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Blinded versus unblinded assessments of risk of bias in studies included in a systematic review

2011· review· en· W1835380909 on OpenAlexaff
Kate Morissette, Andrea C. Tricco, Tanya Horsley, Maggie H Chen, David Moher

Bibliographic record

VenueCochrane Database of Systematic Reviews · 2011
Typereview
Languageen
FieldDecision Sciences
TopicMeta-analysis and systematic reviews
Canadian institutionsUniversity of TorontoOttawa HospitalRoyal College of Physicians and Surgeons of CanadaSt. Michael's HospitalHealth Canada
Fundersnot available
KeywordsCINAHLMedicineMEDLINESystematic reviewCochrane LibraryPublication biasMeta-analysisSelection biasRandomized controlled trialPhysical therapySurgeryPsychological interventionPsychiatryInternal medicinePathology

Abstract

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BACKGROUND: The importance of appraising the risk of bias of studies included in systematic reviews is well-established. However, uncertainty remains surrounding the method by which risk of bias assessments should be conducted. Specifically, no summary of evidence exists as to whether blinded (i.e. the assessor is unaware of the study author's name, institution, sponsorship, journal, etc.) versus unblinded assessments of risk of bias yield systematically different assessments in a systematic review. OBJECTIVES: To determine whether blinded versus unblinded assessments of risk of bias yield systematically different assessments in a systematic review. SEARCH STRATEGY: We searched MEDLINE (1966 to September week 4 2009), CINAHL (1982 to May week 3 2008), All EBM Reviews (inception to 6 October 2009), EMBASE (1980 to 2009 week 40) and HealthStar (1966 to September week 4 2009) (all Ovid interface). We applied no restrictions regarding language of publication, publication status or study design. We examined reference lists of included studies and contacted experts for potentially relevant literature. SELECTION CRITERIA: We included any study that examined blinded versus unblinded assessments of risk of bias included within a systematic review. DATA COLLECTION AND ANALYSIS: We extracted information from each of the included studies using a pre-specified 16-item form. We summarized the level of agreement between blinded and unblinded assessments of risk of bias descriptively. We calculated the standardized mean difference whenever possible. MAIN RESULTS: We included six randomized controlled trials (RCTs). Four studies had unclear risk of bias and two had high risk of bias. The results of these RCTs were not consistent; two demonstrated no differences between blinded and unblinded assessments, two found that blinded assessments had significantly lower quality scores, and another observed significantly higher quality scores for blinded assessments. The remaining study did not report the level of significance. We pooled five studies reporting sufficient information in a meta-analysis. We observed no statistically significant difference in risk of bias assessments between blinded or unblinded assessments (standardized mean difference -0.13, 95% confidence interval -0.42 to 0.16). The mean difference might be slightly inaccurate, as we did not adjust for clustering in our meta-analysis. We observed inconsistency of results visually and noted statistical heterogeneity. AUTHORS' CONCLUSIONS: Our review highlights that discordance exists between studies examining blinded versus unblinded risk of bias assessments at the systematic review level. The best approach to risk of bias assessment remains unclear, however, given the increased time and resources required to conceal reports effectively, it may not be necessary for risk of bias assessments to be conducted under blinded conditions in a systematic review.

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)0.649
metaresearch head score (Gemma)0.870
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: Methods
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.351
Threshold uncertainty score0.433

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.6490.870
Meta-epidemiology (narrow)0.0040.004
Meta-epidemiology (broad)0.0200.024
Bibliometrics0.0330.027
Science and technology studies0.0030.012
Scholarly communication0.0100.017
Open science0.0070.009
Research integrity0.0080.007
Insufficient payload (model declined to judge)0.0100.002

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 head0.905
GPT teacher head0.631
Teacher spread0.274 · 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 designSystematic review
DomainMethods
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

Citations42
Published2011
Admission routes1
Has abstractyes

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