The impact of education to the transition from unemployment to employment in Egypt

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Amany Yashoa Gad

PurposeThis paper aims to identify the level of contribution of different levels of education to remaining in unemployment as well as the transition from unemployment to employment in Egypt.Design/methodology/approachIn this paper, transition probabilities matrix differentiated by gender, age groups, educational levels, marital status and place of residence based on worker flows across employment, unemployment and out of labor force states during the period 2012–2018 using Egypt Labor Market Panel Survey of 2018. The results point to the highly static nature of the Egyptian labor market. Employment and the out of labor force states are the least mobile among labor market states. This is because employment state is very desirable and the out of labor force is the largest labor market states, especially for females. Also, this study examines the impact of different educational levels separately on remaining in unemployment and transition from unemployment to employment state using eight binary logistic regression models.FindingsThe main results of transitions from unemployment to employment are relatively large for males, elder-age, uneducated workers as well as workers who are not married and urban residents, and the results of the logistic regression models consistent with the transition probabilities matrix results, except for few cases. Based on the above findings, there is enough evidence to accept the null hypothesis that no education has a positive significant impact to transition unemployed individuals from unemployment to employment, while less than intermediate as well as higher education have a negative significant impact to transition unemployed individuals from unemployment to employment.Originality/valueThis paper proposes to address the problem of the unemployment among highly educated which is much higher compared with illiterates and try to understand the impact of different levels of education separately on the transition from unemployment to employment, to help the policymakers to eradicate the gap between education and the demand of the labor market in Egypt.

2016 ◽  
Vol 17 (4) ◽  
pp. 654-674 ◽  
Author(s):  
Diego Matricano

Purpose According to an emerging research trend, which seeks to apply the concept of intellectual capital (IC) to the field of entrepreneurship, the purpose of this paper is to test whether IC can affect the start-up expectations of aspiring entrepreneurs. Design/methodology/approach Binary logistic regression models, based on empirical data derived from the Global Entrepreneurship Monitor website and referring to Italy over the years 2005-2010, are used to test the influence of IC (comprising human, structural and relational capital) on start-up expectations. Findings Binary logistic regression models reveal robust results. Human, structural and relational capitals affect start-up expectations in Italy. Only in 2010 did structural capital fail to do so. Research limitations/implications This study has three main limitations. The first concerns the need for further research to confirm the influence of IC on start-up expectations. The second concerns in-depth, more exhaustive analyses that cannot be carried out due to the use of second- hand data. The third deals with the reference only to Italy, over a limited time-span (2005-2010). Originality/value To the best knowledge of the author, this is one of the first empirical studies that investigate whether IC can affect start-up expectations. Results revealed by the regression models might steer other scholars’ interest toward this research path (linking IC and entrepreneurship) that has not yet been properly considered.


Objective: While the use of intraoperative laser angiography (SPY) is increasing in mastectomy patients, its impact in the operating room to change the type of reconstruction performed has not been well described. The purpose of this study is to investigate whether SPY angiography influences post-mastectomy reconstruction decisions and outcomes. Methods and materials: A retrospective analysis of mastectomy patients with reconstruction at a single institution was performed from 2015-2017.All patients underwent intraoperative SPY after mastectomy but prior to reconstruction. SPY results were defined as ‘good’, ‘questionable’, ‘bad’, or ‘had skin excised’. Complications within 60 days of surgery were compared between those whose SPY results did not change the type of reconstruction done versus those who did. Preoperative and intraoperative variables were entered into multivariable logistic regression models if significant at the univariate level. A p-value <0.05 was considered significant. Results: 267 mastectomies were identified, 42 underwent a change in the type of planned reconstruction due to intraoperative SPY results. Of the 42 breasts that underwent a change in reconstruction, 6 had a ‘good’ SPY result, 10 ‘questionable’, 25 ‘bad’, and 2 ‘had areas excised’ (p<0.01). After multivariable analysis, predictors of skin necrosis included patients with ‘questionable’ SPY results (p<0.01, OR: 8.1, 95%CI: 2.06 – 32.2) and smokers (p<0.01, OR:5.7, 95%CI: 1.5 – 21.2). Predictors of any complication included a change in reconstruction (p<0.05, OR:4.5, 95%CI: 1.4-14.9) and ‘questionable’ SPY result (p<0.01, OR: 4.4, 95%CI: 1.6-14.9). Conclusion: SPY angiography results strongly influence intraoperative surgical decisions regarding the type of reconstruction performed. Patients most at risk for flap necrosis and complication post-mastectomy are those with questionable SPY results.


PLoS ONE ◽  
2021 ◽  
Vol 16 (10) ◽  
pp. e0258913
Author(s):  
Imad Al Kassaa ◽  
Sarah El Omari ◽  
Nada Abbas ◽  
Nicolas Papon ◽  
Djamel Drider ◽  
...  

Background Coronavirus disease 2019 (COVID-19) has affected millions of lives globally. However, the disease has presented more extreme challenges for developing countries that are experiencing economic crises. Studies on COVID-19 symptoms and gut health are scarce and have not fully analyzed possible associations between gut health and disease pathophysiology. Therefore, this study aimed to demonstrate a potential association between gut health and COVID-19 severity in the Lebanese community, which has been experiencing a severe economic crisis. Methods This cross-sectional study investigated SARS-CoV-2 PCR-positive Lebanese patients. Participants were interviewed and gut health, COVID-19 symptoms, and different metrics were analyzed using simple and multiple logistic regression models. Results Analysis of the data showed that 25% of participants were asymptomatic, while an equal proportion experienced severe symptoms, including dyspnea (22.7%), oxygen need (7.5%), and hospitalization (3.1%). The mean age of the participants was 38.3 ±0.8 years, and the majority were males (63.9%), married (68.2%), and currently employed (66.7%). A negative correlation was found between gut health score and COVID-19 symptoms (Kendall’s tau-b = -0.153, P = 0.004); indicating that low gut health was associated with more severe COVID-19 cases. Additionally, participants who reported unhealthy food intake were more likely to experience severe symptoms (Kendall’s tau-b = 0.118, P = 0.049). When all items were taken into consideration, multiple ordinal logistic regression models showed a significant association between COVID-19 symptoms and each of the following variables: working status, flu-like illness episodes, and gut health score. COVID-19 severe symptoms were more common among patients having poor gut health scores (OR:1.31, 95%CI:1.07–1.61; P = 0.008), experiencing more than one episode of flu-like illness per year (OR:2.85, 95%CI:1.58–5.15; P = 0.001), and owning a job (OR:2.00, 95%CI:1.1–3.65; P = 0.023). Conclusions To our knowledge, this is the first study that showed the impact of gut health and exposure to respiratory viruses on COVID-19 severity in Lebanon. These findings can facilitate combating the pandemic in Lebanon.


Stroke ◽  
2021 ◽  
Vol 52 (Suppl_1) ◽  
Author(s):  
Radoslav I Raychev ◽  
CrystalAnn Moreno ◽  
Leslie Corless ◽  
Jason W Tarpley ◽  
John F Zurasky ◽  
...  

Introduction: We aimed to investigate the impact of certification status on process of care metrics and clinical outcome in a large multi-center hospital system. Methods: We analyzed data obtained from the Providence Stroke Registry between January 2016 and December 2019. Key process of care metrics and clinical outcome were compared among patients with a discharge diagnosis of stroke and stratified based on site certification: comprehensive stroke center (CSC), thrombectomy-capable stroke center (TSC), primary stroke center (PSC) and no certification (NC). Donner’s adjusted chi-square tests were used to compare proportions for each metric grouped by certification. Generalized linear mixed effects logistic regression models were used to adjust for mode of patient arrival, age, sex, admit NIHSS, and medical history. Results: Data included 45,278 patients. Results from the analyses are summarized in the table. Donner’s adjusted chi-square analyses showed significant differences for metrics across certification groups. Results from the logistic regression models indicated significant differences in IV TPA and EVT treatment, as well as IV TPA treatment times across certification groups. There were no significant differences between TSC and CSC. Conclusions: Patients presenting with acute ischemic stroke at NC and PSC were significantly less likely to receive IV TPA or EVT with significantly less efficient IV tPA treatment times as compared to CSC. However, CSC and TSC sites performed similarly.


2020 ◽  
Vol 49 (9) ◽  
pp. 1859-1877
Author(s):  
José Fernández-Menéndez ◽  
Óscar Rodríguez-Ruiz ◽  
José-Ignacio López-Sánchez ◽  
María Isabel Delgado-Piña

PurposeThe purpose of this paper is to study how job reductions affect product innovation and marketing innovation in a sample of 2,034 Spanish manufacturing firms in the period 2007–2014.Design/methodology/approachPoisson and logistic regression models with random effects were used to analyse the impact of downsizing on some innovation outcomes of firms.FindingsThe results of this research show that the stressful measure of job reductions may have unexpected consequences, stimulating innovation. However downsizing combined with radical organisational changes such as new equipment, techniques or processes seems to have a negative impact on product and marketing innovation.Originality/valueThis research has two original features. First, it explores the unconventional direction of causality from the planned elimination of jobs to innovation outputs. Secondly, the paper looks at the combined effect of downsizing and other restructuring measures on different types of innovation. Following the threat-rigidity theory, we assume that this combination represents a major threat for survivors that leads to lower levels of product and marketing innovation.


Author(s):  
Rik Ossenkoppele ◽  
◽  
Antoine Leuzy ◽  
Hanna Cho ◽  
Carole H. Sudre ◽  
...  

Abstract Purpose A substantial proportion of amyloid-β (Aβ)+ patients with clinically diagnosed Alzheimer’s disease (AD) dementia and mild cognitive impairment (MCI) are tau PET–negative, while some clinically diagnosed non-AD neurodegenerative disorder (non-AD) patients or cognitively unimpaired (CU) subjects are tau PET–positive. We investigated which demographic, clinical, genetic, and imaging variables contributed to tau PET status. Methods We included 2338 participants (430 Aβ+ AD dementia, 381 Aβ+ MCI, 370 non-AD, and 1157 CU) who underwent [18F]flortaucipir (n = 1944) or [18F]RO948 (n = 719) PET. Tau PET positivity was determined in the entorhinal cortex, temporal meta-ROI, and Braak V-VI regions using previously established cutoffs. We performed bivariate binary logistic regression models with tau PET status (positive/negative) as dependent variable and age, sex, APOEε4, Aβ status (only in CU and non-AD analyses), MMSE, global white matter hyperintensities (WMH), and AD-signature cortical thickness as predictors. Additionally, we performed multivariable binary logistic regression models to account for all other predictors in the same model. Results Tau PET positivity in the temporal meta-ROI was 88.6% for AD dementia, 46.5% for MCI, 9.5% for non-AD, and 6.1% for CU. Among Aβ+ participants with AD dementia and MCI, lower age, MMSE score, and AD-signature cortical thickness showed the strongest associations with tau PET positivity. In non-AD and CU participants, presence of Aβ was the strongest predictor of a positive tau PET scan. Conclusion We identified several demographic, clinical, and neurobiological factors that are important to explain the variance in tau PET retention observed across the AD pathological continuum, non-AD neurodegenerative disorders, and cognitively unimpaired persons.


2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Gulsah Gurkan ◽  
Yoav Benjamini ◽  
Henry Braun

AbstractEmploying nested sequences of models is a common practice when exploring the extent to which one set of variables mediates the impact of another set. Such an analysis in the context of logistic regression models confronts two challenges: (i) direct comparisons of coefficients across models are generally biased due to the changes in scale that accompany the changes in the set of explanatory variables, (ii) conducting a large number of tests induces a problem of multiplicity that can lead to spurious findings of significance if not heeded. This article aims to illustrate a practical strategy for conducting analyses in the face of these challenges. The challenges—and how to address them—are illustrated using a subset of the findings reported by Braun (Large-scale Assess Educ 6(4):1–52, 2018. 10.1186/s40536-018-0058-x), drawn from the Programme for the International Assessment of Adult Competencies (PIAAC), an international, large-scale assessment of adults. For each country in the dataset, a nested pair of logistic regression models was fit in order to investigate the role of Educational Attainment and Cognitive Skills in mediating the impact of family background and demographic characteristics on the location of an individual’s annual income in the national income distribution. A modified version of the Karlson–Holm–Breen (KHB) method was employed to obtain an unbiased estimate of the true differences in the coefficients between nested logistic models. In order to address the issue of multiplicity, a recent generalization of the Benjamini–Hochberg (BH) False Discovery Rate (FDR)-controlling procedure to hierarchically structured hypotheses was employed and compared to two conventional methods. The differences between the changes in coefficients calculated conventionally and with the KHB adjustment varied from negligible to very substantial. When combined with the actual magnitudes of the coefficients, we concluded that the more proximal factors indeed act as strong mediators for the background factors, but less so for Age, and hardly at all for Gender. With respect to multiplicity, applying the FDR-controlling procedure yielded results very similar to those obtained by applying a standard per-comparison procedure, but quite a few more discoveries in comparison to the Bonferroni procedure. The KHB methodology illustrated here can be applied wherever there is interest in comparing nested logistic regressions. Modifications to account for probability sampling are practicable. The categorization of variables and the order of entry should be determined by substantive considerations. On the other hand, the BH procedure is perfectly general and can be implemented to address multiplicity issues in a broad range of settings.


2021 ◽  
Vol 50 (Supplement_1) ◽  
Author(s):  
Yingying Wang

Abstract Background Childhood is an important public health issue. Although both thyroid hormone and menarche are known to play a role in body metabolism and energy expenditure, no population-based study has been conducted to investigate the impact of TSH on adipogenesis among population-based girls around puberty. Methods A multi-stage cluster sampling method was used to select one junior middle school from each of 4 study areas: Minhang District in Shanghai, Haimen City in Jiangsu Province, Yuhuan City and Deqing County in Zhejiang Province. A total of 474 girls aged 11 to 14 years from 4 schools were enrolled. Information on demographic factors and puberty stage were collected, and anthropometric measurements and thyroid hormones were determined. Multivariate logistic regression models were used to assess the associations of Thyroid stimulating hormone (TSH) with the risk of obesity measured by body mess index (BMI) and waist circumference (WC). Results Of the 474 girls, the prevalences of BMI-based general obesity and WC-based abdominal obesity were 19.8% (94/474) and 21.7% (103/474), respectively. Compared with normal weight girls, the mean serum TSH concentration was significantly higher in BMI-based general overweight or obese girls (P = 0.037), but not in WC-based central overweight or obese girls (P = 0.173). In the multiple logistic regression models, for girls with highest tertile of serum TSH concentration relative to those in the lowest tertile, the odds ratios were 2.58 (95% CI 1.32 to 5.04) and 2.50 (95% CI 1.30 to 4.81) for overweight or obesity based on BMI and WC after adjustment for puberty stage and other covariates. Conclusions Serum TSH concentration was positively associated with both general and abdominal obesity in school-age girls and the association was independent of puberty. Key messages thyroid stimulating hormone; general obesity; central obesity; school-aged girls; puberty


2019 ◽  
Vol 29 (5) ◽  
pp. 1190-1212 ◽  
Author(s):  
Chang Heon Lee ◽  
Ananth Chiravuri

Purpose Serial crowdfunding is becoming a common phenomenon as entrepreneurs repeatedly return to online crowdfunding to raise capital. In this study, the authors focus attention on serial crowdfunders, that is, entrepreneurs who experience launching more than one crowdfunding project. The purpose of this paper is to investigate the role of past experience on subsequent crowdfunding performance. This study also examines whether initial success vs initial failure leads serial crowdfunders to engage in more explorative behaviors (i.e. switching industry) and to take exploitative actions (i.e. adjusting campaign strategies in terms of goal setting and funding option). Design/methodology/approach Data on serial crowdfunding projects was retrieved from Indiegogo platform. The logistic regression models are estimated to assess the impact of past entrepreneurial experience on subsequent crowdfunding decisions, and to estimate the effects of the three strategies on subsequent funding performance. Findings The results show that serial creators who experienced successful initial crowdfunding are more likely to explore a new industry or product category in the crowdfunding market and to set a higher target capital for the subsequent campaign when they change a project category. Originality/value Despite the fact that there are a considerably large number of serial crowdfunders in crowdfunding market, relatively little research has been conducted to investigate the presence of learning benefits from a previous to a subsequent crowdfunding project. Two competing hypotheses, drawn from the attribution theory and hubris theory of entrepreneurship, were tested in this study to determine the impact of prior success vs failure experience on both subsequent crowdfunding decisions and funding performance.


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