Inter-rater reliability of risk of bias tools for non-randomized studies
Bibliographic record
Abstract
Abstract Purpose There is limited knowledge on the reliability of risk of bias (ROB) tools for assessing internal validity in systematic reviews of exposure and frequency studies. We aimed to identify and then compare the inter-rater reliability (IRR) of six commonly used tools for frequency (Loney scale, Gyorkos checklist, American Academy of Neurology [AAN] tool) and exposure (Newcastle–Ottawa scale, SIGN50 checklist, AAN tool) studies. Methods Six raters independently assessed the ROB of 30 frequency and 30 exposure studies using the three respective ROB tools. Articles were rated as low, intermediate, or high ROB. We calculated an intraclass correlation coefficient (ICC) for each tool and category of ROB tool. We compared the IRR between ROB tools and tool type by inspection of overlapping ICC 95% CIs and by comparing their coefficients after transformation to Fisher’s Z values. We assessed the criterion validity of the AAN ROB tools by calculating an ICC for each rater in comparison with the original ratings from the AAN. Results All individual ROB tools had an IRR in the substantial range or higher (ICC point estimates between 0.61 and 0.80). The IRR was almost perfect (ICC point estimate > 0.80) for the AAN frequency tool and the SIGN50 checklist. All tools were comparable in IRR, except for the AAN frequency tool which had a significantly higher ICC than the Gyorkos checklist (p = 0.021) and trended towards a higher ICC when compared to the Loney scale (p = 0.085). When examined by category of ROB tool, scales, and checklists had a substantial IRR, whereas the AAN tools had an almost perfect IRR. For the criterion validity of the AAN ROB tools, the average agreement between our raters and the original AAN ratings was moderate. Conclusion All tools had substantial IRRs except for the AAN frequency tool and the SIGN50 checklist, which both had an almost perfect IRR. The AAN ROB tools were the only category of ROB tools to demonstrate an almost perfect IRR. This category of ROB tools had fewer and simpler criteria. Overall, parsimonious tools with clear instructions, such as those from the AAN, may provide more reliable ROB assessments.
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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 | 0.668 | 0.861 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.012 | 0.025 |
| Bibliometrics | 0.022 | 0.018 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.005 | 0.009 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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.
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".