A recent study in Neurobiology of Aging attempted to further scientific understanding of how the aging process impacts the human capacity to empathize. While the findings were less than conclusive, they have provided additional support for what neuro-psychological researchers have known for years—functional MRI (fMRI) studies are expensive, and small sample sizes lead to inconclusive results.
The authors of the study phrased their results quite aptly in the closing line of their discussion section, stating, “. . . the present findings contribute to a better understanding of multidirectional age differences in empathy.”
Now I certainly can’t disagree with the authors. Given that directionality is one of the major reasons to engage in quantitative (as opposed to qualitative) research, reminding readers that the brain is a complex and multifaceted organ doesn’t seem to add much to the present literature except for perhaps additional confusion in wondering what it is that they think that they found.
These researchers are not the first, nor will they be the last group of academicians, to under-sample their target population and employ questionable one-tailed tests of significance due to statistical power limitations. And it’s not my intention to slap them on the wrist for less than convincing analyses, among other things. All research is limited in some sense—monetary or otherwise.
That said, because of these limitations in published research, the onus lands on the reader or consumer of study findings to pay careful attention to the research they are ingesting—especially research that has the allure of being “smart” or “fancy” because it employs high-end technology like fMRIs.
I won’t dispute that technology can be amazingly useful for scientific exploration and understanding. However, when corners need to be cut and budgets need to be trimmed—which is an inevitable part of the practical world we live in—scientific findings that come from studies with a heavily trimmed budget may not be quite as fruitful as we would like to assume even though novel technology is employed. A bright and shiny new fMRI machine can most certainly spit out amazingly rich information about a human brain. Alas, if the research budget only permits the study of a handful of brains, it can be difficult to extend those specific findings to the general population and/or learn as many new things about brains as one could with a larger sample of brains to study.
In closing, I’ll paraphrase the wise words of Reading Rainbow’s LeVar Burton: of course you don’t have to take my word for it. . . you can always read the research for yourself and decide.