This presentation is part of a symposium on research issues related to studying symptom clusters. This presentation on issues related to measuring symptom clusters builds upon presentations by members of our research team related to the clinical, conceptual, and design issues inherent in research on symptom clusters. Approaches to symptom cluster measurement have ranged from summing or averaging single items on one or more complex instruments to creating a conglomeration of scores from multiple instruments that measure each symptom very differently and use multiple scaling approaches. For example, in a unidimensional approach, sleep and fatigue and depression could each be measured for severity with single items on a tool like the Side Effect Checklist. A multidimensional approach might yield information about different dimensions of a symptom. For example, the Pittsburgh Sleep Quality Index provides information about perceived sleep quality, latency, duration, efficiency, and disturbance, and daytime dysfunction. The General Fatigue Scale provides information about fatigue intensity, distress, and impact on activities of daily living. The Depression Subscale of the Profile of Mood States Questionnaire provides information on intensity only. The measurement of different dimensions for each symptom presents a challenge to the investigator in justifying the comparability of measures. The latter measurement approach could even be more complex by adding the use of a tool like actigraphy, which uses a computer to collect continuous data that can estimate sleep and wake states. There are varying advantages and disadvantages of each approach in terms of the psychometric properties of reliability, validity, and sensitivity. How should these measures be joined to reflect the concept of a symptom cluster? Criteria for ideal approaches to symptom cluster measurement include: 1) consistent scaling, 2) parallel dimensions of the symptom experience such as severity, distress, amount of time experienced etc. and 3) a consistent time frame. An example of such an instrument that has been used in a national survey of over 1200 cancer patients will be provided. Many clinical studies of symptom clusters focus on patterns of symptom experience over time and changes in symptom clusters that are clinically significant and sensitive to nursing interventions. These foci create additional measurement challenges as sensitivity and response burden become critically important. This presentation will set the framework for consideration of varying analytic approaches in the study of symptom clusters.
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