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Developing core outcome sets for clinical trials: issues to consider

2012· article· en· 1,685 citations· W2104881646 on OpenAlex· 10.1186/1745-6215-13-132

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A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

Canadian affiliationAn author listed a Canadian institution. This is the only route the usual frame has.

Machine scores (provisional)

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

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.

Opus teacher head0.964
GPT teacher head0.780
Teacher spread
0.183 · how far apart the two teachers sit on this one work
Validation status
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

Abstract

The selection of appropriate outcomes or domains is crucial when designing clinical trials in order to compare directly the effects of different interventions in ways that minimize bias. If the findings are to influence policy and practice then the chosen outcomes need to be relevant and important to key stakeholders including patients and the public, health care professionals and others making decisions about health care. There is a growing recognition that insufficient attention has been paid to the outcomes measured in clinical trials. These issues could be addressed through the development and use of an agreed standardized collection of outcomes, known as a core outcome set, which should be measured and reported, as a minimum, in all trials for a specific clinical area. Accumulating work in this area has identified the need for general guidance on the development of core outcome sets. Key issues to consider in the development of a core outcome set include its scope, the stakeholder groups to involve, choice of consensus method and the achievement of a consensus.

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.

The record

Venue
Trials
Topic
Delphi Technique in Research
Field
Social Sciences
Canadian institutions
Institute of Population and Public HealthUniversity of Ottawa
Funders
Medical Research Council
Keywords
Outcome (game theory)MedicineStakeholderClinical trialScope (computer science)Psychological interventionSet (abstract data type)Core (optical fiber)Health careMEDLINEManagement scienceProcess managementNursingPublic relationsComputer scienceBusinessPolitical science
Has abstract in OpenAlex
yes