Hi guys, this is a philosophical framework I've been working on. I'm posting the first half because it's intended to refute the status quo and I believe it can also stand by itself. This is my first post so please let me know if I'm doing something wrong.

The human brain is an infinitely complex organism. However, our society has decided to create a rather reductive framework with which to categorize and label certain behaviors and phenomena it has struggled to understand or accept. We collectively refer to this framework as mental illness. I believe that placing certain human reactions in the category of mental illness is ultimately harmful to the individual and society. I will argue the dangers and limitations of the ideal of mental illness. Furthermore, I will propose a different perspective or framework that will allow us to take a more sober approach to problems we now dismiss as mental illness and to ultimately accomplish an internal resolution or “cure”.

The contemporary and scientific approach to the phenomena we now refer to as mental illness bases itself on a complicated underlying analysis that is surprisingly limited. A mental illness diagnosis compiles data from self-reported acceptable symptoms, observed symptoms, self-reported and observed behaviors that are not commonly accepted by societal norms, brain scans, blood tests, blood pressure readings, and a whole host of other medical data. This data is then analyzed within the scientific and pre-approved scope for mental illness. This leads to a diagnosis from a pre-approved list of diagnoses, and a treatment from a pre-approved list of potential treatments.

While the process I laid out may not be applied to EVERY single patient, for the most part this is how everyone is treated once they board the train of professional mental healthcare. My aim is not to attack this process, but rather the underlying fallacious assumptions that make the contemporary view of mental illness ultimately harmful. At every step of the way there are many decisions and assumptions being made that drive us further away from the truth and the root of the problem. These decisions ultimately aim to place individuals in labeled boxes, and if an individual does not fit any perfectly (they rarely do) the system will shove them into the box with the closest fit.

When society first approaches a case of mental illness, they start with the symptoms, that is the data that will serve as the input for the analysis. However, this data is compromised from the very beginning. Self-reported symptoms assume that the patient understands the relevance of their feelings in the context of scientific medicine. A person may underplay or overplay anxiety. They may not be able to clearly identify the differences between anxiety, stress, panic, and others. They may omit symptoms because they perceive the symptoms to be unacceptable or irrelevant. They may fail to recognize symptoms because their upbringing may have conditioned them to believe those feelings are normal or expected. All these possibilities also apply to self-reported behaviors. The reliability of this particular data input is nothing short of awful.

As far as observed symptoms and behaviors go, these are biased by societal and familial expectations of a person’s behavior. A high-energy and motivated individual may seem dysfunctional in certain contexts. An innovative mind may be seen as unable to utilize reason in certain contexts. Observed symptoms and behaviors may be even less reliable data than self-reported ones due to all the biases (of both selection and perception) that the behavior is filtered through. And while some of us might like to think that professionals are immune to these biases because they are trained and professionals, that is a rather naïve assumption. Their perceptions are biased by a myriad of factors that include professional expectations, cultural factors, self-interest, and monetary considerations, among others.

Regarding the objectively quantifiable data like scans, tests, and readings, a lot of assumptions are either made or disregarded depending on the situation. Most of this data is compared with a baseline number or result, we are assuming that this baseline is an apt benchmark to judge a particular individual, which can be troubling. And often times, readings that deviate from the benchmark are attributed to a mental condition if another explanation is not obvious. Assuming that the benchmark used is correct, that these readings can be interpreted based on benchmarks, and discarding extraneous explanations that are not immediately apparent is troubling in regard to data integrity, to say the least. However, even if we assume that all the quantifiable data is interpreted correctly and it is devoid of flaws and biases, it is still mixed in with the aforementioned symptoms and behaviors. This makes the collective integrity of the data almost nonexistent. Thus, the input for the analysis is, in layman’s terms, absolute shit. Expecting a reliable, informative, and insightful output from the analysis is simply unrealistic.

However, to really drive home the point I’m trying to make, let’s assume that our data is literally perfect. It is devoid of any biases, omissions, or anything else that could possibly compromise the data. Let’s assume that our input data is 100% correct with 100% integrity.

This data, or input, is now utilized to perform our scientific diagnostic analysis that will lead us to a conclusion, diagnosis, or output. The problem here is that we are provided with the analytical framework, a pre-approved way to interpret the data. This is limiting to say the least, and the framework is structured to lead us to certain pre-approved conclusions. Some might take respite in the fact that even though these conclusions, or diagnoses, are limiting, they have been scientifically proven so they must be correct and reliable. The troubling aspect of this is that the scientific method lends itself to confirmation bias and groupthink, and this line of thinking also ignores and dismisses any and all explanations that have not been explicitly studied by science using a very specific and confining system or method.

Even with perfect data, the system that we use to analyze it leads us to likely unreliable conclusions and diagnoses. We then treat these already unreliable and limiting diagnoses with pre-approved treatments that have been developed with the same limitations, pitfalls, and biases as the pool of potential diagnoses. And this is all without taking into account the capitalistic incentives embedded in all the treatments. The industry of treatment makes money with treatment, a cure stops treatment and thus stops cash flow. I do not want to delve into how profiteering further corrupts our societal framework for mental illness because that is too big a topic. Furthermore, I believe that the current framework lends itself to profiteering, so reforming the framework is likely to better align capitalistic incentives.

I said I was gonna propose a different framework, and I will, but this ended up being much longer than I expected and I’m tired. Please let me know what you think, and any questions you may have that help clarify my argument. I will happily address any perceived fallacies in the analysis since this will only make the argument more compelling.

Thank you for reading!