The standardization-generalization dilemma: a way out

Genes Brain Behav. 2010 Nov;9(8):849-55. doi: 10.1111/j.1601-183X.2010.00628.x.

Abstract

Recently, a debate has emerged on the use and necessity of standardization in experimental testing using animal subjects. The difficulties encountered when trying to reconcile standardization and generalization largely underlie this debate. The more specific the testing procedures are, the less one can generalize to more naturalistic situations, including to human clinical populations. If the goal of a study is to generalize to a larger population, there may be a higher risk attached to false-positive than false-negative results; thus the balance sways toward generalization. Heterogenization of housing conditions and of genetic makeup of experimental animals has been suggested as a possible method to increase the generalizability of results. It is important to remain cognizant, however, of situations in which false negatives can be counterproductive or even dangerous, such as when the goal is to elucidate a physiological mechanism, when expected effect sizes are small, in toxicological studies and in drug safety testing. In such cases, experiments based on standardization may provide more useful information. We pose that it is essential that the goal of the specific experiment conducted is clearly defined and that the decision to balance between standardization and generalization must be made based on the specific needs to meet the intended goal. In this light, we discuss a multi-tiered approach to animal experimentation, in which standardization and generalizability are each given precedence during different phases of a project, depending upon the goal of the experiment.

MeSH terms

  • Animal Experimentation / standards*
  • Animals
  • Epigenomics / methods
  • Epigenomics / standards*
  • Genetics, Behavioral / methods
  • Genetics, Behavioral / standards*
  • Humans
  • Models, Animal
  • Phenotype
  • Reproducibility of Results
  • Research Design / standards*
  • Validation Studies as Topic