This study examines the parallel multiple mediators of quality of sleep and occupational burnout between perceived stress and depressive symptoms in psychiatric nurses. Nurses are more likely to experience depression, anxiety, decreased job satisfaction, and reduced organizational loyalty as a result of the stressful work environment and heavy workload. A total of 248 psychiatric ward (PW) nurses participated in this cross-sectional survey study. Structural equation modelling was used for data analysis. In the model of parallel multiple mediators for depressive symptoms, quality of sleep and occupational burnout played mediating roles, and these two mediators strengthened the effect of stress on depressive symptoms, with the final model showing a good fit. Stress, occupational burnout, and quality of sleep explained 46.0% of the variance in psychiatric nurses’ depressive symptoms. Stress had no significantly direct effect on psychiatric nurses’ depressive symptoms, but it had a completed mediation effect on their depressive symptoms through occupational burnout and quality of sleep. This study showed that reduction of occupational burnout and improvement of quality of sleep play important roles against depressive symptoms among PW nurses. Healthcare managers should provide PW nurses with a better environment for improving quality of sleep and reducing occupational burnout.

The study aimed to determine the effectiveness of dignity therapy for end-of-life cancer patients. This was a quasi-experimental study design with a non-randomized controlled trial. Dignity therapy was used as an intervention in the experimental group, and general visit was employed in the control group. Thirty end-of-life cancer patients were recruited, 16 in the experimental group and 14 in the control group. Outcome variables were participants' dignity, demoralization, and depression. Measurements were taken as follows: pre-test (prior to intervention), post-test 1 (the 7th day), and post-test 2 (the 14th day). The effectiveness of the interventions was analyzed the two groups was measured using Generalized Estimating Equation (GEE) with p value set to be less than 0.05. After dignity therapy, the end-of-life cancer patients reflected increased dignity significantly (β = -37.08, SE = 7.43, Wald χ2 = 24.94, p < .001), while the demoralization (β = -39.55, SE = 6.42, Wald χ2 = 37.95, p < .001) and depression (β = -12.01, SE = 2.17, Wald χ2 = 30.71, p < .001) were both reduced significantly. Clinical nurses could be adopting dignity therapy to relieve psychological distress and improve spiritual need in end-of-life cancer patients. Future studies might be expanded to looking at patients vis-à-vis end-of-life non-cancer patients in order to improve their psychological distress. These results provide reference data for the care of end-of-life cancer patients for nursing professionals.

Background: Workplace bullying has been measured in many studies to investigate its effects on mental health issues. However, none have used web-based computerized adaptive testing (CAT) with bully classifications and convolutional neural networks (CNN) for reporting the extent of individual bullying in the workplace. Objective: This study aims to build a model using CNN to develop an app for automatic detection and classification of nurse bullying-levels, incorporated with online Rasch computerized adaptive testing, to help assess nurse bullying at an earlier stage. Methods: We recruited 960 nurses working in a Taiwan Ch-Mei hospital group to fill out the 22-item Negative Acts Questionnaire-Revised (NAQ-R) in August 2012. The k-mean and the CNN were used as unsupervised and supervised learnings, respectively, for: (1) dividing nurses into three classes (n=918, 29, and 13 with suspicious mild, moderate, and severe extent of being bullied, respectively); and (2) building a bully prediction model to estimate 69 different parameters. Finally, data were separated into training and testing sets in a proportion of 70:30, where the former was used to predict the latter. We calculated the sensitivity, specificity, and receiver operating characteristic curve (area under the curve [AUC]), along with the accuracy across studies for comparison. An app predicting the respondent bullying-level was developed, involving the model’s 69 estimated parameters and the online Rasch CAT module as a website assessment. Results: We observed that: (1) the 22-item model yields higher accuracy rates for three categories, with an accuracy of 94% for the total 960 cases, and accuracies of 99% (AUC 0.99; 95% CI 0.99-1.00) and 83% (AUC 0.94; 95% CI 0.82-0.99) for the lower and upper groups (cutoff points at 49 and 66 points) based on the 947 cases and 42 cases, respectively; and (2) the 700-case training set, with 95% accuracy, predicts the 260-case testing set reaching an accuracy of 97. Thus, a NAQ-R app for nurses that predicts bullying-level was successfully developed and demonstrated in this study. Conclusions: The 22-item CNN model, combined with the Rasch online CAT, is recommended for improving the accuracy of the nurse NAQ-R assessment. An app developed for helping nurses self-assess workplace bullying at an early stage is required for application in the future.

Dignity is a basic human right that is related to psychological distress factors in patients with cancer such as depression and demoralization. Hence, the dignity issue is of great importance to healthcare professionals. The present study aimed to advise healthcare professionals regarding the related distress factors of dignity in patients with cancer by investigating its relationship with patients' demographics, disease characteristics, and psychological distress. This was a cross-sectional study design. A convenience sample of 267 patients with cancer from a medical center was recruited into this study. Each patient completed demographics and disease characteristics questionnaires, the Patient Dignity Inventory Mandarin Version, the Demoralization Scale Mandarin Version (DS-MV), and the Patient Health Questionnaire-9 (PHQ-9). Data were analyzed with SPSS 22.0 software. Dignity was significantly correlated with age, demoralization, and depression. Cancer patients aged 65 or above were more likely to have a lower sense of dignity. In the present study, the sensitivity and specificity of the Patient Dignity Inventory Mandarin Version for demoralization (DS-MV≥30) were 84.8% and 79.1% and for depression (PHQ-9≥10) were 73.8% and 70.9% in patients with cancer with an aggregate score of 35 or above. Dignity is significantly correlated with personal demographic characteristics and psychological distress in patients with cancer. The results provide reference data for healthcare professionals to understand and enable dignity in patients with cancer and aid in the development of methods that promote their dignity.