A Method by Which to Assess the Scalability of Field-Based Fitness Tests of Cardiorespiratory Fitness Among Schoolchildren

Sarah Domone, Steven Mann, Gavin Sandercock, Matthew Wade, Chris Beedie

Previous research has reported the validity and reliability of a range of field-based tests of children's cardiorespiratory fitness. These two criteria are critical in ensuring the integrity and credibility of data derived through such tests. However, the criterion of scalability has received little attention. Scalability determines the degree to which tests developed on small samples in controlled settings might demonstrate real-world value, and is of increasing interest to policymakers and practitioners. The present paper proposes a method by which the scalability of cardiorespiratory field-based tests suitable for school-aged children might be assessed. We developed an algorithm to estimate scalability based on a six-component model; delivery, evidence of operating at scale, effectiveness, costs, resource requirements and practical implementation. We tested the algorithm on data derived through a systematic review of research that has used relevant fitness tests. A total of 229 studies that had used field based cardiorespiratory fitness tests to measure children's fitness were identified. Initial analyses indicated that the 5-min run test did not meet accepted criteria for reliability, whilst the 6-min walk test likewise failed to meet the criteria for validity. Of the remainder, a total of 28 studies met the inclusion criteria, 22 reporting the 20-m shuttle-run and seven the 1-mile walk/run. Using the scalability algorithm we demonstrate that the 20-m shuttle run test is substantially more scalable than the 1-mile walk/run test, with tests scoring 34/48 and 25/48, respectively. A comprehensive analysis of scalability was prohibited by the widespread non-reporting of data, for example, those relating to cost-effectiveness. Of all sufficiently valid and reliable candidate tests identified, using our algorithm the 20-m shuttle run test was identified as the most scalable. We hope that the algorithm will prove useful in the examination of scalability in either new data relating to existing tests or in data pertaining to new tests.