examples of misleading statistics in healthcare

You can see the updated version below. For example, a misleading data visualization included in a financial report could cause investors to buy or sell shares of company stock. You should only use log scales when there are clear reasons to graph order of magnitude. The problem was, the graph, which is depicted below, was built with a y-axis on a logarithmic scale instead of a linear one, making it look like the rate of change is smaller than it actually is. While initially, the trend was going towards choosing option A, when grouping surviving patients considering other variables the trend changed to option B. The Cake Is a Lie. Health Misinformation Current Priorities of the U.S. Health (2 days ago) Office of the U.S. We note that these examples come from the context of the United States as that is the context the authors are most familiar with, however, from scanning the news, these seem to be issues common across the world during this highly politicized global pandemic where peoples lives and politicians power are in danger. Finally, how big was the sample set, and who was part of it? The Misuse of Statistics in Politics: Abortion | YIP Institute An example of misleading statistics is when determining whether to take a medical test for a rare but serious disease like spina bifida. As an answer to the issue, Candice Broce, the communications director for Giorgias Governor. The image below shows a graph advertising KFCs crispy chicken twister wrap and comparing its calories with other brands with a similar product. The example above is an example of selective bias; the biologists were recruited, not randomly selected. Lets look at one of them closely. A plot with two vertical axes is inherently more complicated to digest, especially in this case, because the two axes are not designed to show a relationship between two different attributes. Each kind is calculated differently and gives different information (and a different impression) about the data: Improper bubble sizes 13. So, can statistics be manipulated? Be prepared to be confused. For this last question, it would be important to make sure students are not merely concluding mask mandates lead to higher case rates than not having them. . Truncating axes is a very dangerous false statistics practice, as it can help create wrong narratives around important topics. Drinking tea increases diabetes by 50%, and baldness raises the cardiovascular disease risk up to 70%! Evaluate the effectiveness of internal policies and practices in addressing misinformation and be transparent with findings. The ASA continued, Because we understood that another competitors brand was recommended almost as much as the Colgate brand by the dentists surveyed, we concluded that the claim misleadingly implied 80 percent of dentists recommend Colgate toothpaste in preference to all other brands. The ASA also claimed that the scripts used for the survey informed the participants that the study was being performed by an independent research company, which was inherently false. However, the telling of half-truths through study is not only limited to mathematical amateurs. Second, without paying very close attention to the scales of the two vertical axes in the original plot, it would be easy to conclude that counties with mask mandates had dropped below that of those with no mask mandatean incorrect conclusion. Take this first example of a misleading graph that proves global warming is real. Invest in quantifying the harms of misinformation and identifying evidence-based interventions. When the Georgia Department of Public Health posted this plot (see Figure 3), it went viral because of what may have been intentional data manipulation. There is also no evidence to say that the Florida Law Enforcement Department was purposely deceiving the public. Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine. Another issue, and maybe the worst of them all, is that the dates under the bars are not ordered chronologically. Making this a clear example of how the time period that we chose to portray can significantly change the way people will perceive the information. Let's check those mistakes. Going against conventions. Whatever the types of graphs and charts you choose to use, it must convey: - The method of calculation (e.g., dataset and time period). Spain and Italy have large populations, but enormous. should be built in a certain area based on population growth patterns. In addition to our cases motivating discussion of association, the plots also offer an important consideration of how scaling modifications can mislead the consumer. These examples bring up several concepts that are, under the Common Core State Standards for Mathematics (CCSSM) (NGAC & CCSSO 2010), introduced beginning in the sixth grade, such as understanding differences between histograms and bar charts, as well as drawing comparisons between two samples, leading to an understanding of association (for both continuous data and categorical data) and correlation. In a similar fashion, once students have begun to develop an understanding of associationa topic beginning in the eighth grade under CCSSM, and appearing in tertiary statistics as well as quantitative reasoning coursesa time-series plot might be shared, such as the one in Figure 4 taken from this blog post (Acquah Citation2020, May). No, it isn't. The size of India's middle class was 50 . Seasonal flu, meanwhile, only kills around 0.1%. This means that there is no definable justification for the placement of the visible measurement lines. It can be difficult to know which sources of information you can trust. However, some survival rate statistics can be misleading because they don't take into account differences in patient characteristics, such as age, sex, and stage of disease. If you perform a quantitative analysis, sample sizes under 200 people are usually invalid. Television is not the only media platform that can provide examples of bad statistics in the news. This misleading tactic is frequently used to make one group look better than another. The claim, which was based on surveys of dentists and hygienists carried out by the manufacturer, was found to be misrepresentative as it allowed the participants to select one or more toothpaste brands. Figure 1, from the Healthgrades site, shows the results for the first. You will end up with a statistical error called selective bias. According to a definition by the Stanford Encyclopedia of Philosophy, a Simpsons Paradox is a statistical phenomenon where an association between two variables in a population emerges, disappears or reverses when the population is divided into subpopulations. ", we can address 8 methods often used - on purpose or not - that skew the analysis and the results. These false correlations often leave the general public very confused and searching for answers regarding the significance of causation and correlation. The misuse of statistics is a much broader problem that now permeates multiple industries and fields of study. Big data has the ability to provide digital age businesses with a roadmap for efficiency and transparency, and eventually, profitability. A 22-page overview of health misinformation and resources to stop it. Look at the About Us page on the website to see if you can trust the source. Partner with community groups and other local organizations to prevent and address health misinformation. Using the pair of graphs in the first case, a question that could spur thinking about these two phenomenacounties with vs without a mask mandatecould be something like: What does this graph (Figure 1, the one with two axes) make it appear is happening? . Looking for U.S. government information and services? Did we forget to mention the amount of sugar put in the tea or the fact that baldness and old age are related just like cardiovascular disease risks and old age? As mentioned, this is not the only time Fox News has been criticized because of these situations. Evaluate the effectiveness of strategies and policies to prevent and address health misinformation. Misleading graphs in context: Less misleading than expected These are important questions to ponder and answer before spreading everywhere skewed or biased results even though it happens all the time, because of amplification. However, when you look at a longer time period such as 1910 to 2015 (image below) we realize that the debt is actually very low comparing it to other years. Sears' Bamboo fabric > Parent Company: Sears > Ad changed: yes > Settlement Amount: $475,000 Sears Holdings agreed to pay $475,000 and. Grueskin shared some of these insightful examples of misleading statistics in the news in a Twitter thread that became very popular. Managing Partners: Martin Blumenau, Ruth Pauline Wachter | Trade Register: Berlin-Charlottenburg HRB 144962 B | Tax Identification Number: DE 28 552 2148, News, Insights and Advice for Getting your Data in Shape, BI Blog | Data Visualization & Analytics Blog | datapine, NASAs Goddard Institute for Space Studies. You can also ask someone external to your research to look at the data, someone biased to the topic that can confirm your results are not misleading. The size of India's middle class is 300 million people. Really? For these reasons, a firm understanding of data science is an essential skill for professionals. Reuters / Via reddit.com 2. They sure can. Many would falsely assume, yes, solely based on the strength of the correlation. To get this trip started, let's look at a fallacious statistics definition. In this case, there is no way to know if the data were purposefully (mis)represented to support a particular message, or if it were (mis)represented by accident. Some useful questions to ask could be: What purpose might the Georgia Department of Public Health have had in manipulating the plot in this way? Citation2020), this very truth has now been laid bare for the world to see in the media and social media as the general public grapples with making, and making sense of, data-based arguments around COVID-19. Using the wrong graph. However, when considering other factors such as the health conditions in which patients arrived at the hospitals we can drive other conclusions. Tufte (Citation2001) talked about this in his book, The Visual Display of Quantitative Information, making a point that having two vertical axes on a time series plot can be very useful when attempting to show a plausible association between two things. Therefore, using the first graph, and only the first graph, to disprove global warming is a perfect misleading statistics example. These are nine of the most misleading product claims. People also read lists articles that other readers of this article have read. Strengthen the monitoring of misinformation. The plot compared the number of COVID-19 cases over time for counties in Kansas that had mask mandates versus those that did not.
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