Background:Breast cancer patients frequently experience psychological distress during the chemotherapy period.Objectives:This study aimed to evaluate the effect of relaxation with guided imagery on patients with breast cancer.Patients and Methods:A two-group, pretest-posttest, quasi-experimental design with a randomized controlled trial was conducted. Sixty-five breast cancer patients from one medical center in Taiwan were enrolled in the study. These patients were randomly assigned to the experimental group (n = 32) or to the control group (n = 33). Both groups received chemotherapy self-care education, but the experimental group also received relaxation with guided imagery training. The training on relaxation with guided imagery was conducted before chemotherapy, and the patients were supplied with a compact disc detailing the performance of relaxation with guided imagery for 20 minutes daily at home for 7 days after chemotherapy.Results:The experimental group showed significant decreases in insomnia (-0.34 ± 0.83, P < 0.05), pain (-0.28 ± 0.58, P < 0.05), anxiety (-3.56 ± 2.94, P < 0.00), and depression (-2.38 ± 2.70, P < 0.00) between the pretest and the posttest. Comparing the two groups, statistically significant differences were found in the overall symptom distress (B = 0.11, P < 0.05), insomnia (B = 0.50, P <0.05), depression (B = 0.38, P < 0.05), and numbness in physical symptoms (B = 0.38, P < 0.05), as well as in anxiety (B = 3.08, P < 0.00) and depression (B = 1.86, P < 0.00) in psychological distress. One week of relaxation with guided imagery can significantly improve the overall symptoms of distress, insomnia, depression, physical symptoms, and anxiety, and can decrease psychological distress.Conclusions:Relaxation with guided imagery had a positive effect on mediating anxiety and depression in breast cancer patients.

Background: This study investigated the influence of religious beliefs on the health of cancer patients and identified the factors contributing to the influence. Materials and Methods: A questionnaire survey was conducted using a convenient sampling method. A structured questionnaire was used to the samplings, and the data of 200 cancer patients were collected. Results: The effects of religion on the health of cancer patients achieved an average score of 3.58. The top five effects are presented as follows: (a) Religion provides me with mental support and strength, (b) religion enables me to gain confidence in health recovery, (c) religion motivates me to cope with disease-related stress positively and optimistically, (d) religion helps me reduce anxiety, and (e) religion gives me courage to face uncertainties regarding disease progression. Moreover, among the demographic variables, gender, type of religion, and experience of religious miracles contributed to the significantly different effects of religion on patients. Specifically, the effect of religion on the health of patients who were female and Christian and had miracle experiences was significantly (p< .01) higher than that on other patients. Conclusions: These results are helpful in understanding the influence of religious beliefs on the health of cancer patients and identified the factors contributing to the influence. The result can serve as a reference for nursing education and clinical nursing practice.

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Low quality of life, depression and poor quality of sleep are associated with increased mortality in hemodialysis patients. It is not clear which factor has the highest predictive power and what the core element is to explain the predictability. We thus conducted a prospective cohort study that included 151 hemodialysis adults. Three traits of interest were assessed by World Health Organization Quality of Life questionnaire, an abbreviated version (WHOQOL-BREF), Taiwanese Depression Questionnaire, and Athens Insomnia Scale, respectively. They were followed for more than 3 years and the all-cause mortality was 30.5%. The prevalence of quality of life at the lowest tertile, depression and poor quality of sleep was 19.9%, 43.0% and 74.2%, respectively. Discriminant analysis showed the standardized coefficient of each factor as 0.813, −0.289 and 0.066, indicating the highest discriminating power by quality of life to predict mortality. Question 15 “how well are you able to get around?” in the physical health domain of WHOQOL-BREF independently associated a hazard ratio of mortality 0.623 (95% confidence interval 0.423-0.918). Subjective perception of overall quality of life was more related to psycho-social-environmental factors. In conclusion, mobility is an independent and powerful predictor to long term mortality in patients on chronic hemodialysis.

Aims: The purpose of the present study was to investigate healthy lifestyle changes during the period before and after breast cancer diagnosis in Taiwan. Materials and Method: Lifestyle changes during the period before and after cancer diagnosis were assessed by convenience sampling with a structured questionnaire for breast cancer survivors. Results: A total of 235 breast cancer survivors completed the healthy lifestyle scale. The mean values before and after breast cancer diagnosis of the participants were 3.27 and 3.73. The final five dimensions for the period before breast cancer diagnosis were: had not experienced stress; had exercised; had maintained sleep quality; had maintained body weight; and had maintained relationships. The final five dimensions for the period after breast cancer diagnosis were: sleep quality; had not experienced stress; relationship; had exercised; and had maintained body weight. A paired-t test was applied to examine the differences before and after cancer diagnosis, revealing that the total average scores of the participants on the healthy lifestyle scale clearly differed statistically (t= -17.20, p<0.01); and the nine dimensions before and after testing also demonstrate a marked statistical difference (p<0.01). Conclusions: These findings are helpful in understanding the healthy lifestyle changes during the period before and after cancer diagnosis among breast cancer survivors. It is expected that these results can offer references of self-care for this group of patients.

Aims: The purpose of this study was to investigate complementary and alternative medicine use among breast cancer survivors in Taiwan. Materials and Methods: This study employed a descriptive research design approach to detail the CAM use among the target population. Convenience sampling was used along with a structured questionnaire. Results: A total of 230 breast cancer survivors completed the use CAM scale. Prayer, reading books, taking antioxidants, eating various grains, and maintaining a vegetarian diet proved to be the five most frequently used CAM practices among patients in our study. More than 50.0% of the participants reported praying occasionally. More than 40.0% of participants read books occasionally, and 38.7% stated that they occasionally take antioxidants. Conclusions: These results provide more insight into CAM use for nurses who care for breast cancer patients.

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Background Poor quality of sleep and depression are common and highly associated with each other in patients on haemodialysis. We aimed to investigate whether they share common risk factors and how age may influence their development. Methods Cross‐sectional observation study on 120 haemodialysis patients with quality of sleep and depression assessed by Pittsburgh Sleep Quality Index (PSQI) and Taiwanese Depression Questionnaire (TDQ), respectively. Results The prevalence of poor quality of sleep and depression was 92.5% and 43.3%, respectively. PSQI scores were associated with age, gender, education and monthly income while TDQ scores were associated with low serum creatinine and albumin levels. Elderly patients at ages older than 65 had the highest average PSQI score (12.26 ± 4.35) than the young group at age 20–44 (8.25 ± 4.39) (P = 0.028) but the average TDQ scores were similar across three age groups. The proportion of those who had high PSQI scores was significantly higher in the elderly group (54.4%, P = 0.017) and the 44–65‐years group (51.9%, P = 0.028) than the young group (16.7%). The proportion of those who reported normal quality of sleep was much lower in the elderly group (0.0%) than the other two groups (25.0%, P < 0.001 and 11.7%, P < 0.01). The proportions of those who had different ranges of TDQ scores did not show such a pattern of strong age dependence. Conclusions Poor quality of sleep in haemodialysis patients is associated with socio‐economic factors while depression is more related to biochemistry indicators. A majority of older patients suffer very poor quality of sleep while depression appears equally severe and common across different age groups.