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ARTICLES:
Rebecca Muckelbauer, Lars Libuda, Kerstin Clausen, André Michael Toschke, Thomas Reinehr, and Mathilde Kersting
Promotion and Provision of Drinking Water in Schools for Overweight Prevention: Randomized, Controlled Cluster Trial
Pediatrics 2009; 123: e661-e667 [Abstract] [Full text] [PDF]
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[Read eLetters] Random sampling alone does not make a randomized trial
Bruno Giraudeau, Philippe Ravaud   (23 April 2009)

Random sampling alone does not make a randomized trial 23 April 2009
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Bruno Giraudeau,
Biostatistician
INSERM, CIC 202, Tours, France; Université François Rabelais, Tours, France; CHRU de Tours, Tours, F,
Philippe Ravaud

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Re: Random sampling alone does not make a randomized trial

giraudeau{at}med.univ-tours.fr Bruno Giraudeau, et al.

We read with great interest the article by Muckelbauer et al (1), in which the authors assessed whether a combined environmental and educational intervention (aimed at promoting water consumption) reduced the prevalence of overweight among children in elementary schools. The authors claimed that their study was a “randomized, controlled cluster trial” including 32 elementary schools (defined as the cluster units), for a total of 2950 children. However, a scrutiny of this paper led us to wonder why the authors claimed that this trial was randomized, and we think the title is misleading for Pediatrics readers.

The authors indeed specified that “randomization was performed at the city level,” but actually, only two cities were considered. Even for a cluster randomized trial, the number of randomized units has to be higher. Readers may also be confused by the school selection process the authors used. Indeed a random sample of schools from each city was selected to be included in the study. However in a randomized trial, randomization is defined as “the process of randomly allocating participants into one of the arms of a controlled trial,” (2) not as the process of selection of participants. At the end, the authors’ “randomized trial” is really a non- randomized controlled study: “[a] quantitative study estimating the effectiveness of an intervention (harm or benefit) that does not use randomisation to allocate units to comparison groups” (2). In that sense, Figure 1, which does not depict randomization, is accurate. The level of evidence of such a design is somewhat different from the level of evidence of a randomized trial, and at least, authors should have discussed this point as a limitation of their study.

To design the study as a cluster randomized trial, schools should have been randomly allocated to the intervention or the control group, after considering the city as a stratification factor. Such an approach was already used by James et al (3) in conducting a similar study. Doing so may also have prevented schools from declining participation, because consent of the school’s guardians would have been sought before the schools they were in charge of were randomized. As pointed out recently (4), such an approach is essential to prevent post-randomization withdrawal of clusters, which inevitably leads to discarding these clusters for the statistical analysis and thus induces selection bias.

1. Muckelbauer R, Libuda L, Clausen K, Toschke AM, Reinehr T, Kersting M. Promotion and provision of drinking water in schools for overweight prevention: randomized, controlled cluster trial. Pediatrics 2009;123(4):e661-7. 2. Green S, Higgins J, editors (2005) Glossary. Cochrane handbook for systematic reviews of interventions 4.2.5. Available: http://www.cochrane.org/resources/glossary.htm. Accessed 22 April 2009. 3. James J, Thomas P, Cavan D, Kerr D. Preventing childhood obesity by reducing consumption of carbonated drinks: cluster randomised controlled trial. BMJ 2004;328(7450):1237. 4. Giraudeau B, Ravaud P. Preventing bias in cluster randomised trials. PLoS Med 2009;6(5):e1000065.

Bruno Giraudeau INSERM, CIC 202, Tours, France Université François Rabelais, Tours, France CHRU de Tours, Tours, France INSERM, U738, Paris, France

and

Philippe Ravaud Assistance Publique–Hôpitaux de Paris, Hôpital Bichat, Département d’Epidémiologie, Biostatistique et Recherche Clinique, Paris, France, Université Paris 7–Denis Diderot, Paris, France INSERM, U738, Paris, France

Conflict of Interest:

None declared