What term describes an assessment error in which a test result is positive when no pathology is present?

• A. False Positive
• B. False Negative
• C. Type II Error
• D. Type I Error

Answer: (D)

A Type I error explains this scenario. It is the error you make when you conclude there is disease present based on a positive test, even though there is no pathology. In statistical terms, it means rejecting the null hypothesis (that there is no disease) when it is actually true. This is the same concept as a false positive in diagnostic testing. It’s important to connect the idea to testing characteristics: a test with a higher rate of false positives will increase Type I errors, leading to unnecessary follow-up or treatment for patients who don’t actually have the disease.