BackgroundProfessional ethics refers to the use of logical and consistent communication, knowledge, clinical skills, emotions and values in nursing practice. This study aimed to explore and describe factors that affect professional ethics in nursing practice in Iran.MethodsThis qualitative study was conducted using conventional content analysis approach. Thirty nurses with at least 5 years of experience participated in the study; they were selected using purposive sampling. Data were collected through semi-structured interviews and analyzed using thematic analysis.ResultsAfter encoding and classifying the data, five major categories were identified: individual character and responsibility, communication challenges, organizational preconditions, support systems, educational and cultural development.ConclusionsAwareness of professional ethics and its contributing factors could help nurses and healthcare professionals provide better services for patients. At the same time, such understanding would be valuable for educational administrators for effective planning and management.

Implementation of peer education has positive effects on CSE in these patients and reduces their hospital readmission.

Optimization is a topic that has always been discussed in all different fields of science. One of the most effective techniques for solving such problems is optimization algorithms. In this paper, a new optimizer called Multi-Leader optimizer (MLO) is developed in which multiple leaders guide members of the population towards the optimal answer. MLO is mathematically modelled based on the process of advancing members of the population and following the leaders. MLO performance in optimization is examined on twenty-three standard objective functions. The results of this optimization are compared with the results of the other eight existing optimization algorithms including Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Teaching-Learning-Based Optimization (TLBO), Gray Wolf Optimizer (GWO), Grasshopper Optimization Algorithm (GOA), Emperor Penguin Optimizer (EPO), Shell Game Optimization (SGO), and Hide Objects Game Optimization (HOGO). Based on the analysis of the simulation results on unimodal test functions to evaluate exploitation ability and multimodal test functions in order to evaluate exploration ability, it has been determined that MLO has a higher ability to solve optimization problems than existing optimization algorithms.