examples of misleading statistics in healthcare

For example, are visualizations representing the data accurately? Insightful graphs and charts include a very basic, but essential, grouping of elements. Educate students and the public on common tactics used by those who spread misinformation online. While initially, the trend was going towards choosing option A, when grouping surviving patients considering other variables the trend changed to option B. Going against conventions. This page includes the key takeaways from the advisory. Intermediate data points should also be identified and context is given if it would add value to the information presented. Statistics are infamous for their ability and potential to exist as misleading and bad data. Recently, Kellogg's UK was hit with a ban from the ASA (Advertising Standards Authority) after making false health claims in its advert for Special K cereal. Spain and Italy have large populations, but enormous. Grueskin shared some of these insightful examples of misleading statistics in the news in a Twitter thread that became very popular. The most common one is of course correlation versus causation, which always leaves out another (or two or three) factors that are the actual causation of the problem. But you cannot know until you ask yourself a couple of questions and analyze the results you have in between your hands. Oftentimes, data fishing results in studies that are highly publicized due to their important or outlandish findings. The plot compared the number of COVID-19 cases over time for counties in Kansas that had mask mandates versus those that did not. Regardless, many people will look at the graph and get a different idea of what the actual difference is, which is an unethical and dangerous practice. How inclusive was it? It further appears to indicate that counties with no mask mandate have seen relatively no change in number of daily cases. The example above is an example of selective bias; the biologists were recruited, not randomly selected. They can lead to misleading statistics that give you a faulty idea of customer satisfaction and product preferences. Stopping COVID-19 with Misleading Graphs | by Nikita Kotsehub | Towards In CCSSM, students gain experiences with histograms beginning in grade 6, and they begin comparing multiple plots as early as the seventh grade. The pandemic of the novel coronavirus has gripped the entire world and engaged people in consuming scientific informationperhaps more so than any other event in history. Specific wording patterns have a persuasive effect and induce respondents to answer in a predictable manner. Prioritize early detection of misinformation super-spreaders and repeat offenders. We also discuss the possible source/motivations behind such (mis)representation of the data. Evaluate the effectiveness of internal policies and practices in addressing misinformation and be transparent with findings. An official website of the United States government. Why did the first plot look so different? Omitting data 10. Statistical studies can also assist in the marketing of goods or services, and in understanding each target markets unique value drivers. 73.6% of statistics are false. By Dana Litt and Scott Walters, March 24, 2021. Amongst various videos of success cases of patients, merchandising, and unethical messaging included in Purdues marketing strategy to advertise OxyContin as a safe drug, there was a very interesting graph, used to prove to doctors that the drug was non-addictive because it stayed on the patients blood over time avoiding symptoms of withdrawal. Misleading Statistics: Examples of Techniques Used When Research Evidence is Misleading. Much like abortion, global warming is another politically charged topic that is likely to arouse emotions. The lack of statistical literacy from the public, paired with the fact that organizations didnt always share accurate statistical information, lead to widespread misrepresentation of data. Annual Data 3. This is paired with the fact that counties are not always depicted in the same order, but instead in descending order of cases. In this case, the goal is not association, but comparison, thereby making it a bit more difficult to initially interpret the data. On top of that, the numbers can be hard to interpret, whether that's a . Health misinformation has also led to harassment and violence against health workers, airline staff, and other frontline workers tasked with communicating evolving public health measures. However, the telling of half-truths through study is not only limited to mathematical amateurs. We will discuss this specific case in more detail later in the post. While certain topics listed here are likely to stir emotion depending on ones point of view, their inclusion is for data demonstration purposes only. Misleading statistics refers to the misuse of numerical data either intentionally or by error. This example of a misleading use of statistics is perhaps one of the more clear cases of intent to mislead, despite attempts of the administration to make it appear accidentalsee May 19 story about the response in The Atlanta Journal-Constitution (Mariano and Trubey 2020 ). Take this first example of a misleading graph that proves global warming is real. Dietary supplement businesses frequently exaggerate the health benefits of their products. To learn about our use of cookies and how you can manage your cookie settings, please see our Cookie Policy. 2 Steven Strogatzs Twitter comment to show a recreation of a plot showing the number of daily cases of COVID-19 per 100,000 in the population of Kansas. An official website of the During the initial stages of COVID, the general public was forced to consume scientific information in the form of data visualizations to stay informed about the current developments of the virus. This is a clear situation in which the axes are manipulated to show a specific result that is misleading. There are two problems with this. Annual Data 3. A trailer video introducing the Community Toolkit that can be used for educational and training purposes. The birth rate for . Small samples underrepresent your target audience. More than half of all suicides in 2021 - 26,328 out of 48,183, or 55% - also involved a gun, the highest percentage since 2001. No matter how good a study might be, if it's not written using objective and formal language, then it is at risk to mislead. 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. Well, a Simpsons Paradox can happen when an analyst doesnt look at the complete scope of the data. Misinformation about diseases, illnesses, potential treatments and cures, vaccines, diets, and cosmetic procedures is especially harmful. From there naturally stems the question: who paid them? Ioannidis JP. About eight-in-ten U.S. murders in 2021 - 20,958 out of 26,031, or 81% - involved a firearm. This is with the same aim of making it seem like the cases are dropping. You should only use log scales when there are clear reasons to graph order of magnitude. 1. Whatever the types of graphs and charts you choose to use, it must convey: - The method of calculation (e.g., dataset and time period). . Another way of creating misleading statistics, also linked with the choice of sample discussed above, is the size of said sample. 1. It demonstrates the change in air temperature (Celsius) from 1998 to 2012. It is worth mentioning that 1998 was one of the hottest years on record due to an abnormally strong El Nio wind current. To illustrate, a survey asks 20 people a yes-or-no question. First, although there was an obvious decline, the word rapid is not as justifiableit is certainly less pronounced. For example, if you have a data set with a diastolic blood pressure range of 230 (highest diastolic value) to 25 (lowest diastolic value) = 205 (range), an error probably exists in your data because the values of 230 and 25 aren't valid blood pressure measures in most studies. It is fixed". tristin mays big time rush; Convene federal, state, local, territorial, tribal, private, nonprofit, and research partners to explore the impact of health misinformation and establish best practices for prevention. As one out of twenty will inevitably be deemed significant without any direct correlation, studies can be manipulated (with enough data) to prove a correlation that does not exist or that is not significant enough to prove causation. At a glance, the chart makes you believe that The Times has twice as many full-price subscriptions as its competitor. ) or https:// means youve safely connected Statistics - Using the Truth to Mislead - The Health Care Blog Manipulating the Y-axis+ 6. You can see a graph that shows the UK National debt from 1995 to 2016. 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. Moreover, this is a common topic appearing in tertiary introductory statistics courses, as well as courses on quantitative reasoning. Statistics Can Be Misleading, Especially During a Pandemic The growing number of places people go to for information has made it easier for misinformation to spread at a never-before-seen speed and scale. Uncover the power of spider charts with this complete guide including examples, best practices, and more! The most common ways statistics are misused, besides misinterpretation, are the following: faulty polling, flawed correlations, misleading data visuals, selective bias and small sample size (Lebeid 2018). Misleading Coronavirus graphs. Omitting the baseline. Listen with empathy, ask questions, provide alternative explanations, and dont expect success from one conversation. The power of words is huge, therefore, carefully looking at the way a study is written is another great practice to assess its quality. Cumulative VS. Invest in quantifying the harms of misinformation and identifying evidence-based interventions. please save N95s and surgical masks for our healthcare workers who . In this article, we showcase examples of how data related to the COVID-19 pandemic has been (mis)represented in the media and by governmental agencies and discuss plausible reasons why it has been (mis)represented. Share sensitive information only on official, Statistics is regularly used by urban planners to decide how many apartments, shops, stores, etc. Data (Mis)representation and COVID-19: Leveraging Misleading Data This is problematic because this plot was used to describe statistical trends directly to the general public. Learn everything there is to know about the power of professional area charts. Give researchers access to useful data to properly analyze the spread and impact of misinformation. examples of misleading statistics in healthcare But while that may be the case, people are duped by data visualizations every day. The graph generated a big controversy on social media, especially on Twitter, where users pointed out that the Georgia Health Department had repeatedly used misleading statistics during the COVID-19 outbreak. Figure 1, from the Healthgrades site, shows the results for the first. We start by showing a less obvious example of how having statistical literacy, including an understanding of the art of data visualization, can cause speculation about (mis)representations of data. In the field of healthcare, statistics is important for the following reasons: Reason 1: Statistics allows healthcare professionals to monitor the health of individuals using descriptive statistics.. Reason 2: Statistics allows healthcare professionals to quantify the relationship between . Incentivize coordination across grantees to maximize reach, avoid duplication, and bring together a diversity of expertise. Misleading Statistics In Healthcare - health-improve.org Example #1. Proactively address information deficits. A study of millions of journal articles shows that their authors are increasingly reporting p-values but are often doing so in a misleading way, according to a study by researchers at the Stanford University School of Medicine.P-values are a measure of statistical significance intended to inform scientific conclusions. They sure can. Average monthly temperature in New Haven, CT. Now that weve put the misuse of statistics in context, lets look at various digital age examples of statistics that are misleading across five distinct, but related, spectrums: media and politics, news, advertising, science, and healthcare. An example of misleading statistics is when determining whether to take a medical test for a rare but serious disease like spina bifida. Likewise, what are the motives behind it? examples of misleading statistics in healthcare a comment eurasia group chairman. Many would falsely assume, yes, solely based on the strength of the correlation. Really? Clearly, there is a correlation between the two, but is there causation? There is also no evidence to say that the Florida Law Enforcement Department was purposely deceiving the public. As an entrepreneur and former consultant, Mark Suster advises in an article, you should wonder who did the primary research of said analysis. The most recent case happened not too long ago in September 2021. Several Twitter users began attempting to make sense of what the data were actually saying. Use a broader range of credible sourcesparticularly local sources. You are not required to obtain permission to reuse this article in part or whole. 19 Most Misleading Statistics (That Are Technically Correct) Together, we have the power to build a healthier information environment. This is just one of many examples of misleading statistics in the media and politics. Over the next few paragraphs, we provide some possible ways of using the two previous cases to support learning of comparing samples and association, as well as how data visualizations can (mis)lead both unintentionally and intentionally if the consumer is not critically examining them. 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. Revisit this insightful list of bad statistics examples from time to time to remind you of the importance of using data in a proper way! xkdc's comic illustrates this very well, to show how the "fastest-growing" claim is a totally relative marketing speech: Likewise, the needed sample size is influenced by the kind of question you ask, the statistical significance you need (clinical study vs business study), and the statistical technique. 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. Partner with community groups and other local organizations to prevent and address health misinformation. 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. Statistical reliability is crucial in order to ensure the precision and validity of the analysis. You will end up with a statistical error called selective bias. The number of people aged 60 years or older will rise from 900 million to 2 billion between 2015 and 2050 (moving from 12% to 22% of the total global population). You can be drawn in by the good from what appears to be a reputable source and then can. Misleading Data Visualization Real Life Examples - XB Software One of the most misleading, but rather common, tricks is to use relative risks when talking about the benefits of a treatment, for example to say that "Women taking tamoxifen had about 49% fewer diagnoses of breast cancer", while potential harms are given in absolute risks: "The annual rate of uterine cancer in the tamoxifen arm was 30 per 10,000 Engage with your friends and family on the problem of health misinformation. 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). Let's check those mistakes. should be built in a certain area based on population growth patterns. First of all, the X-axis does not have a label, even though according to the chart, it is meant to show the number of cases over time, this doesn't happen. Surgeon General Our Priorities Health Misinformation Health Misinformation With the abundance of health information available today, it can be hard to tell what is true or not. It also happens to be a topic that is vigorously endorsed by both opponents and proponents via studies. Lets look at one of them closely. There are several mistakes made at the time of the data interpretation. In this case 100/1.2% =88. Now, you might be wondering, how can this be misleading? What the data says about gun deaths in the U.S. Now, if the issue here is not obvious enough, we can see that the Y-axis in this chart starts from 58% and ends at 78%, making the 12% drop from 2009 to 2019 look way more significant than it actually is. Misleading Data Visualization Examples 1. We can all benefit from taking steps to improve the quality of health information we consume. An infographic with tips on how to talk to your community about health misinformation. Take care to apply data responsibly, ethically, and visually, and watch your transparent corporate identity grow. 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. Here Are the Most Misleading Product Claims | Time Example 8: Urban Planning. We then build on these examples to draw connections to how they could be used to enhance statistics teaching and learning, especially as it relates to secondary and introductory tertiary statistics coursework. With the rise of advanced technology and globalized operations, statistical analyses grant businesses insight into solving the extreme uncertainties of the market. These false correlations often leave the general public very confused and searching for answers regarding the significance of causation and correlation. This slide includes the key takeaways from the advisory. Evaluate the effectiveness of strategies and policies to prevent and address health misinformation. Statistics are nfi for to ability and capability to existing as misleading and bad data. There, they speak about two use cases in which COVID-19 information was used in a misleading way. The ASA stated that the claim would be understood by readers to mean that 80 percent of dentists recommend Colgate over and above other brands, and the remaining 20 percent would recommend different brands.. 5) How To Avoid & Identify The Misuse Of Statistics? If the sample size of the study is too small to prove its conclusion then you should be responsible enough and not use these results as an absolute truth as this paves the way for future misinformation. We all need access to trusted sources of information to stay safe and healthy. As we mentioned earlier, the sample size is of utmost importance when it comes to deciding the worth of a study or its results. 5 Ways Writers Use Misleading Graphs To Manipulate You - Venngage For some effective examples of visual information, check out this visualization of wealth shown to scale, or Nicky Case's website, which is full of interactive games that explain how society works. Collecting data from too small a group can skew your survey and test results. There is also the broader context here, which is counties with mask mandates are oftentimes counties that are more densely populated and are seeing larger numbers of cases prompting them to take action. But, what about causation? Likewise, in order to ensure you keep a certain distance to the studies and surveys you read, remember the questions to ask yourself - who researched and why, who paid for it, and what was the sample. Address health misinformation in your community by working with schools, community groups, and health care professionals to develop local strategies against misinformation. Imagine you are in need of risky emergency surgery and have to choose between going to hospitals A or B to get it. It becomes hard to believe any analysis! Verify the accuracy of information by checking with trustworthy and credible sources. The Importance of Statistics in Healthcare (With Examples) Quasi-experimental, single-center, before and after studies are enthusiastically performed. Truncating an axis is another way in which statistics can be misleading. Type the claim into a search engine to see if it has been verified by a credible source. These are nine of the most misleading product claims. Top Five False Statistics | TIME.com This conversation will support students in then reconsidering the first plots from Case 1 from the Kansas Department of Health (see Figure 1), with a new understanding of their usefulness. However, when considering other factors such as the health conditions in which patients arrived at the hospitals we can drive other conclusions. Cherry Picking 2. Statistics presented without context should be viewed critically. In the sections that follow we will show two cases of widely disseminated data visualizations that (mis)represent the situation they are describing. Purposely or not, the time periods we choose to portray will affect the way viewers perceive the data. We found 18 examples of false advertising scandals that have rocked big brands some are still ongoing and not all companies have had to pay up, but each dealt with a fair amount of negative. Although this controversy happened around 1996, the case of Purdue Pharma and their highly addictive drug OxyContin is still affecting thousands of American citizens and has already taken the lives of thousands of others to this date, all due to the misuse of statistics as a marketing tactic. This graph makes the argument that masks help "flatten the curve" (or lower the rate of growth of COVID-19 cases) by pointing out that countries with mask usage had lower growth rates than countries without mask usage. Top 10 Most Flawed Sports Statistics - TheSportster So, let's explore some interesting choices of using data visualization tools and discuss why they are misleading. The Challenges of Cancer Misinformation on Social Media - NCI A quick look shows that counties with mask mandates (the orange line) in place have shown a stark decline in COVID-19 cases over the course of about 3 weeks that has led to lower case numbers than counties without a mask mandate. Basically, there is no problem pro se - but there can be. This technique is often used in politics to exaggerate a result that would otherwise be much less interesting. This article provides guidance on best practices for detecting health misinformation and assessing the accuracy of different information sources. In this case, it can create the wrong idea of a product being healthier than it actually is. Because "everyone who has an online presence today is a publisher" (Cairo, 2019, p. 103), inaccurate or misleading information and visualizations spread with unprecedented ease, particularly about health (Lawrence, 2020).People tend to perceive data visualizations about COVID-19 as objective representations of their numbers because they associate charts with logical arguments and . Yet, as we learned from the Argentinian graph, looks can deceive. Too good to be true: 39 products with exaggerated or misleading claims Looking for U.S. government information and services? What is a conclusion you could draw from this plot that would be more accurate (i.e., pushing them to consider association or correlation concepts)? Learn how to identify and avoid sharing health misinformation. Move with urgency toward coordinated, at-scale investment to tackle misinformation. These are the fake health news that went viral in 2019 Misleading Statistics - Real World Examples For Misuse of Data The intent is to convey a shift in focus from cancer screenings to abortion. Citation2020; GAISE College Report ASA Revision Committee Citation2016), there are specific goals related to being a critical consumer or informed citizenwhich includes being able to dissect and make sense of statistical information designed for the general publicas well as content expectations around facility with accurate data visualizations. Look at the About Us page on the website to see if you can trust the source. You can be the judge. But this didnt come easy. Going against convention 8. The field of statistics is concerned with collecting, analyzing, interpreting, and presenting data..