by Sophia Greene

Summary of the Material

Throughout Chapters 7 and 8 of Care and Cure, Stengenga discusses held beliefs in the scientific community regarding the management of research and how researchers come to conclusions after examining the resulting data. One principal school of thought that establishes evidential hierarchies is the evidence-based medicine movement, which emphasizes meta-analyses and randomized controlled trials over cohort and case-control studies. 

Stegenga also explains the process that medical interventions have to undergo before they can be implemented in a clinical setting, and within this discussion he defines two types of studies that are typically conducted: randomly controlled trials (which include randomly allocating some participants into an experimental group and others into a placebo or control group), and case-control studies (which analyze subjects who already grouped together with a specific feature). It is important to understand the difference between these two types of research methods as case-control studies often lead to confounding factors that can lead to correlation being misinterpreted as causation. 

Stegenga further goes on to explain the different biases that can similarly affect scientific conclusions, including confirmation bias, which has a tendency to confirm pre-existing beliefs, and design bias, which is built into the internal design of an experiment. 

Then, animal models and their extrapolation on human populations are discussed, heavily emphasizing the difference between simple extrapolation – the presumption that causation in one population is always justified in another population – and strict extrapolation – the belief that the two populations must not have any causally relevant differences. Both of these methods of thinking lead to the problem of the extrapolator’s circle because they both rely on unknown knowledge to either confirm or deny said unknown knowledge. 

Stegenga goes on to discuss meta-analyses and how they can often lead to different conclusions drawn from the same data, demonstrating how different researchers can make unconstrained choices in how to analyze the evidence. 

To combat this and make research as objective as possible, some researchers believe in the black box thesis, which holds that conclusions should only be based on quantitative evidence, while others believe in the mechanista thesis, which claims that inferences must be based in part on mechanistic evidence – that is reasoning based on the expected effects of interventions based on knowledge about how systems function. 

Moving on to Chapter 8, Stengenga starts by defining objectivity, which is the extent to which evidence is reliable for making inferences, or the extent to which evidence is truth-conducive. He goes on to discuss two major issues that often impede objectivity – namely, publication bias and conflicts of interest. Publication bias occurs when research that finds medical interventions to be ineffective is much less likely to be published, and this is due to the fact that industries often sponsor these studies, and therefore “own” the evidence and can choose whether or not to publish it. Additionally, medical researchers and physicians are often employed or partnered with these sponsors, which makes it difficult to tell if research is truly unbiased, resulting in a conflict of interest.

Another large issue in Stegenga’s discussion of research is in deciding how to regard non-epistemic values in the design and conclusion of experiments. A strong argument is the value-free ideal, which holds that non-epistemic, or statistical, values should not play any role in scientific reasoning; however, many critics argue that that ideal is impossible to uphold, as inherent values of ethics and common sense are used in conducting research. 

Finally, Stengenga considers the idea that the science community can be the solution to maintaining objectivity, highlighting the importance of shared standards to uphold and a response to criticism which allows for new innovation but also checks the validity of such innovations by allowing experts to combat false information and therefore, uphold the objectivity of medical research.

Discussion Questions

• Is the placebo effect inherently good or bad? What about in relation to confirmation bias? Can placebos be considered medical interventions?
• Is extrapolation from animal studies to humans warranted? If so, which approach (simple, strict, or mechanism-based) best legitimizes scientific claims of causation?
• Which values do you believe should be permitted to influence the scientific process? (ie. cultural, ethical, social, political, financial values)
• Additional questions to be considered (not discussed):
  • Do you think that, because critics claim that even randomized trials can never really eliminate confounding factors, all trials should be regarded as flawed?
  • How do the issues of confounding factors and biases influence the day-to-day of practicing physicians, and how do we best eliminate these issues?
  • Should either the lack of statistical evidence or mechanistic evidence be grounds for the invalidation of medical conclusions?
  • Is the way in which we use the term “objective” in everyday speaking accurate to its meaning? Is it possibly harmful to our perception of the information we are presented with?
  • Should industry sponsors of medical research own the evidence from a study? If not, how would that be enforced, and would it affect the amount of research conducted if sponsorships are withdrawn?
  • How is criticism in the scientific community an important factor in advancing objectivity and innovation?

Summary of the Discussion

We opened up our discussion of medical knowledge with the question of whether placebos should be viewed negatively or positively and if they should be valid medical interventions. One thing that was quickly established is that the placebo is not inherently good or bad. Rather, the question lies in how physicians may decide to use it and how they may affect the patients. Throughout the discussion, we mainly considered two areas of thought. One argument was established in the idea that although placebos have their place in research, they should not be used in daily operations of the medical field, such as doctors prescribing them to patients, because it is established in a lie that violates the autonomy of the patient. Furthermore, this dishonesty violates the integrity of the medical field and ties back into medical paternalism as the doctors are essentially making the decision for the patient. On the other hand, if one views the issue through the lens of the biopsychosocial model, taking a placebo may help a patient improve not just physically but also psychologically, improving their overall well-being and health. Additionally, this perspective combats the idea that placebos hurt the morality and responsibility of the medical field by proposing that a patient who seeks out a physician to help them feel better would be less trusting of medicine if that doctor sends them away without any treatment and that a placebo might at least treat some symptoms if not the cause of the illness. While a consensus was not reached, these two attitudes regarding the use of placebos in medicine are both very impactful considerations.

Subsequently, we discussed extrapolating animal studies to humans and which approach to view these correlations is most legitimate. Our class soon agreed on the fact that it is currently necessary because there are limitations on human testing, and that it is most warranted when assessing possible risks to a human population. Additionally, we considered the fact that the simple approach can be relatively difficult to use when they have disparate functions, which means one should be very cautious when drawing these types of conclusions, while mechanism-based reasoning is very useful if there is an underlying basic understanding of the functions between two populations. Moreover, this discussion led us to examine the role of animals in research, and after debating what constitutes justification for any harm done, we concluded that it should be based on epistemology: if there is low epistemic value for causing suffering, the medical knowledge that we are producing is not justifiable if it can not be legitimately extrapolated to humans.

Finally, we considered which values should be permitted to influence the scientific process, given that the value-free ideal is unachievable. While there was the initial impulse to want financial values to be far excluded from the medical world, we did realize monetary concerns are necessary because they are involved in the regulation and funding of research. We considered having an outside committee that is filled with educated members to allocate funds to projects; however, this concept proved to be flawed due to the fact that many sponsors would not want to fund a lab if they could not control the resources. Overall, we came to the understanding that it is impossible to separate values such as financial concerns from medicine solely because so many aspects are contingent upon each other.

Response

Although the understanding of medical knowledge and how it comes about through research can at first seem tedious and demanding, it outlines many foundations of medicine and affects our understanding of current treatment and ongoing research projects along with their future applications. Our discussion of placebos related to many aspects of our previous discussions and raised questions that helped us apply these concepts to real-world examples: how do you define health? Is the goal of medicine to address the cause of the problem, the symptoms of the problem, or both? Does the integrity of medicine rely on the morality of truth or the relationship between the physician and patient? These are important considerations that we should contemplate so that we may be more prepared for conflicts that we may face in the future. Additionally, I find it incredibly pressing to ask ourselves what values should be considered in science and the medical field. In truth, we should question whether these concepts can even be appraised separately at all, as they constantly influence each other in practice if not in theory. Answering these questions for ourselves and recognizing the nuances between the purely empirical facets of medicine versus the sociocultural and economic acceptances and interpretations of scientific evidence will allow us to acknowledge and accept our own tendencies to be influenced. Overall, the discussions we encountered helped to prompt ways of thought that can ensure our understanding of not only the foundations of scientific study but also their implications in everyday life within the medical field.

Works Cited
 Stegenga, Jacob. Care & Cure: An Introduction to Philosophy of Medicine. University of Chicago Press, 2018.