Evidence map›Paper›PMID 35505551›Full record

ReviewWorld neurosurgery2022

Stepped Wedge Cluster Randomized Trials: A Methodological Overview.

Fan Li, Rui Wang

Open access · greenAbstract readReview
In one paragraph

Review in World neurosurgery, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
5.4field-weighted citation impact, top 3% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

21 citing papers in PubMed, 34 citations in OpenAlex.

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  18. Generalizing the information content for stepped wedge designs: A marginal modeling approach.Scandinavian journal of statistics, theory and applications · 2023
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors at 2 institutions in 1 country.

Fan LiDepartment of Biostatistics, Yale University School of Public Health, New Haven, Connecticut, USA; Center for Methods in Implementation and Prevention Science, Yale University, New Haven, Connecticut, USA.
Rui WangDepartment of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts, USA; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA. Electronic address: rwang@hsph.harvard.edu.
Harvard Pilgrim Health Care · USYale University · US

Funding

Network modeling and robust estimation of the intraclass correlation coefficient to inform the design and analysis of cluster randomized trials for infectious diseasesR01AI136947 · NIAID · HARVARD PILGRIM HEALTH CARE, INC. · PI WANG, RUI · 2018 to 2020
$759k
NIAID NIH HHS R01 AI136947
6 · The paper itself

Abstract

backgroundStepped wedge cluster randomized trials enable rigorous evaluations of health intervention programs in pragmatic settings. In the present study, we aimed to update neurosurgeon scientists on the design of stepped wedge randomized trials.

methodsWe have presented an overview of recent methodological developments for stepped wedge designs and included an update on the newer associated methodological tools to aid with future study designs.

resultsWe defined the stepped wedge trial design and reviewed the indications for the design in depth. In addition, key considerations, including mainstream methods of analysis and sample size determination, were discussed.

conclusionsStepped wedge designs can be attractive for study intervention programs aiming to improve the delivery of patient care, especially when examining a small number of heterogeneous clusters.

Indexed as

Research DesignHumansRandomized Controlled Trials as TopicSample SizeCluster randomized trialsIntraclass correlation coefficientMethodological reviewSample size determinationStatistical softwareStepped wedge design

Identifiers

PMID35505551
PMCPMC9074087
OpenAlexW4225130161

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.