The information space during the pandemic contains conflicting and overabundant information about the coronavirus in various forms, from reports to YouTube commentary. Regardless of age, gender, or education, patients may come to believe in conspiracy theories and false data. Some of it is potentially dangerous, further contributing to a public health crisis. However, to refute such claims, one must be able to recognize the fundamental research design flaws and explain the persuasiveness of false information.
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Evaluating Experimental Design
Patients tend to believe in false sources due to their lack of critical design evaluation skills. One such instance is the YouTube presenter who claimed that vitamin B12 administration prevents COVID-19. He described his research experiment as having 200 Marmite-eaters, with only 10 of them getting sick. However, knowingly picking people for the experiment renders it prone to the experimenter bias, which can give false results to confirm the needed claim (The Open University, no date-b). Additionally, it is crucial to determine the correlational relationships, which this study did not do (The Open University, no date-a). For this experiment to be reliable, it would have to take the form of a double-blind study to control for the placebo effect and reduce the number of confounding variables by controlling for individual circumstances (The Open University, no date-e; The Open University, no date-c).
Another instance where a critical evaluation of the information would be required is Dr. Ivor Mectin’s claim that COVID-19 can be cured by ultraviolet light. As a source, he is unreliable: his medical degree credentials or adjacent research are non-existent. Further, Dr. Mectin has a personal interest, claiming to be the inventor and actively selling the ‘Magi-Light’ device. The device can allegedly be ‘tuned to deliver therapeutic light … and treat a range of different illnesses.’ However, no related publications in the field support his claims about the ‘miracle’ cure. This example presents a case for critically evaluating the sources of information.
False Sources’ Persuasiveness
Despite all the pointed experimental weaknesses, false claims, including medical ones, are still persuasive, and the reasons are multifold. People tend to seek information supporting their pre-established view (biased assimilation or confirmation bias) since it spares them the need to challenge their beliefs. Moreover, major social crises like a global pandemic facilitate the spread of misinformation since people want to access shared knowledge quickly. The thought of being able to control and prevent the disease easily is comforting. The main mechanism that underlies this assumption is the placebo effect, hinging on a desire to find relief (The Open University, no dated). Hence, patients are prone to wishful thinking, which makes ‘miracle cures’ much more convincing.
For instance, Dr. Ivor Mectin’s treatment of COVID-19 by ultraviolet light presents patients with a ‘miracle cure .’Regardless of the lacking research and unreliable information, his solution seemingly presents patients with an easy opportunity to bypass the challenges and expenses of the medical system, making it appealing. Many patients would believe in the information with no clinical evidence as long as they consider that self-found cures will improve their condition faster than a specialist.
Moreover, only one recorded patient supported Dr. Mectin, who stated she began feeling better after a sunbed tanning procedure. This observation constitutes a classic post hoc ergo propter hoc fallacy; thereby, people assume that their health improvement after a selected procedure is due to undertaking that procedure (The Open University, no date-c). The tanning procedure likely had nothing to do with the health improvement; an additional effect contributing to the patient’s belief is regression to the mean (her health likely would improve with or without tanning). Lastly, a single case, even more, reliable than this one, would be insufficient to support a claim – however, this story stands out due to the availability heuristic phenomenon.
While no single rule determines the legitimacy of online resources, there are some useful guidelines for determining claims’ reliability and correctness. The rule-of-thumb measures can be abbreviated as PROMPT: presentation, relevance, objectivity, method, provenance, and timeliness (The Open University, no date-e). The crucial criteria of provenance and objectivity, for instance, require the information to have an identifiable source or author, which is honest, neutral, and free from hidden intent. Some of the points to check are the author’s credible qualifications, personal bias, author’s other contributions, and objectivity. Next, when evaluating arguments, it is recommended to inquire whether the claim is logical, has alternative explanations, or hides underlying values and assumptions.
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Lastly, one must ask whether the available experimental evidence justifies the claim: whether it is sufficient, coherent, and relevant. The best available evidence would be objective academic sources from peer-reviewed journals. A good experimental design has a controlled environment, manipulates only a few independent variables at once, measures the dependent variable, allocates randomly to different conditions to avoid confounding variables, and can determine a cause-effect relationship (The Open University, no date-f). Generally, the patients can be advised to evaluate these criteria to find truly reliable experiments.
Overall, much of the misinformation relies on confirmation bias, public lack of causality comprehension, and a particular memorability of sensational stories. Unreliable research goes unnoticed due to people’s lack of knowledge regarding good experiment design requirements. Moreover, at times there is no research in the first place, which is masked by vague statements and the placebo and hoc ergo propter hoc effects. Lastly, patients are prone to believing false claims when it supports their pre-existing beliefs. In sharing the recommendations for checking online resources and evaluating the reliability of experiments, the medical providers may help patients avoid being misinformed.
The Open University (no date-a) 6.3 Correlational studies.
The Open University (no date-b) 6.3 How do scientists know that homeopathy does not work?
The Open University (no date-c) 6.5 Why do people think homeopathy works?
The Open University (no date-d) 7 Focus on methods: placebo effects in practice and research.
The Open University (no date-e) 8.1 Evaluating claims from non-academic sources.
The Open University (no date-f) 8.2 Evaluating arguments.