Validity and Inter-Rater Reliability Testing of Quality Assessment Instruments [Internet]
Notice bibliographique
Résumé
Background Numerous tools exist to assess methodological quality, or risk of bias in systematic reviews; however, few have undergone extensive reliability or validity testing. Objectives (1) assess the reliability of the Cochrane Risk of Bias (ROB) tool for randomized controlled trials (RCTs) and the Newcastle-Ottawa Scale (NOS) for cohort studies between individual raters, and between consensus agreements of individual raters for the ROB tool; (2) assess the validity of the Cochrane ROB tool and NOS by examining the association between study quality and treatment effect size (ES); (3) examine the impact of study-level factors on reliability and validity. Methods Two reviewers independently assessed risk of bias for 154 RCTs. For a subset of 30 RCTs, two reviewers from each of four Evidence-based Practice Centers assessed risk of bias and reached consensus. Inter-rater agreement was assessed using kappa statistics. We assessed the association between ES and risk of bias using meta-regression. We examined the impact of study-level factors on the association between risk of bias and ES using subgroup analyses. Two reviewers independently applied the NOS to 131 cohort studies from 8 meta-analyses. Inter-rater agreement was calculated using kappa statistics. Within each meta-analysis, we generated a ratio of pooled estimates for each quality domain. The ratios were combined to give an overall estimate of differences in effect estimates with inverse-variance weighting and a random effects model. Results Inter-rater reliability between two reviewers was considered fair for most domains (κ ranging from 0.24 to 0.37), except for sequence generation (κ=0.79, substantial). Inter-rater reliability of consensus assessments across four reviewer pairs was moderate for sequence generation (κ=0.60), fair for allocation concealment and “other sources of bias” (κ=0.37, 0.27), and slight for the remaining domains (κ ranging from 0.05 to 0.09). Inter-rater variability was influenced by study-level factors including nature of outcome, nature of intervention, study design, trial hypothesis, and funding source. Inter-rater variability resulted more often from different interpretation of the tool rather than different information identified in the study reports. No statistically significant differences were found in ES when comparing studies categorized as high, unclear or low risk of bias. Inter-rater reliability of the NOS varied from substantial for length of followup to poor for selection of non-exposed cohort and demonstration that the outcome was not present at outset of study. We found no association between individual NOS items or overall NOS score and effect estimates. Conclusion More specific guidance is needed to apply risk of bias/quality tools. Study-level factors that were shown to influence agreement provide direction for detailed guidance. Low agreement across pairs of reviewers has implications for incorporation of risk of bias into results and grading the strength of evidence. Variable agreement for the NOS, and lack of evidence that it discriminates studies that may provide biased results, underscores the need for more detailed guidance to apply the tool in systematic reviews.
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 | 0,586 | 0,784 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,002 |
| Méta-épidémiologie (sens large) | 0,005 | 0,009 |
| Bibliométrie | 0,016 | 0,015 |
| Études des sciences et des technologies | 0,003 | 0,005 |
| Communication savante | 0,006 | 0,005 |
| Science ouverte | 0,004 | 0,006 |
| Intégrité de la recherche | 0,002 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,001 |
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 ».