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People Who See Themselves as Unique Are Drawn to Conspiracy Theories
A new study finds a link between a desire for uniqueness and a willingness to believe in conspiracy theories.
Two opposite statements, both of them true:
- We're all the same — We all crave the same things: shelter, food, company and comfort, and we're all here for just a little while.
- You're unique — The specific details of your life are not the same as anyone else's.
Most people understand and accept this paradox. And yet a study recently published in Social Psychology has found that the more you relate to the second statement—and the less you care about the first—the more likely you are to believe in hidden, malevolent forces at work. It has to do with the way an “I see something other people can't see" attitude reinforces the idea that one is exceptionally perceptive, and unique.
The research—a trio of studies—was conducted by Anthony Lantian, Dominique Muller, Cécile Nurra, and Karen M. Douglas at Grenoble Alps University.
Image source: George Rudy/Shutterstock
The first test was designed to confirm or refute the researchers' prediction that “high believers in conspiracy theories assume that they possess information that other people do not have about the events in question." There were 190 French subjects — with an average age of 24.85, and 117 of whom were female — who responded to online questionnaires in exchange for entry in a gift-card lottery. 63.2% of the respondents were students.
There were two rounds of questions.
- In the first round, the researchers were looking to identify those of their subjects who believed in conspiracies. Using a scale of 1-completely false to 9-completely true, subjects were asked how they felt about the statement, “The assassination of John F. Kennedy was not committed by the lone gunman, Lee Harvey Oswald, but was rather a detailed, organized conspiracy to kill the president."
- The goal of the second round was to determine the degree to which believers were basing their opinions on access to information they felt others didn't have. They were asked to respond to, “The information I used to answer questions asked in the previous Section 1 are: "using a scale of 1-disclosed to the public view to 9-hidden from public view.
Confirming their initial hypothesis, the researchers found that the more strongly respondents believed in the Kennedy assassination conspiracy, the “more they thought they possessed scarce information."
This test looked at subjects who had a need to see themselves as special, to find out if it was true that “people with a chronic high need for uniqueness believe in conspiracy theories to a larger extent." They studied 208 participants—average age, 32.44, and 96 female—who worked for Amazon Mechanical Turk in the U.S. Again, the online test had two phases.
- First, the researchers identified subjects with a need for feeling special using a questionnaire based on the Need for Uniqueness Scale (Snyder and Fromkin, 1977). The respondents' scale of responses went from 1-Strong disagreement to 5-Strong agreement.
- Next, subjects responded to a variety of conspiracy-related statements—none of which used the word “conspiracy" so as to avoid tipping the researchers' hand—to assess their affinity for conspiracy theories, with a scale of 1-Definitely not true to 5-Definitely true. Included were statements such as, “A lot of important information is deliberately concealed from the public out of self-interest," and, “I think that the official version of the events given by the authorities very often hides the truth."
Here again, the researchers' suspicions were borne out: “a higher need for uniqueness… was associated with higher belief in conspiracy theories…"
In the final test, researchers wanted to see if a newly developed sense of specialness also produced a proclivity for conspiracy theories. That is, “people for whom a high need for uniqueness is activated should manifest higher conspiracy beliefs than people for whom a lower need for uniqueness is activated." There were 143 French psychology undergraduates in the final study—age 20.93, and 121 female. A pair of two-part sessions were held. The second was 15 days after the first, and with different testers so the subjects wouldn't be aware this was a followup to the first session.
- In the first session, the researchers began with an assessment of the subjects' level of belief in conspiracies, employing a single-item conspiracy questionnaire (Lantian et al., 2016). Next, subjects were asked to respond to questions based on the Self-Attributed Need for Uniqueness (Lynn & Harris, 1997) scale. In this way, the researchers established baselines for each subject's initial attraction to conspiracy theories and for how much they cared about being special.
- In the second session, subjects were tasked with writing about either the importance of individuality or conformity—the individuality assignment was designed to increase a desire for uniqueness, and the conformity writing was meant to reduce it (Cheema & Kaikati, 2010). Next, subjects read a fake news account of a fictional bus accident in Moldova, after which they were asked to rate their reaction to four statements. Two of the statements reflected a conspiratorial slant—“The coach crash was deliberately planned by the established power in the country"—and two did not—“This event is the result of an unfortunate accident due to uncontrollable factors [e.g., bad weather, mechanical failure, etc.]" Respondents used a scale of 1-Strongly disagree to 9-Strongly agree.
The researchers found that there was in fact a correlation between an attraction to conspiracy theories and a desire for specialness that had only been recently developed. The test's conclusion wasn't as decisive as the team had hoped, however, so a fourth, slightly altered study was run for validation.
You may be reminded of the old joke, “Just because I'm paranoid doesn't mean they're not out to get me," which reminds us that every now and then a conspiracy theory does turn out to be true. By using the Kennedy assassination in one test, the researchers may have stepped into such a gray area, given that the facts in the case do seem somewhat unsettled.
In any event, the next time one of us feels the seductive pull of a juicy conspiracy theory, we might stop and take moment: Are we really seeing something in the world that few others see, or are we just seeing something previously unsuspected about ourselves?
Northwell Health is using insights from website traffic to forecast COVID-19 hospitalizations two weeks in the future.
- The machine-learning algorithm works by analyzing the online behavior of visitors to the Northwell Health website and comparing that data to future COVID-19 hospitalizations.
- The tool, which uses anonymized data, has so far predicted hospitalizations with an accuracy rate of 80 percent.
- Machine-learning tools are helping health-care professionals worldwide better constrain and treat COVID-19.
The value of forecasting<img type="lazy-image" data-runner-src="https://assets.rebelmouse.io/eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpbWFnZSI6Imh0dHBzOi8vYXNzZXRzLnJibC5tcy8yNTA0Njk2OC9vcmlnaW4uanBnIiwiZXhwaXJlc19hdCI6MTYyMzM2NDQzOH0.rid9regiDaKczCCKBsu7wrHkNQ64Vz_XcOEZIzAhzgM/img.jpg?width=980" id="2bb93" class="rm-shortcode" data-rm-shortcode-id="31345afbdf2bd408fd3e9f31520c445a" data-rm-shortcode-name="rebelmouse-image" data-width="1546" data-height="1056" />
Northwell emergency departments use the dashboard to monitor in real time.
Credit: Northwell Health<p>One unique benefit of forecasting COVID-19 hospitalizations is that it allows health systems to better prepare, manage and allocate resources. For example, if the tool forecasted a surge in COVID-19 hospitalizations in two weeks, Northwell Health could begin:</p><ul><li>Making space for an influx of patients</li><li>Moving personal protective equipment to where it's most needed</li><li>Strategically allocating staff during the predicted surge</li><li>Increasing the number of tests offered to asymptomatic patients</li></ul><p>The health-care field is increasingly using machine learning. It's already helping doctors develop <a href="https://care.diabetesjournals.org/content/early/2020/06/09/dc19-1870" target="_blank">personalized care plans for diabetes patients</a>, improving cancer screening techniques, and enabling mental health professionals to better predict which patients are at <a href="https://healthitanalytics.com/news/ehr-data-fuels-accurate-predictive-analytics-for-suicide-risk" target="_blank" rel="noopener noreferrer">elevated risk of suicide</a>, to name a few applications.</p><p>Health systems around the world have already begun exploring how <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7315944/" target="_blank" rel="noopener noreferrer">machine learning can help battle the pandemic</a>, including better COVID-19 screening, diagnosis, contact tracing, and drug and vaccine development.</p><p>Cruzen said these kinds of tools represent a shift in how health systems can tackle a wide variety of problems.</p><p>"Health care has always used the past to predict the future, but not in this mathematical way," Cruzen said. "I think [Northwell Health's new predictive tool] really is a great first example of how we should be attacking a lot of things as we go forward."</p>
Making machine-learning tools openly accessible<p>Northwell Health has made its predictive tool <a href="https://github.com/northwell-health/covid-web-data-predictor" target="_blank">available for free</a> to any health system that wishes to utilize it.</p><p>"COVID is everybody's problem, and I think developing tools that can be used to help others is sort of why people go into health care," Dr. Cruzen said. "It was really consistent with our mission."</p><p>Open collaboration is something the world's governments and health systems should be striving for during the pandemic, said Michael Dowling, Northwell Health's president and CEO.</p><p>"Whenever you develop anything and somebody else gets it, they improve it and they continue to make it better," Dowling said. "As a country, we lack data. I believe very, very strongly that we should have been and should be now working with other countries, including China, including the European Union, including England and others to figure out how to develop a health surveillance system so you can anticipate way in advance when these things are going to occur."</p><p>In all, Northwell Health has treated more than 112,000 COVID patients. During the pandemic, Dowling said he's seen an outpouring of goodwill, collaboration, and sacrifice from the community and the tens of thousands of staff who work across Northwell.</p><p>"COVID has changed our perspective on everything—and not just those of us in health care, because it has disrupted everybody's life," Dowling said. "It has demonstrated the value of community, how we help one another."</p>
"You dream about these kinds of moments when you're a kid," said lead paleontologist David Schmidt.
- The triceratops skull was first discovered in 2019, but was excavated over the summer of 2020.
- It was discovered in the South Dakota Badlands, an area where the Triceratops roamed some 66 million years ago.
- Studying dinosaurs helps scientists better understand the evolution of all life on Earth.
Credit: David Schmidt / Westminster College<p style="margin-left: 20px;">"We had to be really careful," Schmidt told St. Louis Public Radio. "We couldn't disturb anything at all, because at that point, it was under law enforcement investigation. They were telling us, 'Don't even make footprints,' and I was thinking, 'How are we supposed to do that?'"</p><p>Another difficulty was the mammoth size of the skull: about 7 feet long and more than 3,000 pounds. (For context, the largest triceratops skull ever unearthed was about <a href="https://www.tandfonline.com/doi/abs/10.1080/02724634.2010.483632" target="_blank">8.2 feet long</a>.) The skull of Schmidt's dinosaur was likely a <em>Triceratops prorsus, </em>one of two species of triceratops that roamed what's now North America about 66 million years ago.</p>
Credit: David Schmidt / Westminster College<p>The triceratops was an herbivore, but it was also a favorite meal of the T<em>yrannosaurus rex</em>. That probably explains why the Dakotas contain many scattered triceratops bone fragments, and, less commonly, complete bones and skulls. In summer 2019, for example, a separate team on a dig in North Dakota made <a href="https://www.nytimes.com/2019/07/26/science/triceratops-skull-65-million-years-old.html" target="_blank">headlines</a> after unearthing a complete triceratops skull that measured five feet in length.</p><p>Michael Kjelland, a biology professor who participated in that excavation, said digging up the dinosaur was like completing a "multi-piece, 3-D jigsaw puzzle" that required "engineering that rivaled SpaceX," he jokingly told the <a href="https://www.nytimes.com/2019/07/26/science/triceratops-skull-65-million-years-old.html" target="_blank">New York Times</a>.</p>
Morrison Formation in Colorado
James St. John via Flickr
|Credit: Nobu Tamura/Wikimedia Commons|
The scent of sickness: 5 questions answered about using dogs – and mice and ferrets – to detect disease
Could medical detection animals smell coronavirus?
Study confirms the existence of a special kind of groupthink in large groups.
- Large groups of people everywhere tend to come to the same conclusions.
- In small groups, there's a much wider diversity of ideas.
- The mechanics of a large group make some ideas practically inevitable.
The grouping game<img type="lazy-image" data-runner-src="https://assets.rebelmouse.io/eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpbWFnZSI6Imh0dHBzOi8vYXNzZXRzLnJibC5tcy8yNTQ1NDE2Ni9vcmlnaW4uanBnIiwiZXhwaXJlc19hdCI6MTYxMjI2MzA4OX0.RLrswIWbuEzHNqsw0F7EUrp9jPn7OulLPqCxcZT11ik/img.jpg?width=980" id="159b8" class="rm-shortcode" data-rm-shortcode-id="0feb15d2d7dde144c710c2f4f1e5350c" data-rm-shortcode-name="rebelmouse-image" data-width="2767" data-height="382" />
Some of the shapes used in the experiment
Credit: Guilbeault, et al./University of Pennsylvania<p>The researchers tested their theory with 1,480 people playing an online "Grouping Game" via Amazon's Mechanical Turk platform. The individuals were paired with another participant or made a member of a group of 6, 8, 24, or 50 people. Each pair and group were tasked with categorizing the symbols shown above, and they could see each other's answers.</p><p>The small groups came up with wildly divergent categories—the entire experiment produced nearly 5,000 category suggestions—while the larger groups came up with categorization systems that were virtually identical to each other.</p><p><a href="https://www.asc.upenn.edu/news-events/news/why-independent-cultures-think-alike-its-not-in-the-brain" target="_blank">Says Centol</a>a, "Even though we predicted it, I was nevertheless stunned to see it really happen. This result challenges many long-held ideas about culture and how it forms."</p><p>Nor was this unanimity a matter of having teamed-up like-minded individuals. "If I assign an individual to a small group," says lead author Douglas Guilbeault, "they are much more likely to arrive at a category system that is very idiosyncratic and specific to them. But if I assign that same individual to a large group, I can predict the category system that they will end up creating, regardless of whatever unique viewpoint that person happens to bring to the table."</p>
Why this happens<img type="lazy-image" data-runner-src="https://assets.rebelmouse.io/eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpbWFnZSI6Imh0dHBzOi8vYXNzZXRzLnJibC5tcy8yNTQ1NDE4NC9vcmlnaW4uanBnIiwiZXhwaXJlc19hdCI6MTYyMjkzMDg0Nn0.u2hdEIgNw4drFZ2frzx0AJ_MAxIizuM98rdovQrIblk/img.jpg?width=980" id="d3444" class="rm-shortcode" data-rm-shortcode-id="5da57d66e388fad0f1c17afb09af90a7" data-rm-shortcode-name="rebelmouse-image" data-width="1440" data-height="822" />
The many categories suggested by small groups on the left, the few from large groups on the right
Credit: Guilbeault, et al./Nature Communications<p>The striking results of the experiment correspond to a <a href="https://www.nature.com/articles/s41562-019-0607-5" target="_blank">previous study</a> done by NDG that investigated tipping points for people's behavior in networks.</p><p>That study concluded that after an idea enters a discussion among a large network of people, it can gain irresistible traction by popping up again and again in enough individuals' conversations. In networks of 50 people or more, such ideas eventually reach critical mass and become a prevailing opinion.</p><p>The same phenomenon does not happen often enough within a smaller network, where fewer interactions offer an idea less of an opportunity to take hold.</p>