Assessment of study quality for systematic reviews: a comparison of the Cochrane Collaboration Risk of Bias Tool and the Effective Public Health Practice Project Quality Assessment Tool: methodological research
Bibliographic record
Abstract
BACKGROUND: The Cochrane Collaboration is strongly encouraging the use of a newly developed tool, the Cochrane Collaboration Risk of Bias Tool (CCRBT), for all review groups. However, the psychometric properties of this tool to date have yet to be described. Thus, the objective of this study was to add information about psychometric properties of the CCRBT including inter-rater reliability and concurrent validity, in comparison with the Effective Public Health Practice Project Quality Assessment Tool (EPHPP). METHODS: Both tools were used to assess the methodological quality of 20 randomized controlled trials included in our systematic review of the effectiveness of knowledge translation interventions to improve the management of cancer pain. Each study assessment was completed independently by two reviewers using each tool. We analysed the inter-rater reliability of each tool's individual domains, as well as final grade assigned to each study. RESULTS: The EPHPP had fair inter-rater agreement for individual domains and excellent agreement for the final grade. In contrast, the CCRBT had slight inter-rater agreement for individual domains and fair inter-rater agreement for final grade. Of interest, no agreement between the two tools was evident in their final grade assigned to each study. Although both tools were developed to assess 'quality of the evidence', they appear to measure different constructs. CONCLUSIONS: Both tools performed quite differently when evaluating the risk of bias or methodological quality of studies in knowledge translation interventions for cancer pain. The newly introduced CCRBT assigned these studies a higher risk of bias. Its psychometric properties need to be more thoroughly validated, in a range of research fields, to understand fully how to interpret results from its application.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.650 | 0.846 |
| Meta-epidemiology (narrow) | 0.005 | 0.005 |
| Meta-epidemiology (broad) | 0.035 | 0.059 |
| Bibliometrics | 0.050 | 0.046 |
| Science and technology studies | 0.004 | 0.011 |
| Scholarly communication | 0.015 | 0.014 |
| Open science | 0.008 | 0.018 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".