Breast cancer is the third leading cause of death among Korean women after stomach and cervical cancer. Furthermore, the incidence of breast cancer is increasing in contrast to decreasing trends of those two cancers described above. According to the Korean Ministry of Health and Welfare, in 1998, 6.1% of all cancers and 14.1% of cancers in women were breast cancers. Early detection of breast cancer can be achieved by performing periodic breast self‐examinations (BSE), clinical breast examinations, and/or mammography. Women should perform early detection procedures such as BSE or mammography on a regular basis to detect breast cancer earlier. For the cost effectiveness of the program, the identification of high‐risk groups should be conducted, and the provision of community programs for the early detection of breast cancers should be focused on high‐risk groups. The present study was designed to classify the high‐risk groups of breast cancer among rural women in Korea, to provide early detection of breast cancer programs. Breast cancer risk of each participant, aged 35–65 years and who reside in the Korean rural community including Kyungki‐Do and Chungchongbuk‐Do, was assessed utilizing the breast cancer risk appraisal instruments. The tool estimates the six risk factors including age, family history, personal breast disease history, breast‐feeding experience, number of children, and frequency of fat intakes. Breast cancer‐related knowledge and practices were also assessed. The study results identified a 1.5% high‐risk group, 3.8% moderate‐risk group, and 24.0% borderline‐risk group. Approximately 30% of the respondents were above the borderline‐risk groups, which indicate the need for systematic approach for breast cancer prevention and early detection in the community.

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The aim of this study was to investigate whether social structure is associated with cancer pain and quality of life using the Social Structure and Personality Research Framework. This study was a secondary analysis of data from 480 cancer patients. The measurements included socioeconomic variables, self-reported cancer pain using the McGill Pain Questionnaire-Short Form (MPQ-SF), and quality of life measured using the Functional Assessment of Cancer Therapy Scale (FACT-G). The data were analyzed using moderated multiple regression. Cancer pain and quality of life differed significantly with income. The associations between income and pain and quality of life were significant only for the high education group (≥ partial college), and these associations were greater for Caucasians than for their counterparts ( p < .05). When developing interventions, nurses should consider the influence of socioeconomic variables on pain and quality of life while considering possible moderating factors such as education.

Background Standardized pain-intensity measurement across different tools would enable practitioners to have confidence in clinical decision-making for pain management. Objectives The purpose was to examine the degree of agreement among unidimensional pain scales, and to determine the accuracy of the multidimensional pain scales in the diagnosis of severe pain. Methods A secondary analysis was performed. The sample included a convenience sample of 480 cancer patients recruited from both the internet and community settings. Cancer pain was measured using the Verbal Descriptor Scale (VDS), the Visual Analog Scale (VAS), the Faces Pain Scale (FPS), the McGill Pain Questionnaire-Short Form (MPQ-SF) and the Brief Pain Inventory-Short Form (BPI-SF). Data were analyzed using a multivariate analysis of variance (MANOVA) and a receiver operating characteristics (ROC) curve. Results The agreement between the VDS and VAS was 77.25%, while the agreement was 71.88% and 71.60% between the VDS and FPS, and VAS and FPS, respectively. The MPQ-SF and BPI-SF yielded high accuracy in the diagnosis of severe pain. Cutoff points for severe pain were > 8 for the MPQ-SF and > 14 for the BPI-SF, which exhibited high sensitivity and relatively low specificity. Conclusion The study found substantial agreement between the unidimensional pain scales, and high accuracy of the MPQ-SF and the BPI-SF in the diagnosis of severe pain. Implications for Practice Use of one or more pain screening tools that have been validated diagnostic accuracy and consistency will help classify pain effectively and subsequently promote optimal pain control in multi-ethnic groups of cancer patients.