MétaCan
Menu
← Back to cohort
Record W4212880558 · doi:10.21203/rs.3.rs-133475/v1

Prevalence and Methodological Characteristics of Subgroup Analyses in Stepped Wedge Cluster Randomised Trials: Protocol for a Systematic Review

2020· review· en· W4212880558 on OpenAlexafffund
Évèhouénou Lionel Adisso, Monica Taljaard, Louis‐Paul Rivest, Hervé Tchala Vignon Zomahoun, Pierre Durand, France Légaré

Bibliographic record

VenueResearch Square · 2020
Typereview
Languageen
FieldDecision Sciences
TopicMeta-analysis and systematic reviews
Canadian institutionsUniversity of OttawaUniversité Laval
FundersFonds de Recherche du Québec - SantéCanadian Institutes of Health ResearchUniversité Laval
KeywordsChecklistSubgroup analysisCINAHLSystematic reviewMedicineMEDLINECochrane LibraryPsycINFOProtocol (science)Psychological interventionClinical trialRandomized controlled trialFamily medicineMeta-analysisMedical physicsPsychologyAlternative medicinePathologyNursing

Abstract

fetched live from OpenAlex

Abstract Background: The stepped wedge cluster randomised trial is an increasingly common trial design. The design can be useful for informing real-world clinical decision-making, including decisions about the effectiveness of interventions in particular subgroups. However, there is little existing guidance about how to perform subgroup analyses in the stepped wedge design. We aim to determine the prevalence of subgroup analyses and describe statistical methods used to perform them in stepped wedge cluster randomised trials.Methods: We will conduct a systematic review following the methodology recommended in the Cochrane Handbook for Systematic Reviews of Interventions. We report this protocol according to the PRISMA-P checklist. The protocol has been registered in the Open Science Framework. We will search for terms related to ‘stepped wedge’. Sources will be PubMed, Embase, PsycINFO, Web of Science, CINAHL, Cochrane Library, and Current Controlled Trials Register up to 16 October 2020. Studies will be eligible if they are written in English, involve human participants and are primary or secondary reports of planned or completed stepped wedge cluster randomised trials. Two reviewers will first screen the titles and abstracts, then full texts, to select studies that should be included in the review. Disagreements will be solved by consensus through discussion with a third reviewer. We will extract data related to study characteristics including presence or absence of subgroup analyses, characteristics of subgroup variables examined, statistical methods used to perform subgroup analyses, and adherence to the most consistently recommendations suggested for subgroup analyses in general including in clinical trials. We will perform a qualitative synthesis of the extracted data.Discussion: This protocol offers a reproducible and transparent procedure for a systematic review of the literature. It will provide a portrait of the frequency and types of subgroup analyses performed in stepped wedge cluster randomised trials. These results will inform the development of recommendations for subgroup analyses in such trials.Systematic review registration: This protocol has been registered on Open Science Framework, Registration ID: https://osf.io/2kwrz.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmaMetaresearch
Domain: Methods · Genre: Protocol
About the Canadian research system: no · About a Canadian topic: no
Systematic reviewhigh
gptMetaresearch
Domain: Methods · Genre: Protocol
About the Canadian research system: no · About a Canadian topic: no
Systematic reviewmedium
models agreeAgreement compares identical category sets and study designs across arms.

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)0.259
metaresearch head score (Gemma)0.444
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (broad)
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.979
Threshold uncertainty score0.914

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2590.444
Meta-epidemiology (narrow)0.0070.007
Meta-epidemiology (broad)0.0210.027
Bibliometrics0.0170.019
Science and technology studies0.0040.009
Scholarly communication0.0090.012
Open science0.0060.008
Research integrity0.0120.012
Insufficient payload (model declined to judge)0.0440.010

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 head0.962
GPT teacher head0.747
Teacher spread0.215 · 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

Labeled directly by 2 models reading the full record.

Study designSystematic review
DomainMethods
GenreProtocol

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

Citations0
Published2020
Admission routes2
Has abstractyes

Explore more

Same venueResearch Square→Same topicMeta-analysis and systematic reviews→CategoryMetaresearch→French-language works237,207→