The aim of this study was to develop and test an explanatory model for sleep disorders in people with cancer. A hypothetical model was constructed on the basis of a review of previous studies, literature, and sleep models, and 10 latent variables were used to construct a hypothetical model.

Data were collected from April 19 to June 25, 2010, using self-report questionnaires. The sample was 291 outpatients with cancer who visited the oncology cancer center at a university hospital. Collected data were analyzed using SPSS Win 15.0 program for descriptive statistics and correlation analysis and AMOS 7.0 program for covariance structural analysis.

It appeared that overall fit index was good as χ²/df=1.162, GFI=.969, AGFI=.944, SRMR=.052, NFI=.881, NNFI=.969, CFI=.980, RMSEA=.024, CN=337 in the modified model. The explanatory power of this model for sleep disorders in people with cancer was 62%. Further, sleep disorders were influenced directly by cancer symptom experience, dysfunctional beliefs and attitudes about sleep, and past sleep pattern.

Findings suggest that nurses should assess past sleep pattern and consider the development of a comprehensive nursing intervention program to minimize the cancer symptom experience, dysfunctional beliefs and attitudes about sleep, and thus, reduce sleep disorders in people with cancer.

The purpose of this study was to identify cancer-related symptom clusters and to validate the conceptual meanings of the revealed symptom clusters in patients with hepatocellular carcinoma.

This study was a cross-sectional survey and methodological study. Patients with hepatocellular carcinoma (N=194) were recruited from a medical center in Seoul. The 20-item Symptom Checklist was used to assess patients' symptom severity. Selected symptoms were factored using principal-axis factoring with varimax rotation. To validate the revealed symptom clusters, the statistical differences were analyzed by status of patients' performance status, Child-Pugh classification, and mood state among symptom clusters.

Fatigue was the most prevalent symptom (97.4%), followed by lack of energy and stomach discomfort. Patients' symptom severity ratings fit a four-factor solution that explained 61.04% of the variance. These four factors were named pain-appetite cluster, fatigue cluster, itching-constipation cluster, and gastrointestinal cluster. The revealed symptom clusters were significantly different for patient performance status (ECOG-PSR), Child-Pugh class, anxiety, and depression.

Knowing these symptom clusters may help nurses to understand reasonable mechanisms for the aggregation of symptoms. Efficient symptom management of disease-related and treatment-related symptoms is critical in promoting physical and emotional status in patients with hepatocellular carcinoma.