Subjects in experimental research are randomly given to either the control or treatment group. A double blind study has group assignments of every subject from the participant and the researcher experimenting.

If the former is informed of which group they’re assigned, there’s a potential risk of their behavioural change, which will influence the results. On the other hand, if the latter knows which group the former has been assigned, their actions might disclose the task or directly affect the results.

A double blind study protects against such risks, guaranteeing that any significant or insignificant difference between different groups can be assigned to any of the treatments.

Different Blinding Types with Examples

Blinding refers to the withholding group assigned to each participant. Studies can be single binding study (occurs in different study kinds), double binding study or triple blinding study (used mainly in medical research).

• Single Blinding Study: In such a study, participants lack knowledge on which group they’ve been put under until the completion of the experiment to prevent behaviour change. Following is an example of a single blinding study:
• You have come up with a flu vaccine to validate your new treatment’s effectiveness. So, you conduct an experiment, providing the vaccine to half of the participants and the fake vaccine to the remaining that will not be effective.
• If participants realize they’ve got the unreal vaccine and are at risk of the flu, their behaviour might modify. This behaviour change can narrow the loopholes in illness rates among the groups mentioned above, thereby making the flu vaccine less effective.
• So, to achieve uninfluenced and correct research result, you should hide which vaccine is authentic and which is fake.
• Double Blind Study: Researchers carrying out an experimental treatment know every participant’s group. They might inadvertently treat the control group as compared to the treatment group. This can reveal the group assignment to participants or directly influence their outcome. So, the assignment assigned to the group is anonymous to the researcher and the participant. A paradigm of double blind study on the flu vaccine:
• You recruit various experimenters for administering vaccines and evaluate the results of participants. If the experimenters know whether the vaccine is genuine or fake, they may accidentally disclose it to the participants. Thereby directly influence their behaviour and the generated results indirectly as well.
• For example, if experimenters anticipate diminishing the flu symptoms through the vaccine, they may end up evaluating symptoms accidentally incorrectly, perhaps a more effective vaccine. Participants and experimenters are uninformed to group assignments to prevent any anticipation and evaluation on their end. Thus, a smooth double blind study can be carried out on the vaccines.
• Triple Blinding Study: A triple blind study happens when the assignment allocated to the group is unknown to administrators, participants, and those given a task to analyze the information after concluding the experiment.
• Researchers can expect a particular result and analyze the information in various ways once they reach their expected result. An example of a triple blinding study on the flu vaccine:
• In your study on the flu vaccine, you appointed assistants to analyze the information gathered on the rates of infection caused by the flu. You chose to keep group assignments hidden from the involved administrator, participants, and data analyzers – a triple-blind study.
• You must assign participants to group one or group two but don’t provide insights into which group bears which number to those analyzing the data to obtain triple blinding.

Significance of Blinding

The blinding ensures the internal validity of a study or makes you confident enough that any argument, finding or discussion on your flu vaccine will not change the result.

It is unlike a non-blinded study, as in the latter, participants can modify their behaviour or researchers find non-existent effects. Blinding, thus is important and helps avoid biases in scientific research.

Risk Associated with Unblinding

Unblinding happens when researchers blind experimenters or participants but still they gain information on which treatment (fake or real vaccine as in the case of flu vaccine study) is given to them before the completion of an experiment. Thus, unblinding results in indistinguishable outcomes. A suitable paradigm of unblinding:

You’re studying the influence of a recently developed instruction program in your school to better students’ comprehension skills.

You arbitrarily assign this new program to a few students while other students are guided with the standard program. You utilize a single blinding study: you don’t inform students which one out of the two instruction programs they are receiving to keep their behaviour constant. Students in a standard program might put more effort into their reading ability to prepare themselves and for not enrolling in the newly introduced program, or put less effort as they may believe that other students will excel at a much faster rate as compared to them.

Thus, the outcomes can be fallacious unless if you don’t unblind.

• Failure to Blind: Double blind study or triple blinding is usually not possible. However, medical experiments often utilize unreal treatment or a placebo for blinding, while in other research types, the treatment usually can’t be veiled from the experimenter or participant. For instance, physical therapists perform many treatments that cannot be imitated.
  In such scenarios, you should focus on other methodologies to minimize bias.
• Run a single-blind study instead of a double blind study and triple-blind study: Hiding subjects from participants or experimenters may not always be possible. You can stop them from knowing which group they belong to – the control group or treatment group. It is a convenient study and can be used in any type of study other than non-medical studies that don’t allow the use of a placebo in the control group.
• Use objective measures over subjective measures: Participants can hardly influence objective measures over subjective ones; for example, measure fever instead of reporting pain. This reduces the possibility of result influence by experimenters.
• Register data analysis methods in advance: This can stop researchers from implementing various analysis measures until they find the answer they are expecting.

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