This recent study wouldn’t have been so significant if decades of research hadn’t been based on experiments that used mice. The fact is that scientists, both present and past, have almost singularly based scientific research on mice. The use of rodents has been all-encompassing – from biological, biomedical, behavioural and physiological research.
This is the reason why this recent study, which shows that mice might actually fear men involved in research, could possibly cast doubt on the bulk of research made decades ago up to the present. A huge segment of the history of scientific findings could have been influenced by male-induced fear on laboratory settings, where the researchers’ genders had not been accounted for in the analyses.
Lead researcher Jeffrey Mogil of McGill University says that the entire volume of scientific studies conducted on animals has not taken this factor into account. Mogil, who is a pain researcher at McGill, adds that this could have extensive effects if we take into account the significant number of medical research, such as studies on cancer and diseases, performed to mice by male or female researchers.
Nature Methods published the study, which measured pain responses of mice when they were exposed to the presence or smell of men and women in the experiments. Male presence, including male of other species, affected the rodents’ stress, increased their body temperature, and increased their corticosterone levels. Female presence, on the other hand, did not cause any significant change.
Experiments also showed that the presence of a female together with a male at a particular time counteracts the fear or stress. The male effect also diminishes with time until it totally disappears. These are useful findings which researchers can employ in future studies. These can also be used in evaluating past studies. Mogil emphasizes that there will be a need for researchers to indicate the genders of the people involved in the experiment, or the genders of the mice. This information must be accounted for in the statistical analyses.