Decline Effect

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Parts of the following article are based on the Wikipedia article „Decline Effect“ from Wikipedia, as read on 31.8.2019, under the licence of Creative Commons CC-BY-SA 3.0 Unported (short version). A list of the authors is available on the respective page of Wikipedia. Changes are possible and probable.

This article is closely connected to the article on the Replication Crisis, of which the phenomenon of the decline effect is a part. For further explanation and material please see there.

The term Decline effect denotes an effect where the results of scientific studies receive decreasing support over time, meaning that significant results of the first experiments are going down to the mean with further repetition of the same experiments so that the initial scientific hypothesis is no longer to be considered as valid. The effect was found to be quite frequent in pharmacological research as well as in psychology and in social sciences. Within the “hard sciences” like physics and chemistry it has as yet not been explored sufficiently. The Decline effect is part of the Replication Crisis that is unsettling the sciences since ten years.
The term was first described by psychologist Joseph Banks Rhine in the 1930s to describe the disappearing of extrasensory perception (ESP) effects in psychic experiments conducted by Rhine over the course of study or time. In its more general term, Cronbach, in his review article of science "Beyond the two disciplines of scientific psychology" referred to the phenomenon as "generalizations decay."[1]
The term was used and made more widely known in a 2010 article by Jonah Lehrer published in The New Yorker.[2]

Examples

In his article, Lehrer gives several examples where the decline effect is showing. In the first example, the development of second generation anti-psychotic drugs, reveals that the first tests had demonstrated a dramatic decrease in the subjects' psychiatric symptoms.[2] However, after repeating tests this effect declined and in the end it was not possible to document that these drugs had any better effect than the first generation anti-psychotics.

A well-known example of the decline effect can be seen in early experiments conducted by Professor Jonathan Schooler examining the effects of verbalization on non-verbal cognition. In an initial series of studies Schooler found evidence that verbal rehearsal of previously seen faces or colors markedly impaired subsequent recognition.[3] This phenomenon is referred to as verbal overshadowing. Although verbal overshadowing effects have been repeatedly observed by Schooler, as well as other researchers, they have also proven to be somewhat challenging to replicate.[2][4][5] Verbal overshadowing effects in a variety of domains were initially easy to find, but then became increasingly difficult to replicate indicating a decline effect in the phenomenon. Schooler has now become one of the more prominent researchers examining the decline effect. He has argued that addressing the decline effect may require a major revision to the scientific process whereby scientists log their protocols before conducting their research and then, regardless of outcome, report their findings in an open access repository (such as Brian Nosek's "Project Implicit").[6] Schooler is currently working with the Fetzer Foundation to organize a major meeting of scientists from various disciplines to consider alternative accounts of the decline effect and approaches for rigorously addressing it.[7]

In 1991, Danish zoologist Anders Møller discovered a connection between symmetry and sexual preference of female birds in nature. This sparked a huge interest in the topic and a lot of follow-up research was published. In three years following the original discovery, 90% of studies confirmed Møller's hypothesis. However, the same outcome was published in just four out of eight research papers in 1995, and only a third in next three years.[8]

Explanations

One of the explanations of the effect is regression toward the mean (this is a statistical phenomenon happening when a variable is extreme on the first experiments and by later experiments tend to regress towards average), although this does not explain why sequential results decline in a linear fashion, rather than fluctuating about the true mean as would be expected.[5]

Another reason may be the publication bias: scientists and scientific journals prefer to publish positive results of experiments and tests over null results, especially with new ideas.[2] As a result, the journals may refuse to publish papers that do not prove that the idea works. Later, when an idea is accepted, journals may refuse to publish papers that support it.

In the debate that followed the original article, Lehrer answered some of the questions by claiming that scientific observations might be shaped by one's expectations and desires, sometimes even unconsciously, thus creating a bias towards the desired outcome.[8]

A significant factor contributing to the decline effect can also be the sample size of the scientific research, since smaller sample size is very likely to give more extreme results, suggesting a significant breakthrough, but also a higher probability of an error. Typical examples of this effect are the opinion polls, where those including a larger number of people are closer to reality than those with a small pool of respondents.[9] This suggestion would not appear to account for the observed decrease over time regardless of sample size. Researcher John Ioannidis offers some explanation. He states that early research is usually small and more prone to highly positive results supporting the original idea, including early confirmatory studies. Later, as larger studies are being made, they often show regression to the mean and a failure to repeat the early exaggerated results.[10][11][12]

A 2012 report by National Public Radio's show "On The Media"[13] covered scientists who are exploring another option: that the act of observing the universe changes the universe, and that repeated measurement might actually be rendering earlier results invalid. In other words, antipsychotic drugs did work originally, but the more we measured their effectiveness, the more the laws governing those drugs changed so they ceased to be effective. Science fiction author Geoff Ryman explores this idea and its possible ramifications further in his 2012 short story What We Found,[14] which won the Nebula Award for Best Novelette in 2012.[15]

Discussion

Several commenters have contested Jonah Lehrer's view of the decline effect being a problematic side of the phenomenon, as presented in his New Yorker article. "The decline effect is troubling because it reminds us how difficult it is to prove anything. We like to pretend that our experiments define the truth for us. But that's often not the case. Just because an idea is true doesn't mean it can be proved. And just because an idea can be proved doesn't mean it's true. When the experiments are done, we still have to choose what to believe." [2]

Lehrer's statements about the difficulty of proving anything and publication bias find support from Jerry A. Coyne. Coyne holds that in the fields of genetics and evolutionary biology, almost no research is replicated and there is a premium motivation offered for publishing positive results of research studies. However, he also contests Lehrer's approach of applying conclusions on all fields of science, stating that in physics, chemistry or molecular biology, previous results are constantly repeated by others in order to progress in their own research.[16]

One concern that some [17] have expressed is that Lehrer's article may further fuel people's skepticism about academic science. It was long believed that Lehrer's article originally hinted that academic science is not as rigid as people would like to believe. It is especially the article's ending that has upset many scientists and led to broad criticism of the article. Lehrer ends the article by saying: "Just because an idea is true doesn't mean it can be proved. And just because an idea can be proved doesn't mean it's true. When the experiments are done, we still have to choose what to believe." This has upset scientists in the scientific community. Many have written back to Lehrer and questioned his agenda. Some have characterized Lehrer's assertion as "absurd", while others claiming that Lehrer is trying to use publication bias as an excuse for not believing in anything.[17]

As an answer to the many comments Lehrer received upon publishing the article, Lehrer published a comment on his blog, The Frontal Cortex,[8] where he denied that he was implicitly questioning science and scientific methods in any way. In the same blog comment, Lehrer stated that he was not questioning fundamental scientific theories such as the theory of evolution by natural selection and global warming by calling them "two of the most robust and widely tested theories of modern science".

A further clarification was published as a follow-up note in The New Yorker.[8] In this note, entitled "More Thoughts on the Decline Effect", Lehrer tries mainly to answer the critics by giving examples where scientific research has both failed and succeeded. As an example, Lehrer uses Richard Feynman's commencement speech at Caltech in 1974 as a starting point. In his commencement speech, Feynman used Robert Millikan's and Harvey Fletcher's oil drop experiment to measure the charge of an electron to illustrate how selective reporting can bias scientific results. On the other hand, Feynman finds solace in the fact that other scientists will repeat other scientists' experiments and hence, the truth will win out in the end.

References

  1. Cronbach, L. J. (1975). "Beyond the two disciplines of scientific psychology". American Psychologist. 30 (2): 116–127. doi:10.1037/h0076829.
  2. 2.0 2.1 2.2 2.3 2.4 Jonah_Lehrer (2010). The Truth Wears Off. The New Yorker.
  3. J. W.Schooler: Verbal overshadowing of visual memories: Some things are better left unsaid; In: Cognitive Psychology, Vol. 22, 1990, issue 1, pp.36–71
  4. Chin, J. M.; Schooler, J. W. (2009). "Why do words hurt? content, process, and criterion shift accounts of verbal overshadowing". European Journal of Cognitive Psychology. 20 (3): 396–413. doi:10.1080/09541440701728623.
  5. 5.0 5.1 Schooler, J (2011). "Unpublished results hide the decline effect". Nature. 470 (7335): 437. doi:10.1038/470437a. PMID 21350443.
  6. http://projectimplicit.net/nosek/
  7. Mooneyham, B. W.; Franklin, M. S.; Mrazek, M. D.; Schooler, J. W. (2012). "Modernizing Science: Comments on Nosek and Bar-Anan (2012)". Psychological Inquiry. 23 (3): 281–284. doi:10.1080/1047840X.2012.705246.
  8. 8.0 8.1 8.2 8.3 Jonah Lehrer (2010-12-09). "The Mysterious Decline Effect". Wired.
  9. John Allen Paulos (2010). The decline effect and why scientific 'Truth' so often turns out wrong. ABC News.
  10. Ioannidis, J. P. A. (2005). "Why Most Published Research Findings Are False". PLoS Medicine. 2 (8): e124. doi:10.1371/journal.pmed.0020124. PMC 1182327. PMID 16060722.
  11. Ioannidis, J. P. A. (2005). "Contradicted and Initially Stronger Effects in Highly Cited Clinical Research". JAMA: the Journal of the American Medical Association. 294 (2): 218–228. doi:10.1001/jama.294.2.218. PMID 16014596.
  12. David Gorski (2010). The "decline effect": Is it a real decline or just science correcting itself?. Science-based Medicine.
  13. Brooke Gladstone (2012). The 'Decline Effect' and Scientific Truth. NPR On The Media. Archived from the original on 2012-07-04.
  14. Geoff Ryman (2012). The Year's Best Science Fiction. St. Martin's Griffin.
  15. Mike Addelman (2012). Ryman wins one of world’s top science fiction prizes. University of Manchester.
  16. Jerry Allen Coyne (2010). Why Evolution is True. Wordpress.
  17. 17.0 17.1 John Horgan (2010). The truth we'll doubt: Does the decline effect mean that all science is "truthy"?. Scientific America.