The nature of the

CR evaluation, therefore, is “absolute.” Determining if a person’s blood pressure is normal based on his/her systolic and diastolic pressures is a good example of a CR evaluation. When the measurement interest is on “the more (e.g., number of pull-ups a student can do), or less (e.g., how fast a student can finish a one-mile run/walk click here test), the better”, the NR evaluation is more appropriate. Constructing an NR evaluation is relatively easy as long as a large, current and representative sample of a population can be obtained and regularly updated. With such a sample, norms (e.g., percentiles and percentile ranks) can be computed and derived. There are, however, several major limitations often associated with the NR evaluation framework. First, it is difficult to update

norms regularly due to cost, time, and manpower constraints. As an example, the PPFA’s norms were based on the 1985 National School Population Fitness Survey and there have been no major national fitness studies in the USA since the 1980s. As a result, these outdated values likely do not reflect current norms (e.g., an 80th percentile from the 1980s may now be equivalent to the 90th percentile), but rather how the present values compare to the previous norms, making them inaccurate in its original evaluation framework and the key “percentage” information no longer exists. Second, the interpretation under the NR evaluation depends on the “normal” Selleckchem CX 5461 status of the reference population. The designations of “average” or “above average” have limited meaning if the majority of a population is not normal (e.g., obese, unfit or unhealthy). Third, the selection of a percentile associated with health outcome measures (e.g., 85th or 95th percentiles as the cutoff values for “overweight” or “obese”) is often arbitrary with little scientific foundation. It is likely that other percentiles (say 83th vs. 97th) may

be the more appropriate values for when connecting these cut-off values with outcome variables of interest (e.g., health outcomes such as metabolic syndrome). Fourth, the employment of the NR evaluation framework tends to reward children and youth who are already fit while potentially discouraging those who are not fit. If rewards are based on achieving the 85th percentile (as with the PPFA) only highly fit youth may be motivated to try to achieve it. Less fit youth may be less motivated because they know their chances of achieving the standard are very low. If unfit students are less motivated during physical fitness testing they may come to perceive physical education classes, especially physical fitness testing, as a punitive, rather than enjoyable. The problem of the “17% in the 95th percentile” statement noted earlier is a good example of the first three limitations of the NR evaluation.