are needed to help reduce this avoidable waste in research.

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 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)0.619
metaresearch head score (Gemma)0.896
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.278
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.6190.896
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0100.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
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 head0.967
GPT teacher head0.680
Teacher spread0.287 · 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