Blinded versus unblinded assessments of risk of bias in studies included in a systematic review
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,649 | 0,870 |
| Méta-épidémiologie (sens strict) | 0,004 | 0,004 |
| Méta-épidémiologie (sens large) | 0,020 | 0,024 |
| Bibliométrie | 0,033 | 0,027 |
| Études des sciences et des technologies | 0,003 | 0,012 |
| Communication savante | 0,010 | 0,017 |
| Science ouverte | 0,007 | 0,009 |
| Intégrité de la recherche | 0,008 | 0,007 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,010 | 0,002 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; l’étiquette directe de Gemma et le classifieur distillé Codex s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».