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Table 1 presents examples of validation of interpretation of PROs. A major challenge faces developers and users of these measures in establishing a testable theory of the expected and observed relationships among the different concepts and domains of quality of life.

Table 1

Validity and Interpretability of Patient-Reported Outcomes

MeasureValidationInterpretation
Measure of dyspnea in patients with lung diseaseCorrelation with walk test distance, global ratings of dyspneaAn improvement of 4 points represents a small but important difference
Measure of fatigue in patients with heart failureCorrelations with other questionnaires that tap into fatigueAn improvement of 0.5 represents a small but important difference
Measure of vision-related quality of lifeCorrelation with traditional visual acuity measuresResponses in accord with logical expectations for ordered effects (respondents who can drive at night almost always have no other limitations due to vision; respondents unable to recognize others when they are close are severely limited by vision in all aspects of their lives

It is as important to establish a theory of how to link clinical variables with health-related quality of life as it is to link larger determinants of PROs such as political unrest, economic depression, inequalities, and sociocultural trends and processes (Wilson and Cleary, 1995; Patrick and Erickson, 1993; Patrick and Chiang, 2000).
Patrick D.L., Erickson P. (1993). Health status and health policy: Quality of life in health care evaluation and resource allocation. New York: Oxford University Press.