Abstract:Cancer patients may experience multiple concurrent symptoms caused by the cancer, cancer treatment, or their combination. The complex relationships between and among symptoms, as well as the clinical antecedents and consequences, have not been well described. This paper examines the literature on cancer symptom clusters focusing on the conceptualization, design, measurement, and analytic issues. The investigation of symptom clustering is in an early stage of testing empirically whether the characteristics defined in the conceptual definition can be observed in cancer patients. Decisions related to study design include sample selection, the timing of symptom measures, and the characteristics of symptom interventions. For self-report symptom measures, decisions include symptom dimensions to evaluate, methods of scaling symptoms, and the time frame of responses. Analytic decisions may focus on the application of factor analysis, cluster analysis, and path models. Studying the complex symptoms of oncology patients will yield increased understanding of the patterns of association, interaction, and synergy of symptoms that produce specific clinical outcomes. It will also provide a scientific basis and new directions for clinical assessment and intervention. Key Words: Symptoms, symptom clusters, symptom management, quality of life Article: INTRODUCTION Typical symptoms associated with cancer and its treatment include fatigue, nausea-vomiting, pain, depression, and difficulty sleeping. In cancer care, these symptoms can be caused by cancer, cancer treatment, or the combination of cancer and cancer treatment. Despite the knowledge that individuals undergoing cancer therapy are likely to experience multiple concurrent symptoms, most research on symptoms in cancer has examined individual symptoms.1 The relationship between and among cancer symptoms and the impact on quality of life have not been evaluated systematically. The purpose of this paper is to examine critical research issues related to the conceptualization, design, measurement, and analysis of multiple concurrent symptoms or symptom clusters in oncology. The Concept of a Symptom ClusterRecently, Dodd et al .2 called for consideration of the "symptom cluster" in oncology research to capture the complexity of the cancer symptom experience. The term "symptom cluster" has not

Patients with diabetes must incorporate a complicated regimen of self-management into their daily lives (e.g., taking medication, diet, exercise). Diabetes self-management (DSM) is the cornerstone for controlling diabetes and preventing diabetic complications. The purpose of this study was to test a model describing the effects of individual and environmental factors on DSM in a sample of patients with diabetes in Beijing, China. Survey data were gathered from a convenience sample of 201 Chinese adults with type 2 diabetes during outpatient visits. Data were analyzed using structural equation modeling. Model fit indices indicated a good fit to the data. In the final model, belief in treatment effectiveness and diabetes self-efficacy were proximate factors affecting DSM. Knowledge, social support, and provider-patient communication affected self-management indirectly via beliefs and self-efficacy. The findings provide a theoretical basis to direct the development of interventions for improving DSM in Chinese individuals with diabetes.

The results of the study provide researchers and clinicians with detailed comparisons of the performance of established fatigue measures in cancer patients undergoing treatment to use when selecting measures of CRF.