I contend that there is only medicine, not a variety of flavors of medicine. The medicine you should care for or call by that name is the kind that is testable and works. Keep in mind that clinical testing is one of many forms of testing that can validate medical interventions.
If I told you once, I’ll tell you again: definitions are important in science. Undoubtedly, the definitions below are imperfect and I’d appreciate alternatives making their way into the comments section. To my taste, they are fine for the purposes of this discussion.
Lets start by defining 3 major intersecting elements of the matter at hand:
- Science, according to Wikipedia’s sourcing of the Online Etymology Dictionary’s content, is defined as “a systematic enterprise that builds and organizes knowledge in the form of testable explanations and predictions about the universe.”
- Medicine, as defined by the Oxford English Dictionary, is “the science or practice of the diagnosis, treatment, and prevention of disease.”
- Belief, according to Stanford’s Encylopedia of Philosophy, refers “to the attitude we have, roughly, whenever we take something to be the case or regard it as true. To believe something, in this sense, needn’t involve actively reflecting on it.”
These 3 concepts can be seen as feeding back and forth on one another.
- A belief arises, inexplicably or based on prior knowledge. It then needs to be broken down as succinctly as possible so that its essential principles can morph into a testable hypothesis with the minimal number of variables possible.
- This hypothesis does not become accepted because there is evidence to support it. It becomes accepted — progressively — by accumulating failed experimental attempts seeking to tear it down. Evidence supporting the hypothesis is often sought in parallel or may stem from the attempts to disprove it.
- If the hypothesis has enough supportive data of sufficient quality outweighing all evidence to the contrary then it can be termed medicine (in the context of beliefs relating health & disease).
How exactly a hypothesis is accepted as valid or invalid (point #3) is often messy business. This is because we are on the blurry edge of the space where ‘knowns’ & ‘unknowns’ collide.
There are a million different reasons why things that putatively ‘work’ cannot and should not be called medicine. This label is reserved for things with evidence stemming from sound scientific testing. Some things are simply unconfirmed medicines in the waiting. I think this is the case with some so-called ‘alternative medicines’ as well as with consistently poo-pooed lifestyle factors — both of which have roles to play in health. This is not an argument for only using tried-&-true treatments since there are many situations where novel experimentation and educated intuition are appropriate. It is a lot of what makes science exciting! However, until data is in for EVERYONE to question OPENLY, a good scientist should abstain from calling his or her intervention(s) medicine. Or simply making unwarranted claims of certainty or misrepresenting the limitations of their knowledge. A safe bet on whether or not a person is well aware of what they’re doing and saying is that most questions should typically be met with a flat “I don’t know”. Yes, N = 1’s are great and I am an avid self-experimenter finding lots of value in it. I am careful to not form too solid a world view based solely on my experiences. This is one of my pet-peeves with the Paleo blogoshpere (or any other health related blogospheres) which extrapolates the “everyone is different” (sound) meme to suggest that their own evaluation of themselves is — by default — more important than other lines of evidence. If only things were so simple…There is no clear road-map: you have to constantly adjust what you appear to experience with other information out there. It is a life-long lesson in humility to be a true scientist (at heart — not by title. Titles are meaningless).
Lets take 1 tangible example of each scenario. 1 scenario is an ‘alternative medicine’ intervention that is worth scrutinizing/testing. The other scenario is of an ‘alternative medicine’ intervention not deserving a 2nd glance.
Example of an ‘out there’ hypothesis fulfilling deserving further scientific scrutiny: acupuncture. More specifically, it is auricular acupuncture. It has been used for an immense variety of conditions, syndromes and symptoms. The only effect it appears to have is on pain management. The effect appears to be quite weak — at best. A recent review article entitled “Efficacy of Auricular Therapy for Pain Management: A Systematic Review and Meta-Analysis” blandly concludes that:
auricular therapy can be used as an adjunct therapy for pain management and, therefore, reduce analgesic use to minimize potential adverse effects and tolerance. Nonetheless, further studies—particularly large scale of RCTs—are needed to further confirm the efficacy of auricular therapy for pain and must take into consideration important features of methodological design, which include point specification, stimulation, treatment duration, placebo effects, and patient expectations of treatment outcomes
Acupuncture is certainly not quackery. It may just work very poorly. In the grand scheme of medical things however, it is not vying for a prominent role in medicine. Understanding the neurophysiology and placebo/nocebo effects relating to such interventions are interesting avenues to follow, maybe one day telling us more about the nature of acupuncture’s effect(s). Moving on…
Example of an ‘out there’ hypothesis undeserving of further scientific scrutiny: homeopathy
It fails simple logic. It fails right out of the gate, on many fronts. For one, it is based on the silly notion that the more diluted the supposed active component is in the solution, the higher its potency. This contradicts the time-tested concept that has yet to receive a single piece of evidence disproving it: the greater the quantity of something, the larger the dose. U-curves are still dose-dependent U-curves, people. They simply describe non-linear relationships between 2 or more variables. A clear, logic fail (see below).
Furthermore, the dilutions indices are so large that they cause uncontrollable laughing and scoffing amongst the scientifically inclined. See this table below for a good laugh:
This is overkill but deserved. Lets hammer the nail into the coffin of homeopathy by quoting the recent Optum “Overview Report on the Effectiveness of Homeopathy for Clinical Conditions: Evaluation of the Evidence”, which concludes:
There is a paucity of good-quality studies of sufficient size that examine the effectiveness of homeopathy as a treatment for any clinical condition in humans. The available evidence is not compelling and fails to demonstrate that homeopathy is an effective treatment for any of the reported clinical conditions in humans.
The fact that homeopathy got this level of scientific scrutiny when lower-school maths and high-school physics is enough to disprove its outrageous claims is a waste of time and energy. Hopefully they can no serve their intended purpose.
Being clear about what can be called medicine and what can’t or shouldn’t, does not mean one is close minded. On the contrary, it demonstrates an understanding of the general limits of knowledge generally and ones own knowledge. It’ll be hard to think outside of the box, so to speak, if you’re not willing to recognize you’re in a box in the first place. That box is an exciting place to be and it is vast, really vast. It should be cherished as a launching pad for expanding it. If done with a little intellectual integrity — the better!
Check-out the #EvoMed summit and make up your own mind.
[Edit/Mea Culpa: 23/11/2014]
I wrote “Acupuncture is certainly not quackery. It may just work very poorly.” I now realize that acupuncture can be correctly labeled as quackery as per its definition on Wikipedia: “Quackery is the promotion of unproven or fraudulent medical practices”. I changed my mind, mainly due to 2 things:
1) the reassessment of the ‘significance’ of p-values in biomedical literature (see “An investigation of the false discovery rate & the misinterpretation of p-values” by David Coloquhon http://dx.doi.org/10.1098/rsos.140216)
2) the readjustment of my expectations regarding the statistical occurrence of actual ‘true’ results in biomedical literature (see “Why most published research findings & false” by John Ioannidis http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=1182327&tool=pmcentrez&rendertype=abstract)
I realized that I was applying a double-standard of ‘evidence required’ for acupuncture studies compared to my more rigorous approach with genetic, pharmacological or nutritional studies. My use of the word “weak” was somewhat euphemistic for “nothing to see here”.
Lastly, I would like to note that the definition of quackery can be applied problematically to viable medical treatments. For example, “ketogenic diets for epilepsy” or “marijuana as a treatment for pain” are recognized as unproven or ineffective medical treatments and the general consensus amongst medical institutions mirrors that position. This however, is incorrect. The science behind both of these unconventional modern medical approaches is sound.
This is me trying not to throw the baby out with the bath water.