Reporting of environmental outcomes in randomised clinical trials: a protocol for a scoping review
Bibliographic record
Abstract
INTRODUCTION: To increase the sustainability of healthcare, clinical trials must assess the environmental impact of interventions alongside clinical outcomes. This should be guided by Standard Protocol Items: Recommendations for Interventional Trials (SPIRIT) and Consolidated Standards of Reporting Trials (CONSORT) extensions, which will be developed by The Implementing Climate and Environmental Outcomes in Trials Group. The objective of the scoping review is to describe the existing methods for reporting and measuring environmental outcomes in randomised trials. The results will be used to inform the future development of the SPIRIT and CONSORT extensions on environmental outcomes (SPIRIT-ICE and CONSORT-ICE). METHODS AND ANALYSIS: This protocol outlines the methodology for a scoping review, which will be conducted in two distinct sections: (1) identifying any existing guidelines, reviews or methodological studies describing environmental impacts of interventions and (2) identifying how environmental outcomes are reported in randomised trial protocols and trial results. A search specialist will search major medical databases, reference lists of trial publications and clinical trial registries to identify relevant publications. Data from the included studies will be extracted independently by two review authors. Based on the results, a preliminary list of items for the SPIRIT and CONSORT extensions will be developed. ETHICS AND DISSEMINATION: This study does not include any human participants, and ethics approval is not required according to the Declaration of Helsinki. The findings from the scoping review will be published in international peer-reviewed journals, and the findings will be used to inform the design of a Delphi survey of relevant stakeholders. OPEN SCIENCE: Registered with Open Science 28 of February 2025.
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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 | 0.334 | 0.384 |
| Meta-epidemiology (narrow) | 0.006 | 0.007 |
| Meta-epidemiology (broad) | 0.010 | 0.014 |
| Bibliometrics | 0.020 | 0.024 |
| Science and technology studies | 0.005 | 0.010 |
| Scholarly communication | 0.012 | 0.013 |
| Open science | 0.007 | 0.011 |
| Research integrity | 0.017 | 0.017 |
| Insufficient payload (model declined to judge) | 0.082 | 0.039 |
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".