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Methods used to develop the SPIRIT 2024 and CONSORT 2024 Statements

2024· article· en· W4392284134 on OpenAlexaff
R. Tunn, Isabelle Boutron, An‐Wen Chan, Gary S. Collins, Asbjørn Hróbjartsson, David Moher, Kenneth F. Schulz, Jennifer Anne de Beyer, Camilla Hansen Nejstgaard, Lasse Østengaard, Sally Hopewell

Bibliographic record

VenueJournal of Clinical Epidemiology · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicDelphi Technique in Research
Canadian institutionsOttawa Public HealthOttawa HospitalUniversity of OttawaWomen's College HospitalUniversity of Toronto
FundersMedical Research CouncilNational Institute for Health and Care Research
KeywordsConsolidated Standards of Reporting TrialsMedicineAlternative medicinePathology

Abstract

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OBJECTIVES: To describe, and explain the rationale for, the methods used and decisions made during development of the updated SPIRIT 2024 and CONSORT 2024 reporting guidelines. METHODS: We developed SPIRIT 2024 and CONSORT 2024 together to facilitate harmonization of the two guidelines, and incorporated content from key extensions. We conducted a scoping review of comments suggesting changes to SPIRIT 2013 and CONSORT 2010, and compiled a list of other possible revisions based on existing SPIRIT and CONSORT extensions, other reporting guidelines, and personal communications. From this, we generated a list of potential modifications or additions to SPIRIT and CONSORT, which we presented to stakeholders for feedback in an international online Delphi survey. The Delphi survey results were discussed at an online expert consensus meeting attended by 30 invited international participants. We then drafted the updated SPIRIT and CONSORT checklists and revised them based on further feedback from meeting attendees. RESULTS: We compiled 83 suggestions for revisions or additions to SPIRIT and/or CONSORT from the scoping review and 85 from other sources, from which we generated 33 potential changes to SPIRIT (n = 5) or CONSORT (n = 28). Of 463 participants invited to take part in the Delphi survey, 317 (68%) responded to Round 1, 303 (65%) to Round 2 and 290 (63%) to Round 3. Two additional potential checklist changes were added to the Delphi survey based on Round 1 comments. Overall, 14/35 (SPIRIT n = 0; CONSORT n = 14) proposed changes reached the predefined consensus threshold (≥80% agreement), and participants provided 3580 free-text comments. The consensus meeting participants agreed with implementing 11/14 of the proposed changes that reached consensus in the Delphi and supported implementing a further 4/21 changes (SPIRIT n = 2; CONSORT n = 2) that had not reached the Delphi threshold. They also recommended further changes to refine key concepts and for clarity. CONCLUSION: The forthcoming SPIRIT 2024 and CONSORT 2024 Statements will provide updated, harmonized guidance for reporting randomized controlled trial protocols and results, respectively. The simultaneous development of the SPIRIT and CONSORT checklists has been informed by current empirical evidence and extensive input from stakeholders. We hope that this report of the methods used will be helpful for developers of future reporting guidelines.

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)0.531
metaresearch head score (Gemma)0.759
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 score0.469
Threshold uncertainty score0.578

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.5310.759
Meta-epidemiology (narrow)0.0050.006
Meta-epidemiology (broad)0.0060.010
Bibliometrics0.0280.017
Science and technology studies0.0050.008
Scholarly communication0.0140.010
Open science0.0070.012
Research integrity0.0070.016
Insufficient payload (model declined to judge)0.0300.012

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 head0.767
GPT teacher head0.749
Teacher spread0.018 · 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

Citations39
Published2024
Admission routes1
Has abstractyes

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