Repeatability analysis improves the reliability of behavioral data.

Reliability of data has become a major concern in the course of the reproducibility crisis. Especially when studying animal behavior, confounding factors such as novelty of the test apparatus can lead to a wide variability of data which may mask treatment effects and consequently lead to misinterpretation. Habituation to the test situation is a common practice to circumvent novelty induced increases in variance and to improve the reliability of the respective measurements. However, there is a lack of published empirical knowledge regarding reasonable habituation procedures and a method validation seems to be overdue. This study aimed at setting up a simple strategy to increase reliability of behavioral data measured in a familiar test apparatus. Therefore, exemplary data from mice tested in an Open Field (OF) arena were used to elucidate the potential of habituation and how reliability of measures can be confirmed by means of a repeatability analysis using the software R. On seven consecutive days, male C57BL/6J, BALB/cJ and 129S1/SvImJ mice were tested in an OF arena once daily and individual mouse behavior was recorded. A repeatability analysis was conducted with regard to repeated trials of habituation. Our data analysis revealed that monitoring animal behavior during habituation is important to determine when individual differences of the measurements are stable. Repeatability values from distance travelled and average activity increased over the habituation period, revealing that around 60% of the variance of the data can be explained by individual differences between mice. The first day of habituation was significantly different from the following 6 days. A three-day habituation period appeared to be sufficient in this study. Overall, these results emphasize the importance of habituation and in depth analysis of habituation data to define the correct starting point of the experiment for improving the reliability and reproducibility of experimental data