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Cited by 159Statistical Methods in Clinical TrialsMeta-analysis and systematic reviewsAdvanced Causal Inference Techniques

Bias in identifying and recruiting participants in cluster randomised trials: what can be done?

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Eldridge, S., Kerry, S., Torgerson, D. J·2009·BMJ
DOI 10.1136/bmj.b4006
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Abstract

Blinded recruitment of participants presents particular challenges for cluster trials, but careful design can minimise the risk of selection bias

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Crossref · 10.1136/bmj.b4006

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  • The heterogeneity in cluster definitions reinforces SWD's versatility.

    “This heterogeneity reinforces SWD's versatility, consistent with Eldridge et al. (2019) (117).”

    From Applications and implementation considerations for stepped-wedge designs in sub-Saharan Africa: a systematic review (2026) · cites this paper as [117]

    The Background (p. 5) and trial examples (p. 16) describe different kinds of clusters, including schools, villages, general practices, and health centres. But the paper does not discuss stepped-wedge designs or say that variation in cluster definitions demonstrates their versatility; a search for “stepped wedge” found no relevant passage. (LLM, conf=0.78)

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  • Knowledge of treatment condition at the time of patient recruitment is known to be a risk factor for differential identification and recruitment of participants across treatment arms, unless recruitment and identification are conducted by someone blind to the treatment allocation or the inclusion criteria are broad.

    “Knowledge of treatment condition at the time of patient recruitment is known to be a risk factor for differential identification and recruitment of participants across treatment arms [1,14,16,37], unless recruitment and identification are conducted by someone blind to the treatment allocation or the inclusion criteria are broad [2,11,14].”

    From Cluster randomized trials of individual-level interventions were at high risk of bias (2021) · cites this paper as [11]

    Split into 2 atoms — 1 confirmed, 1 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.

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  • Recruitment and identification biases are a unique source of bias under cluster randomization, with trials being particularly vulnerable to this bias when it is necessary to identify or recruit individuals into the study after randomization.

    “Recruitment and identification biases are a unique source of bias under cluster randomization, with trials being particularly vulnerable to this bias when it is necessary to identify or recruit individuals into the study after randomization [1,11].”

    From Cluster randomized trials of individual-level interventions were at high risk of bias (2021) · cites this paper as [11]

  • Studies such as those by Calum Davey and Badara Cisse illustrate the value of accounting for temporal trends to reduce bias.

    “Studies such as those by Calum Davey (35) and Badara Cisse (34) illustrate the value of accounting for temporal trends to reduce bias, aligning with guidance on SWD's analytical strengths (117).”

    From Applications and implementation considerations for stepped-wedge designs in sub-Saharan Africa: a systematic review (2026) · cites this paper as [117]

    The citation to this paper is attached to the phrase about guidance on stepped-wedge designs’ analytical strengths, rather than to the named studies. The Conclusion (p. 13) discusses preventing recruitment-related selection bias in cluster trials and cautions that analytical solutions may not fully correct it. Searches for stepped-wedge designs and temporal trends found no passage addressing the attributed guidance. (LLM, conf=0.75)

    Experimental — accuracy not yet measured

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Cites

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Research works printed but not linked: 17

  1. 1 Puffer S, Torgerson DJ, Watson J. Evidence for Risk of Bias in Cluster Randomised Trials: A Review of Recent Trials Published in Three General Medical Journals. BMJ 2003; 327 :785
  2. 4 Murray DM. (1998) Design and Analysis of Group-Randomised Trials . Oxford University Press, London.
  3. 8 Sondergaard J, Hansen DG, Aarslev P, Munck AP. A multifaceted intervention according to the Audit Project Odense method improved secondary prevention of ischemic heart disease: a randomised controlled trial. Fam Pract 2006; 23(2):198-202.
  4. 9 HuttonJL Are distinctive ethical principles required for cluster randomised controlled trials? Stat Med 2001; 20:473-88.
  5. 10 Eldridge SM, Ashby D,Feder GS Informed patient consent to participation in cluster randomized trials: an empirical exploration of trials in primary care Clinical Trials 2005;2:91-8
  6. 11 Kannus P, Parkkari J, Niemi S, Pasanen M, Palvanen M, Järvinen M, Vuori I. Prevention of hip fracture in elderly people with use of a hip protector. New England Journal of Medicine 2000;343: 15061513
  7. 12 Hahn S, Puffer S, Torgerson DJ, Watson J. Methodological bias in cluster randomised trials. BMC Medical Research Methodology 2005; 5,10.
  8. 14 Kontiokari T, Sundqvist K, Nuutinen M, Pokka T, Koskela M, Uhari M. Randomised trial of cranberry-lingonberry juice and Lactobacillus GG drink for the prevention of urinary tract infections in women. BMJ 2001;322:1-5
  9. 15 Turk V, Burchell, Burrha S, Corney R, Elliott S, Kerry S, Molloy C, Painter K. An evaluation of the implementation of hand held health records with adults with learning disabilities:A Cluster Randomised Control Trial JARID 2009 in press
  10. 16 Griffiths C, Foster G, Barnes N, Eldridge S, Tate H, Begum S et al. Specialist nurse intervention to reduce unscheduled asthma care in a deprived multiethnic area: the east London randomised controlled trial for high risk asthma (ELECTRA). BMJ 2004; 328(7432):144.
  11. 17 Mohan P, Iyengar SD, Martines J, Cousens S, Sen K. Impact of counselling on careseeking behaviour in families with sick children: cluster randomised trial in rural India. BMJ 2004; 329(7460):266.
  12. 18 King M, Davidson O, Taylor F, Haines A, Sharp D, Turner R. Effectiveness of teaching general practitioners skills in brief cognitive behaviour therapy to treat patients with depression: randomised controlled trial. BMJ 2002;324:947-52.
  13. 19 Borm GF, Melis RJF, Teerenstra S, Peer PG. Pseudo cluster randomization: a treatment allocation method to minimize contamination and selection bias. Statistics in Medicine 2005;24: 3535-3547.
  14. 20 Hewitt CJ, Torgerson DJ, Miles JNV. Taking account of non-compliance in randomised trials. Canadian Medical Association Journal 2006;175:347-48.
  15. 24 Little P, Williamson I, Warner G, Gould C, Gantley M, Kinmonth AL. Open randomised trial of prescribing strategies for sore throat. BMJ 1997;314:722-27.
  16. 25 Kendrick D, Illingworth R, Woods A, Watts K, Collier J, Dewey M, Hapgood R, Chen C. Promoting child safety in primary care: a cluster randomised controlled trial to reduce baby walker use. BJGP 2005;55:582-588
  17. 26 Berger VW. Selection bias and covariate imbalances in randomised clinical trials . (2005) Wiley, Chichester, England.

Cited by

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Authors
Eldridge, S., Kerry, S., & Torgerson, D. J.
Affiliations
  • University of London (GB)
  • St George's, University of London (GB)
  • University of York (GB)
Corresponding author
Torgerson, D. J
ORCID
Venue
BMJ
Publisher
BMJ
Published
2009-10-09
Volume
339
Issue
oct09 1
Pages
b4006-b4006
ISSN
  • 0007-1447 (ISSN-L)
  • 0959-8138
  • 1468-5833
DOI
10.1136/bmj.b4006
OpenAlex
W2037592202
Cited by
159
References
4
Citations by year
2026: 7 · 2025: 13 · 2024: 8 · 2023: 19 · 2022: 10 · 2021: 17 · 2020: 12 · 2019: 10 · 2018: 10 · 2017: 5 · 2016: 6 · 2015: 8 · 2014: 8 · 2013: 10 · 2012: 6
FWCI
4.44
Type
journal article
Language
en
Open access
Locations
  • BMJ (publishedVersion)
  • PubMed (publishedVersion)
  • White Rose Research Online (University of Leeds, The University of Sheffield, University of York) (submittedVersion)
  • DigitalGeorgetown (Georgetown University Library) (submittedVersion)
Topics
  • Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
  • Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
  • Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
Keywords
selection bias, participant recruitment, blinding, recruitment bias, trial design
MeSH terms
Patient Education as Topic, Random Allocation, Bias, Selection Bias, Cluster Analysis, Randomized Controlled Trials as Topic, Patient Selection

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