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Introduction: In the field of healthcare, lifelong learning is considered a quality indicator due to its potential to enhance healthcare services and the knowledge and skills of healthcare professionals. The purpose of this research is to investigate and document the attitudes and behavior of healthcare professionals from different healthcare institutions toward lifelong learning using artificial intelligence., The Study Achieves Two Objectives: Identifying healthcare professionals' interest in formal lifelong learning and determining how they engage in lifelong learning. Additionally, this study aims to develop a dynamic web platform with several key features including an introduction page, navigation menu, document download form, document table, and download, delete, and resume buttons., Methodology: The study was conducted from 07/04/2022 to 19/05/2022 and involved a sample of 114 healthcare professionals from various locations in Morocco. A questionnaire comprising three sections (personal information, lifelong learning for personal development, and lifelong learning for professional development) was used as the research instrument., Results: The average age of the participants was 43 years, and 76.8% had more than 11 years of experience in the field. The results indicate a correlation between professional development and lifelong learning among healthcare professionals. The two most important factors driving lifelong learning were identified as the advancement of the healthcare profession and the need to elevate the quality of care. Also, this research objective is to develop a dynamic online platform featuring an introduction page, navigation menu, document download form, document table, and download, delete, and resume buttons., Conclusions: According to the findings, healthcare professionals consider lifelong learning an ongoing and continuous process essential to their work., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Introduction: the pediatric emergency department is the first contact between the population and the hospital. Consequently, its dysfunction influences the quality of the general health care system. However, any successful policy must first be based on convincing results hence the need to better explore this service, diagnose the various dysfunctions, and survey disease trends to identify the needs of the local population. In this perspective, we propose to describe the epidemiological profile of children hospitalized at the emergency service of the Mother-Child hospital, University Hospital Centre Marrakech, and establish the prevalence table for childhood pathologies., Methods: a retrospective study was carried out in pediatric emergency services for 1658 hospitalized patients between March 2015 and December 2018. The collected data concerns mainly the socio-demographic, clinical profile, evolution status, mode of admission, and medical history., Results: the characterization of the studied population by sex and age showed a predominance of male with a sex ratio of 1.36, infants with 625 patients. Concerning the final diagnosis, the most frequent pathologies affected the respiratory system in 28% of cases, then the digestive system (11.3%), while infectious pathologies represented 10.7% of admissions. The death rate in the emergency department was 7.4%. Multivariate analysis of the data showed a statistically significant relationship between the final diagnosis (16 diseases by a system according to The International Statistical Classification of Diseases and Related Health Problems 10th Revision (ICD-10)) and age, season, and weight. Thus, for the association between the digestive system diseases and weight (aOR=1.052, 95% CI= 1.019-1.086, p=0.02). While for the skin and subcutaneous tissue diseases and the autumn season (aOR=11.37, 95% CI= 1.272-101.777, p=0.03) and age has a negative significance for most diseases., Conclusion: the epidemiological profile study will allow knowledge of patient´s pathologies typology for a well-supported and better definition of needs., Competing Interests: The authors declare no competing interests., (Copyright: Siham Jbari et al.)

Abstract: This pilot study aimed to assess the effects of high-fidelity simulation on cardiopulmonary resuscitation (CPR) self-efficacy and knowledge retention compared to case-based learning. A two-group, experimental, longitudinal design was adopted. Fifty-two undergraduate nursing students were invited to participate in the study, which was conducted between March and May 2019. The results show statistically significant differences in favor of the experimental group on both CPR knowledge retention and self-efficacy one month after training. These findings may assist nurse educators to implement high-fidelity simulation in CPR education., Competing Interests: The authors have declared have no conflict of interest., (Copyright © 2022 National League for Nursing.)

Background & Objective: Mathematical modeling is the most scientific technique to understand the evolution of natural phenomena, including the spread of infectious diseases. Therefore, these modeling tools have been widely used in epidemiology for predicting risks and decision-making processes. The purpose of this paper is to provide an effective mathematical model for predicting the spread of Covid-19 pandemic., Methods: Our mathematical model is performed according to a SIDR model for infectious diseases. Epidemiological data from four countries; Belgium, Morocco, Netherlands and Russia, are used to validate this model. Also, we have evaluated the efficiency of Morocco's Covid-19 countermeasures and simulated the different relaxation plans in order to predict the effects of relaxation countermeasures., Results and Conclusions: In this paper, we developed and validated a new way of data aggregation, modeling and interpretation to predict the spread of Covid-19, evaluate the efficiency of countermeasures and suggest potential scenarios. Our results will be used to keep the spread of Covid-19 under control in the world., (Copyright © 2021. Published by Elsevier Ltd.)