Acupuncture for hypertension – more evidence that it does not work

acupuncture for hypertension

The claims for acupuncture have any clinical usefulness are vastly overblown with evidence ranging from weak to nonexistent to dangerous. As Steven Novella at Science-Based Medicine once wrote, acupuncture is nothing more than “theatrical placebo.” On the long list of ridiculous claims for this pseudoscience is using acupuncture for hypertension treatment – and once again, real biomedical science shows it is worthless.

And now, it’s time to examine a systematic review that debunks the false claim that acupuncture for hypertension is useful.  Continue reading “Acupuncture for hypertension – more evidence that it does not work”

Your personal pseudoscience detector

Pseudoscience is like bubble gum. It tastes pretty good, it’s fun to blow bubbles, and it annoys some people. But eventually, the flavor leaves, and you find that you’re just chewing on some nutritionally dubious substance. Now you have to find a place to spit it out.

Or I guess you can swallow it, and it stays in your intestines for the rest of your life. Oh sorry, that’s more junk science.

If you read something that makes some medical claim, here’s a quick and easy checklist to determine if it’s pseudoscience. Or real science-based medicine. What we all need is an official, Skeptical Raptor endorsed, pseudoscience detector. Continue reading “Your personal pseudoscience detector”

Logical fallacies – debunking pseudoscience

Logical fallacies are essentially errors of reasoning in making an argument – identifying them is an excellent tool in debunking pseudoscience and other junk science. When logically fallacious arguments are used, usually based on bad reasoning to support a position (or to try to convince someone to adopt the same position), it is considered a fallacy.

Most of you didn’t know, because I didn’t promote it much, but I had a link in the menu for a list of logical fallacies. It lay fallow, barely read by me or, apparently, anyone else.

However, I decided to update and improve my list of favorite logical fallacies used by all of the pseudoscience crowd. There are many more logical fallacies than what I list, but this blog is focused on providing evidence, in a snarky way, against anti-science claims made by everyone from the vaccine deniers to creationists. Continue reading “Logical fallacies – debunking pseudoscience”

Anti-vaccine lunacy–more lies about Gardasil

One of the hallmarks of pseudoscience is an over-reliance on confirmation rather than refutation of a hypothesis. The antivaccine crowd are well-known for this particular violation of the scientific method. As discussed previously, science works on refutation–creating experiments that might actually disprove a hypothesis as a method to develop evidence in support of it. The anti-vaccination crowd actually hypothesizes (but not in a scientific sense) that a vaccine or set of vaccines was the causal factor in some side effect (autism, death, or whatever else), then they should establish an experiment (double-blinded of course) that would refute that hypothesis. If at some point, the data cannot refute it, then the anti-vaccinationists would have supporting data for their particular supposition. 

But instead of actually performing experiments (which cost money, which may show that they are wrong, or which might not be ethical), they resort to mining data to prove their point. Data mining is dangerous, because confirmation bias, that is, finding information or data that supports a belief while ignoring all other data that does not, makes the data suspect or even useless.

So, in that vein, the anti-vaccinationists often mine data from any database they can find, such as the Vaccine Adverse Event Reporting System (VAERS),  which is a program for vaccine safety, managed by the Centers for Disease Control and Prevention (CDC) and the Food and Drug Administration (FDA). VAERS functions as a post-marketing safety surveillance program (similar to other programs for almost every regulated medical device and pharmaceutical) which collects information about adverse events (whether related or unrelated to the vaccine) that occur after administration of vaccines.

VAERS has numerous limitations, including lack of scientifically designed questions, unverified reports, underreporting, inconsistent data quality, and absence of an unvaccinated control group. VAERS is basically a collector of information, but has limited value in making conclusions since it does not provide information that is obtained in a controlled manner.  However, it does have some usefulness, in that certain trends may be spotted given enough time and data points. Continue reading “Anti-vaccine lunacy–more lies about Gardasil”

Pseudoscience and vaccine denialism (updated)

We frequently use the term “pseudoscience” to describe the ideology of certain groups:  antivaccinationists, evolution deniers (creationists), global warming deniers, HIV/AIDS denialism, and almost anything in the areas of parapsychology, alternative medicine, and sasquatch. The science denialists (broadly defined as any group who rejects the scientific consensus on any subject without valid scientific support) always seem to be insulted by the word “pseudoscience”, even though the name is given to them both as a pejorative, but also because its based on their non-scientific, but scientific-sounding method of providing information.

In fact, there are several hallmarks that indicate to most educated individuals as to what is or is not pseudoscience. Real science is a systematic and rational method to organize and analyze “knowledge” into testable explanations and predictions. Sometimes, it appears that the anti-science crowd believes that science is just a word, not a philosophy which is organized as the scientific method. It isn’t some magical system that only smart people in secret ivory towers practice. The scientific method is simply a set of logical steps:

  1. Formulate a question: Based on observations of the natural world. Maybe you notice that sky is blue, and you ask “why is the sky blue?” Or “how do I design a vaccine to encourage the immune system to prevent a virus from causing a disease?” Of course, the questions can become much more complex as we make more detailed observations of the our world.
  2. Hypothesis: An hypothesis is a conjecture, based on the knowledge obtained while formulating the question, that may explain the observed behavior of a part of our universe. The hypothesis may be broad or very narrow. One could make a hypothesis that life can evolve on many planets across the universe. Or one could make a hypothesis that a drug can cure a disease in a small population of individuals. A proper hypothesis must include a null hypothesis, that is, the scientist must be willing to test that the null hypothesis is also false (a sort of double negative). This null hypothesis is that the new vaccine does nothing and that any disease prevention are due to chance effects. Researchers must also show that the null hypothesis is false. A scientific hypothesis must be falsifiable, meaning that one can identify a possible outcome of an experiment that conflicts with predictions deduced from the hypothesis; otherwise, it cannot be meaningfully tested. This all sounds complicated, but digested down to its simplest form, it means that a scientist is always willing to attempt to prove that the hypothesis is wrong
  3. Prediction: Once a hypothesis is developed, then the a prediction (or more than one prediction) is made based on the hypothesis. For example, if a vaccine is supposed to prevent a disease, then the prediction is made that it prevents some some amount of the disease above what would be assumed just by random chance. For example, without the vaccine it might be predicted that only 10% of individuals might be immune to the disease, but with the vaccine, it would be predicted that 85% would be immune. In all fields of science, the hypothesis leads to predictions which are different than what would be found simply by coincidence or randomness. Also, the hypothesis must be powerful enough to create more accurate predictions than alternative hypotheses.
  4. Test: This is the conducting of experiments or investigations to determine whether the real world behaves as predicted by the hypotheses. These experiments are observations which will agree with or conflict with the predictions; if they agree, then the confidence in the hypothesis will increase. On the other hand, if there is conflict, the confidence will, of course, decrease. Experiments should be designed to minimize possible errors, especially through the use of appropriate scientific controls. Medical and drug experiments utilize double-blind clinical trials to limit confirmation bias, a tendency towards confirmation of the hypothesis under study. 
  5. Analysis: This involves determining what the results of the experiment show and deciding on the next actions to take. The predictions of the hypothesis are compared to those of the null hypothesis, to determine which is better able to explain the data. In cases where an experiment is repeated many times, a statistical analysis such as a chi-squared test may be required. If the evidence has falsified the hypothesis, a new hypothesis is required; if the experiment supports the hypothesis but the evidence is not strong enough for high confidence, other predictions from the hypothesis must be tested. Once a hypothesis is strongly supported by evidence, a new question can be asked to provide further insight on the same topic. Evidence from other scientists and one’s own experience can be incorporated at any stage in the process. Many iterations may be required to gather sufficient evidence to answer a question with confidence, or to build up many answers to highly specific questions in order to answer a single broader question. Continue reading “Pseudoscience and vaccine denialism (updated)”

Identifying science denialism and pseudoscience

Science denialism, a form of pseudoscience, is everywhere these days. There’s the oft-discussed vaccination denialists who refuse to vaccinate children because they believe that vaccines cause some condition (usually autism), and Big Pharma hides evidence. Or AIDS denialists who believe that HIV doesn’t cause AIDS. Or global warming deniers who think that either global warming isn’t happening or, if it is, it’s not caused by human activities. Or evolution denialists, like Ken Ham, who think that one hundred years of scientific research can be ignored for a book that was written 5000 years ago to help illiterate pastoral farmers understand the natural world. It’s not just science, of course, there are Holocaust deniers, who think that no Jews were killed by the Nazis. There are even 9/11 deniers (usually called truthers) who think that Big Government (probably in league with Big Pharma) is hiding the truth about what really happened on 9/11. Continue reading “Identifying science denialism and pseudoscience”

Pseudoscience and logical fallacies in geology

If you ask any biologist or medical researcher about pseudoscience, they would probably talk about creationism, most of complementary and alternative medicine (CAM), homeopathy, sasquatch, and a few other things not so much in the public eye.  In the physical sciences, we hear about the global warming denialists, the Theory of the Big Bang denialists, and, again, a few other things that aren’t really famous.  But in the total world of pseudoscience, it always seemed like medicine gets the bulk of it, but that just may be a matter of perspective rather than reality. Continue reading “Pseudoscience and logical fallacies in geology”

How pseudoscience makes its case-Part 1. Revised and repost.

This is a two-part article that partially describes how the science-denialist makes their case, not necessarily why humans accept it so easily.  I’m not a psychiatrist, and I certainly don’t play one on TV.  I thought we should start with the scientific method, or how real science works.

I always get suspicious when someone makes an argument with the statement of “it’s been proven to work”, “the link is proven”, or, alternatively, they state some negative about scientifically supported therapies. Typically, I hear these kinds of statements from the pseudoscience pushing crowd. For example, real science has debunked the “there is a proven link between vaccines and autism,” a common and popular pseudoscientific belief.  Or that most alternative medicine (CAM) therapies work based on numerous logical fallacies that suspends reason, and accepts “belief” in the therapy, something that evidence-based medicine just doesn’t do. Continue reading “How pseudoscience makes its case-Part 1. Revised and repost.”

Pseudoscience and the anti-vaccine lunacy

We frequently use the term “pseudoscience” to describe the ideology of certain groups:  anti-vaccinationists, evolution deniers (creationists), global warming deniers, and almost anything in the areas of parapsychology, alternative medicine, and sasquatch.  The science denialists (broadly defined as any group who rejects the scientific consensus on any subject without valid scientific support) always seem to be insulted by the word “pseudoscience” as if it’s a pejorative without foundation. Continue reading “Pseudoscience and the anti-vaccine lunacy”

How pseudoscience makes its case. Part 1.

I decided to write a three-part article here that partially describes how they make their case, not necessarily why humans accept it so easily.  I’m not a psychiatrist, and I certainly don’t play one on TV.  I thought we should start with the scientific method, or how real science works.

I always get suspicious when someone makes an argument with the statement of “it’s been proven to work”, “the link is proven”, or, alternatively, they state some negative about scientifically supported therapies. Typically, I hear these kinds of statements from the pseudoscience pushing crowd. For example, real science has debunked the “there is a proven link between vaccines and autism,” a common and popular pseudoscientific belief.  Or that most alternative medicine (CAM) therapies work based on numerous logical fallacies that suspends reason, and accepts “belief” in the therapy, something that evidence-based medicine just doesn’t do.

In fact, science rarely uses the term “proven”, because the scientific method is not a system to make a definitive answer on any question–scientists always leave open the possibility of an alternative hypothesis that can be tested. If the alternate hypothesis can be supported through experimentation, then it can replace the original one. When an alternative medicine or junk science supporter states “it has been proven,” ask where is the evidence.  What is more troubling is that someone who believes in these therapies cannot imagine that they don’t work, what is called falsification, which is a hallmark of good science.  Whenever I hear that a scientist say, “we were wrong, it doesn’t work,” my retort is “excellent, good science.”

The scientific method is an unbiased systematic approach to answer questions about the natural world, including medicine. It has several basic steps:

  1. Define the question–this could be anything from “does this compound have an effect on this disease?” or “how does this disease progress?”
  2. Observations–this is the subjective part of science. Do we observe trends or anomalies? Does a physician notice that every patient from a town or neighborhood exhibit the same disease? A lot of science arises from observations of the natural world. One of the most famous stories in the early history of medicine is when Edward Jenner observed that milkmaids rarely were infected by smallpox because they were exposed to cowpox, a less virulent disease.
  3. Hypothesis–taking the observations, create a hypothesis that can be tested. In Jenner’s case, he hypothesized that exposure to cowpox immunized individuals to small pox.
  4. Experiment–simply, the scientist then tests the hypothesis with experiments and collect the data. The experiments are not designed to solely validate the hypothesis but may also attempt to contradict it.
  5. Analyze–this requires statistics to determine the significance or results.
  6. Interpret–sometimes the data leads to a revision of the hypothesis, which means the scientist has to return to steps 3-6. Or it confirms or supports the hypothesis, which means the researcher can move to Step 7.
  7. Publish results–in today’s scientific community, the results require peer-review, which subjects the data, analysis and interpretation to the scrutiny of other scientists before publication. This is a critical step that ensures that the results can stand up to criticism. It does not prove anything, but it does support the hypothesis.
  8. Retesting–Many times the research is repeated by others, or the hypothesis may be slightly revised with additional data. Science is not static, it constantly revises theories as more data is gathered. For this reason alone, science is not an absolute, it is constantly seeking new data.

Science is an evidence-based systematic analysis without inherent opinion or emotion. In other words, it is a method to cut through opinions and anecdotal observations, so that one can have some reasonable expectation that a medicine or device will work as planned. CAM fails to utilize scientific method. Supporters of CAM usually perform experiments to confirm the hypothesis, never to contradict it. It is the fundamental principle of falsifiability, that is, that if a hypothesis is false, it can be shown in experimentation that allows science to have an open mind about the world. When you speak to a believer of CAM, they almost never assume that their treatment cannot work.

It’s interesting that CAM and pseudoscience start out with observations of the real world. For example, CAM therapies sometimes work, not because of the therapies themselves, but because humans just get better from many diseases. So, these CAM therapies rely upon confirmation bias, that is, the tendency to accept information that supports your beliefs, or even post hoc ergo propter hoc, a logical fallacy which says “since that event followed this one, that event must have been caused by this one.”  Humans too often conflate correlation and causation.  Just because events follow one another, that doesn’t mean one causes the other.  I suppose that’s how superstitions arise.

Part 2 of this discussion will be out as soon as I write it. It will discuss how to tell what is “proven” or what is science.  Stay tuned.