The Absence of Normality

The Absence of Normality

In behavioral science, normality appears defined as the absence of the characteristic being studied. Behavioral research experiments typically recruit at least two groups of people; one group that has been screened to ensure they show behavioral traits of the abnormality being studied, and another group that does not display these traits – the control group. Any number of tests can then be given to all groups and any differences that appear based upon group identity can be verified statistically and the difference published as a finding.

However, it is worth noting that there are no studies determining normality in mental health, after all, in a field that struggles with resource and funding, what would any research team have to gain by pursuing a credible diagnosis for normality? This means that normality is not scientifically verified and is made all the more impossible to pursue by the ever changing nature of a person’s mental health.

Yet, for such a cherished moniker of considering oneself normal, is it good enough to define it simply by the traits/dysfunctions/disorders that you do not have? It appears to be a travesty of thought to make an observation of somebody displaying difference to you and declaring that you are normal because you are not that. How satisfied would we be in situations where we needed to learn about another person, in knowing simply what they are not?

How do you determine a person’s substance by the absence of traits?

Lennard J. Davis notes in ‘The Disability Studies Reader’ (4th Ed.) that the terms norm and average only entered European languages in the 19th Century. Their arrival coincided with ideas that were being used in the field of statistics. What had been applied in the mathematical determination of astronomical events bled over into the study of human characteristics, such as height and weight. However in this natural accretion, unguided and subject to nineteenth century prejudices, the search for normal behaviors quickly became marred by the assumptions of the privileged.

Statistics is a powerful tool and can be used with great effect to convince scientists of the objectivity of research, but they are only as powerful as their interpretation. Statistics can demonstrate difference like nothing else, but the basis of comparison is loaded with assumptions of deviance versus absence of deviance. When it comes to understanding something as precious as humanity, is that good enough for us? Every single study should have a rigorous definition of what has been considered normal in light of the research question. Normal is needed for statistics to work.

Normality seems to be everything about humanity that we do not consider different or deviant, yet when pressed would struggle to define. This leads one to ask, “Is normality more of a feeling than a state of being?” Normality appears to have a lot in common with the mathematical concept of zero. Both concepts trick us into thinking they are well defined when it is in fact the opposite. The infinity of the absence tricks us into thinking there is substance.

In a world of scientifically and medically confirmed diagnoses, the definition of a normal person is one who would without fail qualify for the control group in any research (unless their socioeconomic markers do not match). Normality is a permanent membership in the control group for every possible behavioral experiment, yet this is clearly impossible, and even inhuman.

In a world where those who have been deemed different are having to fight for more inclusion and equal rights, conversations around normality matter.

If only there was a condition called Manifestly Normal Disorder, a list of symptoms to define normal would have to be rigorously defined in order to screen for the experimental group.

It is worth reminding ourselves that the middle of the bell curve is not where to find normal. Normal is the bell curve.

Mental Health Equality and Research Bias

In a way, control groups are more important to all research trials than the experimental group. When planning a study, researchers hope to show that they have found unequivocal difference between the group they are interested in and the group that has been considered healthy, normal, typical, etc. If the experimental conditions, delivered to both groups under the same circumstances then show a statistically different result or response, important information about a key difference between the groups can be reported. These responses could be different health outcomes from taking a drug, behavioral differences, or differences in physiology or biochemistry.

The problem is that control groups are not the stalwart comparisons we have assumed them to be.

There is no guidance on what healthy, normal, or typical actually mean. Researchers create their control group along with their study, and one of the most important things they look for are people who do not show the biology, behavior, or diagnosis they will use to create their experimental group. The control group is therefore simply the absence of traits that has been reserved for the experimental group. There can be additional measures to increase the power of the comparison, such as matching the experimental group for age, sex, race, etc., but these only strengthen the comparison, they do not justify why the control group should be considered healthy, normal, or typical.

This means that when the research is designed, a member of the control group is at first a stereotype or a symbol that the researchers then try to match with real people, unlike the experimental group, who are likely to be chosen from medical history or diagnosis. There is no diagnosis for normal and the use of a medical history would be to determine that it simply does not contain the events of interest in the experimental group. The control group is thus largely created from an absence of experimental traits and the ideas of what the researchers have decided to call normal as the antithesis of what they are investigating.

Researchers are upfront and do report at length about how their groups were created, however the way the control group is positioned throughout the study, as the anti-experimental group, is never really challenged, perhaps because this is how modern research has always been done. The readers’ focus is often on the point of interest, the interesting things about a certain group of humans that they have often spent their careers studying, and if they can be convinced that the control group is different enough from the experimental traits but matched for everything else, then any significance in the result must mean something.

But our bodies are constantly in flux with changing biochemistry that is influenced by our habits, diets, environments, and simple aging, so that what is true one moment might not be true the next. Tumors can be missed for years until they become problematic; stress, abuse, and trauma can be hidden from the public view; alcoholism, smoking, and drug use can be missed, as can rare genetic disorders; people may have simply stopped exercising; a change in drinks consumption might now mean the person is imbibing more microplastics. There is no reason these people cannot participate in a control group, but this should be done by excluding the language of healthy, normal, or typical. In our zeal to discover new truths, we must not forget that in the scheme of things, we know almost nothing. By declaring a control group as normal, we become guilty of claiming too much.

This approach to research obviously came from a history of studying disease and illness. When researchers are studying sick patients, it makes sense to call those without sickness healthy, normal, or typical – but within the strict confines of scientific research, where the quest for meaning has to be tightly regulated, calling anyone healthy, normal, or typical to any realistic standard is impossible. When the focus is disease, research bypasses the person to open discussion on the level of systems, organs, and cells, and it is seen as something foreign within a person. When the focus is mental disorder, the person cannot be bypassed and a new paradigm for analysis is warranted.

This might come across as pedanticism, but this is the root cause of considerable ill feeling with those living with autism, ADHD, and other classically defined mental disorders that are now defined as neurodivergent. In order to learn more about these disorders, there is no harm in having the experimental group with the traits (or diagnosis), or a control group that does not demonstrate these traits, but to use healthy, normal, or typical to define the control group immediately implies the experimental group is unhealthy, abnormal, or atypical. To carry this further, the experimental group for studies in mental disorder are also often referred to as disordered or dysfunctional, which would then mean the control group is ordered and functional – which would even be strange descriptors for this group.

There is no question that many people living with the traits of what have been termed disorders are either striving or seeking to strive on their own terms. With mindfulness, compassionate support networks, and either behavioral or pharmacological therapy, as needed, they are contributing to society, figuring out their place in the world, and constantly finding ways to overcome adversity – this is all demonstrably, and painfully human. Surely the value of their struggle merits not being compared to a group defined more by absence than by substance, a group that is determined to be the healthy alternative to themselves?

With the huge success of the neurodiversity movement and the introduction of more positive terminology such as neurodiverse and neurotype, research is now perfectly positioned to change. While debates still rage about what these traditionally defined disorders mean, whether their respective diagnoses are credible, and how the line between disorder and order might have been tragically oversimplified, the nuts and bolts for designing studies can be addressed, making us ready for when it is time to figure out what it really means to be human.