Use of the CONSORT Statement and Quality of Reports of Randomized Trials
Bibliographic record
Abstract
CONTEXT: The Consolidated Standards for Reporting of Trials (CONSORT) statement was developed to help improve the quality of reports of randomized controlled trials (RCTs). To date, a paucity of data exists regarding whether it has achieved this goal. OBJECTIVE: To determine whether use of the CONSORT statement is associated with improvement in the quality of reports of RCTs. DESIGN AND SETTING: Comparative before-and-after evaluation in which reports of RCTs published in 1994 (pre-CONSORT) were compared with RCT reports from the same journals published in 1998 (post-CONSORT). We included 211 reports from BMJ, JAMA, and The Lancet (journals that adopted CONSORT) as well as The New England Journal of Medicine (a journal that did not adopt CONSORT and was used as a comparator). MAIN OUTCOME MEASURES: Number of CONSORT items included in a report, frequency of unclear reporting of allocation concealment, and overall trial quality score based on the Jadad scale, a 5-point quality assessment instrument. RESULTS: Compared with 1994, the number of CONSORT checklist items in reports of RCTs increased in all 4 journals in 1998, and this increase was statistically significant for the 3 adopter journals (pre-CONSORT, 23.4; mean change, 3.7; 95% confidence interval [CI], 2.1-5.3). The frequency of unclear reporting of allocation concealment decreased for each of the 4 journals, and this change was statistically significant for adopters (pre-CONSORT, 61%; mean change, -22%; 95% CI, -38% to -6%). Similarly, 3 of the 4 journals showed an improvement in the quality score for reports of RCTs, and this increase was statistically significant for adopter journals overall (pre-CONSORT, 2.7; mean change, 0.4; 95% CI, 0.1-0.8). CONCLUSION: Use of the CONSORT statement is associated with improvements in the quality of reports of RCTs.
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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 | 0.640 | 0.798 |
| Meta-epidemiology (narrow) | 0.004 | 0.005 |
| Meta-epidemiology (broad) | 0.013 | 0.013 |
| Bibliometrics | 0.032 | 0.035 |
| Science and technology studies | 0.005 | 0.016 |
| Scholarly communication | 0.017 | 0.011 |
| Open science | 0.010 | 0.012 |
| Research integrity | 0.016 | 0.026 |
| Insufficient payload (model declined to judge) | 0.009 | 0.007 |
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".