Self-diagnosis

Post Reply New Topic

Don't miss the key point:

Self-diagnosis of autism doesn't mean you are autistic.

You don't know if you are autistic (or not) until medical diagnosis.


Hence you only have suspicions.

I think quite a few people said this quite a few times within this thread.

The DSM and ICD diagnostic criteria for autism are very easy to understand. Some Internet searches for clinical and university exemplars yield very good information to explain details of the criteria. If an individual is willing to compare the criteria and clinical exemplars to the individual's own life, it would be apparent quite quickly if they match the behaviors, characteristics and comorbids of the individual. It is remarkably easy to use all this information to conclude accurately whether an individual is likely to be autistic. I accept that a nonprofessional conclusion means little in accomplishing a diagnosis. But, in my case, at least, my diagnosticians actually thanked me and offered to refund part of my assessment fees because I had "done so much of the work" that they would have had to do themselves. I describe this experience only to demonstrate that, if a layman can do "so much of the work" in his own diagnosis, it is also likely that any layman can arrive at a conclusion (suspicion) that he or she is self-identified as autistic to a degree that approaches the certainty of professional diagnosticians. After all, most self-reported screening tests are accurate to the 80th percentile or better compared to clinical diagnoses.

So... Do you still exist?

Did you ever exist? Do I exist? Oh, Gawd!

I think, therefore I am.

Literally no one in this thread argued with you about this, myself included. You repeatedly stated that someone isn't autistic until diagnosed. That's what started this whole debate.

I don't really feel the need to continue this, as we now agree.

So, autism is a communication disorder, among other things. So it stands to reason that if you relate to Autistics you might not be communicating clearly.

I recently used a method where I wrote down a detailed paper on all of my sensory, emotional regulation, and social communication challenges. I included specific examples. The mental health professional said that the paper alone was proof I was obsessive, lol. It was 8 pages long! But after reading it, I had the first "Real" conversation I've ever had with a professional. I was never able to get my words around what's going on with me. Writing out a detailed report of my concerns really let the conversation shift.

You're confusing the phrase "norming" for making new criteria. Norming is a process where they take a standardized test like the ADOS or the WAIS and they figure out where most people fall in their score. They decide what is "normal."

It is already good testing process to norm a standardized test on various populations. Different ages are included. Different social-economic situations. And yes, different genders. That the autism tests haven't been normed for gender differences is a blairing example of things gone amok. It is broadly accepted in professional circles that autism shows slightly differently in girls. We have all those results. But they still haven't normed the diagnostic tests according to gender.

All this stuff about letting people be themselves would be fine and dandy if one of the genders wasn't consistently getting shafted. Ignoring gender differences really means letting boys continue to define the disorder and making girls be just a sub-set of boys. Men are the standard and women are judged according to how well they fit the male standard. If you turn that around, and try to judge how well boys fit into the female standard, you'll get a revolt. But judging girls by mens' standards is just fine. That's what gender bias is all about.

You can see other examples of this in the study of hear disease, stroke, alzhimers, ADHD, the administration of certain drugs- most recently, they discovered that women were being overdosed by twice the needed dose because all the ambien studies were normed on men. Its a large issue that is bigger than autism and has nothing to do with letting people be themselves. If you have a female body, you will still need 1/2 the dose of ambien as men. Because women are not just smaller men. We do have differences.

Yes, sampling bias is (one of the) largest elephants in the room of autism research.

I see it every day and that it passes unseen and/or unchallenged so often by so many is hard to fathom sometimes.

Why can't they use a diverse population: boys, girls, transgender people, people of all different cultures, ETC, and create diagnostic criteria with ranges that would satisfy all these groups? I get why this is necessary for physical conditions where people are physically different. I don't get why this segregation should apply to psych research. Wouldn't we start getting criteria that are considered pathological for one gender or group, while being within the norms for another group? How does this help anyone? It especially doesn't help people who feel they don't fit into whatever group they were classified in.

The thing is, aren't you creating new criteria, in a sense, if you Norm the tests based on different groups? Aren't all of these tests measuring and pathologizing thoughts and behavior, in some cents?

It's an immense issue in research design. The use of control groups is mandatory in many designs, because you need comparison groups in order to estimate whether the semblance of difference is real. That's the theory, and in itself there is no problem there.

However. (And it's a very big however, can't go into it much here). Choice of the control groups in social science is subject to conflicting variables, including pre-existing beliefs that the researcher may have (and often does) though these may not be held consciously.

Thanks, B19. You're right about the need for control groups when measuring differences. The question is, which ones? Should there be a control group for each gender? Each race? Each country? Of course, you could compare someone to multiple control groups and get different results, or try and control for all the factors to see if their difference is statistically significant. This is all well and good for research.

What happens though when clinicians start treating people differently based on assumptions made because of their gender or race or whatever? It's one thing to research differences. It's quite another to base diagnoses and clinical judgment on test results that differ across groups. The clinicians would be making assumptions, rather than treating functional limitations as an individual. If you're a boy and get Score X, we can't diagnose you. If not, well then, you definitely have an impairment. Maybe I'm still misinterpreting something, but I see a definite potential there for giving different treatments to different people who may display the exact same symptoms, based on their compared test scores.

Let me focus on one specific word from your sentence:

likely


Someone can only conclude that their suspicions may be correct.


But until medical diagnosis, 'likely', 'possibly', 'most certainly' etc all fall under one term:

Unknown.



It is remarkably easy for me to read the diagnostic criteria for a brain tumor and assume my sore head is a brain tumor (I personally wouldn't say my conclusion is 'accurate' - or a conclusion).

Could it be a tumor? Yes.
But it may also not be a tumor.


This is the point I was trying to make with the sun rotating the earth analogy.

Why did people believe the sun rotated the earth? Because it looked like it did. What does the earth rotating the sun look like? Exactly the same.



There's a jump of logic here.

I think that an individual has a good understanding of psychology and knows that most symptoms that present themselves in any condition are ones that manifest themselves in a severe manner, can properly diagnose themselves.

The individual knows themselves far more than the psychiatrist, hopefully. Also have you seen some of the people that graduate with psych degrees??

Here's a made up example DataB4: suppose that I decide to study whether autistic children like popcorn more than neurotypical children. I approach the research design in good faith, and I ask the local children's health clinic to select every tenth child from the last 500 autism diagnoses they have made. (Just say). For my comparison group of NT children, I select every tenth child from 500 children enrolled at a normal school, ruling out those who have ASD. Is that a good design? Many would say that it is.

One big difficulty is the assumption error built into the general notion of the validity of comparing clinical samples with "normal" samples in this way. One of the problems is that you don't know how normal either group really is. Are clinical samples of ASD children enrolled at a clinic different from ASD children who are not enrolled, and is the difference between THOSE two groups significant in itself? Likewise the "normal" children may be significantly not normal to the real norm (ie if we could measure everyone on a characteristic, which we can't) in a number of ways. Perhaps the school is in a particularly poor or wealthy area, for example.

There are so many fish hooks. One thing that I would like to clarify in passing is that 'bias' in science usually doesn't refer to intentional bias on the researcher's part. Bias is considered to be faulty factors that result in findings that appear real though are not ("artifacts").