The ROBINS‐I and the NOS had similar reliability but differed in applicability: A random sampling observational studies of systematic reviews/meta‐analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: There is a lack of evidence on the usage of the quality assessment tool-the Risk Of Bias In Nonrandomized Studies-of Interventions (ROBINS-I). This article aimed to measure the reliability, criterion validity, and feasibility of the ROBINS-I and the Newcastle-Ottawa Scale (NOS). METHODS: A sample of systematic reviews or meta-analyses of observational studies were selected from Medline (2013-2017) and assessed by two reviewers using ROBINS-I and the NOS. We reported on reliability in terms of the first-order agreement coefficient (AC1) statistic. Correlation coefficient statistic was used to explore the criterion validity of the ROBINS-I. We compared the feasibility of the ROBINS-I and NOS by recording the time to complete an assessment and the instances where assessing was difficult. RESULTS: Five systematic reviews containing 41 cohort studies were finally included. Interobserver agreement on the individual domain of the ROBINS-I as well as the NOS was substantial with a mean AC1 statistic of 0.67 (95% CI: 0.50-0.83) and 0.73 (95% CI: 0.65-0.81), respectively. The criterion validity of the ROBNS-I was moderate (K = 0.52) against NOS. The time in assessing a single study by ROBINS-I varied from 7 hours initially to 3 hours compared with 30 minutes for the NOS. Both reviewers rated "bias due to departure from the intended interventions" the most time-consuming domain in the ROBINS-I, items in the NOS were equal. CONCLUSIONS: The ROBINS-I and the NOS seem to provide the same reliability but vary in applicability. The over-complicated feature of ROBINS-I may limit its usage and a simplified version is needed.
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Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Metaresearch Domain: Methods · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | Metaresearch Domain: Methods · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | high |
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.572 | 0.692 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.066 | 0.021 |
| Bibliometrics | 0.001 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.004 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 it