Improving the reporting of randomised pilot and feasibility studies: a consort statement extension
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
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.
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 | 0.156 | 0.256 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it