A closed-book, multiple-choice examination following this article tests your under standing of the following objectives:1. Define and better understand burnout and moral distress. 2. Identify the impact that burnout and resilience have among nurses. 3. Discuss the results of the study.To read this article and take the CE test online, visit www.ajcconline.org and click "CE Articles in This Issue. " No CE test fee for AACN members.Background The high level of stress experienced by nurses leads to moral distress, burnout, and a host of detrimental effects. Objectives To support creation of healthy work environments and to design a 2-phase project to enhance nurses' resilience while improving retention and reducing turnover. Methods In phase 1, a cross-sectional survey was used to characterize the experiences of a high-stress nursing cohort. A total of 114 nurses in 6 high-intensity units completed 6 survey tools to assess the nurses' characteristics as the context for burnout and to explore factors involved in burnout, moral distress, and resilience. Statistical analysis was used to determine associations between scale measures and to identify independent variables related to burnout. Results Moral distress was a significant predictor of all 3 aspects of burnout, and the association between burnout and resilience was strong. Greater resilience protected nurses from emotional exhaustion and contributed to personal accomplishment. Spiritual well-being reduced emotional exhaustion and depersonalization; physical well-being was associated with personal accomplishment. Meaning in patient care and hope were independent predictors of burnout. Higher levels of resilience were associated with increased hope and reduced stress. Resilience scores were relatively flat over years of experience. Conclusions These findings provide the basis for an experimental intervention in phase 2, which is designed to help participants cultivate strategies and practices for renewal, including mindfulness practices and personal resilience plans. (American Journal of Critical Care. 2015; 24:412-421)

No abstract

MRI is a sensitive method for detecting subtle anatomic abnormalities in the neonatal brain. To optimize the usefulness for neonatal and pediatric care, systematic research, based on quantitative image analysis and functional correlation, is required. Normalization-based image analysis is one of the most effective methods for image quantification and statistical comparison. However, the application of this methodology to neonatal brain MRI scans is rare. Some of the difficulties are the rapid changes in T1 and T2 contrasts and the lack of contrast between brain structures, which prohibits accurate cross-subject image registration. Diffusion tensor imaging (DTI), which provides rich and quantitative anatomical contrast in neonate brains, is an ideal technology for normalization-based neonatal brain analysis. In this paper, we report the development of neonatal brain atlases with detailed anatomic information derived from DTI and co-registered anatomical MRI. Combined with a diffeomorphic transformation, we were able to normalize neonatal brain images to the atlas space and three-dimensionally parcellate images into 122 regions. The accuracy of the normalization was comparable to the reliability of human raters. This method was then applied to babies of 37 to 53 post-conceptional weeks to characterize developmental changes of the white matter, which indicated a posterior-to-anterior and a central-to-peripheral direction of maturation. We expect that future applications of this atlas will include investigations of the effect of prenatal events and the effects of preterm birth or low birth weights, as well as clinical applications, such as determining imaging biomarkers for various neurological disorders.