CONSORT 2010 statement: extension checklist for reporting within person randomised trials
Bibliographic record
Abstract
Evidence shows that the quality of reporting of randomised controlled trials (RCTs) is not optimal. The lack of transparent reporting impedes readers from judging the reliability and validity of trial findings and researchers from extracting information for systematic reviews and results in research waste. The Consolidated Standards of Reporting Trials (CONSORT) statement was developed to improve the reporting of RCTs. Within person trials are used for conditions that can affect two or more body sites, and are a useful and efficient tool because the comparisons between interventions are within people. Such trials are most commonly conducted in ophthalmology, dentistry, and dermatology. The reporting of within person trials has, however, been variable and incomplete, hindering their use in clinical decision making and by future researchers. This document presents the CONSORT extension to within person trials. It aims to facilitate the reporting of these trials. It extends 16 items of the CONSORT 2010 checklist and introduces a modified flowchart and baseline table to enhance transparency. Examples of good reporting and evidence based rationale for CONSORT within person checklist items are provided.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.625 | 0.734 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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; both teacher heads 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".