University of Jordan

About: University of Jordan is a education organization based out in Amman, Jordan. It is known for research contribution in the topics: Population & Medicine. The organization has 7796 authors who have published 13764 publications receiving 213526 citations.

A review of the literature regarding stress among nursing students during their clinical education

Abstract: Background: There has been increased attention in the literature about stress among nursing students. It has been evident that clinical education is the most stressful experience for nursing students. Aim: The aim of this paper was to critically review studies related to degrees of stress and the type of stressors that can be found among undergraduate nursing students during their clinical education. Methods: The search strategy involved the utilization of the following databases: MEDLINE (Medical Literature on-Line), CINAHL (Cumulative Index to Nursing and Allied Health Literature), PsycINFO (Psychology Information) and PubMed. Keywords were stress, undergraduate nursing students, clinical practice. The review included those studies published between 2002 and 2013, conducted in any country as long as reported in English, and including a focus on the clinical practice experience of nursing students. Thirteen studies met the eligibility criteria. Results: Four themes were identified: initial clinical experience, comparison between different academic years, cross-cultural comparison, and eustress aspects of clinical experience. Implications for nursing and health policy: This review expands current knowledge in the area of stress in clinical settings and calls for further research. Nursing teachers should utilize the findings of this review to direct their students during clinical practice. Moreover, hospital administrators need to promote policies to promote a training environment where students are supported and inspired.

An enhanced associative learning-based exploratory whale optimizer for global optimization

Abstract: Whale optimization algorithm (WOA) is a recent nature-inspired metaheuristic that mimics the cooperative life of humpback whales and their spiral-shaped hunting mechanism. In this research, it is first argued that the exploitation tendency of WOA is limited and can be considered as one of the main drawbacks of this algorithm. In order to mitigate the problems of immature convergence and stagnation problems, the exploitative and exploratory capabilities of modified WOA in conjunction with a learning mechanism are improved. In this regard, the proposed WOA with associative learning approaches is combined with a recent variant of hill climbing local search to further enhance the exploitation process. The improved algorithm is then employed to tackle a wide range of numerical optimization problems. The results are compared with different well-known and novel techniques on multi-dimensional classic problems and new CEC 2017 test suite. The extensive experiments and statistical tests show the superiority of the proposed BMWOA compared to WOA and several well-established algorithms.