Core Outcome Measures in Effectiveness Trials (COMET) initiative: protocol for an international Delphi study to achieve consensus on how to select outcome measurement instruments for outcomes included in a ‘core outcome set’
Bibliographic record
Abstract
BACKGROUND: The Core Outcome Measures in Effectiveness Trials (COMET) initiative aims to facilitate the development and application of 'core outcome sets' (COS). A COS is an agreed minimum set of outcomes that should be measured and reported in all clinical trials of a specific disease or trial population. The overall aim of the Core Outcome Measurement Instrument Selection (COMIS) project is to develop a guideline on how to select outcome measurement instruments for outcomes included in a COS. As part of this project, we describe our current efforts to achieve a consensus on the methods for selecting outcome measurement instruments for outcomes to be included in a COS. METHODS/DESIGN: A Delphi study is being performed by a panel of international experts representing diverse stakeholders with the intention that this will result in a guideline for outcome measurement instrument selection. Informed by a literature review, a Delphi questionnaire was developed to identify potentially relevant tasks on instrument selection. The Delphi study takes place in a series of rounds. In the first round, panelists were asked to rate the importance of different tasks in the selection of outcome measurement instruments. They were encouraged to justify their choices and to add other relevant tasks. Consensus was reached if at least 70% of the panelists considered a task 'highly recommended' or 'desirable' and if no opposing arguments were provided. These tasks will be included in the guideline. Tasks that at least 50% of the panelists considered 'not relevant' will be excluded from the guideline. Tasks that were indeterminate will be taken to the second round. All responses of the first round are currently being aggregated and will be fed back to panelists in the second round. A third round will only be performed if the results of the second round require it. DISCUSSION: Since the Delphi method allows a large group of international experts to participate, we consider it to be the preferred consensus-based method for our study. Based upon this consultation process, a guideline will be developed on instrument selection for outcomes to be included in a COS.
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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 | 0.346 | 0.269 |
| Meta-epidemiology (narrow) | 0.005 | 0.004 |
| Meta-epidemiology (broad) | 0.005 | 0.007 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.006 | 0.009 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.006 | 0.011 |
| Research integrity | 0.009 | 0.015 |
| Insufficient payload (model declined to judge) | 0.050 | 0.019 |
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".