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Opinion

Lingering gaps permeate public perception of science

by  /  6 February 2015

Glynnis Jones / Shutterstock.com

When it comes to research, scientists and the public don’t always see eye to eye. It’s a long-standing problem, but the results of survey released last week reveal where this opinion gap has grown.

Researchers from the Pew Research Center surveyed 3,748 members of the American Association for the Advancement of Science and 2,002 men and women from the general public. They asked the participants questions probing their views on everything from the role of science in society to specific, touchy subjects.

The groups agree on the poor quality of school education in science, technology, engineering and math, with 46 percent of scientists and 29 percent of the public giving it a ranking of ‘below average.’

There is also overlap in views about childhood vaccines, with 86 percent of scientists and 68 percent of the public believing they should be required, despite claims falsely linking them to autism. These figures haven’t changed much since a 2009 Pew survey, but the fact that one-third of the public thinks vaccines should be optional is worrying, especially in light of the current measles outbreak spreading across the country.

On most other hot-button issues, scientists and citizens are more divided. The biggest gap is for genetically modified (GM) foods, which are considered unsafe by 57 percent of the public but only 12 percent of scientists. There is also a considerable split on evolution, with 98 percent of scientists endorsing the view that humans evolved over time, compared with just 65 percent of the public.

The two groups also diverge on the state of science in the U.S. A whopping 92 percent of scientists say the country’s scientific achievements are “the best” or “among the best,” an upbeat assessment shared by only 54 percent of the public. The gulf on this issue has grown since 2009, when 65 percent of the public considered the U.S. a scientific leader.

“If we don’t have a receptive public that fully understands the nature of science, it makes it much more difficult for society to reap the benefits,” Alan Leshner, chief executive officer of the American Association for the Advancement of Science, said in a press briefing about the findings.

The scientists are not entirely enthusiastic about the state of science in the U.S., either: Only 52 percent say, “This is a good time for science,” down from 76 percent in 2009.

The split on genetically modified foods may reflect the public’s lack of understanding about the most fundamental aspects of the issue, including what makes something a GM food.  The only way to fill the information void, Leshner says in an editorial accompanying the survey results, is for scientists to engage in “genuine, respectful dialogues” with the public.

It’s important not only to help people understand the science, he says, but to acknowledge their fears, political views and religious beliefs.

Research suggests Leshner is right: Simply giving people accurate information is often not enough to influence their opinions and actions; sometimes, these efforts can even backfire. A study last year in Pediatrics found, for example, that pointing out the lack of evidence for a link between vaccines and autism actually made skeptical parents less likely to vaccinate their children. If talking at people doesn’t work, perhaps listening to them will be more effective.


  • Seth Bittker

    Regarding, “…Simply giving people accurate information is often not enough to influence their opinions and actions; sometimes, these efforts can even backfire,” it seems to me that this statement is as applicable to many of the scientists doing autism research today as it is to general public. While some autism researchers are truly open to new findings in the literature, it seems to me that too many cling to certain dogmas which justify their preconceived views of this disorder.
    Here are some dogmas that I think are much too prevalent among scientists:
    1) “The increase in the nominal prevalence of autism is not real.” In other words it reflects identification of cases that would have been missed previously and broadening inclusion criteria. The studies used to justify this statement point out that some of the increase can be explained through factors that do not reflect increases in dysfunction. For example, this Danish study suggests that 60% of the increase over one period of time was related to such factors. http://www.ncbi.nlm.nih.gov/pubmed/25365033 The nominal increase in the US since the early 1980s is something over 2000%. So even if we assume that a significant portion of the increase (say 60% as in this Danish study) can be explained by nominal only factor, that still leaves a real increase of around 800%. In addition the nominal rates of prevalence of autism keep increasing and if the increase were merely picking up cases that had been missed before there should be a dramatic decrease in the percentage of overall autism diagnoses that are severe (for example lack of speech). Yet recent studies suggest that about 30% of those that are being diagnosed with autism still do not speak. http://www.ncbi.nlm.nih.gov/pubmed/23460690 Another way to look at whether the increase in prevalence in autism is real is to look at it in the context of other autoimmune diseases which are increasing as well. One could ask the same question about these autoimmune diseases where the increase is not quite as dramatic as with autism. Yet with some there are objective measures that show that the nominal increase is quite real. For example with celiac increased prevalence by at least a factor of 4 since the 1950s is a fact based on serology studies: http://www.sciencedirect.com/science/article/pii/S001650850900523X

    2) “Autism is 80% genetic.” This statement was made by a very prominent autism researcher at the so-called 18th Annual Advances in Autism Conference held at Mount Sinai Hospital. Statements like this are often used to minimize the importance of environmental factors in autism. I believe many can be traced back to models based on twin and sibling studies in the context of autism such as this one: http://ajp.psychiatryonline.org/doi/abs/10.1176/appi.ajp.2010.10020223 Studies based on these kinds of models are dubious. The environment that I grew up in was very similar to the environment that my sister grew up in, was somewhat similar to the environment that other contemporaries in the United States grew up in, was somewhat different from the environment that contemporaries in Sweden grew up in, and was very different from the environment that contemporaries in Nigeria grew up in. In addition the environment in the United States today is very different from the environment that existed in the United States a couple of decades ago. There is greater use of acetaminophen today, there are much higher levels of fortification and supplementation of vitamins today, there are somewhat higher rates of breastfeeding, there are somewhat lower levels of lead in air pollution, there is greater exposure to flame retardants, there are different pesticides in use, and there are a larger number of vaccines and a different metals mix in them. The environment is not constant and the “average” environmental exposure to a particular compound at any given point in time in a particular location is likely far from optimal and what is optimal in fact is likely highly dependent on an individual’s genetics. This means that any estimate of the genetic component of autism using a group of people at a particular point in time can be very misleading. A relevant question is what percentage of a particular population that have autism today would have gotten it in an environment that is optimal for their particular genetics? This is a very difficult question to answer, and I do not see how a study using a model based on specific population over a certain time frame can really shed much light on this. However, I would suggest that it is a small fraction of those that ultimately do get autism today.

    3) “Many claims are made regarding treatments that are supposedly effective [for autism], but only ABA has been scientifically verified as effective to date.” http://www.asatonline.org/research-treatment/clinical-corner/ethics-and-evidence-based-practice/ Admittedly many scientists no longer make this particular silly claim, but some with a behavioral focus still make statements like this, and many dismiss data in the literature that supports the use of OTC supplements in the context of autism. Double blinded placebo controlled studies have found:
    a) Supplementation with omega 3 fatty acids reduces hyeractivity in autism.
    b) Supplementation with N-aceytlcysteine reduces irritability and stereotyping in autism.
    c) Supplementation with sulforphane results in substantial improvements in behavior in autism.
    d) Supplementation with carnitine significantly improvement in behavior in autism.
    e) Supplementation with probiotics improves dysbiosis markers and modestly improves behavior in autism.
    In addition there are a number of other supplements for which there is excellent biologic rationale and some trial data supporting use such as vitamin C, folinic acid, and methylcobalamin.

    4) “Autism is caused by dysfunction within the brain, therefore we should focus the research effort on the brain.” Statements like this are used to justify research on brain imagining, brain anatomy, and brain tissue in the context of autism. However, any serious perusal of the literature shows that autism is a whole body disease and there are biochemical characteristics of those with autism that are quite different from controls. For example:
    a. Immune dysfunction.
    b. Elevations in monoamine neurotransmitters in the young.
    c. Methylation deficits. Often the oxidized to reduced glutathione ratios are high.
    d. Low plasma cysteine and higher sulfate excretion than controls. This means there is a functional sulphation deficit.
    e. Lower levels of fatty acids in blood plasma than controls.
    f. Higher testosterone than controls.
    g. Higher levels of oxidative stress as demonstrated by markers.
    h. Vascular damage as demonstrated by markers.
    i. Intestinal dysbiosis.
    While each of these metabolic characteristics have implications for neurology, it would seem that few are the result of dysfunctional neurology. Instead it would seem that in autism it almost always is dysfunctional biochemistry driving dysfunctional neurology. For this reason I would suggest studying biochemistry would be more useful than studies of the brain itself in the context of autism.

  • gregboustead

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  • Questioning Answers

    “When it comes to Excel, though, Reinhart and Rogoff aren’t all that different. Wall Streeters can relate. Prominent financial blogger James Kwak calls Excel “one of the greatest, most powerful, most important software applications of all time.” But perhaps we ask too much of the program, or perhaps of our ability to cut and paste. In the past few years, Excel has been implicated in some of the biggest blunders on Wall Street and in finance in general.”

    How do I know this isn’t how the vaccine study is being done? Because, let’s face it, epidemiology is just a statistical analysis. The example I pulled is in the financial sector. I don’t know if they used Excel for their data analysis, or if a formula error permeated each subsequent analysis of the data. But, I also remember from an old statistics class, you can make statistics say whatever you want them to. Very smart people putting a parentheses in the wrong place. (10+4)*2, or 10+4*2? I think it is hard to tell the difference between drug side effects listed, may cause rash, difficulty breathing, or death from what was observed in certain children after a vaccine. Why can we say because someone died when taking Tecfidera (developed a brain infection and died) that that was caused by Tecfidera vs what parents are saying they observed in their children post vaccine. People jump on you and say “correlation does not equal causation”. That only happened to one person in the Tecfidera trial. Not exactly statistically significant. As long as we are relying on epidemiological data, I think we need to keep an open mind that we might be wrong. And, maybe, I am not wholly understanding epidemiological data and why scientists think it is so infallible. But, therein lies your problem with the public. Explain the study more. Not just, this study shows we are not wrong and we are too smart to ever be wrong.

  • Questioning Answers

    This probably explain better what I’m trying to say in the first paragraph “In the wake of last year’s $6.2 billion JPMorgan Chase ( JPM 1.71% ) trading loss, traders have been fired, top executives have been hauled in front of Congress, and the FBI, among other regulators, is investigating. But you know who really needs to be questioned? Bill Gates. According to an internal report on the trading loss released in February, the model that was supposed to monitor and limit the amount of risk the bank’s London traders were taking was “operated through a series of Excel spreadsheets, which had to be completed manually, by a process of copying and pasting data from one spreadsheet to another.” One key measure was added when it should have been averaged. The result: Risk officers at JPMorgan believed the credit derivatives bets were half as risky as they actually were.”

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