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Record W3158982666 · doi:10.1136/bmjopen-2021-049093

Methods and results used in the development of a consensus-driven extension to the Consolidated Standards of Reporting Trials (CONSORT) statement for trials conducted using cohorts and routinely collected data (CONSORT-ROUTINE)

2021· article· en· W3158982666 on OpenAlexafffund
Mahrukh Imran, Linda Kwakkenbos, Stephen J. McCall, Kimberly A McCord, Ole Fröbert, Lars G. Hemkens, Merrick Zwarenstein, Clare Relton, Danielle B. Rice, Sinéad Langan, Eric I Benchimol, Lehana Thabane, Marion Campbell, Margaret Sampson, David Erlinge, Helena M. Verkooijen, David Moher, Isabelle Boutron, Philippe Ravaud, Jon Nicholl, Rudolf Uher, Maureen Sauvé, John Fletcher, David Torgerson, Chris Gale, Edmund Juszczak, Brett D. Thombs

Bibliographic record

VenueBMJ Open · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicDelphi Technique in Research
Canadian institutionsMcGill University Health CentreMultiple Sclerosis Society of CanadaDalhousie UniversityOttawa HospitalMcMaster UniversityJewish General HospitalUniversity of OttawaImpactChildren's Hospital of Eastern OntarioMcGill UniversityWestern University
FundersCanadian Institutes of Health ResearchNational Institute for Health and Care ResearchMedical Research CouncilCanadian Child Health Clinician Scientist ProgramDepartment of Health and Social CareCanada Research ChairsCanadian Association of GastroenterologySteno Diabetes Center AarhusCrohn's and Colitis CanadaWellcome Trust
KeywordsConsolidated Standards of Reporting TrialsChecklistMedicineDelphi methodStakeholderDelphiFamily medicineGuidelineMedical educationNursingPsychological interventionPsychologyComputer sciencePublic relations

Abstract

fetched live from OpenAlex

OBJECTIVES: Randomised controlled trials conducted using cohorts and routinely collected data, including registries, electronic health records and administrative databases, are increasingly used in healthcare intervention research. A Consolidated Standards of Reporting Trials (CONSORT) statement extension for trials conducted using cohorts and routinely collected data (CONSORT-ROUTINE) has been developed with the goal of improving reporting quality. This article describes the processes and methods used to develop the extension and decisions made to arrive at the final checklist. METHODS: The development process involved five stages: (1) identification of the need for a reporting guideline and project launch; (2) conduct of a scoping review to identify possible modifications to CONSORT 2010 checklist items and possible new extension items; (3) a three-round modified Delphi study involving key stakeholders to gather feedback on the checklist; (4) a consensus meeting to finalise items to be included in the extension, followed by stakeholder piloting of the checklist; and (5) publication, dissemination and implementation of the final checklist. RESULTS: 27 items were initially developed and rated in Delphi round 1, 13 items were rated in round 2 and 11 items were rated in round 3. Response rates for the Delphi study were 92 of 125 (74%) invited participants in round 1, 77 of 92 (84%) round 1 completers in round 2 and 62 of 77 (81%) round 2 completers in round 3. Twenty-seven members of the project team representing a variety of stakeholder groups attended the in-person consensus meeting. The final checklist includes five new items and eight modified items. The extension Explanation & Elaboration document further clarifies aspects that are important to report. CONCLUSION: Uptake of CONSORT-ROUTINE and accompanying Explanation & Elaboration document will improve conduct of trials, as well as the transparency and completeness of reporting of trials conducted using cohorts and routinely collected data.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.427
metaresearch head score (Gemma)0.602
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Reporting · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.573
Threshold uncertainty score0.706

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.4270.602
Meta-epidemiology (narrow)0.0040.003
Meta-epidemiology (broad)0.0030.007
Bibliometrics0.0200.015
Science and technology studies0.0030.004
Scholarly communication0.0080.005
Open science0.0050.008
Research integrity0.0050.007
Insufficient payload (model declined to judge)0.0460.019

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.

Opus teacher head0.856
GPT teacher head0.695
Teacher spread0.161 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designQualitative
DomainReporting
GenreMethods

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".

Quick stats

Citations25
Published2021
Admission routes2
Has abstractyes

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