Editor’s note: This article combines elements of several articles about pseudoscience published in 2012 and 2013. It’s been revised to include some newer information and split into two parts to improve readability. Over time, more topics will be covered.
Let’s start with a quote (edited for clarity and because some points aren’t germane to this article) from the just-retired Jon Stewart, in his final rant ever on the Daily Show:
Continue reading “Pseudoscience and science – bullshit vs. rational thought”
Updated 4 November 2014 to add some ironic analysis of Doshi’s “not-an-epidemiologist” background.
A few months ago, I wrote an article about Peter Doshi, a Ph.D. who is doing some postdoctoral work at Johns Hopkins University, one of the leading institutions of higher learning in the USA. Doshi is truly not very notable in science, except last year, he wrote an article about flu vaccines, basically employing the Nirvana Fallacy that because flu vaccines aren’t 100% effective they are worthless. Since vaccines are fundamentally a medical procedure to mitigate risk with a very low risk of adverse events, even 50% effectiveness will save thousands of lives. But we’ll get back to that.
The article he wrote is not actually based on real research, but appears to be an opinion paper–kind of like the opinion papers written by creationists who want to convince anyone who will listen that dinosaurs lived with humans. Doshi denies that most flu’s are even caused by the influenza virus. I guess the CDC’s high tech diagnostic tests for influenza are all wrong. But then again Doshi presents no evidence.
Because of the zombie myths of the antivaccination world, myths or papers that are reanimated every few months because the vaccine denier community actually lacks any fresh evidence to support their nonsense. So Doshi’s paper from 2013 is resurrected in the antivaccination press. A few days ago, an obscure pseudoscience promoting website started banging the drum about Doshi’s comments. The article, found in the Realfarmacy website, has this scary headline: “Johns Hopkins Scientist Reveals Shocking Report on Flu Vaccines.” Makes it sound like Doshi wrote another article. Which he didn’t. Continue reading “The zombie anti-vaccine lie–Peter Doshi and the appeal to authority”
One of the tropes of pseudoscience pushers is that science is too fungible, that is, scientists can change their mind or, horrors of horrors, refuse to make an absolute “this is the TRUTH™” statement. There are numerous articles, published in peer-reviewed, high impact factor journals, that state “more research should be done to confirm these results.” The anti-science crowd uses these comments as “evidence” that science isn’t sure about something.
Black/white absolute truth doesn’t exist in real science. Many people state that science “seeks truth,” and it does, if we do not ascribe moral qualities to the word “truth.” Actually, science seeks evidence to support or refute a hypothesis (or some other scientific principle like a theory). It’s all about the evidence (and the quality thereof), not about proving that it’s either this or that.
Part of the problem, amongst both “pro-science” and anti-science types is that they both think that science is some magical word to either be loved or despised depending on the answer it provides. But science is, in reality, a coherent method to find an answer to a question about the natural universe, but it is not itself the answer. Science is a systematic and logical process, using the scientific method, that finds and builds data, and eventually knowledge, into testable explanations and predictions about the natural universe. it is not a magical word that implies truth, but it is a rigorous process to separate meaningless information from high quality evidence in support or refutation of an explanation of the natural world.
Oftentimes, someone will report that “scientists believe that birds are living dinosaurs” or “scientists believe humans cause global warming.” To the lay audience that sounds like a bunch of men and women, sitting in an apartment with a keg of beer, a dartboard, and inventing some new theory. OK, in my experience, we have often sat around with a keg of beer and a dartboard, but we were discussing 10 years of research and how to sum it up clearly. Or wondering if a new set of results adds to the data or may actually move us in a different direction. But all of it was based on many years of hard work (including education, bench and field research, withering criticisms from peers and mentors, and countless nights of worrying if an experiment would fail because the power went off), not just making a random guess.
Moreover, even after hard work, publications, and critiques, science is filled with doubt. New evidence, as long as it is as strong as the evidence that supported a previously held explanation, can create new explanations and predictions. The whole scientific process is based upon criticism, open-mindedness and accumulation of new data. It’s not based on “ok, we’re done, we’ve answered all of the questions.” Science evolves over times, because it simply isn’t dogmatic. Continue reading “Science is not based on absolutes–Richard Dawkins proves that”
Seth Mnookin: The Autism Vaccine Controversy and the Need for Responsible Science Journalism.
The Huffington Post is not known for it’s pro-science editorial content, but I do appreciate that Mnookin writes there. The irony is kind of dripping that the article is a plea for responsible science journalism, when it’s posted at HuffPo, but I always enjoy good irony.
This is part of my ongoing discussion on how quacks use pseudoscience to push their myths and potions on the world. Part 1 discussed the scientific method, which allows us to objectively analyze the natural world. Part 2 discussed the best way for us to examine the difference between science and pseudoscience.
I just read an outstanding analysis, by Steven Novella, MD, a clinical neurologist at Yale University, of how pseudoscience (those who pretend to praise the scientific method, yet do it in a way that is not actually science) and anti-science (those who repudiate science outright, or even undermine science, with subjective analysis and untestable spirituality) to reject evidence-based medicine.
Dr. Novella clearly states how science in medicine works:
This leads us to the final continuum – the consensus of expert opinion based upon systematic reviews can either result in a solid and confident unanimous opinion, a reliable opinion with serious minority objections, a genuine controversy with no objective resolution, or simply the conclusion that we currently lack sufficient evidence and do not know the answer. It can also lead, of course, to a solid consensus of expert opinion combined with a fake controversy manufactured by a group driven by ideology or greed and not science. The tobacco industry’s campaign of doubt against the conclusion that smoking is a risk factor for lung cancer is one example. The anti-vaccine movement’s fear-mongering about vaccines and autism is another.
Basically, science evolves over time. A conclusion that lacks sufficient evidence may eventually be supported by better analysis or groundbreaking research. You’ll notice that anti-science and pseudoscience pushers do not allow themselves to participate in the this continuum of research–they state emphatically that they are right.
Science, by its very nature, must be falsifiable, meaning that any hypothesis or theory has the logical possibility that it can be contradicted by an observation or the outcome of a physical experiment. Just because a hypothesis or theory is “falsifiable,” we do not conclude that it is false. To the contrary, we understand that if it is false, then some observation or experiment will provide a reproducible result that is in conflict with it. Simply put, science assumes that it has it all wrong, and attempts to determine why a particular theory or hypothesis is wrong. Of course, in these attempts, usually more evidence is found to support the original theory. Just because science requires falsifiability, that does not mean that it will ever be falsified, but science is open to the possibility. In other words, science evolves.
Pseudoscience, by its very nature, is not falsifiable. It is mostly based on assertion rather than scientific observation, so it cannot be tested by experiment or observation. Creationism is a perfect example. It is based on a human text (the bible), so there is no experiment that could be designed to test the text, since it non-responsive in a natural sense. It would be like trying to scientifically show that the muppets existed.
Two of the most misused and misunderstood terms in evaluating scientific evidence are correlation and causation, two powerful analytical tools that are critical to evidence based medicine. Correlation is the grouping of variables that may occur together. For example, smoking correlates with lung cancer in that those who smoke tend to develop lung cancer at a statistically significant rate. It’s important to note that correlation does not prove causation. However, once you have numerous well-designed studies that correlate lung cancer to smoking, along with adding in biological and physiological models that support the correlation, then we can arrive at a consensus that not only is smoking correlated with lung cancer, it causes it.
We observe correlations every day. But they are subjective observations for which we cannot state a causal relationship without substantial research. The anti-vaccination movement is rife with these observations which they use to “prove” a cause. An anti-vaccine conspiracy website claims that pregnant women are miscarrying babies after getting the shot. The fact is that there is a statistical chance that women will miscarry during any pregnancy. This is random variability not a cause. In fact, based on the rate of miscarriage, we could expect that thousands of women would miscarry within 24 hours of getting the H1N1 flu shot. But it’s not correlation, unless significant studies show a causal relationship. For example, I’m also sure that thousands of people broke a bone or had a desire to eat a burger after getting the shot, but that’s because in a large enough population of individuals, you can find literally millions of different actions after getting a shot.
So, the miscarriage rate after receiving the swine flu shot is not correlated. It’s just a random observation. And there is no biological cause that could be described. Nevertheless, the “flu vaccine causes miscarriage” conspiracy has been thoroughly debunked by research, but still the internet meme continues. Pseudoscience sometimes uses the same methodology (or lack of methodology) to make positive assertions. Homeopaths will claim that their dilutions will cure whatever disease, yet they do not have scientific evidence supporting them, but there plenty of evidence that debunks what they practice.
As part of my analysis of medical claims of causation or “cures”, I often use this logic to test the possibility of the usefulness of any alternative medicine–is there any physical, chemical or biological mechanism that will allow the quack procedure to work? If you cannot imagine it without violating some of the basic laws of science, then we should stand by Occam’s razor, which states often times the simplest solution is the best. So, if there is no evidence of vaccinations being correlated, let alone causal, to autism, then that remains the simplest solution. To explain a possible tie without any evidence would require us to suspend what we know of most biological processes.
As I’ve said in other posts, the internet gives us so much information, we tend to value it equally, as if every website provides accurate and logical data points. Maybe you have a friend who had a miscarriage 24 hours after receiving the swine flu vaccine. Maybe you’ve heard that many people have. But that’s not science, that’s just a subjective observation. Or even confirmation bias.
Once again, Dr. Novella says it perfectly:
In conclusion, correlation is an extremely valuable type of scientific evidence in medicine. But first correlations must be confirmed as real, and then every possible causational relationship must be systematically explored. In the end correlation can be used as powerful evidence for a cause and effect relationship between a treatment and benefit, or a risk factor and a disease. But it is also one of the most abused types of evidence, because it is easy and even tempting to come to premature conclusions based upon the preliminary appearance of a correlation.