ABSTRACT
BACKGROUND: This study was conducted to survey the incidences, severity, and variables influencing depression and the correlation between pain and depression in Korean cancer patients. METHODS: The results of a survey were collected from 142 patients, 79 male and 63 female (mean age 51.9 years), who were hospitalized at a major metropolitan tertiary care hospital for cancer treatment from January to June of 1999. Factors of depression and the level of pain were examined by a self-reported survey employing the Korean version of the Beck Depression Inventory (BDI) and an abridged version of the Brief Pain Inventory respectively. Demographic and clinical characteristics of patients were compiled by reviewing their medical records. The difference in the level of depression among patient groups was analyzed with the t-test and ANOVA, and the correlation between variables with the Pearson correlation coefficient. RESULTS: The mean scores of the worst pain for the last 24-hours was 6.1 +/- 2.2, the average pain for the last 24-hours 4.4 +/- 1.9, and the mean scores of pain at the time of the survey was 3.5 +/- 2.3, while the mean scores of the least pain for the last 24 hours was 2.3 +/- 1.8. The mean BDI scores were 23.7 +/- 1.0, and 55.6% of the patients were found to be in depression (cut off point 21). Scores of depression for cancer patients were higher than in the normal population. The correlations between the worst pain for the last 24 hours and depression, average pain for the last 24-hours and depression, pain at present and depression were significant. Significant differences were found among groups of cancer patients with pain with respect to gender, level of education, and ECOG. There was a significant positive correlation between depression and pain. CONCLUSIONS: More than 50% of cancer patients with pain were suffering from depression. The variables like the degree of pain, gender, level of education, ECOG, and age were significantly related to depression in cancer patients. The findings of this study could be used for identifying high-risk patients in need of intervention and planning effective therapeutic strategies for cancer patients.