Measurement validity is an essential component of evidence-based practice, to assure that our assessment tools provide us with accurate information for decision making. Although clinicians constantly face uncertainty in patient management, many decision making strategies can be applied to reduce this uncertainty.
Concepts of measurement validity were introduced in Chapter 6. In this chapter we present statistical procedures related to the accuracy of diagnostic tools, choosing cut-off scores, the application of clinical prediction rules, and methods for measuring clinically meaningful change.
VALIDITY OF DIAGNOSTIC TESTS
Many measuring instruments are specifically designed as screening or diagnostic tools. In a traditional medical framework, a diagnostic test is used to determine the presence or absence of a disease or abnormal condition. A screening test is usually done on individuals who are asymptomatic, to identify those at risk for certain disorders, and to classify patients who are likely to benefit from specific intervention strategies. Because these procedures involve allocation of resources, present potential risks to patients and are used for clinical decision making, it is important to verify their validity.
The results of a diagnostic or screening procedure may be dichotomous, categorical or continuous. The simplest tests will have only a dichotomous outcome: positive or negative, such as pregnancy or HIV status. A categorical test would involve ratings on an ordinal scale, such as +++, ++, +, − to reflect degree of sensation or reflexes. A continuous scale provides the most information regarding the outcome, such as a test measuring degrees of range of motion or hearing decibel level. Ordinal and continuous scales are often converted to dichotomous outcomes using cutoff scores to indicate a "normal" or "abnormal" response.
The ideal diagnostic test, of course, would always be accurate in discriminating between those with and without the disease or condition; it would always have a positive result for someone with the condition, whether a mild or severe case, and a negative result in everyone else. But we know that such tests are not perfect. They may miss abnormalities in those with a particular disorder, or they may identify abnormalities in those without the disorder.
We determine how good a test is by comparing the test result with known diagnostic findings obtained by a reference standard.∗ The reference standard will reflect the patient's true status, either the presence or absence of the condition. The assumption is made that the individual performing the test is blind to the true condition, eliminating possible bias. In some situations, the reference standard will be a concurrent test, such as an X-ray or blood test. In other situations, it will be obtained at a future time, as with a long-term outcome or autopsy. Sometimes there is no clear standard, and one must be defined or created. For instance, studies related to falls often ...