Mixed-methods study to develop extensions to the SPIRIT and CONSORT statements for factorial randomised trials: the Reporting Factorial Trials (RAFT) study
Bibliographic record
Abstract
BACKGROUND: Extensions to Standard Protocol Items: Recommendations for Interventional Trials (SPIRIT) and Consolidated Standards of Reporting Trials (CONSORT) reporting recommendations specifically for factorial trials have been developed by the Reporting Factorial Trials (RAFT) study group. This article describes the processes and methods used to develop the extensions. OBJECTIVE: To develop SPIRIT and CONSORT extensions for factorial trials. DESIGN AND PARTICIPANTS: A four-phase, consensus-based approach was used: phase 1: scoping review, phase 2: Delphi survey (n=104 respondents in round 1), phase 3: consensus meeting (n=15 members) and phase 4: checklist finalisation. RESULTS: In phase 1, the scoping review identified 31 reporting recommendations, which formed a long list of 50 concepts (19 applied to the SPIRIT extension and 31 applied to the CONSORT extension) to include in the guideline development. In phase 2, a three-round Delphi survey resulted in two new concepts being added and ended with 49 concepts (19 applied to SPIRIT and 30 applied to CONSORT) reaching consensus to remain, with only three concepts meeting the exclusion criteria. In phase 3, the concepts were further refined and translated into specific extension item wording, through an extensive review process conducted by the core RAFT team and leading trial experts, who attended a 2-day hybrid meeting. The resulting 9 SPIRIT items and 17 CONSORT items were further evaluated and developed through an iterative process in phase 4, to promote user acceptance and uptake. CONCLUSION: Uptake of the CONSORT and SPIRIT extensions will improve the conduct of factorial trials, as well as understanding and interpretation of such trials. By reporting on how these extensions were developed, we promote transparency of this process and share learning experiences to develop best practice when developing reporting guidelines.
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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 | 0.488 | 0.587 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.011 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.013 | 0.003 |
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".