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Quality of stepped-wedge trial reporting can be reliably assessed using an updated CONSORT: crowd-sourcing systematic review.

Publication ,  Journal Article
Hemming, K; Carroll, K; Thompson, J; Forbes, A; Taljaard, M; SW-CRT Review Group,
Published in: J Clin Epidemiol
March 2019

OBJECTIVES: The Consolidated Standards of Reporting Trials extension for the stepped-wedge cluster randomized trial (SW-CRT) is a recently published reporting guideline for SW-CRTs. We assess the quality of reporting of a recent sample of SW-CRTs. STUDY DESIGN AND SETTING: Quality of reporting was asssessed according to the 26 items in the new guideline using a novel crowd sourcing methodology conducted independently and in duplicate, with random assignment, by 50 reviewers. We assessed reliability of the quality assessments, proposing this as a novel way to assess robustness of items in reporting guidelines. RESULTS: Several items were well reported. Some items were very poorly reported, including several items that have unique requirements for the SW-CRT, such as the rationale for use of the design, description of the design, identification and recruitment of participants within clusters, and concealment of cluster allocation (not reported in more than 50% of the reports). Agreement across items was moderate (median percentage agreement was 76% [IQR 64 to 86]). Agreement was low for several items including the description of the trial design and why trial ended or stopped for example. CONCLUSIONS: When reporting SW-CRTs, authors should pay particular attention to ensure clear reporting on the exact format of the design with justification, as well as how clusters and individuals were identified for inclusion in the study, and whether this was done before or after randomization of the clusters, which are crucial for risk of bias assessments. Some items, including why the trial ended, might either not be relevant to SW-CRTs or might be unclearly described in the statement.

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Published In

J Clin Epidemiol

DOI

EISSN

1878-5921

Publication Date

March 2019

Volume

107

Start / End Page

77 / 88

Location

United States

Related Subject Headings

  • Systematic Reviews as Topic
  • Research Design
  • Randomized Controlled Trials as Topic
  • Humans
  • Epidemiology
  • Crowdsourcing
  • Cluster Analysis
  • 4202 Epidemiology
  • 11 Medical and Health Sciences
  • 01 Mathematical Sciences
 

Citation

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MLA
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Hemming, K., Carroll, K., Thompson, J., Forbes, A., Taljaard, M., & SW-CRT Review Group, . (2019). Quality of stepped-wedge trial reporting can be reliably assessed using an updated CONSORT: crowd-sourcing systematic review. J Clin Epidemiol, 107, 77–88. https://doi.org/10.1016/j.jclinepi.2018.11.017
Hemming, Karla, Kelly Carroll, Jennifer Thompson, Andrew Forbes, Monica Taljaard, and Monica SW-CRT Review Group. “Quality of stepped-wedge trial reporting can be reliably assessed using an updated CONSORT: crowd-sourcing systematic review.J Clin Epidemiol 107 (March 2019): 77–88. https://doi.org/10.1016/j.jclinepi.2018.11.017.
Hemming K, Carroll K, Thompson J, Forbes A, Taljaard M, SW-CRT Review Group. Quality of stepped-wedge trial reporting can be reliably assessed using an updated CONSORT: crowd-sourcing systematic review. J Clin Epidemiol. 2019 Mar;107:77–88.
Hemming, Karla, et al. “Quality of stepped-wedge trial reporting can be reliably assessed using an updated CONSORT: crowd-sourcing systematic review.J Clin Epidemiol, vol. 107, Mar. 2019, pp. 77–88. Pubmed, doi:10.1016/j.jclinepi.2018.11.017.
Hemming K, Carroll K, Thompson J, Forbes A, Taljaard M, SW-CRT Review Group. Quality of stepped-wedge trial reporting can be reliably assessed using an updated CONSORT: crowd-sourcing systematic review. J Clin Epidemiol. 2019 Mar;107:77–88.
Journal cover image

Published In

J Clin Epidemiol

DOI

EISSN

1878-5921

Publication Date

March 2019

Volume

107

Start / End Page

77 / 88

Location

United States

Related Subject Headings

  • Systematic Reviews as Topic
  • Research Design
  • Randomized Controlled Trials as Topic
  • Humans
  • Epidemiology
  • Crowdsourcing
  • Cluster Analysis
  • 4202 Epidemiology
  • 11 Medical and Health Sciences
  • 01 Mathematical Sciences