Unfortunately, this kind of risk-benefit analysis is not easy to do and is riddled with problems. From a statistical point of view, people are not very good about assessing risk. For example, most people are far more afraid of flying on a plane than driving on a highway, even though the actual risk of injury or death is much higher when driving. We tend to underestimate risks when we feel we are in control (we are driving) and overestimate them when someone else is in control (the pilot is flying the plane). Similarly, when some parents decide not to vaccinate, they feel in control and may underestimate the risks. Because the vaccines are manufactured and given by others, these parents may feel less in control and may overestimate the risks.
We also have a hard time comprehending small risks. We can generally grasp a one in ten risk, maybe even a one in a hundred risk. However, once the risk is higher, people tend to lump them all in a category of “low risk,” not distinguishing between a one in a thousand and a one in a million risk. Those risks are markedly different, though. If four million babies are born every year in the United States, a one in a thousand risk affects four thousand babies where a one in a million risk affects only four babies. The risks associated with vaccines and with the diseases they prevent are often in the range of one in a thousand to one in a million. So when we lump these “low risk” events together, we might not realize that some events are truly riskier than others and that more children might be affected.
It is also hard to separate out the emotional overlay in a risk-benefit analysis. In our opinion, you shouldn’t try to remove emotions from the decision, but you should try to recognize hidden emotions. By opening them up to the light of day, you might begin to see how they are influencing your decision.
You can then decide if you want to give them that much influence.
For example, we have a family in our practice that had a child born with a specific genetic abnormality. The diagnosis was very unexpected because their prenatal testing had put them at low risk for this problem, around one in five hundred pregnancies. The situation was very hard on the parents, and it took time for them to adjust to their child’s special needs.
When they became pregnant again, they were clear they did not want to risk facing this genetic abnormality again. They opted for every prenatal test, no matter how low the risk of abnormality. They knew they were not making decisions based on statistics but on emotions. In this risk-benefit analysis, their emotions were the driving factors.