ABSTRACT
Moral sensitivity, missed nursing care and moral distress among healthcare professionals have received considerable attention in recent years. These factors represent important healthcare challenges for new nurses (graduation to 2 years of work experience). However, studies on the relationships among these variables in the context of new nurses in China remain lacking. AIMS: To explore the relationships among moral sensitivity, missed nursing care and moral distress in the context of new nurses in China. RESEARCH DESIGN: A cross-sectional descriptive survey was conducted. PARTICIPANTS AND RESEARCH CONTEXT: A total of 228 new nurses were recruited from three tertiary hospitals in Qingdao, Shandong Province, China. Participants provided their sociodemographic and professional information and completed the Chinese Moral Sensitivity Questionnaire-Revised Version, the Chinese Missed Nursing Care Survey Version and the Chinese Moral Distress Scale-Revised Version. The data were analysed using Spearman's correlation analysis and multiple linear regression analysis. RESULTS: The means and standard errors of moral sensitivity, missed nursing care and moral distress were 40.71 (0.39), 9.82 (0.78) and 34.87 (2.41), respectively. The variable of missed nursing care exhibited a significant negative relationship with moral sensitivity and a significant positive relationship with moral distress. Regression analysis revealed that the main factors influencing new nurses' moral distress were educational background, nature of job, current unit, frequency of night shifts and the dimensions of moral strength and responsibility. These factors can explain 14.9% of the total variation. CONCLUSION: The findings revealed that higher rates of missed nursing care were associated with lower moral sensitivity and greater moral distress among new nurses. Therefore, developing interventions to reduce missed nursing care may be a promising strategy for improving moral sensitivity and preventing moral distress among new nurses. IMPLICATIONS FOR THE PROFESSION AND/OR PATIENT CARE: In hospitals, moral distress can be improved by focusing on modifiable factors such as staffing resources, leading to better promoting new nurses' health and improving the quality of care. This study can highlight practices accounting for moral sensitivity and missed nursing care in nursing research and training programmes. REPORTING METHOD: Strengthening the reporting of observational studies in epidemiology (STROBE) statement. PATIENT OR PUBLIC CONTRIBUTION: No patient or public contribution.
ABSTRACT
Image registration is an important basis of image processing, which is of great significance in image mosaicking, target recognition, and change detection. Aiming at the automatic registration problem of multi-angle optical images for ground scenes, a registration method combining point features and line features to register images is proposed. Firstly, the LSD (Line Segment Detector) algorithm is used to extract line features of images. The obtained line segments whose length are less than a given threshold are eliminated by a visual significant algorithm. Then, an affine transform model obtained by estimating a Gaussian mixture model (GMM) is applied to the image to be matched. Lastly, Harris point features are utilized in fine matching to overcome shortages of methods based on line features. In experiments, the proposed algorithm is compared with popular feature-based registration algorithms. The results indicate that the proposed algorithm in this work has obvious advantages in terms of registration accuracy and reliability for optical images acquired at different angles.