Effect of editors' implementation of CONSORT guidelines on the reporting of abstracts in high impact medical journals: interrupted time series analysis
Bibliographic record
Abstract
OBJECTIVE: To investigate the effect of the CONSORT for Abstracts guidelines, and different editorial policies used by five leading general medical journals to implement the guidelines, on the reporting quality of abstracts of randomised trials. DESIGN: Interrupted time series analysis. SAMPLE: We randomly selected up to 60 primary reports of randomised trials per journal per year from five high impact, general medical journals in 2006-09, if indexed in PubMed with an electronic abstract. We excluded reports that did not include an electronic abstract, and any secondary trial publications or economic analyses. We classified journals in three categories: those not mentioning the guidelines in their instructions to authors (JAMA and New England Journal of Medicine), those referring to the guidelines in their instructions to authors but with no specific policy to implement them (BMJ), and those referring to the guidelines in their instructions to authors with an active policy to implement them (Annals of Internal Medicine and Lancet). Two authors extracted data independently using the CONSORT for Abstracts checklist. MAIN OUTCOME: Mean number of CONSORT items reported in selected abstracts, among nine items reported in fewer than 50% of the abstracts published across the five journals in 2006. RESULTS: We assessed 955 reports of abstracts of randomised trials. Journals with an active policy to enforce the guidelines showed an immediate increase in the level of mean number of items reported (increase of 1.50 items; P=0.0037). At 23 months after publication of the guidelines, the mean number of items reported per abstract for the primary outcome was 5.41 of nine items, a 53% increase compared with the expected level estimated on the basis of pre-intervention trends. The change in level or trend did not increase in journals with no policy to enforce the guidelines (BMJ, JAMA, and New England Journal of Medicine). CONCLUSION: Active implementation of the CONSORT for Abstracts guidelines by journals can lead to improvements in the reporting of abstracts of randomised trials.
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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 | 0.657 | 0.894 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.015 |
| Bibliometrics | 0.007 | 0.014 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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".