Improving the reporting of randomised pilot and feasibility studies: a consort statement extension
Bibliographic record
Abstract
Pilot and feasibility studies underpin much of current health related research, including randomised controlled trials. The number of reports in which authors describe their studies as pilot or feasibility studies is increasing and there is currently a lot of interest in this area. However, in spite of a number of papers that have recommended ways in which the reporting of these studies could be improved, reporting remains poor. Using CONSORT endorsed methodology including a large Delphi study (n=93) and an international consensus meeting (n=26) we have developed a CONSORT extension for randomised pilot and feasibility studies. Much of the existing CONSORT statement for randomised controlled trials does apply to these types of study. However, sometimes the application of the items is different from that in RCTs designed to evaluate the effect of an intervention or therapy and some CONSORT items are not applicable or have needed some alteration. We are currently writing the explanation and elaboration statement for this CONSORT extension. We will present the major issues in reporting these types of randomised studies and use examples to illustrate good and bad practice. This work is part of a larger programme of work on pilot and feasibility studies.
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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 | 0.822 | 0.860 |
| Meta-epidemiology (narrow) | 0.004 | 0.006 |
| Meta-epidemiology (broad) | 0.006 | 0.015 |
| Bibliometrics | 0.013 | 0.015 |
| Science and technology studies | 0.005 | 0.011 |
| Scholarly communication | 0.009 | 0.015 |
| Open science | 0.005 | 0.014 |
| Research integrity | 0.010 | 0.019 |
| Insufficient payload (model declined to judge) | 0.012 | 0.006 |
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".