Update: the paper is now published in Current Directions in Psychological Science; you can find my summary of the paper on Twitter.
I’ve written a very brief piece on embracing the complexity of mental health problems, entitled “Studying mental disorders as systems, not syndromes” (download). I also had the opportunity to give a keynote on the paper, which you can find on youtube. This was a lot of fun to make, given that I created an entirely new presentation (no recycling of old material!).
In this blog, I’ll briefly summarize the core message of the short paper and talk. This will be interspersed with some beautiful images I was able to create using an AI tool making images from text input, for which I used the title of the paper.1
1. Introduction: lack of progress
In the paper, I describe the dire situation we find ourselves in. Over the last decades, many specialists have worked tirelessly to improve the lives of people affected by mental health problems. Mental health has also received increased political and funding priority. Despite these global efforts, however, progress in understanding, predicting, and treating mental disorders remains disappointing. There are many reasons for this lack of progress, and I discuss two roadblocks: diagnostic literalism and reductionism.
2. Diagnostic literalism
I show, using examples from the history of psychiatric nosology, that many categories and thresholds we use for research purposes are somewhat arbitrary, shaped to a considerable degree by historical forces rather than empirical evidence. I demonstrate that current diagnostic categories are manufactured, rather than discovered, and put that into context of many other manufactured nosological systems. Beavers and elephants are not like helium and magnesium: they are not natural kinds with sufficient and necessary properties that allow to uniquely identify them; the idea that species are natural kinds is pre-Darwinian. Because categorization of mental illness is somewhat arbitrary does not imply that categorized things “do not exist”. There is a continuum between normal and abnormal blood pressure, and where to draw the boundary is somewhat arbitrary, but that does not mean high blood pressure (or beavers, or depression) does not exist.
The superimposition of categorical diagnoses on the complex landscape of mental health problems explains the situation we find ourselves in. This makes it obvious that diagnostic categories and thresholds listed in the DSM are meant as clinically useful tools with heuristic value: they don’t have clear thresholds like water and steam, and cannot be neatly separated like helium or magnesium. However, we study them as if this were the case, e.g. in case control studies, which I refer to as diagnostic literalism.
3. Reductionism
Reductionism is one of the most powerful frameworks for trying to understand systems: figuring out the properties of the whole given the parts. This works well for simple mechanical systems, such as bicycles, but has limits when systems become increasingly complex, such as the stock market, the weather, or the internet. I showcase that research on mental disorders has been conducted largely within strongly reductionist frameworks, and discuss, as an example, biological reductionism. I briefly review research efforts, concluding that biological psychiatry has led to considerable insights about how human genes and brains work, but has told us relatively little about the biology of specific mental disorders.
This lack of progress is not because biology is not crucially involved in predisposing or mediating disease trajectory——it arises because we have focused on studying the biology of particular DSM labels that are likely the wrong targets, and because we have studied biology (at least largely) in isolation. Diagnostic literalism and reductionism have formed a vicious cycle of reification, and continue to do so whenever we talk about “risk factors for schizophrenia”, “genes for major depression”, and “symptoms of PTSD”.
4. Embracing complexity
Reductionism is helpful to fix systems such as bicycles, but mental disorders are not like bicycles: they arise within a person over time, and are best understood as phenomena resulting from interactions of biopsychosocial elements organized in hierarchies of inter-dependent levels. I discuss a few features such systems have, including emergence, stable states, phase transitions, and behaving in ways that aren’t necessarily intuitive. I conclude that understanding mental disorders as dynamic entities that can no longer be decomposed into simple cause-effect relations highlights the importance of studying mental health systems holistically. Doing so successfully will require building more interdisciplinary bridges, and open our ivory towers to theories and methods from network and systems sciences, fields with a long and rich tradition.
Great Post! The approach of studying mental disorders as systems rather than syndromes offers a promising shift in understanding their complexity. By examining the dynamic interactions within these systems, we can potentially uncover deeper insights into the underlying mechanisms and develop more effective interventions.
Hello Eiko,
My name is Ben Spaloss. It was nice seeing you give a talk on this subject today.
“It has often been said that the science of psychology suffers from physics envy—a facetious reference to the fact that most of its journals and training programs have assigned priority—indeed, often exclusive validity—to findings obtained by means of the practices of older disciplines focused on the study of inanimate matter, such as physics”
-Mihaly Csikszentmihalyi, as the first line of the forward for the Handbook of Research Methods for Studying Daily Life.
I love the idea of studying psychology through a complexity framework. I struggle though, because it seems a lot of the ideas and concepts we have in psychology lack an ontological basis that many of the interconnected units within complex systems in other disciplines have. Mihaly goes into this idea later in the same forward:
“The lack of agreement as to what is worth studying about the human psyche is, of course, a consequence of the difference between what psychology studies as distinct from all the other sciences. Physicists, chemists, or even biologists need not be concerned about understanding what they are studying; they only need to know how matter, or living organisms, work—at least as seen from the perspective of the human observers. No one expects a chemist to question the experience of being a water molecule, nor a physicist to worry what an atom feels when it is split. This is presumably because molecules and atoms are not conscious systems. In psychology, however, it is essential to take into account the level of complexity of the human organism, with its self-reflective, conscious potential; to fail to understand the subjective experience of people means to miss what is most unique, and perhaps most
important, about them.”
If we were to take a systems approach to studying mental problems, we would be relying on “units” within the system that are subjective and experiential. Do you think we would have symptoms as our “units” interacting in the system? Or maybe processes of change? Would we study dimensions of experience like attention, cognition, and affect? Or concepts, like present moment attention, believability of negative thoughts, and emotional acceptance. If we don’t need nomothetic validation, what if we just made up concepts on the fly, as long as it mapped well to the data explaining that individual person?
I am curious, because if you are anything like me, you cannot help but try and “see” this idea of complex psychology as you live it, right? Like, you can see non-linearity when one thought slip into mind that changes your interpretation of your entire current moment experience or phase transitions and stable states in how we believe and change our minds, right?
Maybe this is not landing for you and I look like an idiot right now. If so, ah. I tried my best. Apologies my friend.
But if this is landing, I am curious how you catch glimpses of this view of psychological life in living it.
Thanks for sharing your thoughts Ben.
You asked:
“If we were to take a systems approach to studying mental problems, we would be relying on “units” within the system that are subjective and experiential. Do you think we would have symptoms as our “units” interacting in the system? Or maybe processes of change? Would we study dimensions of experience like attention, cognition, and affect? Or concepts, like present moment attention, believability of negative thoughts, and emotional acceptance. If we don’t need nomothetic validation, what if we just made up concepts on the fly, as long as it mapped well to the data explaining that individual person?”
The short answer is: yes to all of those. But which of those matter, for which person, for what disorder, for understanding vs prediction, is pretty much entirely unexplored (and therefore unclear) at this point. RDoC for instance has been trying to work on a matrix that summarizes core transdiagnostic mechanisms, including bio, psycho, and social variables or processes. But if they got it “right” is unclear until this matrix proves to help with description, explanation, prediction, and control. The same goes for the HiTOP framework, a hierarchical taxonomy, and some other approaches.
So I think of your comment here as summarizing many open questions most people in this emerging field of network science in psychopathology would agree are fully unanswered and need exploring.