Accuracy in detecting inadequate research reporting by early career peer reviewers using an online CONSORT-based peer-review tool (COBPeer) versus the usual peer-review process: a cross-sectional diagnostic study
Bibliographic record
Abstract
BACKGROUND: The peer review process has been questioned as it may fail to allow the publication of high-quality articles. This study aimed to evaluate the accuracy in identifying inadequate reporting in RCT reports by early career researchers (ECRs) using an online CONSORT-based peer-review tool (COBPeer) versus the usual peer-review process. METHODS: We performed a cross-sectional diagnostic study of 119 manuscripts, from BMC series medical journals, BMJ, BMJ Open, and Annals of Emergency Medicine reporting the results of two-arm parallel-group RCTs. One hundred and nineteen ECRs who had never reviewed an RCT manuscript were recruited from December 2017 to January 2018. Each ECR assessed one manuscript. To assess accuracy in identifying inadequate reporting, we used two tests: (1) ECRs assessing a manuscript using the COBPeer tool (after completing an online training module) and (2) the usual peer-review process. The reference standard was the assessment of the manuscript by two systematic reviewers. Inadequate reporting was defined as incomplete reporting or a switch in primary outcome and considered nine domains: the eight most important CONSORT domains and a switch in primary outcome(s). The primary outcome was the mean number of domains accurately classified (scale from 0 to 9). RESULTS: The mean (SD) number of domains (0 to 9) accurately classified per manuscript was 6.39 (1.49) for ECRs using COBPeer versus 5.03 (1.84) for the journal's usual peer-review process, with a mean difference [95% CI] of 1.36 [0.88-1.84] (p < 0.001). Concerning secondary outcomes, the sensitivity of ECRs using COBPeer versus the usual peer-review process in detecting incompletely reported CONSORT items was 86% [95% CI 82-89] versus 20% [16-24] and in identifying a switch in primary outcome 61% [44-77] versus 11% [3-26]. The specificity of ECRs using COBPeer versus the usual process to detect incompletely reported CONSORT domains was 61% [57-65] versus 77% [74-81] and to identify a switch in primary outcome 77% [67-86] versus 98% [92-100]. CONCLUSIONS: Trained ECRs using the COBPeer tool were more likely to detect inadequate reporting in RCTs than the usual peer review processes used by journals. Implementing a two-step peer-review process could help improve the quality of reporting. TRIAL REGISTRATION: Clinical.Trials.gov NCT03119376 (Registered April, 18, 2017).
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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 | 0.574 | 0.835 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.005 | 0.008 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.003 | 0.002 |
| 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 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".