Tuesday, January 19, 2016

The Paradox of Trust in Science

As an undergraduate student, I find that most, if not all, of my lectures incorporate information which students naturally presume is credible, reliable evidence. Very rarely does a professor inquire about the shortcomings of data or urge us to approach publications from a critical perspective. Upon reading a PubPeer article and learning that 25% of 120 randomly selected published papers revealed image data errors made me ponder why we constantly accepted literature as truth. I was frequently under the impression that if a study was published, it underwent a rigorous review process and was subsequently immortalized in an impressive journal....thus what was there to question? It was only after I joined a lab when I began to pause and truly assess studies within the growing scope of my knowledge. I also became increasingly aware of one of the greatest challenges facing research scientists: striking a balance between the demanding pressure to publish and being conscientious about data production throughout. 

The case of the overhyped medical press does not surprise me, however. I personally have fallen prey to such articles, namely those that occupy headlines with "breakthrough findings" that daily use items are carcinogenic. It's no secret that journalists are cognizant of how to grasp the layman's attention, albeit with content that isn't scientifically sound. Often, such articles are followed by disclaimers that, for example, the hot new weight loss drug working "miracles" is contingent upon x, y, z and/or has yet to be tested on humans. 

On another note, it is reassuring to know that individuals are making strides towards developing peer feedback initiatives such that widespread expertise can be offered (PubPeer) or in the case of PubMed Commons, establish an ongoing review system. But, there is much more that needs to be done to achieve the level of scientific credibility humanity deserves. As we discussed in lecture, statistics' primary objective is to identify and avoid bias, therefore it is imperative that as a scientific community, we understand and implement the appropriate tests/tools to prevent unacknowledged flaws from persisting throughout our comprehension. Further, we must better integrate sound statistics knowledge with our perception of the research process - specifically as elucidated by Bayesian analysis, what a 5% false positive rate of scientific hypotheses means for our ability to reproduce given results. I hope that all contributors to this dynamic field can eventually become more well-versed in statistics to better uphold ethical standards and ultimately, allow the public to regain its trust in the currently misleading realm of scientific research.  

1 comment:

  1. Thanks for giving your perpective on this topic. I had a more simplistic, assuming perspective when it came to scientific research than I realized prior to my own research experiences. The degree of caution I place on titles and conclusions which, as you mentioned, are often very enticing to the general public is much different now. Reading articles is no longer simply reading, but a constant struggle to determine if the work is truly credible, and if so, is it for the reasons the authors state? I agree with you, and likely the rest of the class, that more should be done to ensure the validity of research. While changes to the system as a whole is likely the best way to pursue this is, I believe there is much we can accomplish through our own personal integrity and critical, unbiased analysis of others' and our own work.