Case for Cause

This was originally posted as Case for Cause, but here is being used as a post for the 4th core of realism.

Law of causation

The first component to the name of the blog and the subsequent development of a knowledge based practice is cause. Consider cause the noun and cause the verb and their inescapable integration. It is easier to start with cause the verb. Cause the verb is same thing as causation. Of the three dictionaries I regularly consult (Oxford Dictionary of Mathematics (ODM), Oxford Dictionary of Philosophy (ODP) and Oxford Dictionary of Computing (ODC)) the only one with a rather simple definition of causation was the ODM: Causing or producing an effect. Cause the verb is the action of causing. A cause (n) is not defined in any of my regularly referenced dictionaries, so I went to my old college dictionary (Webster’s Ninth New Collegiate Dictionary, 1988 - purchased for College Writing I at U Lowell in 1988 (3 years prior to UMass Lowell began)), cause(n): a reason for an action or condition; something that brings about an effect. Cause the noun is something, but not just anything, something that brings about an effect (that therefore requires cause the verb - the action). Anything that is (i.e. exists, being vs. non being) is something, but not everything is a cause at all times. For now this post will continue to focus on the causes that exist without focusing on what I mean by exist as the metaphysics of being vs. non being is too big for me to take on - though I will have to at some point to discuss the seeming “cause” of “nothing”, such as “Not doing your exercises caused you to deteriorate.” Here we imagine non being to be a cause, so it does need to be addressed and I do think we have a reasonable solution that saves the overall system of thought being developed.

David Hume had a problem with causation which has led to years of dialogue about the existence of causation. However, from what I can tell (and I am very limited), Hume’s main problem with causation was our ability to know causation (http://www.iep.utm.edu/hume-cau/) . Hume was an empiricist (“philosophy that attempts to tie knowledge to experience.” ODP). His solution to what we think we see as causation was the constant conjunction theory of causation: “Two events A and B are constantly conjoined if when one occurs the other does; this relationship is what is meant by saying that one causes the other, or that if more is intended by talking of causation, nevertheless this is all that we can understand by the notion (ODP).” From what I can tell this is very empirical way of looking at it - which makes sense for Hume as an empiricist. We continue to recognize what Hume has stated about our empirical observations - if you have heard the statement that “correlation does not imply causation” then you are saying that the empirical data of constant conjunction (correlation) does not imply a causal association. I agree with this, but is that all we can know? To an empiricist I think it is. This is where I find the limits of empiricism, and one of the main reasons I am a critical realist. (Note, I have left out a lot of thinking related to Kant’s Critique of Pure Reason where he argues for the unity of consciousness presupposing orderly experience with universal and necessary laws - all of which is part of the critical realist approach. In other words, Kant refuted Hume).

The empirical perspective also turns out to be a limiting factor in current approaches to evidence based practice. Simply gathering empirical evidence does not lead to the generation of knowledge about cause, as Hume pointed out, it cannot. The empiricist approach to practice is limited in attribution to cause and thus cause is not a major part of the dialogue. I believe it should be. I believe that practice is primarily about causal inference, reasoning about causes. Even when we consider the reliability of a test, or the validity of a measure we are reasoning that whatever we intend to test or measure is causing our instrument or measurement system to change in a predictable, reliable and meaningful way for interpretation. The collection of empirical facts cannot produce knowledge about causes. Don’t get me wrong, the collection of empirical facts is a necessary condition, but not a sufficient condition. In all honesty, there is no one that would attempt to claim verbally that empirical facts are a sufficient condition for knowledge to guide practice. But actions sometimes deceive our verbal proclamations.

To summarize today’s post. Cause is critical for reasoning in clinical practice. Cause cannot be known simply from empirical data. Therefore the empirical tradition cannot be the epistemological framework  for a knowledge based practice.  I hope to build an epistemological framework (foundation) for a knowledge based practice (system) on critical realism (“any doctrine reconciling the real, independent objective nature of the world (realism) with a due appreciation of the mind-dependence of the sensory experiences whereby we know about it (hence, critical)” (ODP)). Critical realism allows us to take empirical facts from the “real, independent, objective” world and know about it through our mind (rationalism). I think critical realism rejects skepticism (which is quite important for any epistemology), and is a balance between pure empiricism and pure rationalism.

I do not imagine there is much debate about the importance of causal reasoning in clinical practice, or that causal reasoning presupposes cause, causation, causality. So this post does not provide a justification for cause, it presupposes cause as important and attempts to explain how cause will be used in development to avoid extremes, and to avoid skepticism.

  It is important to recognize that when philosophy was driven to the extremes of empiricism by Hume the result was skepticism, particularly with regard to cause. Don’t get me wrong - the extreme of rationalism is not much better for clinical practice. For the extremes of rationalism I am reminded of a recent post by Matt Asher on R-Blogger:

“The more I learn about the history of science, the more clear it becomes that the primary impediment to the advancement of science isn’t the existence of rubes, it’s the supposedly smart, putatively scientific people who are unwilling to consider evidence that contradicts their worldview, their authority, or their self-image. We see this pattern over and over, perhaps most tragically in the unwillingness of doctors to wash their hands until germ theory was developed, despite evidence that hand washing led to a massive reduction in patient mortality when assisting with births or performing operations.”

  Here - assuming what Asher writes is true, and assuming the doctors did not believe the empirical evidence because there was no rationale theory to support the evidence - we confront a tragic situation whereby extreme rationalism negatively impacted clinical practice. And perhaps there are more cases of rationalism negatively impacting practice than empiricism. But most people would agree that a balance between empirical and rational approaches have their place in generating knowledge of the truth, which then informs (guides) practice (I do realize that I cannot rest my argument on “most people will agree” - I am working on a better defense than that).

   A quick comment about extreme empiricism. In my course - Evidence Directed Care - this past fall (2014) I had 33 third year DPT students do two projects where they assessed both a systematic review and a clinical practice guideline using currently published approaches to assessment of evidence (highly influenced by an extreme empiricism tradition). Out of the 66 projects there were very few conclusions that seemed to indicate that the students knew something after they were done. The most prevalent result was skepticism about the content matter under consideration. Don’t get me wrong, they knew how to assess the evidence based documents, they knew how to assess the evidence from an extreme empirical perspective; but the approach left them - often times - more confused about the causal relationships investigated by the documents and therefore about how to apply the “knowledge” (or lack there of) in practice. This skepticism could be the real state (realism) - it could be true that there is an uncertain, low probability, or perhaps no causal relation in the variables under study in these 66 documents. Or, it could be the result of the application of an extreme empirical approach - it could be what we learned from Hume (see the previous post). The approach I am suggesting does not disregard empirical evidence towards an extreme rationalism. So the approach I am suggesting does not call for a cessation of all data collection - far from it - collect the data, run  the analyses, it is needed. But it does suggest an explicit regard for the rationale process of building causal models for use in inferential networks (dynamic inference).

   Ok - Assuming it is true that a balance between empirical and rational approaches is required, the big question becomes how do we determine the right balance? Is it a static balance, or a dynamic balance? In other words - is there an approach that holds regardless of the state of empirical evidence and rational models (static balance), or does the approach need to change based on the state of empirical evidence and rational models (dynamic balance)? If static - what is the approach? If dynamic - what is the approach, in particular what determines the need to change the approach?

   As you have probably already figured out, in proposing critical realism as the foundation for clinical epistemology (see the page on Knowledge Based Practice) I am proposing a balance between empiricism and rationalism. Due to the importance of causal reasoning in clinical practice, I hope to build a system that clearly articulates how our understanding about cause through these two systems of thought arbitrates their balance in an iterative process of modeling building (next post will be on models), and those models (representations of knowledge) then allow us to make inferences for clinical practice decision making (after models will post on inference).

   For those of you familiar with the work of Judea Pearl you are likely wondering why I have not referred to him yet - believe me his book has greatly influenced my thinking and it will be more explicit when I post about models (they are causal models after all).

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