Survivorship Bias

Survivorship bias is a cognitive bias that refers to the irrational tendency to overestimate the likelihood of survival among people who have survived an experience, such as surviving a disease or a near-death experience.

Explanation:

• Survivorship bias occurs when we judge the likelihood of an event happening based on our own experiences or the experiences of others who have survived similar events.
• People tend to overestimate the survival rate of survivors, because we naturally remember and recall survivors more easily than those who did not survive.
• This bias can lead to inaccurate judgments about the likelihood of survival, as it does not account for the fact that survivors are not a random sample of the population.
• Survivors are often more likely to be healthy, motivated, and have a higher survival rate than the general population.

Examples:

• Overestimating the likelihood of survival after a cancer diagnosis based on the experiences of survivors.
• Overestimating the likelihood of surviving a car crash based on the fact that you have not experienced a crash.
• Overestimating the likelihood of recovering from a serious illness based on the experiences of those who have recovered.

Causes:

• Confirmation bias: The tendency to seek out and interpret information that confirms our existing beliefs.
• Availability bias: The tendency to recall and weigh events that are more readily available to our mind.
• Framing bias: The influence of how information is presented on our judgments.

Consequences:

• Inaccurate decision-making: Can lead to incorrect judgments about risks and prognosis.
• Overtreatment: Can lead to unnecessary interventions and treatments.
• False reassurance: Can provide a false sense of security and reduce caution.

Mitigating survivorship bias:

• Consider the sample: Be aware of the limitations of your own sample of survivors.
• Seek diverse perspectives: Consult with a range of sources to get a more complete view.
• Account for survival bias: Be cautious when making judgments based on your own experiences or those of others.
• Seek statistical information: Consult with healthcare professionals or statistics experts for accurate data and probabilities.