Friday, September 27, 2002: 1:15 PM-2:45 PM

Symptoms as Clusters

Recently, attention has shifted from the study of individual symptoms to the study of symptom clusters. A symptom cluster has been defined as concurrent symptoms that influence one another (Dodd, Miaskowski, & Paul, 2001). Although this shift has directed attention to the importance of symptom management, there has not been a systematic articulation or testing of possible hypotheses that could explain how interventions targeted to two or more symptoms might influence the overall symptom experience. This symposium will describe and analyze the problems and issues that must be considered in designing research related to the study of symptom clusters.

The first presentation will approach the problem of symptom clusters from the perspective of the clinican in managing multiple symptoms in clinical practice. Case examples of symptom clusters will be used to examine the complexity of this problem.

In the second presentation, conceptual issues will be examined including the naming and definition of a symptom cluster, the potential relationships between and among component symptoms, and the potential effect of an intervention on the cluster and its components.

The third presentation will focus on study design issues that impact the study of symptom clusters. Research on symptom clusters presents several design challenges. Depending upon the focus of the individual study, these challenges range from recognizing and dealing with factors likely to influence symptom reporting to establishing temporal precedence within complex causal processes that change over time. The purpose of this presentation is to explore some of these issues and propose design strategies that may be helpful in addressing some of these complex issues.

In the fourth presentation, measurement issues will be discussed. Approaches to symptom cluster measurement have ranged from adding single items on one or more complex instruments to creating a conglomeration of scores from multiple instruments that measure constructs very differently and used multiple scaling approaches. Criteria for ideal approaches to symptom cluster measurement will be discussed and exemplified.

The focus of the fifth presentation will be on the analysis of data in research on symptom clusters. This presentation will provide examples of how a variety of statistical analyses (including hierarchial cluster analysis and mediation analysis) can be used to explore the underlying association among processes that lead to the phenomena of symptom clusters.

With a clear grounding in the clinical practice of symtom management, this symposium will provide important conceptual information for the study of symptom clusters.

Organizer:Kyra M. Whitmer, PhD, associate professor
Why Address Symptoms as Clusters?
Kyra M. Whitmer, PhD, associate professor
Considering the Concept of a Symptom Cluster
Andrea Barsevick, DNSc, director of nursing research & education, Susan Beck, APRN, PhD, FAAN, associate dean for research and scholarship, Kyra M. Whitmer, PhD, associate professor, William Dudley, PhD
Design Issues and Considerations for Research on Symptom Clusters
Lillian Nail, PhD, FAAN, Dr. May Rawlinson Distinguished professor & senior scientist, Susan Beck, APRN, PhD, FAAN, associate dean for research and scholarship, Andrea Barsevick, DNSc, director of nursing research & education, Kyra M. Whitmer, PhD, associate professor, William Dudley, PhD
Issues in Measuring Symptom Clusters
Susan Beck, APRN, PhD, FAAN, associate dean for research and scholarship, Andrea Barsevick, DNSc, director of nursing research & education, William Dudley, PhD, director of applied statistics, Lillian Nail, PhD, FAAN, Dr. May Rawlinson Distinguished professor & senior scientist, Kyra M. Whitmer, PhD, associate professor
Statistical Approaches for the Study of Symptom Clusters
William Dudley, PhD, Susan Beck, APRN, PhD, FAAN, associate dean for research and scholarship, Andrea Barsevick, DNSc, director of nursing research & education

The Advancing Nursing Practice Excellence: State of the Science