Retractions of Scientific Papers Are Skyrocketing

A trend that bodes ill for the future of scientific publishing, and another signal that science is under attack, is the soaring number of research papers being retracted. According to a recent report in Nature magazine, over 10,000 retractions were issued for scientific papers in 2023.

Although more than 8,000 of these were sham articles from a single publisher, Hindawi, all the evidence shows that retractions are rising more rapidly than the research paper growth rate. The two figures below depict the yearly number of retractions since 2013, and the retraction rate as a percentage of all scientific papers published from 2003 to 2022.

Clearly, there is cause for alarm as both the number of retractions and the retraction rate are accelerating. Nature’s analysis suggests that the retraction rate has more than trebled over the past decade to its present 0.2% or above. And the journal says the estimated total of about 50,000 retractions so far is only the tip of the iceberg of work that should be retracted.

An earlier report in 2012 by a trio of medical researchers reviewed 2,047 biomedical and life-science research articles retracted since 1977. They found that 43% of the retractions were attributable to fraud or suspected fraud, 14% to duplicate publication and 10% to plagiarism, with 21% withdrawn because of error. The researchers also discovered that retractions for fraud or suspected fraud as a percentage of total articles published have increased almost 10 times since 1975.

A recent example of fraud outside the biomedical area is the 2022 finding of the University of Delaware that star marine ecologist Danielle Dixson was guilty of research misconduct, for fabricating and falsifying research results in her work on fish behavior and coral reefs. As reported in Science magazine, the university subsequently sought retraction of three of Dixson’s papers.

The misconduct involves studies by Dixson of the behavior of coral reef fish in slightly acidified seawater, in order to simulate the effect of ocean acidification caused by the absorption of up to 30% of human CO₂ emissions. Dixson and Philip Munday, a former marine ecologist at James Cook University in Townsville, Australia, claimed that the extra CO₂ causes reef fish to be attracted by chemical cues from predators, instead of avoiding them; to become hyperactive and disoriented; and to suffer loss of vision and hearing.

But, as I described in a 2021 blog post, a team of biological and environmental researchers led by Timothy Clark of Deakin University in Geelong, Australia debunked all these conclusions. Most damningly of all, the researchers found that the reported effects of ocean acidification on the behavior of coral reef fish were not reproducible.

The investigative panel at the University of Delaware endorsed Clark’s findings, saying it was “repeatedly struck by a serial pattern of sloppiness, poor recordkeeping, copying and pasting within spreadsheets, errors within many papers under investigation, and deviation from established animal ethics protocols.” The panel also took issue with the reported observation times for two of the studies, stating that the massive amounts of data could not have been collected in so short a time. Dixson has since been fired from the university.

Closely related to fraud is the reproducibility crisis – the vast number of peer-reviewed scientific studies that can’t be replicated in subsequent investigations and whose findings turn out to be false, like Dixson’s. In the field of cancer biology, for example, scientists at Amgen in California discovered in the early 2000s that an astonishing 89% of published results couldn’t be reproduced.

One of the reasons for the soaring number of retractions is the rapid growth of fake research papers churned out by so-called “paper mills.” Paper mills are shady businesses that sell bogus manuscripts and authorships to researchers who need journal publications to advance their careers. Another Nature report suggests that over the past two decades, more than 400,000 published research articles show strong textual similarities to known studies produced by paper mills; the rising trend is illustrated in the next figure.

German neuropsychologist Bernhard Sabel estimates that in medicine and neuroscience, as many as 11% of papers in 2020 were likely paper-mill products. University of Oxford psychologist and research-integrity sleuth Dorothy Bishop found signs of paper mill-activity last year in at least 10 journals from Hindawi, the publisher mentioned earlier.

Textual similarities are only one fingerprint of paper-mill publications. Others include suspicious e-mail addresses that don’t correspond to any of a paper’s authors; e-mail addresses from hospitals in China (because the issue is known to be so common there); manipulated images from other papers; twisted phrases that indicate efforts to avoid plagiarism detection; and duplicate submissions across journals.

Journals, fortunately, are starting to pay more attention to paper mills, revamping their review processes for example. They’re also being aided by an ever-growing army of paper-mill detectives such as Bishop.

Next: Exactly How Large Is the Urban Heat Island Effect in Global Warming?

How Elizabeth Holmes Abused Science to Deceive Investors

Even in Silicon Valley, which is no stranger to hubris and deceit, it stands out – the bold-faced audacity of a young Stanford dropout, who bilked prominent investors out of hundreds of millions of dollars for a fictitious blood-testing technology based on finger-stick specimens.

Credit: Associated Press

Elizabeth Holmes, former CEO of now defunct Theranos, last year settled charges of massive financial fraud brought by the U.S. SEC (Securities and Exchange Commission), and now faces criminal charges in California for her multiple misdeeds. But beyond the harm done to duped investors, fired employees and patients misled about blood test results, Holmes’ duplicity and pathological lies only add to the abuse being heaped on science today.

One of the linchpins of the scientific method, a combination of observation and reason developed and refined for more than two thousand years, is the replication step. Observations that can’t be repeated, preferably by independent investigators, don’t qualify as scientific evidence. When the observations are blood tests on actual patients, repeatability and reliability are obviously paramount. Yet Theranos failed badly in both these areas.

Holmes created a compact testing device originally known as the Edison and later dubbed the minLab, supposedly capable of inexpensively diagnosing everything from diabetes to cancer. But within a year or two, questions began to emerge about just how good it was.

Several Theranos scientists protested in 2013 that the technology wasn’t ready for the market. Instead of repeatable results, the company’s new machine was generating inaccurate and even erroneous data for patients. Whistleblowers addressing a recent forum related how open falsification and cherry-picking of data were a regular part of everyday operations at Theranos. And technicians had to rerun tests if the results weren’t “acceptable” to management.

Much of this chicanery was exposed by Wall Street Journal investigative reporter John Carreyrou. In the wake of his sensational reporting, drugstore chain Walgreens announced in 2015 that it was suspending previous plans to establish blood testing facilities using Theranos technology in more than 40 stores across the U.S.

Among the horrors that Carreyrou documented in a later book were a Theranos test on a 16-year-old Arizona girl, whose faulty result showed a high level of potassium, meaning she could have been at risk of a heart attack. Tests on another Arizona woman suggested an impending stroke, for which she was unnecessarily rushed to a hospital emergency room. Hospital tests contradicted both sets of Theranos data. In January 2016, the Centers for Medicare and Medicaid Services, the oversight agency for blood-testing laboratories, declared that one of Theranos' labs posed "immediate jeopardy" to patients.

Closely allied to the repeatability required by the scientific method is transparency. Replication of a result isn’t possible unless the scientists who conducted the original experiment described their work openly and honestly – something that doesn’t always occur today. To be fair, there’s a need for a certain degree of secrecy in a commercial setting, in order to protect a company’s intellectual property. However, this need shouldn’t extend to internal operations of the company or to interactions between the very employees whose research is the basis of the company’s products.

But that’s exactly what happened at Theranos, where its scientists and technicians were kept in the dark about the purpose of their work and constantly shuffled from department to department. Physical barriers were erected in the research facility to prevent employees from actually seeing the lab-on-a-chip device, based on microfluidics and biochemistry, supposedly under development.

Only a handful of people knew that the much-vaunted technology was in fact a fake. In a 2014 article in Fortune magazine, Holmes claimed that Theranos already offered more than 200 blood tests and was ramping up to more than 1,000. The reality was that Theranos could only perform 12 of the 200-plus tests, all of one type, on its own equipment and had to use third-party analyzers to carry out all the other tests. Worse, Holmes allegedly knew that the miniLab had problems with accuracy and reliability, was slower than some competing devices and, in some ways, wasn’t competitive at all with more conventional blood-testing machines.

Investors were fooled too. Among the luminaries deceived by Holmes were former U.S. Secretaries of State Henry Kissinger and George Shultz, recently resigned Secretary of Defense and retired General James Mattis – all of whom became members of Theranos’ “all-star board” – and media tycoon Rupert Murdoch. Initial meetings with new investors were often followed by a rigged demonstration of the miniLab purporting to analyze their just-collected finger-stick samples.

Holmes not only fleeced her investors but also did a great disservice to science. The story will shortly be immortalized in a movie starring Jennifer Lawrence as Holmes.

Next: How the Scientific Consensus Can Be Wrong

Corruption of Science: Scientific Fraud

One of the most troubling signs of the attack on science is the rising incidence of outright fraud, in the form of falsification and even fabrication of scientific data. A 2012 study published by the U.S. National Academy of Sciences noted an increase of almost 10 times since 1975 in the percentage of biomedical research articles retracted because of fraud. Although the current percentage retracted due to fraud was still very small at approximately 0.01%, the study authors remarked that this underestimated the actual percentage of fraudulent articles, since only a fraction of such articles are retracted.

One of the more egregious episodes of fraud was British gastroenterologist Andrew Wakefield’s claim in a 1998 study that 8 out of 12 children in the study had developed symptoms of autism after injection of the combination MMR (measles-mumps-rubella) vaccine. As a result of the well publicized study, hundreds of thousands of parents who had conscientiously followed immunization schedules in the past panicked and began declining MMR vaccine. And, unsurprisingly, outbreaks of measles subsequently occurred all over the world.

But Wakefield’s paper was slowly discredited over the next 12 years, until the prestigious medical journal The Lancet formally retracted it. The journal’s editors then went one step further in 2011 by declaring the paper fraudulent, citing unmistakable evidence that Wakefield had fabricated his data on autism and the MMR vaccine. Shortly after, the disgraced gastroenterologist’s medical license was revoked.

In 2015, Iowa State University researcher Dong Pyou Han received a prison sentence of four and a half years and was ordered to repay $7.2 million in grant funds, after being convicted of fabricating and falsifying data in trials of a potential HIV vaccine.  On multiple occasions, Han had mixed blood samples from vaccinated rabbits into human HIV antibodies to create the illusion that the vaccine boosted immunity against HIV. Although Han was contrite in court, one of the prosecuting attorneys doubted his remorse, pointing out that Han’s job depended on research funding that was only renewed as a result of his bogus presentations showing the experiments were succeeding.

In 2018, officials at Harvard Medical School and Brigham and Women’s Hospital in Boston called for the retraction of a staggering 31 papers from the laboratory of once prominent Italian heart researcher Piero Anversa, because the papers "included falsified and/or fabricated data." Dr. Anversa’s research was based on the notion that the heart contains stem cells, a type of cell capable of transforming into other cells, that could regenerate cardiac muscle. But other laboratories couldn’t verify Anversa’s idea and were unable to reproduce his experimental findings – a major red flag, since replication of scientific data is a crucial part of the scientific method.

Despite this warning sign, the work spawned new companies claiming that their stem-cell injections could heal hearts damaged by a heart attack, and led to a clinical trial funded by the U.S. National Heart, Lung and Blood Institute. The Boston hospital’s parent company, however, agreed in 2017 to a $10 million settlement with the U.S. government over allegations that the published research of Anversa and two colleagues had been used to fraudulently obtain federal funding. Apart from data that the lab fabricated, the government alleged that it utilized invalid and improperly characterized cardiac stem cells, and maintained deliberately misleading records. Anversa has since left the medical school and hospital.

Scientific fraud today extends even to the publishing world. A recent sting operation involved so-called predatory journals – those charging a fee without offering any publication services (such as peer review), other than publication itself. The investigation found that an amazing 33% of the journals contacted offered a phony scientific editor a position on their editorial boards, four of them immediately appointing the fake scientist as editor-in-chief.   

It’s no wonder then that scientific fraud is escalating. In-depth discussion of recent cases can be found on several websites, such as For Better Science and Retraction Watch.

Next week: Consensus in Science: Is It Necessary?

Corruption of Science: The Reproducibility Crisis

One of the more obvious signs that modern science is ailing is the reproducibility crisis – the vast number of peer-reviewed scientific studies that can’t be replicated in subsequent investigations and whose findings turn out to be false. In the field of cancer biology, for example, researchers discovered that an alarming 89% of published results couldn’t be reproduced. Even in the so-called soft science of psychology, the rate of irreproducibility hovers around 60%. And to make matters worse, falsification and outright fabrication of scientific data is on the rise.

The reproducibility crisis is drawing a lot of attention from scientists and nonscientists alike. In 2018, the U.S. NAS (the National Association of Scholars in this case, not the Academy of Sciences), an academic watchdog organization that normally focuses on the liberal arts and education policy, published a particularly comprehensive examination of the problem. Although the emphasis in the NAS report is on the misuse of statistical methods in scientific research, the report discusses possible causes of irreproducibility and presents a laundry list of recommendations for addressing the crisis.

The crisis is especially acute in the biomedical sciences. Over 10 years ago, Greek medical researcher John Ioannidis argued that the majority of published research findings in medicine were wrong. This included epidemiological studies in areas such as dietary fat, vaccination and GMO foods as well as clinical trials and cutting-edge research in molecular biology. 

In 2011, a team at Bayer HealthCare in Germany reported that only about 25% of published preclinical studies on potential new drugs could be validated. Some of the unreproducible papers had catalyzed entirely new fields of research, generating hundreds of secondary publications. More worryingly, other papers had led to clinical trials that were unlikely to be of any benefit to the participants.

Author Richard Harris describes another disturbing example, of research on breast cancer that was conducted on misidentified skin cancer cells. The sloppiness resulted in thousands of papers being published in prominent medical journals on the wrong cancer. Harris blames the sorry condition of current research on scientists taking shortcuts around the once venerated scientific method.

Cutting corners to pursue short-term success is but one consequence of the pressures experienced by today’s scientists. These pressures include the constant need to win research grants as well as to publish research results in high-impact journals. The more spectacular that a paper submitted for publication is, the more likely it is to be accepted, but often at the cost of research quality. It has become more important to be the first to publish or to present sensational findings than to be correct.      

Another consequence of the bind in which scientists find themselves is the ever increasing degree of misunderstanding and misuse of statistics, as detailed in the NAS report. Among other abuses, the report cites spurious correlations in data that researchers claim to be “statistically significant”; the improper use of statistics due to poor understanding of statistical methodology; and the conscious or unconscious biasing of data to fit preconceived ideas.

Ioannidis links irreproducibility to the habit of assigning too much importance to the statistical p-value. The smaller the p-value, the more likely it is that the experimental data can’t be explained by existing theory and that a new hypothesis is needed. Although p-values below 0.05 are commonly regarded as statistically significant, using this condition as a criterion for publication means that one time in twenty, the experimental data could be the result of chance alone. The NAS report recommends defining statistical significance as a p-value less than 0.01 rather than 0.05 – a much more demanding standard.

The report further recommends integration of basic statistics into curricula at high-school and college levels, and rigorous educational programs in those disciplines that rely heavily on statistics. Beyond statistics, other suggested reforms include having researchers make their data available for public inspection, which doesn’t often occur at present, and encouraging government agencies to fund projects designed purely to replicate earlier research, which again is rare today. The NAS believes that measures like these will help to improve reproducibility in scientific studies as well as keeping advocacy and the politicization of science at bay.

Next week: Corruption of Science: Scientific Fraud