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Imagine a sports injury researcher claiming: ‘the effect of the injury prevention programme we reported in the trial is unbiased because we analysed according to the intention-to-treat principle’ (ITT). This sounds appealing for clinicians, coaches and athletes. However, before implementing results from such trial, readers should consider whether the athletes in the trial actually complied with the intervention. The appealing message above from the researcher strongly depends on the ‘whereabouts’ of the athletes. Those in the intervention group(s) need to be fully compliant to draw a meaningful conclusion regarding the effect of the intervention.
In studies affected by low compliance, we believe that drawing a conclusion on the effect of an intervention may be misleading as low compliance may bias results if data are analysed according to the ITT principle.1 We encourage clinicians, coaches and athletes to take a sceptical, cautious step back when reading bombastic conclusions in the sports injury literature. Researchers should do their best to deal with low compliance during (1) study design, (2) data collection and (3) when analysing data from sports injury trials. As a part of a BJSM educational series on methods in randomised controlled trials (RCTs), we discuss here an alternative analytical approach to the ITT—‘instrumental variable (IV) analysis’.2
Low compliance is problematic
To illustrate the problem of compliance, we used a data set from an RCT with 40-week follow-up investigating the efficacy of an Athletics Injury Prevention Programme (AIPP) to reduce injury complaints leading to restrictions in athletics participation (PREVATHLE: CPP Ouest II-Angers, number: 2017-A01980-53; ClinicalTrials.gov Identifier: NCT03307434). In this trial, track and field athletes (n=840) were allocated to either a control group (n=391, reference group), who were asked to continue their usual training, or an intervention group (n=449), who were asked to perform the specifically designed AIPP twice a week. Interestingly and thought-provokingly, …
Twitter @PascalEdouard42, @RUNSAFE_Rasmus
Correction notice This article has been corrected since it published Online First. The title, table 1 and the conclusion have all been updated.
Contributors PE: substantial contributions to the conception and design of the project, implementation of the project, data collection, analysis and interpretation of data, drafting, writing and revising of the manuscript and final approval of the version to be published. KS: substantial contributions to the analyses and interpretation of data, writing and revising of the manuscript, and final approval of the version to be published. LN: substantial contributions to interpretation of data, writing, revising of the manuscript and final approval of the version to be published. MAM: substantial contributions to the analyses and interpretation of data, writing and revising of the manuscript, and final approval of the version to be published. RON: substantial contributions to the conception and design of the manuscript, analysis and interpretation of data, drafting, writing and revising of the manuscript, and final approval of the version to be published.
Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.
Competing interests None declared.
Provenance and peer review Not commissioned; internally peer reviewed.
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