Syrian Refugee Women’s Maternal Mental Health Perceptions, Coping Strategies, and Help-Seeking Practices in Lebanon

Introduction: Globally, 27 million female refugees of reproductive age are subjected to numerous socio-ecological factors that increase their risks of mental health issues, especially during the postpartum period. This study seeks to explore Syrian refugee mothers’ experiences and perceptions of postpartum depression. Methods: We used a qualitative phenomenological approach to interview purposively sampled typical postpartum Syrian mothers living in informal camps in Lebanon to evaluate their maternal mental health perceptions, coping strategies, and help-seeking practices. Results: Results revealed three major themes: conceptualizing maternal depression as extraordinary and ordinary, cultural perceptions of mental health help-seeking, and coping with negative emotions. Discussions: Findings are critical to Lebanon and other Muslim refugee-hosting countries as they can inform future health policies, health care delivery models, and community interventions. Utilizing culturally and religiously appropriate frameworks in assessing and providing mental health services to this vulnerable group can substantially improve mental health services’ acceptance, utilization, and impact

Decision Support Systems and Their Role in Rationalizing the Production Plans: A Case Study on a Plant in Najaf

This research focuses on how to analyze production plans based on quantitative indicators, enabling managers to produce plans that produce the results that help make full use of resources to achieve the company’s goals, maximize profits, and reduce costs to the lowest possible level. These concepts covered in this research, presented in three parts. The first part covers the scientific methodology and literature review, the second part describes the theoretical side, including presentation and analysis of DSS and the concepts of sensitivity analysis and production planning, and the third part covers the application side, applying the discussed measurements in an organization to achieve results, and recommendations

Impact of Intellectual Capital on Realizing University Goals in a Sample of Jordanian Universities

Purpose – This paper aims to examine the direct impact of four components of  intellectual capital  (leadership and strategy, human capital, structural capital, and  relational capital) on realizing university goals(academic goals, maintaining and developing staff, improving community relationships, achieving the university’s plans and programs, and attracting the new students) in a sample of three Jordanian universities: University of Jordan (the oldest and largest Jordanian University founded 1962), Al Zaytoonah University of Jordan ( a private university founded in 1993) and  Middle East University( a private university founded in 2005). To measures  the impact of  its components  on realizing university goals, a set of hypotheses were developed, questionnaire was built and evaluated by reference group, and data from a sample of  university staff to test these hypotheses. Intellectual capital has a significant effect on university performance in meeting its goals. Furthermore, leadership, human and relational capital have in general a significant effect on realizing majority of university goals, and  more than structural capital. Keywords?Intellectual capital, university leadership human, structural, relational capital, university goals

The Impact of the Key Dimensions of Entrepreneurship on Opportunities for the Success of New Ventures in the Greater Amman Municipality

This research attempted to shed light on the effects of entrepreneurship dimensions on small businesses. The research aimed to study the impact of key dimensions of entrepreneurship on opportunities of venture survival and growth. The independent variables selected for this study are related to the five dimensions of entrepreneurship—characteristics of entrepreneur, entrepreneurship support policy, general environment, entrepreneurship activities, and information and electronic entrepreneurship—and their effect on survival and growth opportunities of small projects (the dependent variables). The research results and analysis revealed no significant impact on growth opportunities for small businesses. There is significant support for policy enhancing the general environment and chances for business survival and growth. There was no impact from information and electronic entrepreneurship on survival and growth chances. Finally, the authors present several recommendations including inviting Jordanian companies and governmental institutions and organizations to adopt  entrepreneurship concepts and practices, bringing more attention to entrepreneurship concepts as well as providing  technical and financial assistance to new entrepreneurs, issuing an annual  report on the entrepreneurial activities and projects, and  encouraging studies and research on the entrepreneurship in Jordan. Keywords: Entrepreneurship, leadership, entrepreneurial dimension properties, and chances of survival

The relationship between sleep and glucose control in gestational diabetes

This study set out to investigate the association between sleep among pregnant women with gestational diabetes (GDM) and their glucose control. Functional data analysis (FDA) methods were applied to glucose data collected via continuous glucose monitoring (CGM) systems. FDA is an advanced statistical method that respects the complexity of the dense auto-correlated data produced from repeated measurement of glucose over time. 192 pregnant women with GDM at their third trimester were recruited. Over a period of one week participants wore an actigraph (Actiwatch2 Respironics) which is a watch-like device on their non-dominant wrist to objectively measure their sleep, have a professional CGM system (iPro2 Medtronic) attached to them to continuously measure and record their interstitial glucose every 5 minutes, and complete the Pittsburgh Sleep Quality Index (PSQI) questionnaire to self-report their habitual sleep pattern for the previous month. Their demographic data and type of treatment they received were also collected. 152 participants had sufficient data retrieved from them, i.e. the PSQI questionnaire data and at least one night actigraphy-derived sleep data and one 24-hour day of CGM data. Using FDA methods, sequential glucose values data-points recorded over time with the CGM system were converted into a smooth 24-hour glucose curves with a functional form (as a function of time). The glucose curve was then used as one value, instead of the multiple data-points values it represents. Glucose control was assessed using the smooth glucose curves, as well as, a conventional summary metrics. The associations between participants’ actigraphy-derived and self-reported sleep characteristics and glucose control, were evaluated using standard and multilevel regression modelling for the conventional CGM data summary metrics and functional regression modelling for the smooth glucose curves. The study discovered a positive association between sleep disturbances and glucose control. Sleep disturbances were measured as poor sleep quality, short and long sleep durations compared to an average 6-8 hours sleep duration and difficulties in initiating and maintaining sleep. The timing and the amplitude of these associations were more apparent with FDA regression models than regression models with summary metrics. This study recommends the use of FDA in research involving the use of CGM systems, and encourages the clinician and the policy makers to consider sleep disturbances as a risk factor in glycaemic dysregulation in GDM

Global Perspectives on Task Shifting and Task Sharing in Neurosurgery.

BACKGROUND: Neurosurgical task shifting and task sharing (TS/S), delegating clinical care to non-neurosurgeons, is ongoing in many hospital systems in which neurosurgeons are scarce. Although TS/S can increase access to treatment, it remains highly controversial. This survey investigated perceptions of neurosurgical TS/S to elucidate whether it is a permissible temporary solution to the global workforce deficit. METHODS: The survey was distributed to a convenience sample of individuals providing neurosurgical care. A digital survey link was distributed through electronic mailing lists of continental neurosurgical societies and various collectives, conference announcements, and social media platforms (July 2018-January 2019). Data were analyzed by descriptive statistics and univariate regression of Likert Scale scores. RESULTS: Survey respondents represented 105 of 194 World Health Organization member countries (54.1%; 391 respondents, 162 from high-income countries and 229 from low- and middle-income countries [LMICs]). The most agreed on statement was that task sharing is preferred to task shifting. There was broad consensus that both task shifting and task sharing should require competency-based evaluation, standardized training endorsed by governing organizations, and maintenance of certification. When perspectives were stratified by income class, LMICs were significantly more likely to agree that task shifting is professionally disruptive to traditional training, task sharing should be a priority where human resources are scarce, and to call for additional TS/S regulation, such as certification and formal consultation with a neurosurgeon (in person or electronic/telemedicine). CONCLUSIONS: Both LMIC and high-income countries agreed that task sharing should be prioritized over task shifting and that additional recommendations and regulations could enhance care. These data invite future discussions on policy and training programs

Status and Trends of Physical Activity Surveillance, Policy, and Research in 164 Countries: Findings From the Global Observatory for Physical Activity—GoPA! 2015 and 2020 Surveys

Background: Physical activity (PA) surveillance, policy, and research efforts need to be periodically appraised to gain insight into national and global capacities for PA promotion. The aim of this paper was to assess the status and trends in PA surveillance, policy, and research in 164 countries. Methods: We used data from the Global Observatory for Physical Activity (GoPA!) 2015 and 2020 surveys. Comprehensive searches were performed for each country to determine the level of development of their PA surveillance, policy, and research, and the findings were verified by the GoPA! Country Contacts. Trends were analyzed based on the data available for both survey years. Results: The global 5-year progress in all 3 indicators was modest, with most countries either improving or staying at the same level. PA surveillance, policy, and research improved or remained at a high level in 48.1%, 40.6%, and 42.1% of the countries, respectively. PA surveillance, policy, and research scores decreased or remained at a low level in 8.3%, 15.8%, and 28.6% of the countries, respectively. The highest capacity for PA promotion was found in Europe, the lowest in Africa and low- and lower-middle-income countries. Although a large percentage of the world’s population benefit from at least some PA policy, surveillance, and research efforts in their countries, 49.6 million people are without PA surveillance, 629.4 million people are without PA policy, and 108.7 million live in countries without any PA research output. A total of 6.3 billion people or 88.2% of the world’s population live in countries where PA promotion capacity should be significantly improved. Conclusion: Despite PA is essential for health, there are large inequalities between countries and world regions in their capacity to promote PA. Coordinated efforts are needed to reduce the inequalities and improve the global capacity for PA promotion

Generalized Estimating Equations for Mixed Models

Most statistical approaches of molding the relationship between the explanatory variables and the responses assume subjects are independent. However, in clinical studies the longitudinal data are quite common. In this type of data, each subject is assessed repeatedly over a period of time. Therefore, the independence assumption is unlikely to be valid with longitudinal data due to the correlated observations of each subject. Generalized estimating equations method is a popular choice for longitudinal studies. It is an efficient method since it takes the within-subjects correlation into account by introducing a working correlation matrix. Although the generalized estimating equations’ methodology considers correlation among the repeated observations on the same subject, it ignores the between-subject correlation and assumes subjects are independent. The objective of this dissertation is to provide an extension to the generalized estimating equations to take both within-subject and between-subject correlations into account by incorporating the random effect b to the model. If our interest focuses on the regression coefficients, we regard the correlation parameter as nuisance and estimate the fixed effects using the estimating equations. If our interest focuses either on both the correlation parameter and the variance of the random effects or on the coefficient parameters and the association structure, then building an additional system of estimating equations analogous to the first estimating equations can serve to estimate either the correlation parameter and coefficients parameter, simultaneously or the variance of the random effects and the coefficient parameter, simultaneously. This estimating equations method has no closed form solution and can be solved iteratively. For example, Newton-Raphson is a popular iterative method to be used. We illustrate through simulation studies and real data applications the performance of the proposed methods in terms of bias and efficiency. Moreover, we investigate their behaviors compared to those for existing methods such as generalized estimating equations (GEE), generalized linear models (GLM) and generalized linear mixed models (GLMM). For further studying the performance of newly proposed method, the new approach is applied to the epilepsy data that was studied by many others Fitzmaurice, Laird, and Ware (2012)

Developing A Security Model for Enterprise Networks (SMEN)

Enterprise network (EN) supports thousands of users, and interconnects many networks. EN integrates different operating systems and hosts hundreds of servers that provide several services such as web applications, databases, E-mail, and others. Security threats represent a serious problem to EN. They try to damage enterprise confidentiality, integrity, and availability. Security provides protection against attacks, hacking, and data theft. In this paper, we propose a security model (SMEN) of EN. The proposed model provides security at different layers. It integrates both hardware and software security solutions. We perform a defense evaluation for the proposed model The results show that SMEN was able to detect and prevent all attacks and malwares that were induced by the framework Metasploit. Performance evaluation shows that applying proposed model has a little negative effect on bandwidth utilization and hence on network performance