Ten Research Methods Articles Every Parent Of an Autistic Child Should Understand

Perhaps understandably, many parents of autistic children keep an eye on (or attempt to keep an eye on) the latest research and treatments. Parents' lists are regularly flooded with discussion of various treatment methods, medical research studies, psychological studies, and just about anything else one could imagine... most of it related to research.

At the same time, the average parent knows around as much about how research is conducted and about what study findings really mean as does the average sixth-grader. This combination is very much not a good thing.

Simply put, many of the conclusions parents reach when reading the literature are not anywhere near accurate. Even many of the most basic aspects of research are commonly misunderstood in truly dramatic fashions.

The ideal solution, of course, would be to sit every parent of an autistic child down and give them a series of college-level (undergraduate or postgraduate) classes on the scientific process. Unfortunately, this is pretty spectacularly unrealistic. Frankly, many parents could use classes on critical thinking skills, too, but that's every bit as unrealistic.

As such, I've compiled a "Top Ten" list of papers which cover things that most parents don't get. Of course, like any such list, there are a number of biases operating in how I've constructed this. Perhaps a reader will be able to spot some of these... and, as an exercise for my readers, I've tried to make a few of them as blatantly obvious as possible. Narrowing this down to ten papers was emphatically not easy, and there are a number of papers which almost (but did not quite) make the cut for a variety of reasons. I may blog on a few of them later.

To finish: for the purposes of this list, I've defined "research methods articles" as any peer-reviewed writing dealing primarily with the design, conducting, and interpretation of research.

Edit: Also note that there's usually more than one good article on any of these topics, and I excluded "duplicate" articles. I often had to drop very good articles which deserved to be on this list because of that.



10. Strech & Tilburt (2008). Value judgements in the analysis and synthesis of evidence.

One of the (many) reasons why conflicts of interest are so important when dealing with research is the fact that there is a lot of wiggle-room in experimental design. Scientists routinely make value judgments in designing and interpreting research, and this paper serves to highlight many of the ways in which this impacts the process of research.

Just as a quick illustration: how do my value judgments impact the content of this top 10 list?



9. Rutter (2008). Epidemiological methods to tackle causal questions.

In this paper, Matthew Rutter (who I admittedly have issues with relating to other works) discusses the issue of attempting to determine the cause of something without being able to manipulate it in a lab (or clinical trial, etc.). Of course, in the modern autism world, it's more important to understand how it's possible to establish the reverse -- that something is not the cause of something else -- without an experiment... and that is, admittedly, often far simpler.

8. Lesaffre (2008). Use and misuse of the p-value.

Statistical significance testing is one of the most ubiquitous aspects of the modern scientific process. Unfortunately, it's also the source of many of the problems with it. As scientists haven't been able to find (or settle on) a better alternative, however, it still pops up just about everywhere.

One statistic -- the p-value -- is central to this process. Unfortunately, many people (including scientists) misunderstand just what the p-value is, what it means, and what it represents. Lesaffre's paper discusses this and the issues surrounding it.



7. The PRISMA statement.

One of a number of "reporting standards" documents which standardize scientific reporting in the medical literature, the PRISMA statement deals with systematic reviews and meta-analyses, and specifically with which items of the review's process and methodology most need to be reported.

The other documents of this type (e.g. the CONSORT and STROBE statements) are also very important, but the PRISMA statement deals with ways to document the possibility of biases that effect the process of drawing a conclusion from the entire body of available literature. By contrast, the others deal with the conclusion of single studies.

Of course, since what's important is understanding, most interested parents should read the explanation and elaboration document, not the PRISMA statement itself.

Were I doing a longer list, the CONSORT statement, at least, would be in here. As is, however, I believe that the biases covered by the PRISMA statement to be more important for parents of autistic children to understand... and, frankly, I felt that one major standards document was enough for this list.



6. Manchikanti (2008). Evidence-based medicine, systematic reviews, and guidelines in interventional pain management, part I: Introduction and general considerations.

The concept of evidence-based medicine has revolutionized clinical practice over the past few decades. This article discusses the concept of evidence-based medicine, its history, its tools, and countless other related topics, providing a great introduction to the medical literature... and provides a basic foundation for understanding it.

Best of all, it's available for free.

5. Ioannidis (2008). Perfect study, poor evidence: Interpretation of biases preceding study design.

Even if a study is designed, conducted, analyzed, and reported perfectly, it can still be biased or otherwise flawed in a large number of ways. This paper reviews and discusses this phenomenon, including (but not even close to limited to) such factors as poor scientific relevance, straw man effects, and the importance of the analysis of the geometry of a research field.

4. Ioannidis (2008). Why most discovered true associations are inflated.

When something is first discovered, researchers' estimates of its importance are generally exaggerated. This article discusses this phenomenon and the reasons for it, painting an unusually frank and readable picture of just why this happens.



3. Ioannidis (2005). Why most published research findings are false.

One of the more annoying aspects of science is the fact that we know that most of our discoveries are simply wrong. The problem, however, is that we don't usually know which ones until far later. This is one of many reasons why replication is so important in the sciences and why the habit of interpreting individual studies, taken in isolation, as "definitive" is really, really problematic. "False positive" findings abound in science -- especially the social and medical sciences -- and often lead armchair scientists or doctors astray.

This paper, one of the most influential papers published in the last decade, discusses this phenomenon and the reasons for it. If you have time to read the responses and the discussion that followed the publication of this article, that is also very much worth the effort of doing. I particularly recommend Mooneshinghe, Khoury, & Jannssens's (2007) essay, Most published research findings are false—But a little replication goes a long way.

The full text is available for free. I really love open-access scientific literature. Long live PLoS!



2. Altman (2002). Poor-quality medical research: What can journals do?

Poor-quality research is a problem in any field. Simply put, it's possible for a poorly-designed study to find anything, no matter how absurd. If I really wanted, I could easily design a study that, while looking legitimate to uninformed non-experts, would conclude that the Rocky mountains are flatter than a random pancake from IHOP. There is even precedent for this.

This is why expertise in experimental design and research methods is so important... both for designing and interpreting studies. Critical appraisal of any research is key, and you can never just trust the author's interpretation of his own work. It's also a large part of why a number of processes (e.g. peer review) are in place and why doctors get so up in arms about irresponsible media reporting.

And this article is available for free from JAMA. Have I yet mentioned that I love open-access literature?

1. Simon (2008). Lost in translation: problems and pitfalls in translating laboratory observations to clinical utility.

Where to begin? This one article manages to cover about half of what's wrong with modern clinical autism research and with autism research funding priorities. Forget the political issues involved and the tie-ins between genetic research and prenatal testing. Forget the issue of whether a medical model is appropriate for autism or not. Forget even the normocentric bias which pervades most autism research and the question of whether or not it is appropriate to view autism as a disease.

Today, most funding into basic research into autism goes into attempts to understand the underlying biological processes that differentiate autistic and non-autistic individuals. This is a tremendously complicated task, one which has countless problems which I could rant about for hours. The sheer amount of money which this task has already gone into this task (and which it will likely require in the future) is mindboggling... not to mention researcher time and effort, etc.

This doesn't mean that I think that the task is worthless. Basic understanding of biological factors and processes is rarely worthless. There are, however, a phenomenal number of difficulties in taking these (usually incomplete) understandings and doing anything useful with them. At the same time, other approaches (what Simon refers to as focusing on "predictive laws rather than on trying to understand the [biological] why of those laws", p. 2 of the author's manuscript, parenthetical word added) offer far better cost-effectiveness... and neatly avoid a lot of the convolutions in the process which Simon spends the rest of the paper explaining.

Edit (3/21/10): An excellent discussion of some of the factors I'm trying to talk about can be found here. A dissenting -- but still valid -- opinion regarding that specific application can be found here. Many thanks to Tyler Cowen and Michelle Dawson for highlighting these and pointing me in their directions. Additionally, to avoid a misreading of the above: focusing on predictive laws does not avoid the need for translational research; it simply makes the process thereof less convoluted. One example of this would be in finding and using valid and robust surrogate endpoints within studies... but this is a much, much longer discussion.

This paper (the author's manuscript of which is available for free here) is an excellent discussion these problems... albeit in a different context. This context actually represents the paper's largest flaw, one which annoys the heck out of me: Simon is a cancer researcher and the paper was published in a cancer research journal. If, however, we are to understand the issues involved with taking the medical research models applied to cancer and applying them to autism (as Autism Speaks and others repeatedly insist on doing), we must first understand the issues with those models in general -- and they very much have them, even when they're used appropriately. This paper does an excellent job of highlighting those.

Edit: Corrected a spelling error.

Research Priorities

There was a recent conversation on the ASAN discussion list about research priorities and the ASAN's policies about supporting (or not supporting) certain lines of research. While I cannot speak for the ASAN as a whole, I can outline my own opinions on the matter.

It is common practice to divide research into so-called "basic research" and "applied research". Simply put, basic research involves finding out what the heck's going on; applied research figures out how to change and/or improve it. Basic research produces knowledge which informs and guides applied research; applied research produces what we commonly refer to as "technology".

For an example, a study that investigates the way autistics learn would be basic research. A study that investigates how to best teach autistic students would be applied research. For obvious reasons, the latter sort of study benefits considerably from the former -- it's far easier to design a teaching method when you understand how your student learns.

Judging the value of applied research is comparatively simple and straightforward. Its value is a function of that which it creates. Research into ways to make autistic children act like neurotypical children, for instance, is highly valued by those who view this as an important treatment goal and actively opposed by many (if not most) of those who do not.

Attempting to judge the value of basic research, however, is notoriously more tricky. Most people, however, judge the value of a concerted effort into investigating a basic research topic as a function of the value (or percieved/expected value) of the applied research that it is expected to inform.

Because of this, you can tell a lot about a person (or an organization) by the areas of research (basic or applied) that they prioritize. Autism Speaks, for instance, funds a lot of research into the genetics of autism. What does this area promise?

Well, given that gene therapy is (at least for now) a pipe dream and the extent to which we (don't) understand the human genome, the main benefit of knowing which genes cause or contribute to autism would be in the area of testing. Simply put, that knowledge would allow us to develop a genetic test.

The primary "advantage" of a genetic test is that it can be done prenatally. Going by historical data on how such information has been used, this means that it will be used to selectively abort fetuses that will develop (or are judged "at risk of developing") into autistic children.

This says quite a bit about Autism Speaks.

As for my own research priorities? I just want more basic research into the ways autistics think and learn. There's a reason why I almost always enjoy Michelle Dawson's papers.

Grad school does strange things to your mind.

Now that I'm between semesters (school starts back up again on Monday), I have a bit more free time. I've been using some of it to read non-ABA research as, frankly, I'm getting sick and tired of certain tendencies in the ABA literature.

To this end, I picked up a 1982 paper by Kahneman and Tversky which was published in Cognition. The paper is entitled On the study of statistical intuitions, and is the earliest academic citation I could find for conjunction fallacy... although the usual "original experiment" is another paper.

In my reading, however, I came across the following:

Errors and biases in judgement under uncertainty are the major source of data for the mapping of the boundaries of people's statistical intuitions. In this context it is instructive to distinguish between errors of application and errors of comprehension. A failure in a particular problem is called an error of application if there is evidence that people know and accept a rule that they did not apply. A failure is called an error of comprehension if people do not recognize the validity of the rule that they violated.

An error of application is most convincingly demonstrated when a person, spontaneously or with minimal prompting, clutches his head and exclaims: 'How could I have missed that?'

I laughed.

Then I realized that I'd been finding a peer-reviewed journal article humorous. Gyah, does grad school ever mess with your brain...

What. The. HECK?

Recently (within the last week or two), I got into something of a debate with Michelle Dawson regarding the internal validity of single-subject designs. As a result, I've been spending some time reviewing the literature and looking for a design to pick apart. While doing so, I came across a paper entitled "Functional analysis of stereotypical ear covering in a child with autism."

The abstract -- the entire abstract -- is as follows:

We studied stereotypical ear covering in a child with autism. Results of a descriptive analysis were inconclusive but revealed a correlation between ear covering and another child's screaming. An analogue functional analysis showed that ear covering was emitted only when the screaming was present.

Way to avoid citing other literature, people.

The rest isn't much better. To quote the last paragraph of the paper:

These findings suggest that ear covering was maintained by negative sensory reinforcement (noise attenuation) and illustrate the importance of linking descriptive and analogue functional analyses when idiosyncratic events are implicated in behavioral maintenance. Whether a similar relation between ear covering and noise occurs for other children with autism awaits further investigation. However, the current data set implicates a previously unidentified source of reinforcement as one possible cause of stereotypical behavior.

Umm... that is most certainly not a "previously unidentified source of reinforcement". Documentation on what we politely call "sensory issues" in autism goes back a biiiiit further than 2003.

A Book Review

As a grad student, I do a lot of reading. Some of it I enjoy. Some of it... not so much. Some of my reading is assigned for my classes; some of it is purely to help with my assignments. And, every now and then, I get to engage in that most rare of reading activities: reading for my own pleasure.

Don't get me wrong here. I love psychology. I even have a T-shirt that says so (with the elaboration, "It's a conditioned response"). It's just that ABA isn't my main area of interest... and many of the articles are simply appalling. Overall, it's fun, mind, and some of the articles are very interesting, but I find that I have to remind myself why I love psychology from time to time. If I didn't, it'd become a "mere" perseverative interest, and I don't want that.

Not that I don't love my perseverations. I do. It's just that perseverations shift. Psychology is something that I never want to get bored with.

Sunday, through a series of coincidences, I found a book that helped me to remember why I chose this field.

The book, entitled The Psychology of Harry Potter, is a gleeful romp through J. K. Rowlings's fictitious world. Each chapter, written by various experts in a wide variety of fields of psychological science, applies a different aspect of psychology to various parts of Harry's world, including:

• Why wizards lack ability with logic and common sense (Chapter One; you can blame it on Hogwarts)
• The ways the House system encourages conflict and divison (Chapter Three)
• The woeful inadequacies of Hogwarts's career councilling services (Chapter Four)
• The romantic attachment styles of the main trio of the book, as interpreted under the lens of attachment theory (Chapter Six)
• The ways in which Harry's various losses have helped him grow as a person(and why he's not an utter wreck after growing up with the Dursleys; Chapters Seven amd Eight)

And, of course, many others. There are, in fact, a total of twenty-two articles in the volume.

In addition to simply being fun, however, the book serves as an introduction to many basic psychological principles and research. I can think of few texts that illustrate the application and real-world relevance of psychology in such an entertaining manner.

This isn't to say, however, that the book's a substitute for formal instruction. It isn't. But, for anyone who wishes to learn about the discipline, I find it difficult to think of a more entertaining way to get acquainted.

This is, oddly enough, especially true for autistic individuals. I do not (for obvious reasons) have figures on how many of us have perseverated on Harry Potter or related phenomena.

It's my firm belief that the discipline of psychology could use more autistic psychologists. Books like this are a great way to develop a love of the discipline. They are also a fun way to come to understand some of the things about NT behavior that have confused us throughout our lives.

That's not to say that this book is perfect. Some of the chapters (e.g. Chapter Two) are worse than others. As educational entertainment, though, The Psychology of Harry Potter is top-notch.

And if anyone wants to debate any of the points made in any of the articles... I'm game.

Still more on Ozanoff et al., 2005

As I've said before, one of the major advantages of being a grad student is access to the faculty. I finally got to speak to someone familiar with the MMPI about Ozanoff et al., and several interesting things came from the discussion.

First off, the L scale (one of the validity scales, intended to detect attempts to represent yourself as "better" than you really are) probably isn't valid for assessing autistics. I commented on that a bit in my previous post, but I wasn't fully aware of the sort of questions that were involved in the L scale.

Simply put, autistics would legitimately answer many of them in a different manner than neurotypicals.

What I found out about the restructured clinical (RC) scales, however, calls into question a number of things about my first set of observations. At least some of the effects I noted are probably explainable by the differences in scores on the RCd, or demoralization, scale, which measures common factors that influence all of the original scales.

For the record, the autistic group scored higher on that one.

Of course, even within the RC scales, there were effects. Aside from the aforementioned effect on the RCd scale, the autistic group scored higher on the RC2 scale, which measures low positive emotions. This is probably explainable by the fact that nearly a quarter of the selected sample had a diagnosis of major depression... and the change in the statistics when these persons are factored out supports this conclusion.

Finally, autistic individuals scored lower on the RC9 (hypomanic activation) scale, which basically measures hyperactivity. I'd comment on how interesting this was if the effect was anywhere near substantial.

You see, even with everything I've mentioned so far? None -- none -- of the autistic means were in the clinically significant range. While there was one scale (8/8-K, officially known as the schizophrenia scale, which measures odd thinking and social alienation) in which 40% of the sample was in the clinical range, this only really means that 40% of the sample thought "strangely" enough and were socially alienated enough for the result to attract a doctor's (or a psychologist's) attention.

More on Ozonoff et al. (2005)

In a previous post, I spoke about a 2005 study on the MMPI profiles of "high-functioning" autistics. In that post, I mentioned that there were aspects of the study that I couldn't comment on too much as I lacked critical knowledge.

One of the advantages of being a grad student, however, is access to university resources. At Nova, this includes an entire (small) library dedicated to psychological testing. Given that the MMPI is the most commonly used psychological test -- period -- the fact that it included a good bit of relevant documentation should be no surprise.

It took me less than five minutes to find information on the PSY-5 scales. It took me somewhat longer to photocopy the relevant pages, but a good bit of that time was spent looking for a copy machine.

The RC scales, on the other hand, weren't covered in the books that I looked through. Fortunately, however, another benefit of being a grad student is access to the faculty. I plan to ruthlessly exploit that to gain relevant knowledge.


In any event, I forgot to mention a few things in my last commentary, namely the validity scales. The autistic group in Ozonoff et al.'s study scored higher on the L, F, Fb, and Fp scales overall.


Those scales are primarily intended to detect attempts to misrepresent yourself by appearing as other than you are. While Ozonoff et al. do not discuss any of these results other than the L scale, they attribute that effect to "limitations in insight and self- and other-awareness". I believe that this explanation is somewhat contrived.

Given that this study was authored in part by the personnel responsible for diagnosing the persons involved, given that this study was authored by at least in part by personnel at the clinic that the subject pool was recruited from, given that the authors take a psychopathological approach to autism treatment, given that the test was presumably administered by the personnel in question, and given that the treatment methods based on that approach usually involve what amounts to training the autistic individual to pretend that they are neurotypical, I suspect that the real explanation is just a bit simpler.

On the PSY-5 scales, which are based around something akin to the Big 5 Personality Factors, the autistic group typically scored lower on the aggression and disconstraint scales. The aggressiveness scale is exactly what it sounds like... which is interesting, given the stereotype of autistic children as aggressive.

The disconstraint scale, on the other hand, is a measure of risk-taking, impulsivity, untraditionality, and lack of preference for routine... among other things If this sounds a bit backward, it is. Most of the PSY-5 scales are defined as the opposite of Big 5 personality traits.

Finally, the autistic sample scored higher on the introversion scale. This... shouldn't be a surprise given that a low score typically means that the person is highly social in nature. While I think that this is a real effect, I have to wonder about the possibility of they study's use of psychology students as a sample contaminating this result.

And that is all I can add until I get around to talking to someone who can help me interpret the RC scales.

Autistic Personality Disorder?

Someone e-mailed the ASAN mailing list recently seeking advice about seeking services. Part of the delemma involved her local vocational rehab service paying for a doctor who concluded that she had schizotypal personality disorder instead of Asperger syndrome, which she already had a diagnosis of.

According to the message, this conclusion was based on the results of a test that sounded an awful lot like the MMPI.

Beyond the clinical malpractice involved (the MMPI shouldn't be used as the sole basis for a diagnosis), there's the issue of the test's validity in assessing autism. Specifically, it isn't any more valid for that than it is for assessing brain damage.

I can say that with confidence now, thanks to Michelle Dawson. When I commented on the matter, explaining the MMPI and how it works, I added a comment that I wasn't aware of any attempts to validate the test for an autistic population. She then mentioned that there was a paper on the MMPI-2 and autistics and provided me with the citation. When I mentioned that my university didn't have access to the 2005 issues of the journal it was in (NSU does have access to the 2003 and 2004 issues), she e-mailed me a copy.

I've done a citation search and a reverse citation search on the paper as well -- and a keyword search in PsycInfo for good measure -- so I can say with a good degree of confidence that it's the only published paper on the topic. There may be more in press, of course, but that's not reference material that a clinical practitioner would have access to, barring highly unusual circumstances.

I estimate the odds of these circumstances (such as the clinician being on the research team for a follow-up study) to be somewhere between the odds of me getting struck by lightning within five minutes of finishing this blog entry and the odds of me winning the next lottery.

For the record, I haven't purchased any tickets.

The study itself is pretty interesting. I have my fair share of issues with the intro, of course, mainly due to the purely psychiatric/psychopathological approach that it takes to explaining what autism is. Others have written extensively on this topic and the sort of harm that this sort of thing can do, however, so I won't go there.

The experiment itself was actually pretty simple. They gave the MMPI-2 to 21 "high-functioning" autistics and Aspies, then did the same to a control group. Following this, they compared the resulting profiles.

I have my fair share of criticisms of what they did. For one thing, the sample sizes were far, far too small. The initial autistic group was composed of 21 adults (a mix of "high-functioning" autistics -- defined as those who could score in the normal range on the WASI -- and Aspies), which isn't even enough to expect a decent standard distribution, much less an adequate comparison between groups. Of these, one was disqualified from consideration (he left too many questions blank) meaning that the final autistic sample was only 20 people.

Similarly, the initial non-autistic sample consisted of 25 college students, recruited from an introductory psychology class. Of these, one was disqualified... apparently for trying to just answer everything with the same response regardless of what the question said. The TRIN scale (one of the MMPI's validity scales) measures attempts to do that.

The experimentors did try to match the samples, at least, and did so based on WASI results, age, and gender. Unfortunately, college students aren't representitive of the general population, and students from an intro psychology class are less so than most. I am not certain how this may have effected the study, mainly because I'm not sure about differences between college students and the general population on the MMPI. I will note, however, that this fact introduces confounds.

Fortunately, however, the authors acknowledge most of the above in their discussion.

Judging by the results, it looks like my initial concern (that the correlational relationships that the MMPI is based on might not hold true for an autistic population, thereby rendering the test results invalid) isn't the case, at least for adult, "high-functioning" autistics and for adult Aspies. That said, the reporting conventions are one area where I have... issue... with the study. Simply put, no statistical significance testing was conducted.

Fortunately, there's enough data reported that you could, theoretically, go back and conduct significance testing yourself. Unfortunately, this is a pain in the butt when you have to do it for 61 sets of data. I suppose that I could use a spreadsheet to do it for me, but it's still an annoyance... especially since it's standard practice to report this stuff.

The explanation given in the paper is as follows:

Because the sample sizes in this study were modest and this investigation is exploratory and descriptive in nature, effect sizes (e.g., the magnitude of group differences), ds, are reported, rather than statistical significance.

This makes sense, after a fashion, but it makes replication with a larger sample essential... and doesn't really excuse the annoyance. Given the way most statistical packages are set up, reporting the relevant data is roughly five minutes' work.

On the plus side, this has rather forcibly reminded me that I'm getting somewhat out of practice with calculating statistics and solving equations by hand.

So, that taken care of, what were the findings? On the core scales of the MMPI, the autistic sample scored higher on the tests for depression (even after five autistic participants who had a diagnosis of major depression were excluded), social introversion, and schizophrenia. This last would be more meaningful were it not for the fact that the MMPI's schizophrenia scale really measures social alienation and ways of thinking that are different from the norm. Autistics also typically scored lower on the hypomania scale.

One issue that this brings up is the issue of exogenous versus endogenous depression. The autistic sample was recruited from the University of Utah Child and Adolescent Specialties Clinic, meaning that all of them were treated there. This means that they all had at least one life event in common, and, in fact, the article mentions a second: all of them were diagnosed by either Dr. Sally Ozonoff or Dr. Janet E. Lainhart. The possiblity of a relationship is not considered in the paper... and the MMPI does not make a distinction between the two types of depression. Although, as a personality test, it is presumably designed to focus on depression as a personality trait, I know of at least one study that uses the MMPI to evaluate non-trait depression in the form of postpartum depression. While vulnerability to postpartum depression may be a trait, it is difficult to consider the depression itself to be such.

This is not to accuse Dr. Ozonoff or Dr. Lainhart of malpractice. I know very little about either of them... and less about their clinical practice. This is, in fact, precisely why I point out the above possiblity. The paper does not even begin to address this challenge.

On the content scales, the largest group difference was that autistics scored higher on the social discomfort scale. This... should not be a surprise. Their higher scores on the low self-esteem scale is probably related to a combination of environmental effects and the depression difference noted above. This is also backed up by an elevation of the negative treatment indicators scale, which measures physical and emotional distress.

I'd also like to mention an elevation in the work interference scale, which measures personal difficulties that interfere with work. This, too, is hardly news to the autistic community.

For the supplementary scales, the autistic group scored higher on the repression and anxiety scales. Again, this can easily be explained by life events. Certain nasty things, like bullying, tend to happen to us.

On the other hand, the autistic sample scored lower on the MacAndrew Alcoholism-Revised scale and the Addiction Potential scales, both of which measure vulnerability to substance abuse. Way to go, us!

On the other hand, this may be because we're painfully aware of the dangers thereof.

Then, we come to the ego strength scale, which is a bit tricky to explain. While it was originally intended to asess the degree to which a client can benefit from psychotherapy, this is by the standards of psychoanalytic theory. As such, it seems to measure adaptability, personal resources, tendency to seek help, ability to deal with others, and good physical health... among a host of other things. The autistic group scored lower, overall, on this measure... but, given the sheer variety of things that it assesses, I'm reluctant to ascribe meaning to this.

The rest of the results pertain to the revised clinical (RC) and PSY-5 scales. Unfortunately, I lack critical knowledge needed to properly interpret this and will be seeking information over the next week or so as I try to avoid spending the eighty bucks or so needed to buy a proper assessment book. I have an old copy of Graham's textbook on the MMPI (I picked it up at a book-sale), but it doesn't provide information on them. As such, I'll need to do some more searching.

Another interesting set of data provided is the percentage of the sample who provided clinically significant scores on the various scales. 40% of the sample provided clinically-significant elevations in the schizophrenia scale (I discuss the meaning of this briefly above, but suffice it to say that I doubt it means that the description of autism as "childhood schizophrenia" was even partially right)... and the post-traumatic stress disorder scale.

I don't believe I need to explain why that last bit is worrying.

The discussion for the paper was, overall, well-researched as far as I can tell (I'm not familiar with all of the papers cited), but every bit as... off... in tone as the intro.

And, of course, the article does absolutely nothing to change my opinion that the MMPI is completely inappropriate as a diagnostic measure for autism.