A false negative is a type of error that occurs in the context of medical testing or other forms of decision-making. It is the opposite of a false positive, and it occurs when a test result indicates that a person does not have a particular condition, disease, or characteristic, when in fact they do.

One common example of a false negative occurs in the context of pregnancy tests. For example, a woman may take a home pregnancy test and receive a negative result, indicating that she is not pregnant. However, if she subsequently visits a doctor and undergoes more thorough testing, it may be discovered that she is indeed pregnant. In this case, the false negative result of the home pregnancy test may have caused the woman to delay seeking medical care or to make decisions about her health and lifestyle that were based on incorrect information.

Another example of a false negative can occur in the context of testing for infectious diseases. For example, a person may be tested for HIV and receive a negative result, indicating that they are not infected with the virus. However, if the person subsequently becomes ill with symptoms that are consistent with HIV, they may be retested and found to be positive for the virus. In this case, the false negative result of the initial test may have caused the person to engage in risky behaviors or to delay seeking medical care, potentially leading to more severe illness or even death.

Overall, false negatives can have significant negative consequences for individuals and society as a whole. In the context of medical testing, they can lead to delays in diagnosis and treatment, which can result in worsening health outcomes and increased costs. In other contexts, such as criminal justice or security screening, false negatives can allow dangerous individuals or objects to pass undetected, potentially leading to harm. Therefore, it is important to take steps to reduce the occurrence of false negatives, such as using more accurate or sensitive tests, and to consider the potential consequences of false negatives when making decisions based on test results.