2008 Woodie Awards
Think you're mentally normal? Think again
Issue date: 5/1/08
Third, abnormal testing is not tied to gender in any statistically significant way. Men are not more likely to be "abnormal," nor is the reverse true, despite what you may want to think about your most recent ex. Race was also not a significant factor.
However, rates of abnormality do show interesting correlations to age, education and IQ levels.
But even after these variables are factored out of the equation, scientists have still found that certain levels of abnormal testing in healthy adults are "normal."
It is vital that doctors receive accurate tests for the normality of their patients' performances so they can make accurate and helpful diagnoses. Therefore, the team has concluded, there are certain statistical models that predict levels of abnormal test scores in healthy, normal adults.
But because the simulations are not always perfect, the best way of analyzing test results is this: If a patient tests normally more often than is predicted for normal people, that person is likely to be fine.
The opposite is also generally true: If a person tests significantly more abnormally than the predictions for a normal person, it might be that the person's brain is somehow not working at normal capacity.
But that's about as accurate and straightforward as the test results come. Mainly, it's important that doctors use their training and keen skills of observation.
The point to go home with is this: "Abnormality" rolls along a bell curve, so even with one little abnormality blighting your record, you're likely ahead of the curve, anyhow. This is Hopkins, after all.
However, rates of abnormality do show interesting correlations to age, education and IQ levels.
But even after these variables are factored out of the equation, scientists have still found that certain levels of abnormal testing in healthy adults are "normal."
It is vital that doctors receive accurate tests for the normality of their patients' performances so they can make accurate and helpful diagnoses. Therefore, the team has concluded, there are certain statistical models that predict levels of abnormal test scores in healthy, normal adults.
But because the simulations are not always perfect, the best way of analyzing test results is this: If a patient tests normally more often than is predicted for normal people, that person is likely to be fine.
The opposite is also generally true: If a person tests significantly more abnormally than the predictions for a normal person, it might be that the person's brain is somehow not working at normal capacity.
But that's about as accurate and straightforward as the test results come. Mainly, it's important that doctors use their training and keen skills of observation.
The point to go home with is this: "Abnormality" rolls along a bell curve, so even with one little abnormality blighting your record, you're likely ahead of the curve, anyhow. This is Hopkins, after all.
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