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Record W2468146373 · doi:10.1186/s13643-016-0276-7

Publication of reviews synthesizing child health evidence (PORSCHE): a survey of authors to identify factors associated with publication in Cochrane and non-Cochrane sources

2016· article· en· W2468146373 on OpenAlexafffund
Lisa Hartling, Kassi Shave, Denise Thomson, Ricardo M. Fernandes, Aireen Wingert, Katrina Williams

Bibliographic record

VenueSystematic Reviews · 2016
Typearticle
Languageen
FieldDecision Sciences
TopicMeta-analysis and systematic reviews
Canadian institutionsUniversity of AlbertaCochrane
FundersCanadian Institutes of Health Research
KeywordsMedicineFamily medicineCochrane collaborationAlternative medicineSystematic reviewMEDLINECochrane LibraryPathologyLaw

Abstract

fetched live from OpenAlex

BACKGROUND: Cochrane Child Health maintains a register of child-relevant Cochrane systematic reviews (SRs) to provide a comprehensive source of high-quality evidence. However, a large number of SRs are published outside of The Cochrane Collaboration (Cochrane), impacting the comprehensiveness of the Cochrane Database of Systematic Reviews (CDSR). We surveyed authors who published child-relevant SRs with Cochrane and elsewhere in the medical literature to (1) understand their experiences in preparing and publishing SRs and (2) identify factors influencing choice of publication venue. METHODS: We identified SRs published in the CDSR for the most recent complete year prior to our study (2013; n = 145). We searched the medical literature and randomly selected the same number of SRs published the same year. We developed an internet-based survey and contacted the corresponding author of each review via email. Data were analyzed descriptively. Qualitative analysis elicited common themes from open-ended questions. RESULTS: Seventy-six (26 %) responded: 41 % Cochrane, 42 % non-Cochrane, and 17 % published in both venues. Among respondents who published their SR in both venues (n = 13), 46 % found it easier to publish in a non-Cochrane journal, 15 % easier with Cochrane, and 31 % similar. Main reasons for conducting SRs with Cochrane (n = 44) were Cochrane's positive reputation (82 %) and good impact factor (66 %). Among respondents who published their SR in a non-Cochrane journal (n = 32), most frequent reasons for not conducting their SR with Cochrane were time required to follow Cochrane processes (25 %), lack of knowledge about how to conduct an SR with Cochrane (19 %), administrative processes (16 %), and perception that non-Cochrane journals yielded more interest (16 %). Among respondents who published their SR in a non-Cochrane journal (n = 32), 78 % did not register their review and 22 % did not prepare a protocol. CONCLUSIONS: Key reasons for publishing in Cochrane are its positive reputation and impact factor. Reasons for publishing in non-Cochrane sources include lack of familiarity or challenges with the Cochrane processes and desire to publish in a source more directly relevant to the topic of interest. End users looking for evidence in the form of SRs need to be aware that there is a vast number of SRs published across the medical literature. Efforts to optimize the identification of SRs in non-Cochrane sources (e.g., through effective labeling or protocol/review registration) and their content will help end users find the necessary synthesized evidence to support clinical practice.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.204
metaresearch head score (Gemma)0.627
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.796
Threshold uncertainty score0.982

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2040.627
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0230.026
Science and technology studies0.0020.003
Scholarly communication0.0110.012
Open science0.0030.011
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.623
GPT teacher head0.527
Teacher spread0.096 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designObservational
DomainEvaluation
GenreEmpirical

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

Citations2
Published2016
Admission routes2
Has abstractyes

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