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Cited by 47Meta-analysis and systematic reviewsStatistical Methods in Clinical TrialsHealth Policy Implementation Science

A systematic review of cluster randomised trials in residential facilities for older people suggests how to improve quality

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Diaz-Ordaz, Karla, Froud, Robert, Sheehan, Bart, Eldridge, Sandra·2013·BMC Medical Research Methodology
DOI 10.1186/1471-2288-13-127PMC PMC4015673
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Abstract

BACKGROUND: Previous reviews of cluster randomised trials have been critical of the quality of the trials reviewed, but none has explored determinants of the quality of these trials in a specific field over an extended period of time. Recent work suggests that correct conduct and reporting of these trials may require more than published guidelines. In this review, our aim was to assess the quality of cluster randomised trials conducted in residential facilities for older people, and to determine whether (1) statistician involvement in the trial and (2) strength of journal endorsement of the Consolidated Standards of Reporting Trials (CONSORT) statement influence quality. METHODS: We systematically identified trials randomising residential facilities for older people, or parts thereof, without language restrictions, up to the end of 2010, using National Library of Medicine (Medline) via PubMed and hand-searching. We based quality assessment criteria largely on the extended CONSORT statement for cluster randomised trials. We assessed statistician involvement based on statistician co-authorship, and strength of journal endorsement of the CONSORT statement from journal websites. RESULTS: 73 trials met our inclusion criteria. Of these, 20 (27%) reported accounting for clustering in sample size calculations and 54 (74%) in the analyses. In 29 trials (40%), methods used to identify/recruit participants were judged by us to have potentially caused bias or reporting was unclear to reach a conclusion. Some elements of quality improved over time but this appeared not to be related to the publication of the extended CONSORT statement for these trials. Trials with statistician/epidemiologist co-authors were more likely to account for clustering in sample size calculations (unadjusted odds ratio 5.4, 95% confidence interval 1.1 to 26.0) and analyses (unadjusted OR 3.2, 1.2 to 8.5). Journal endorsement of the CONSORT statement was not associated with trial quality. CONCLUSIONS: Despite international attempts to improve methods in cluster randomised trials, important quality limitations remain amongst these trials in residential facilities. Statistician involvement on trial teams may be more effective in promoting quality than further journal endorsement of the CONSORT statement. Funding bodies and journals should promote statistician involvement and co-authorship in addition to adherence to CONSORT guidelines.

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  • Others have assessed about 40% of cluster trials to be at risk of these types of biases; and sometimes this has been reported to be somewhat lower despite including many trials with post randomization recruitment.

    “Others have assessed about 40% of cluster trials to be at risk of these types of biases [2,7,28]; and sometimes this has been reported to be somewhat lower despite including many trials with post randomization recruitment [10,13].”

    From Cluster randomized trials of individual-level interventions were at high risk of bias (2021) · cites this paper as [7]

    The Results > Trial quality section (page unavailable) reports possible identification/recruitment bias in 5 of 73 trials (7%), with another 24 (33%) classified as unclear; the paper’s 40% figure combines those categories. Its Methods > Analysis section says cluster trials often recruit participants after randomisation, but the cited passages do not establish that many trials in this review did so. Thus the lower assessed proportion is supported, but the post-randomisation-recruitment qualification is not established for this review. (LLM, conf=0.83)

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  • Cluster-randomized designs are known to be at increased risk of bias compared to the individually randomized design.

    “Cluster-randomized designs are known to be at increased risk of bias compared to the individually randomized design [1], [2], [7], [10], [13], [16], [28], [37].”

    From Cluster randomized trials of individual-level interventions were at high risk of bias (2021) · cites this paper as [7]

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Research works printed but not linked: 1

  1. Spillman BC Lubitz J New estimates of lifetime nursing home use: have patterns of use changed? Med Care 2002 13 10 965 975 12395029

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Authors
Diaz-Ordaz, K., Froud, R., Sheehan, B., & Eldridge, S.
Affiliations
  • Queen Mary University of London (GB)
  • John Radcliffe Hospital (GB)
  • University of London (GB)
ORCID
Venue
BMC Medical Research Methodology
Publisher
Springer Science and Business Media LLC
Published
2013-10-22
Volume
13
Issue
1
Pages
127-127
ISSN
1471-2288 (ISSN-L)
DOI
10.1186/1471-2288-13-127
PMC
PMC4015673
OpenAlex
W2112655450
Cited by
47
References
36
Citations by year
2025: 1 · 2024: 2 · 2023: 1 · 2022: 5 · 2021: 7 · 2020: 4 · 2019: 2 · 2018: 6 · 2017: 9 · 2016: 4 · 2015: 3 · 2014: 3
FWCI
0.68
Type
journal article
Language
en
Open access
Licence
Locations
  • BMC Medical Research Methodology (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Warwick Research Archive Portal (University of Warwick) (acceptedVersion)
  • LSHTM Research Online (London School of Hygiene and Tropical Medicine) (acceptedVersion)
  • Queen Mary Research Online (Queen Mary University of London) (submittedVersion, cc-by)
Funders
National Institute for Health and Care Research
Topics
  • Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
  • Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
  • Health Sciences › Health Professions › General Health Professions › Health Policy Implementation Science
Keywords
trial quality, CONSORT statement, nursing homes, older adults
MeSH terms
Data Interpretation, Statistical, Homes for the Aged, Humans, Cluster Analysis, Randomized Controlled Trials as Topic, Research Report, Quality Improvement

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