NTs Are Weird

I’ve seen lots of writing lately about the horrors of the anti-vaccine crowd and scientifically bogus autism treatments. While I am also against these things, I may not be against them for the same reason as others - and I think we are creating a dangerous situation if our primary problem with the anti-vaccine crowd and other scientifically bogus treatment promoters is the unscientific nature of their work.

Sure, the unscientific nature is an issue. And we are right to speak against that.

But we better be careful. There very well could be scientifically valid “treatments” one day that still demean the person with autism - or maybe the treatments make us “indistinguishable”, and actually do that, but at great personal cost. I don’t think that’s what any of us want (at least not if you generally enjoy reading this blog).

Not every scientifically correct treatment or idea is going to be ethical - and ethics are what we need to be careful to be talking about, not just scientific correctness, lest the unethical, but scientifically-correct treatment be encouraged by our very opposition to the anti-vax crowd!

For instance, let’s say an autism “treatment” was proven to meet the treatment’s stated goal of “indistinguishability”. It may have met very stringent scientific standards, may have been studied via experiments with excellent design, and had the results of these experiments analyzed with the proper application of statistics. That doesn’t mean that the treatment should be used, only that it does what it says it will do.

So, the next question would become, “Is the goal a good one?” And the other question that must be asked, “So, does the good outweigh the bad?” Nearly every “treatment” is going to have negatives (for instance, everyone recognizes many drugs are good for treating infections, but we also recognize that those drugs have side-effects). Science doesn’t make value judgments about “goodness” or “badness”, but only makes judgments about whether or not claims are plausible. A plausible claim isn’t necessarily the same as a “good” goal. The answers to these would tell us whether or not the treatment was ethical.

I’m worried even about some people associated with “our side” in the blogosphere and internet as a whole - as I read their writings and talk to them, I find that they may be less concerned with neurodiversity and disability rights than scientific correctness - that they wouldn’t be opposed to what I, and many other autistics, would consider “unethical treatment” if that treatment’s development met the requirements of rigorous scientific work. Such “friends” are no friends of mine.

Martin Luther King Jr. said it well: “Our scientific power has outrun our spiritual power. We have guided missiles and misguided men.”

I see a lot of bloggers talking about the evils of things like the mercury causation theory or chelation, but doing it in a way that hurts people like me.

I’ll say this plainly: The scientific method, alone, is not enough for people like me. Not yet, anyhow. If you only use scientifically approved accommodations, supports, therapies, etc, with me, you will ruin my life. Period.

Now, I’m not unscientific by any means. But I also recognize the limitations of science. Science hasn’t yet studied everything. There are still areas science knows little about, such as autism and medicine in general (seriously).

I’m on a list where there is a lot of debate right now over the scientific merits of word prediction in speech devices. Most (all?) of the studies show word prediction to be a bad thing because it interferes with muscle memory (the word prediction list often changes order based on your vocabulary usage, so that YOUR most frequently used words are at the top). But these studies have a few flaws, besides for people who happen to be “exceptions” to the majority that the studies show who do worse with word prediction. For instance, I type at 100+ words per minute (yes, really - you can ask my friends if you don’t believe this). I’m in exactly the category that won’t find word prediction useful, according to the studies, as I have advanced muscle memory (you can’t think by the letter to type this speed - you are typing whole words at once). Yet, occasionally I simply don’t know how to spell something. I can either go to another tool, or use a device that gives me a word prediction list to help me spell. Sure, I won’t use word prediction 99% of the time, but that one percent of the time might be critical to allow people to understand what I am trying to say to them.

Yet science isn’t on my side. At least not strictly so. There is no study that shows that what I say above is actually true.

That’s why the scientific method alone isn’t enough. You also need to couple it with scientific reasoning and general common sense.

Sure, the mercury hypothesis is still wrong, as there is enough science out there to disprove that, and there is no feasible scientific reasoning in support of it. But sometimes in our zealousness to discount the mercury hypothesis, we are hurting people when we require an impossible burden of proof - especially in the area of communication.

Institutional Review Boards (IRB) exist at almost all research institutions that involve human subjects. An IRB’s purpose is to ensure that human subjects of research are fully informed of the risks of participation and that no research places undue risk upon a research subject.

I find it interesting however that I have never heard of an autistic person being asked to participate in an IRB to review research that includes autistic subjects. For some reason, we aren’t seen as having anything to add to the review process.

Yet, US regulations that cover IRBs are actually quite clear on this - 45 CFR 46 specifies, among other things, that IRBs membership should include a diverse membership that includes points of view that may be important in making ethical decisions. For instance, “If an IRB regularly reviews research that involves a vulnerable category of subjects, such as children, prisoners, pregnant women, or handicapped or mentally disabled persons, consideration shall be given to the inclusion of one or more individuals who are knowledgeable about and experienced in working with these subjects.” Unfortunately this law still gets one part wrong: “experienced in working with these subjects” is not quite the same as being in the vulnerable group. I suspect the perspective of, say, a prison guard, while obviously quite experienced with working with prisoners, is going to be very different than the perspective of the actual prisoner.

Even when an IRB doesn’t “regularly review research” involving autistic people, an IRB always has the option of bringing in an outside consultant with specific expertise. This should always be done when research on a vulnerable group of people is done, such as autistic people. And, at least one of these consultants should be someone with actual autism. But make no mistake - for IRBs that regularly deal with research involving autistic people, the autistic person shouldn’t be a mere consultant, but an actual voting member.

I’ve never heard of an autistic person actually being asked to participate in an IRB, though. I wonder why…perhaps we’re not seen as people who can provide any ethical insight into research done to and on us.

This is an area that students, professors, and researchers are very well equipped to change though. Find out who is on your institution’s IRB (note that your institution may have several, such as a campus-wide IRB and a department-level IRB). Ask about who they would bring in if research on autistic people was discussed. Suggest the inclusion of actual people with autism. If you’re a researcher, submitting potential research to your IRB, suggest that an autistic person be included. If you’re part of a large research institution, and your subdivision of the organization often does research on autistic people, consider forming an IRB for your subdivision that specifically includes autistic people and has the proper legal framework to halt research (this in no way prevents the institutional or higher level IRB from also needing to provide approval - it just provides one more place to catch problems). Even if your organization has perfect ethical standards, why wouldn’t you want autistic people involved in reviewing the ethics of research being done on autistic people? Wouldn’t that help an organization avoid the appearance of evil?

I’d love to hear someone comment that they have participated in IRBs, either as an autistic person or with autistic people (and the autistic people should be people who publicly identify as autistic, and can thus fully function as an advocate). I hope I’m wrong and autistic people routinely participate in these things.

In a past article, I showed, using the number 1 in 150 for number of autistics, and the US population, that around 26,000 autistics will be born this year (you can debate whether they are born autistic or not, but around 26,000 will be autistic - either at birth or within a few years, depending on your political views), but 600,000 people will die this year of heart disease. Of course there is nothing amazing about these numbers - they are in line with numbers from other countries around the world. So, in essence, over 20 times the number of “newly created autistics” will die this year due to heart disease. Yet autism continues to be considered “extremely common” and the “biggest health epidemic the nation has ever seen.” No wonder health care policy is such a mess today, if 600,000 deaths a year are ignored for the sake of 26,000 newly minted autistics (I’ll add that most of these autistics will not die fitting the stereotype of a low functioning autistic - most will speak, be able to use the toilet, etc).

But, nonetheless, there has been a particular interest by many in the idea that a polluted environment causes autism. Thus, when there is a “hot spot”, especially if that hot spot is in a place like New Jersey, which, factual or not is known as a place with high pollution, it is assumed that this demonstrates a “connection.”

However, before you can decide that where people live has anything to do with autism, you need to do a few things. The very first thing you must do is to eliminate other variables. Perhaps different areas of the country diagnose autism slightly differently, resulting in different autism rates. Perhaps culture is relevant to the manifestation of autism (the canonical example of this is eye contact, which is useless for diagnostic purposes in some cultures). The average wealth of an area also has a key effect, and must be accounted for in the study. Controlling these variables is beyond the scope of this article, but it is very important and has a very important affect upon diagnosis.

The other thing you must do - and in fact all quantitative science aims to do - is to determine whether two things are connected, or, as scientists say, correlated. When studying rates of something (like autism) in a population categorized by geography, you are attempting to say geography is correlated with the rate of autism. What this really means, to the scientist, is that autism is not randomly distributed geographically. If geography has no connection to autism, and is thus randomly distributed, then you are just as likely to find autistics in Paris as in Denver, or even Brick Township. (This is also called the “null hypothesis” - good quantitate science attempts to prove the null hypothesis, and only when that doesn’t happen is the real hypothesis considered as perhaps being accurate)

That moves us to Brick Township, New Jersey, USA. In 2001, a study was published in Pediatrics which was interpreted to mean that there was an epidemic of autism in Brick Township. This study is often cited by those who want to show that pollution causes autism. After all, if there was an extremely high rate of autism in a certain small geographic area, it might be worth looking into, to determine if there is something that is causing it. However, looking back at that study, we find that 6.7 out of every 1000 children were autistic - in other words, 1 in 149. Being that the commonly cited (by organizations promoting the idea of environmental autism) rate of autism is 1 in 150, it doesn’t exactly look like Brick Township is different from anywhere else in the US. In fact, what is striking is how accurate that 1 in 150 number may be.

So, dismissing Brick Township’s “extremely high” rate of autism (which is the same as the rest of the US’s), we are left with mostly anecdotical reports of “There are 3 autistic kids in my neighborhood alone” and other similar reports to demonstrate that there is “high” rates of autism in some areas. So, how would we determine whether an area’s high rate of autism is a result of correlation with geography?

The first thing you have to do is understand how a random distribution works, so that you can see whether things are random geographically when it comes to autism. If you don’t know what random distribution looks like, you don’t know whether or not the results are a product of randomness.

To do that, I constructed a short Perl program that calculated the number of autistics in 20,000 groups of 300 “children”. Each child had a 1 in 150 chance of being “diagnosed” by my program. Each group of 300 was chosen to represent a medium-sized neighborhood, which might have around 300 kids in it. I simulated 20,000 of these neighborhoods to find out how many would have “more than expected” numbers of autistics, if autistics are randomly distributed. My program created a large datafile which consists of the “group number” (starts at zero and increments to 19,999), the number of “autistics” in that group, and the percentage of autistics in that group’s 300 members.

The raw results were that a total of 40,053 “autistics” were diagnosed by my program. Since each child had a 1 in 150 chance of diagnosis, we would expect a number very close to 40,000 - and we are right on target. Our actual (measured) rate of autism was 1 in 149.8. The random distribution could be graphed as:

As you can see, this very closely resembles a bell curve centered on 1 or 2 autistics out of a group of 300. Now, if I told someone that, in real life, there were 6 neighborhoods in the US out of 20,000 I studied that had an autism rate of 1 in 33, or nearly 5 times the US average, most people would agree that we should study them. But if a scientist only found 6 groups out of 20,000, he would conclude that this matches a random distribution and studying these 6 groups would be a waste of time, as a random distribution would naturally produce a few “hotspots”. Unless the number of hot spots is higher than what could be explained from a random distribution, it’s not worth investigation, as the random distribution sufficiently explains those groups, and it most certainly is not due to pollution or other environmental factors. Now, if 100 groups had a rate of 1 in 33, that would be worth investigation scientifically, as the random distribution would only be able to explain somewhere around 6 of those groups, and pollution, environmental factors, or other variables might be responsible for the higher rate of autism.

Unfortunately scientists know this, but many lay people do not. They hear of a high rate of autism (1 in 33!!!) and immediately say, “Hey, there has to be a cause!” Scientists, however, look at it and say, “1 in 33, okay, but is there a correlation? In other words, could this be explained by a random distribution, or could it not?” Sadly, this is counter-intuitive to many people, and people are often more willing to trust their “instinct” than the scientific facts. Living in a neighborhood with a 1 in 33 rate of autism doesn’t necessarily mean that there is anything but chance at work.

A couple of other interesting facts from my fictional autism data: One third of autistic children are in neighborhoods that have a rate of autism over twice the 1 in 150 rate. And only 14% are in neighborhoods with less than the 1 in 150 rate. This probably explains why anecdotical accounts of “lots of autistic people in my neighborhood” are so common. More autistic people live in neighborhoods with more autistic people (how is that for a truism), and less autistics live in neighborhoods with less autistic people! This is the nature of the random distribution. And, in fact, we know that one third of autistic children will live in neighborhoods (assuming all neighborhoods have exactly 300 kids) with at least twice the normal rate of autism, even if chance alone can explain the distribution of autistic people.

Now of course we know that autism isn’t completely random, and that there is a strong, but not complete, genetic basis to autism. But we must be very careful when looking at poorly designed studies and anecdotes when we look for that “other” causal factor of autism. Statistics, once again, are essential - and if someone doing the research can’t explain why the results couldn’t be explained by the random distribution, that person has no business publishing results, as he doesn’t have the very basic information he needs to draw any conclusion whatsoever (I’ll note that people who can do statistics, in the scientific world at least, probably also know how to use a computer program called SAS, and, even more importantly, how to interpret the results). Statistics are the key to understanding science, and most science - in particular epidemiology - absolutely requires statistics. The statistics are at least as important as going out and counting people. There’s an old saying - “There are lies, damned lies, and statistics.” Perhaps a better one would be “There is faulty research, damn faulty research, and research based on gut feeling.”

I’ve seen quite a bit of bad science lately. I would like to do my part to teach the basics of science.

First, some statistics! You cannot understand the majority of research today without some understanding of statistics. The point of statistics is not to lie (despite the popular myth) but rather to figure out if there truly is significance in the results, or if the results might be explainable by just random coincidence. For instance, someone might want to figure out if men are more or less intelligent than women. If you pick 5 men and 5 women randomly, there is a chance that you just happened to pick 5 extraordinarily dumb men and 5 extraordinarily smart women. You then run some tests on them and find out - get this - that the women are smarter. Another researcher, doing the exact same study, might find, “Hey, no, they aren’t smarter! In my sample men were far smarter!” There are statistical methods to greatly minimize this problem, and these statistical methods are important. The statistical methods also can tell us that the data isn’t complete enough for us to draw a conclusion. “Gut Instinct” isn’t enough.

For example, let’s say I want to do the above study. So I create two groups - a group of men, and a group of women, each with 30 members. I then classify each member of each group into one of three categories - dumb, average, super-smart. I get the following results:

Dumb Men: 5
Dumb Women: 10
Average Men: 13
Average Women: 8
Super-Smart Men: 12
Super-Smart Women: 12

So, it looks like men and women are just as likely to be super-smart, and perhaps I somehow managed to select a lot of super-smart people (perhaps I did my sample selection at a university). But, what is interesting, is that men are much more likely to be average than women - and women are more likely to be dumb. In fact there are twice as many dumb women than dumb men!

But it’s not all as it seems!

I didn’t actually conduct the experiment. I wrote a short Perl program (code available upon request!) that creates two groups of 30 (men and women), and randomly selects a category (dumb, average, super-smart) for each sample member. Thus, if the laws of chance hold out, I should have around 10 people in each category. I didn’t! But it’s still random, just like it is possible for a truly random coin to turn up “heads” when flipped twice in a row, giving a 100% heads rate and 0% tails rate, even though we know it “should” be heads exactly once for every two flips. Small random samples don’t necessarily demonstrate randomness.

Simply put, small samples don’t prove anything.

What does this have to do with autism? Commonly, the “evidence” for therapies, causation theories, etc, are almost always based on a very small sample and a binary event. Kids with ABA become non-autistic (in theory they compare previously autistic kids who both had and didn’t have ABA and record outcomes - two classifications for each group). Vaccines cause autism. They then do this type of research with a handful of kids - not enough to demonstrate statistical significance.

There’s one more problem with this though. Let’s say that all the autistic kids you know received vaccines sometime in their lifetime. Chances are so did the vast majority of non-autistic kids you know! The real question is: compared to unvaccinated kids, is there a difference in the chance of a vaccinated kid becoming autistic? You can’t do this with a small sample size (as demonstrated by my sample size of 30 being broken into distinct groups) using data that is categorical. You most certainly can’t demonstrate it without at least comparing the two groups! And that’s a bigger problem. Most “personal experience” anecdotical evidence in support of (or against) autism therapies, causation, etc, is based on “friend of a friend” anecdotes, which, due to the nature of the evidence, is a limited sample size. Others, instead of selecting a random sample gather their sample from a group that is less than a true representation of the data (consider research that does ignore the existence of adult autistics when proving that autism is a relatively new condition - typically they talk to parents of children and ask if they have seen autistic adults, most of which have not seen recognizably autistic adults very often; that doesn’t mean these adults don’t exist, it just means that they aren’t hanging around parental support groups or people who attend parental support groups).

So be cautious of research. Ask what the sample size was. Ask whether the thing being measured was binary (autistic/non-autistic; recovered/not-recovered; etc), continuous (like IQ), or some sort of grouping (dumb, average, super-smart). Find out how many people were in the other group (it shouldn’t be zero). Ask what kind of statistical test was performed (it should be more than a count, a percentage, or an average). Ask what the computed error was in that test (most statistical tests generate a confidence and/or error values, which let you know how likely the results represent what they claim to represent). Ask why they chose the statistical test they chose - if they can’t explain that, I wouldn’t put much faith into their results. Ask them what the “null hypothesis” that they were testing was. If you really want to know if they know what they are talking about, ask about why they used a given confidence level.

Yes, this requires some work on your part. Most people probably don’t know how to interpret the answers to the above questions, but I think most can learn. Anyone doing science needs to understand these things. Statistics are a key to understanding results and not being “tricked” by randomness!

Stay tuned, we’ll talk high school genetics next time!

There are a couple big news stories this week. The first one was a CDC study that gives a better estimate at the number of autistic people in various states of the US. Besides the fact that the study doesn’t really prove anything - for or against my side - and the fact that it gives a lower prevalence than many other studies, it’s being spread epidemic rhetoric. Those of you who read my blog often know that I tend to dislike epidemic rhetoric, as I’m not a fan of being told that people wish I didn’t exist (and I wouldn’t exist without autism - even a “harmless” cure would certainly turn me into someone else).

It’s rather hurtful to find out that people think the world would be better off without you.

Another story was about some mice that were created to have a Rett-like (Rett Syndrome is one form of autism) condition, with a few major exceptions, like it isn’t really Rett-like at all. But aside from that, it’s being reported as a tremendously great thing because we can possibly cure Rett down the road. There’s just the small part of the “treatment” being so stressful for the mice that many of them died in the process of being treated. But I see no reason why at least some wouldn’t care about that - if it gave them even a hint of the promise of curing their child.

After all, the world would be better without people like me (I don’t have Rett, but I have no doubt people would love to cure my type of autism too).

The problem isn’t the studies themselves. It’s the reporting. It’s the idea that everyone reading the stories would agree that if autism is more common than some people thought, it is a really horrible thing for the world. More people like me, clearly, are a bad thing. It’s the idea that a cure is a great idea, because, once again, it’s better to be neurologically typical rather than like me. Sure, excuses are made up to make these views sound better - they hint at parent’s suffering, or medical conditions that may coexist with autism. But in reality there is a simple and basic assumption: Autism is bad, being autistic is bad, and one day hopefully we won’t have to deal with autistics in our midst.

Some other blogs talking about the new CDC study or the death of mice:

Problems with Prevalence, from Kev’s blog
If they break it, they can fix it…sometimes, from Kassaine’s blog

A few months ago, a study was done that found an apparent connection between alcohol consumption during pregnancy and some cases of autism. The study seemed to be basically well done, and likely found a real connection.

This is in contrast to the vaccine connection. With vaccines, there is no respected study that shows any such thing with vaccines. Even the supporters have resorted to tactics such as claiming the number of “mercury poisoned” autistics is actually so low as to be unmeasurable.

So, why isn’t the research on alcohol and autism being publicized? Why aren’t the leading autism organizations talking about the need to prevent alcohol consumption by parents (and, also, the need for earlier detection of pregnancy, as many mothers drink between the time they become pregnant and the time they learn that they are pregnant). Could it be that this study shows a connection that people don’t like to see?

Or, could it be that there are no big law firms hoping to cash in on the lawsuits? After all, who would you sue? You can’t get the parents to sign up to sue themselves, and parent’s don’t have the money of a mega-corporation, so there’s not much money to go around among the lawyers for such a lawsuit. You can’t really sue the alcohol companies, either, since most of the world has very strongly indicated that they want alcohol to drink, whether it has harmful effects or not - besides, almost every bottle of liquor I’ve seen recently has a warning about drinking while pregnant. I’ve not seen any commercials on TV or in magazines trying to get pregnant women to drink alcohol, either. In addition, and most important, juries understand alcohol and the fact that drinking during pregnancy is bad. It would be hard to persuade them that the alcohol companies are trying to make people drink while pregnant (this is in contrast to the vaccine issue, where the average person doesn’t understand the very technical arguments made by both sides).

So, perhaps there are special interests manipulating parents right now. There are leading organizations who are searching for a cause of autism, while ignoring a very likely cause, at least for some cases of autism. Once again, I ask, “Why is that?”

(for clarity, I don’t know if alcohol causes more than a tiny amount of autism - I certainly wouldn’t accuse any parent of harming their child by drinking, nor do I think guilt over one beer consumed two days after becoming pregnant is in the interest of anyone)

A few weeks ago, I wrote about My Autistic “Superpowers.”

As I’ve experienced in the past, this article was misunderstood by some. One of the people misunderstanding my superpower article was Michelle Dawson, an autistic advocate who I truly admire. I respect her work, and believe anyone would be well-served by reading her writing. Nothing I say below should imply that I believe she is an enemy, as she has done far more for the cause than I have. We do, however, have a disagreement, as reasonable people sometimes will have.

I’ve read her words (you can too - see this page, starting with comments around comment 5193). (Also - if someone knows how to post on her board, please post a link to this message - I don’t want Michelle to feel that I’m commenting about her without giving her the chance to respond) I’ve also seriously considered what she said, and admit that my choice of wording wasn’t as clear as I strive for.

But, I very much disagree with the claims she makes about my writing. She makes several, which I’ll talk about below.

First, there is the claim that I see two types of autistics - people with skills and without. I don’t see people that way. However, I do, as a thought experiment, believe that even a hypothetical “completely unskilled person” deserves rights and respect. In other words, I reject the argument that argues for respect to autistics based on any skill. Even if I believed that every single autistic on the planet had a skill that was superior to the average NT skill, I *still* would find it wrong to use this skill as the basis of arguing for our value in the world. I think there are too many people without demonstrable skills in the world - autistic or not - that are hurt by such arguments. So…I don’t believe in two types of autistics based on skills they have. That’s a reading into my words that’s not intended.

Second, there is a misunderstanding of my usage of “skill”, “superpower”, etc. I’m not talking, for instance, about the types of things Michelle mentions being studied, which show that often times autistics do have skills that haven’t been recognized, because of lumping categories together that should not be lumped together in some research. I trust that the research’s findings is accurate and correct! In fact, I find the research (the little I understand of it - I admit my scientific understanding is lacking in this area) fascinating and wonderful! But not because it shows that we shouldn’t kill autistic people. There are better reasons for not killing *anyone* that can be applied specifically to autistics as well as the general population. Nor am I referring to savant skills, which I find fascinating as well. Nor even am I saying an autistic who has an ability, skill, etc, should be ashamed or embarrassed instead of glad and even proud to have such a skill! I’m saying that autistics (this is a thought experiment - whether the hypothetical example I give actually exists or not is a question for the researchers, but the experiment is vital for building a framework of human rights for disabled people) without skills - if they exist at all - should have the same rights as those with skills.

That said, the skills I’m referring to are not the types of things explicitly tested for in Montreal. Instead, they are things that the average person would see and say “Wow, he’s autistic, but it’s okay because he can …” Generally they aren’t giving the tests used in the research to autistic people and using those test results to draw that conclusion, either! Instead, they note that an autistic has a girlfriend, so, wow, that autistic must be okay and an exception after all. I oppose that type of thinking because of what it says about the autistic who doesn’t have a girlfriend.

Finally, I completely agree that the researchers have found two types of autistics. However, I very much disagree with the labels of “Autism” and “Asperger’s Syndrome” for those two categories. I think something was found that is meaningful and important, and that there are two categories which may or may not be entirely separate diagnostic categories (I’m welcome to correction however). But I also believe there is no standard differentiation mechanism for determining who is autistic and who is aspergic that has gained anything near scientific consensus. Every researcher, doctor, etc, has his own views that they bring into the situation. It just so happens that the Montreal researchers’ views found a separation that actually means something. But until there is consensus on who is autistic and who is aspergic, I believe these categories should be called something else.

I welcome Michelle’s response, and hope I’ve managed to make my side clear. I believe that there is significant misunderstanding every time I say anything about the value of people not being dependent upon any skills, so I’m sort of used to it. But I hope that I can have the chance to clarify what I mean. Once the other person understands my view, I welcome disagreement just as much as agreement - I just want that agreement/disagreement based on what I actually believe, not based on a misreading or miscommunication (I take full responsibility for any misreading or miscommunication, however). I also welcome any correction if and where I’ve mischaracterized Michelle’s views or the Montreal research, as I’m an expert on neither.

From Europe: http://news.scotsman.com/uk.cfm?id=1308572006

The summary of the article was that a supposedly-blind trial became a not-very-blind trial, and had significant difficulties in keeping people in the study for the entire course of the study. The cure this time is “helpful” bacteria.

Many of the parents, apparently, refused to allow their child to receive a placebo and indicated that their children had very helpful results while on the bacteria. Of course the reason placebos are used is to control for “placebo effect” - basically, if you give someone a drug that has no real effect (or give it to their child), but they don’t know it’s useless, often they’ll report benefits from the new “drug”. By giving everyone a ‘drug’ you can look for differences between the group that had the known useless drug and the drug being tested for usefulness.

So, the fact that parents are reporting a benefit isn’t surprising. And once they knew that the placebo was a placebo, the research truly is invalid.

The right response to this would be to fix the bad research, and, if it was warranted research (I’m not sure if it is or isn’t - you have to do a risk/benefit analysis for the research, and also examine the likely effects based on understanding the science behind the research), redo the research. The wrong response is to contact the press about your breakthrough, when your research is at best inconclusive and at worst misleading.

I guess we get to look forward to autistic kids getting injected with live bacteria in the not-so-distant future.