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.  

Publication Pressure and Scientific Integrity

Research today sits on the cusp of an incredible era. The evolution of technology has created a plethora of tools capable of addressing nearly any scientific question from nearly any angle. Microscopy, nanoparticles, sequencing and hundreds of other fields have advanced wildly while at the same time becoming more affordable. This has made scientists more productive, more effective, and led to many more publications flooding the desks of editors of scientific journals. In order to keep up and to stay relevant, the best journals have become more selective. They expect in vivo observations, a biomedical context, and a complete and compelling story. Which is great. Except that such studies typically take years and years to complete without any publishable findings in the interim. With the current environment in academia, where “publish or perish” is a very real concern, this selectivity for the most compelling or unusual articles is frequently a death sentence for some of the best, brightest, and most principled investigators.

Cue PLoS One; one of many journals of its kind that hopes to allow for “a faster path to publishing in a high-quality peer-reviewed journal.” According to its website, “all work that reaches rigorous technical and ethical standards is published and freely and immediately available to everyone.” In my personal and completely unsubstantiated opinion, I think this is a great mission statement. I believe research happens in very small increments, and the ability to publish those increments gives scientists a way to mark their progress as they march toward a more complete understanding. These types of journals also provide an outlet for less-sensational follow up work or negative results, which at its best would debunk false results that are misguiding the efforts of the scientific community and at worst would save some poor graduate student from sweating over a hopeless project. Supposedly if these papers are deemed to meet “technical and ethical standards” they will be freely disseminated to the scientific community. The extent to which these journals serve this purpose in reality, however, is in dispute.

In an article in The Economist in 2013 titled “Trouble in the Lab,” the authors question the utility of these lower-tier journals. In regards to publishing negative results they write: “Journals, thirsty for novelty, show little interest in it; though minimum-threshold journals could change this, they have yet to do so in a big way.”

But the fault cannot be wholly placed on the shoulders on these publications. It is not exciting to try to replicate previously published results, or to write a manuscript centered on a null hypothesis. The authors acknowledge that “Most academic researchers would rather spend time on work that is more likely to enhance their careers. This is especially true of junior researchers, who are aware that overzealous replication can be seen as an implicit challenge to authority. Often, only people with an axe to grind pursue replications with vigour—a state of affairs which makes people wary of having their work replicated.” This is disconcerting for a profession that derives its relevance from a public perception of dogged adhesion to the search for truth and a strong personal sense of integrity.

With a wealth of technological tools and bright minds, scientific research finds itself in an exciting yet perilous position. Moving forward it will be critical to balance the thrill of scientific discovery with the necessity of healthy skepticism. I believe, unlike the author of the cited article, in the ability of the scientific community to police itself. If academic research is to stay relevant, however, we need to acknowledge the importance of negative and mundane results in a more systematic fashion.

How to become a qualified future Scientist

After viewing the video of deception and reading articles about unreality in science, I feel more pressured of becoming a qualified future scientist than ever.  This is good as it makes me, a graduate student in biomedical science, to think deeply about what's important to carry on along our way of pursuing a scientific career.

As mentioned in Dan Ariely's video, there might be a "fudge factor" which underlines our cheating behaviour.  If people signed the honor code before the test, their cheating behaviour was greatly reduced.  It signifies the importance of awareness.  The awareness that biased research might cause very "bad impact" should be beared in our minds before we design our research, during our data collection and at pre-publication status.  "Bad impact" might be the failure of a drug, the waste of time and cost into the research, or the damage to our reputation in the field. As a student in cancer research, attempting to find a "cure" to pediatric brain cancer, one "bad impact" might be creating the "false hope" to those young patients and their parents or family.

Other than being aware of possible bad impact, it is also important for us biologists to be armed with basic concepts of statistical knowledge. In Jeremy Berg's blog and the article of "Trouble at the lab", they mentioned that scientists tend to produce false positive data and barely publish false negative data, which is more reliable from the perspective of statistics.  This may explain for the most biomedical non- reproducible experiments.  If we knows better about statistics, we would at least not overstate our conclusions considering the possibility of producing false positive result is not that low.  Though no statement is 100 percent true in science as mentioned by Jared Horvath, there must be ways for us to improve our methodology in conducting and communicating science, for example, better interpreting our data.  Nowadays, peer reviews call more attention on statistical explanation, which might attribute to more involving of statistics in biological research.

Now realizing that we are under the age of "publish or perish", we should avoid being pushed to nowhere by the tides of publication stress.  A good start to change might be the awareness of possible bad impact on our society by uncareful research and the integrating of biostatistics in biomedical science.

Is the Pressure too much?

The pressure to publish is ruining science. Don't get me wrong, publishing data and sharing it with other scientists is critical for the advancement of science. However the issue comes when scientist feel so pressured to turn out X number of publications a year that they cut corners. 

Scientific journals focus on novel findings that can advance the world of science to include in their journals. In general this means a hypothesis confirmed for each article. An article in the economist took out the calculators and did the math, showing that up to 35% of published confirmed hypothesizes are false based on the very statistics that scientists use to confirm or reject a hypothesis. Of course this is assuming the statistics were done properly in the first place.

Many things can go wrong leading to an experiment that biases the research to a certain result. Often things that may bias research are looked over simply because the research would not realize that it could bias the results. In the situation where a scientist feels overly pressured to publish, bias may come about through desperation to confirm a hypothesis.

In a blog on Scientific American, Jared Hovarth mentions that part of science is learning from mistakes and using those mistakes to advance research forward. However with today’s journals focusing on success and limited money for replication, it is hard to weed out those 35% of falsely confirmed hypothesizes. I thing that for science to become more efficient and progress more swiftly, journals should publish more articles that disprove hypothesizes. Not only would this decrease the desperation to confirm a hypothesis, but it would also help other scientist focus their own research.

One of the reasons I have always admired science is because I considered it a pure art to seek out a true answer. When biased gets involved, science becomes less pure and less reliable. Though there are many sources to introduce bias, the pressure to publish is a completely unnecessary pressure to influence results. Publishing should be where the truth is spread and data is shared, not a pressure to doctor results and skew data.