For example, when asking consumers to compare the tastes of different brands of a product, the identities of the latter should be concealed — otherwise consumers will generally tend to prefer the brand they are familiar with. Similarly, when evaluating the effectiveness of a medical drug, both the patients and the doctors who administer the drug may be kept in the dark about the dosage being applied in each case — to forestall any chance of a placebo effect, observer bias, or conscious deception.
Blinding can be imposed on researchers, technicians, subjects, funders, or any combination of them. The opposite of a blind trial is an open trial. Blind experiments are an important tool of the scientific method, in many fields of research — from medicine, forensics, psychology and the social sciences, to natural sciences such as physics and biology and to market research. In some disciplines, such as drug testing, blind experiments are considered essential. In other disciplines, blind experiments would be very useful, but they are totally impractical or unethical. An oft-cited example is in the field of developmental psychology. Although it would be scientifically expedient to raise children under arbitrary experimental conditions, such as on a remote island with a fabricated enculturation, it is obviously a violation of ethics and human rights.
The terms blind (adjective) or to blind (transitive verb) when used in this sense are figurative extensions of the literal idea of blindfolding someone. The terms masked or to mask may be used for the same concept. (This is commonly the case in ophthalmology, where the word 'blind' is often used in the literal sense.)
In a single-blind experiment, the individual subjects do not know whether they are so-called "test" subjects or members of an "experimental control" group. Single-blind experimental design is used where the experimenters either must know the full facts (for example, when comparing sham to real surgery) and so the experimenters cannot themselves be blind, or where the experimenters will not introduce further bias and so the experimenters need not be blind. However, there is a risk that subjects are influenced by interaction with the researchers — known as the experimenter's bias. Single-blind trials are especially risky in psychology and social science research, where the experimenter has an expectation of what the outcome should be, and may consciously or subconsciously influence the behavior of the subject.
A classic example of a single-blind test is the "Pepsi challenge". A marketing person prepares several cups of cola labeled "A" and "B". One set of cups has Pepsi, the others have Coca-Cola. The marketing person knows which soda is in which cup but is not supposed to reveal that information to the subjects. Volunteer subjects are encouraged to try the two cups of soda and polled for which ones they prefer. The problem with a single-blind test like this is the marketing person can give (unintentional or not) subconscious cues which bias the volunteer. In addition it's possible the marketing person could prepare the separate sodas differently (more ice in one cup, push one cup in front of the volunteer, etc.) which can cause a bias. If the marketing person is employed by the company which is producing the challenge there's always the possibility of a conflict of interests where the marketing person is aware that future income will be based on the results of the test.
In a double-blind experiment, neither the individuals nor the researchers know who belongs to the control group and the experimental group. Only after all the data have been recorded (and in some cases, analysed) do the researchers learn which individuals are which. Performing an experiment in double-blind fashion is a way to lessen the influence of the prejudices and unintentional physical cues on the results (the placebo effect, observer bias, and experimenter's bias). Random assignment of the subject to the experimental or control group is a critical part of double-blind research design. The key that identifies the subjects and which group they belonged to is kept by a third party and not given to the researchers until the study is over.
Double-blind methods can be applied to any experimental situation where there is the possibility that the results will be affected by conscious or unconscious bias on the part of the experimenter.
Computer-controlled experiments are sometimes also erroneously referred to as double-blind experiments, since software may not cause the type of direct bias between researcher and subject. Development of surveys presented to subjects through computers shows that bias can easily be built into the process. Voting systems are also examples where bias can easily be constructed into an apparently simple machine based system. In analogy to the human researcher described above, the part of the software that provides interaction with the human is presented to the subject as the blinded researcher, while the part of the software that defines the key is the third party. An example is the ABX test, where the human subject has to identify an unknown stimulus X as being either A or B.
Effective blinding can be difficult to achieve where the treatment is notably effective (indeed, studies have been suspended in cases where the tested drug combinations were so effective that it was deemed unethical to continue withholding the findings from the control group, and the general population), or where the treatment is very distinctive in taste or has unusual side-effects that allow the researcher and/or the subject to guess which group they were assigned to. It is also difficult to use the double blind method to compare surgical and non-surgical interventions (although sham surgery, involving a simple incision, might be ethically permitted). A good clinical protocol will foresee these potential problems to ensure blinding is as effective as possible. It has also been argued that even in a double-blind experiment, general attitudes of the experimenter such as skepticism or enthusiasm towards the tested procedure can be subconsciously transferred to the test subjects.
Evidence-based medicine practitioners prefer blinded randomised controlled trials (RCTs), where that is a possible experimental design. These are high on the hierarchy of evidence; only a meta analysis of several well designed RCTs is considered more reliable.
One example of a blind analysis occurs in neutrino experiments, like the Sudbury Neutrino Observatory, where the experimenters wish to report the total number N of neutrinos seen. The experimenters have preexisting expectations about what this number should be, and these expectations must not be allowed to bias the analysis. Therefore, the experimenters are allowed to see an unknown fraction f of the dataset. They use these data to understand the backgrounds, signal-detection efficiencies, detector resolutions, etc.. However, since no one knows the "blinding fraction" f, no one has preexisting expectations about the meaningless neutrino count N' = N x f in the visible data; therefore, the analysis does not introduce any bias into the final number N which is reported. Another blinding scheme is used in B meson analyses in experiments like BaBar and CDF; here, the crucial experimental parameter is a correlation between certain particle energies and decay times—which require an extremely complex and painstaking analysis—and particle charge signs, which are fairly trivial to measure. Analysts are allowed to work with all of the energy and decay data, but are forbidden from seeing the sign of the charge, and thus are unable to see the correlation (if any). At the end of the experiment, the correct charge signs are revealed; the analysis software is run once (with no subjective human intervention), and the resulting numbers are published. Searches for rare events, like electron neutrinos in MiniBooNE or proton decay in Super-Kamiokande, require a different class of blinding schemes.
The "hidden" part of the experiment—the fraction f for SNO, the charge-sign database for CDF—is usually called the "blindness box". At the end of the analysis period, one is allowed to "unblind the data" and "open the box".
Category:Design of experiments Category:Pharmacology Category:Clinical research Category:Scientific method
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