TLDR: In a blinded experiment, information that could influence the participants is kept hidden until after the experiment is done. This helps reduce biases and errors that can come from people's expectations or knowledge of the experiment. Blinding can be done for different people involved in the experiment, like the participants, researchers, and data analysts. It's an important tool in scientific research, especially in fields like medicine. However, it's not always possible or ethical to blind everyone in every type of experiment.

Blinded experiments have been used for a long time. The first known blinded experiment was conducted in 1784 by the French Royal Commission on Animal Magnetism. They blindfolded mesmerists and asked them to identify objects filled with "vital fluid," but they couldn't do it. In 1817, a blind experiment compared the musical quality of a Stradivarius violin to a guitar-like design. The judges listened to the instruments behind a curtain to avoid bias. Blinding has been used in various fields, including medicine, physics, social sciences, and forensics.

Blinding is important because it helps reduce biases and errors. If participants or researchers know which treatment they're receiving or administering, it can affect their behavior and perception of the results. For example, if a patient knows they're receiving a certain medication, they might report different outcomes compared to if they didn't know. Blinding can also help prevent observer bias, where researchers' expectations influence their observations. Unblinding, when someone figures out the hidden information, can introduce bias and affect the results of the experiment.

Blinding can be challenging in some cases. For example, it's difficult to blind surgical interventions or compare surgical and non-surgical treatments. In pharmacological trials, unblinding is common, especially in studies on pain medication and antidepressants. Patients and clinicians often figure out the treatment assignments, which can affect the results. Blinding is also important in other fields like music auditions, where judges listen to performers behind a curtain to avoid bias.

There are different levels of blinding, like single-blind, double-blind, and triple-blind studies. These terms describe who is blinded to what information. However, the meaning of these terms can vary from study to study, so it's important to report who was blinded and how well the blinding was done. Assessing the success of blinding can be challenging, but it's necessary to ensure the quality of the experiment.

Blinding is not always perfect, and there can be instances of premature unblinding, where participants figure out the hidden information before the study is complete. Premature unblinding can introduce bias and affect the results. It can happen when participants infer information from experimental conditions or when they experience side effects that reveal their treatment assignment. Asking participants to guess their treatment can also prompt them to try to infer the information, leading to unblinding.

In some cases, it's necessary to unblind participants after the study is complete to inform them of their treatment allocation. This is called post-study unblinding and is done as a courtesy to study participants. It's not mandatory, but it's a common practice. Premature unblinding, on the other hand, is a source of bias and should be strictly documented and reported.

Bias due to poor blinding can favor the experimental group and lead to inflated effect sizes and false positives. It's important to assess and report the success of blinding to ensure the validity of the results. Blinding is considered essential in medicine, but there is evidence of high levels of unblinding in pharmacological trials for pain and depression. Blinding is also important in other fields like acupuncture, physics, social sciences, and forensics.

In summary, a blinded experiment is one where information that could influence the participants is kept hidden until after the experiment is complete. It helps reduce biases and errors that can come from people's expectations or knowledge of the experiment. Blinding is important in various fields of research, but it can be challenging to achieve in some cases. Unblinding can introduce bias and affect the results, so it's important to assess and report the success of blinding.