Chronic Fatigue TS: A Case Study

Kathryn Schulz argues in “Evidence”, a chapter of her book called Being Wrong, that we need to “learn to actively combat our inductive biases: to deliberately seek out evidence that challenges our beliefs, and to take seriously such evidence when we come across it” (Schulz, 377”). By attending to counterevidence we can avoid making errors in our conclusions.

He explains why UCTs are as popular as they are in modern society, and why people should nevertheless disregard and approach them with caution. What Keeley refers to as “virtues” are the reason for the popularity of UCTs. He gives the virtue of explanatory reach as the first and main reason for UCTs popularity, which is the account of all knowledge including errant data. This is in stark contrast to the received theory, which is imperfect by nature. This quality of UCTs is particularly attractive because it appeals to human rationality by allowing for no loopholes. Keely argues that errant data alone is not significant enough, and that a theory should never fit all of the data. This leads into one of the main points, concerning falsifiability and skepticism. Unfalsifiability is acceptable when the item or person under investigation is not actively trying to escape from the investigator. Keeley contends that the problem is not the innate unfalsifiability, but rather the increasing amount of skepticism required. Keely seeks a hole in the concept of conspiracy theories that accounts for a person’s innate sense that belief in a particular conspiracy theory is not justified. In the case of the natural sciences, falsifiability is acceptable because of the rigorous protocols in place, and therefore, we are warranted in believing scientific claims.

In a 2011 Mother Jones article, “The Science of Why We Don’t Believe in Science,” Chris Mooney, liberal author and journalist for the Washington Post, argues that people who have strong beliefs and value systems have difficulty being objective because their emotions allow them to reject or twist evidence they receive from observed facts and science. To support his claim, he provides both examples and scientific research showing that people can deny science and personally observed facts. The main examples he discusses are how people deny climate change, evolution, and the need for vaccinations for serious childhood diseases such as measles.

In his book The Great Influenza, author John M. Barry writes about his opinion on the characteristics of scientists and their research. He believes that science is full of uncertainty and scientists must be able to deal comfortably with the unknown, as well as the fact that scientists must be creative and accept that their own beliefs can be easily broken by their own research. He accomplishes this by utilizing rhetorical strategies such as allusions, references to relatable examples, and a “matter of fact”, harsh tone.

Facts are statements that are indisputably true. Truthful statements are authentic because they are widely accepted to be accurate and fit reality. When answering the question “given access to the same facts , how is it possible that there can be disagreements between experts in a discipline?”, one must consider the definition of an expert. For the sake of this paper I am defining an expert as someone who excels in their field , and constantly evolves their knowledge as their field progresses. I believe that disagreements between experts when presented with the same facts, occur because of bias. Bias is a sway towards one side or view of a situation or statement. Therefore I ask , how does someone’s personal bias affect their interpretation

Scientific sensationalism does not just water down the conversation surrounding important issues, it can make them dangerous. Because democracies hinge on an informed public, with increasing amounts of sensationalism, this public may be desensitized to genuinely alarming scientific discoveries because the have become acclimated to attention grabbing headlines

For example, he first tells that "8 of 10 children born in United States will never know a sky dark enough for the milky way". This worrying statistic, probably unknown for the reader, will provoke reader's concern on he topic discussed. Bogard's mistake was to avoid the source of information of this statistic, so the audience will not know whether or not this fact is true. However, he get along with evidence by quotating World Health Organization and American Medical Association, being that both agree with his main claim. He keeps building his argument in telling obvious facts, connected by deductive reasoning. As an example "All life evolved to the steady rythm of bright days and dark nights [...] And too little darkness [...] spells trouble for all". Finally, Bogard also metions statistics based on NASA's pictures, irrefutable proofs about light polution increase. In mentioning official health organizations, obvious and daily facts, statistics and personal evidence, the cogency of the argument gains strength and becomes irrefutable. Consecuently, the author precludes readers to contradict his reasoning, gaining their

Not only do we have a tendency to ignore and misinterpret evidence that conflicts with our own views; we also have tendency to look for and recognize only evidence that confirms them. We tend to look for confirming rather than disconfirming evidence, even though the latter can often be far more revealing.

Medicine is often called an art rather than a science. While I do not agree with this assessment entirely, because I believe in the value of empirically-gathered evidence, I do understand why many patients are frustrated by what often seems like contradictory studies supporting different health treatments. One week it seems as if there is an article in the newspaper stressing that preventative screening is valuable; the next week there is an article stating that too much testing can yield too many false positives. One week exercise is stressed as a means of weight loss, the next week a healthy diet. From a layperson's and even a provider's perspective, this can seem confusing. There is also an unfortunate degree of confusing chatter from the commercial purveyors of medicine, promoting specific drugs or treatments.

In light of the evidence that is presented, with least research to assist in understanding the issues

The Report dated 06/19/2017, indicated that the claimant had severe fatigue and chronic pain secondary to systemic lupus erythematosus and hemochromatosis. He was deemed incapacitated from 05/01/2017 through 07/31/2017. Monthly appointment for blood letting was advised. A referral to Hematology and Oncology was made.

With all the bad science in the media the general public is often confused as to which are the correct choices. Educating the public to be better consumers of science would improve general health and lower the need for access to healthcare (Pincus, Esther, DeWalt, & Callahan 1998).

Assumptions in the title of this essay imply that results, theories and laws resulting from the current system of peer review multiple perspectives produce completely infallible objective truth, this is a false premise. Whilst the group of knowers known as the scientific community have collectively less bias than one lone knower trying to understand the universe, there is still collective and engrained level of institutional bias. The same problems of confirmation bias and expectation are present in a group of knowers just as they are with one single knower. According to Karl Popper (1902-1994) the best way to eliminate any expectation and confirmation bias was to falsify and disprove rather than confirm one’s hypothesis and predictions. Popper argues: no matter how convincing an argument or theory is, all that is needed to disprove it is one piece of valid counterclaiming evidence. Whilst this theory is valid on an individual level, it really becomes an effective tool in the objectivity of science on a large scale. Despite this attempt at objectifying and ‘protecting against’ error and bias it is inadequate due to inherent flaws in the scientific method. Induction, moving from the specific to the general, is the key element in scientific logic. Any theory or law ‘proved’ through this logic has some key flaws: the main flaw being that inductive logic can never be certain of any event happening or of any prediction. Richard van de Lagemaat

Disagreement may aid the pursuit of knowledge in the natural and human sciences because disagreement leads to new discoveries. Disagreement is about gathering reliable knowledge as well as using this newfound knowledge, and occurs when a group fails to reach a consensus over the logic of an argument. Knowledge is composed of facts, information, and skills acquired by a person through experience or education. Two areas of knowledge that are impacted by disagreement are human science and natural science. Human science is the study of human behavior and how humans gather information. Natural science is a branch of science that deals with the physical world. In order for a disagreement to occur, one must be familiar with the subject and have his or her own prediction that is different from the norm. Therefore, to advance knowledge in the areas of human and natural science, people must disagree. The roles of logic, reason, and emotion will be investigated to see how they are used to help gain new knowledge in both human and natural science.

A glass of wine a day keeps the doctor away. Is it enough to just say this without any real evidence to support it? Is just wanting it to be true enough to convince you? The answer to these two questions could be the difference between acknowledging accurate information presented in a scientific article and accepting insufficient information presented in a lay article. Lay articles provide brief summaries on the concepts in documented research studies. Scientific articles thoroughly describe and report findings in research studies. In order for either article to be believable, important information should be included. This information includes the population of interest and the sample in the study, the independent and dependent variables and their levels, scale of measurement for each variable, the null and research hypothesis, the test statistic used and its significance level (p value or α value), results of the study, research errors, and the assumptions for the specific test statistic. According to Nolan and Heinzen (2011), authors of Essentials of Statistics for the Behavioral Sciences, assumptions are, “Characteristics that we ideally require the population from which we are sampling to have (scaled DV, randomly selected, normally distributed) so that we can make accurate inferences (Nolan & Heinzen, 154).” Comparing a lay article to a scientific article can aid in one’s perception of which type of article most effectively presents all of the necessary information