Maternal Mortality Rate (MMR) in Ethiopia remains one of the highest in the world due in part to very limited use of maternal health services. However, the underlying factors for limited use of the services and hence the high MMR are not well known. The purpose of this study was to identify factors associated with use of maternal health services and maternal health risks, to analyze inequity patterns between use of maternal health services and maternal health risks, and to measure the magnitude and trends in inequity. Behavioral-cultural and structural theories of health inequalities were used to frame the study. Research questions included whether there were trends of inequity in use of maternal health services, if sociodemographic characteristics were associated with use of the services, and whether inequities in use of the services were associated with maternal health risks. The study design was quantitative and used data collected through Demographic and Health Surveys (DHS) conducted in 2000, 2005, and 2011. DHS had employed stratified 2-stage cluster design; this analysis used logistic regression method, odds ratio chi-square test, and correlation measures. The findings indicated statistically significant inequities on use of antenatal care and skilled birth attendant services associated with women's residence, level of education, income, administrative region, distance to a health facility, out-of-pocket payment for health services, and involvement in decision making. Based on the findings, it is recommended to design maternal health policies and programs that improve access and use of the services, specifically for women in rural areas, with no education and with limited economic capacity. Further research is also recommended for regions where sample size was limited. Maternal health policies and programs designed to reach the most disadvantaged women could increase service use and improve maternal health, leading to positive social change.

Thesis (MPA.) -- University of Limpopo, 2017 / In the pre-democratic era, recruitment and selection practices in South Africa were generally based on segregationist policies and legislation that reserved most skilled jobs for white employees. The post 1994 Constitution brought a new dimension by introducing principles that promote fair, non-bias, objective and equitable recruitment. The motivation is derived from section 195 1 (i) of the Constitution of Republic of South Africa of 1996 which states that employment of personnel should be fair, without prejudice, objective and should represent the demographics of South Africa. Section 195 (i) stipulates that the employment of personnel should be “…based on ability, objectivity, fairness, and the need to redress the imbalance of the past…”. The Public Service Act 103 of 1994, section 11 stipulates that in the filling of posts in the public service due consideration must be given to democratic values and principles, and appointments should be based on qualifications, skills and competencies. Furthermore, the Public Service Regulation 2001 states that the persons who are recommended for appointment in a position must have the necessary skills and competencies, and that the process must be fair and unbiased. Equally, the Employment Equity Act (1998) prohibits discrimination in employment that is based on race, gender, religion, nationality, disability, etc. Within this context, the aim of the study was to determine if the Mpumalanga Department of Human Settlements adheres to ethics in its recruitment and selection processes as stipulated by various legislations. The ethics would include recruiting and selecting people with relevant qualifications, skills, and competencies in a fair and unbiased manner by following the right procedures. Relying on a mixed methods research design, the study used interviews and questionnaires to elicit data from 50 employees in the Mpumalanga Department of Human Settlements. The study found that the MDHS had policies and strategies to promote ethics in its recruitment and selection processes; although these were hampered by weak implementation efforts. Incidents of favouritism, nepotism, political interference and lack of confidentiality were experienced in recruitment and selection of employees. In some cases, appointed candidates lacked the necessary skills and qualifications. Given this, it was recommended, inter alia, that implementation of ethics policies and strategies should be improved to ensure integrity and compliance in recruitment and selection processes within the MDHS environment.

No description available.

Given the reality of a diverse and multicultural workplace in Canada, and the benefits of inclusion for both employees and employers, it is reasonable for employers to consider the inclusion of immigrants. This study explored (a) skilled immigrants’ perceptions of inclusion in an energy company in Edmonton, Alberta, Canada, (b) what these perceptions revealed about the diversity climate in the workplace, and (c) how these perceptions could inform and challenge the inclusion practices in the company. Eighteen participants were interviewed in-depth to determine their perceptions of a number of indicators of inclusion. The participants identified that communication (language and culture-specific communication styles), relationships, and organizational practices were salient in their experiences. Immigrants who had previous relevant work experience in the country reported the most positive experiences. The climate of the company led to strong perceptions of satisfaction and belonging, but low perceptions of fairness and equity. Suggestions for the company to improve its diversity and inclusion climate included attending to the experiences and development of women, contractors, and immigrants who are new to Canada or the company. Recommendations included initiatives to support relationships amongst employees, intercultural training and support for internationally educated professionals and Canadian colleagues including leaders, and talent management that would result in more cultural diversity at the senior leadership levels of the company.

No description available.

[pt] As atividades de transporte aéreo devem ser fiscalizadas para garantir a adequação dos níveis de segurança e procedimentos operacionais, no Brasil essa atividade é realizada pela Agência Nacional de Aviação Civil (ANAC). Diversos aeroportos devem ser fiscalizados e em cada um deles uma inspeção diferente pode ser necessária. Os inspetores estão alocados em centros da ANAC em diferentes estados e é importante que o custo dessa atividade de inspeção seja minimizado, respeitando as regras existentes. Nesse sentido, essa dissertação de mestrado propõe dois modelos matemáticos para alocação de agentes qualificados para a realização de missões de fiscalização no território brasileiro. O objetivo é a definição de quais colaboradores formarão cada equipe de fiscalização, minimizando o custo de deslocamento dos agentes. O modelo proposto nesse trabalho é multi-período, para o planejamento operacional quinzenal, com a definição do período que as atividades devem ocorrer, da equipe de inspetores multi-habilitados em atividades de inspeção, multi-origens e multi-destinos. A modelagem é feita no LINGO e em Julia com a utilização do pacote JuMP e dos solvers Gurobi e CPLEX. O Modelo 1 propõe uma reformulação de artigos da literatura e possui tempo de solução entre 2 e 25 vezes menor. O Modelo 2 leva em consideração aspectos não considerados até então no Modelo 1, além disso, dada a quantidade de variáveis de decisão, foi utilizada para resolução do modelo heurística baseada na geração de colunas com programação dinâmica, proposta pelo autor, capaz de reduzir em até 95 porcento a quantidade de variáveis de decisão. A heurística permitiu a obtenção de solução inteira em instâncias que não a obtiveram com o modelo completo. / [en] Air transport activities must be inspected to ensure the adequacy of safety levels and operating procedures, in Brazil this activity is carried out by the National Civil Aviation Agency (ANAC). Several airports must be inspected and at each airport a different inspection may be required. The inspectors are located in ANAC centers in different states and it is important that the cost of this inspection activity is minimized, respecting the existing rules. In this sense, this master s thesis proposes two mathematical models for the allocation of qualified workforce to carry out inspection missions in the Brazilian territory. The objective is to define which employees will form in each inspection team, minimizing the cost of displacement of agents. The model proposed in this work is multi-period, for fortnightly operational planning, with the definition of the period that the activities must occur, of a team of multiskilled inspectors in inspection activities, multi-sources and multi-destinations. Modeling is done in LINGO and Julia using the JuMP package and the solvers Gurobi and CPLEX. Model 1 proposes a reformulation of articles in the literature and has a solution time between 2 and 25 times shorter. The second model takes into account aspects not considered so far in Model 1, in addition, given the amount of decision variables, it was used to solve the heuristic model based on the generation of columns with dynamic programming, proposed by the author, capable of reducing by up to 95 percent the amount of decision variables. The heuristic allowed obtaining an integer solution in instances that did not have a solution with the complete model.

No description available.

No description available.

No description available.

<p dir="ltr">Recurrent stroke, infection, and seizure are some of the most common complications in stroke survivors. Recurrent stroke leads to death in 38.6% of survivors, and infections are the most common risk factor for seizures, with stroke survivors that experience an infection being at greater risk of experiencing a seizure. Two predictive models were generated, recurrent stroke and post-infection seizure, to determine stroke survivors at greatest risk to help providers focus on prevention in higher risk residents.</p><p dir="ltr">Predictive models were generated from a retrospective study of the Long-Term Care Minimum Data Set (MDS) 3.0 (2014-2018, n=262,301). Techniques included three data balancing methods (SMOTE for up sampling, ENN for down sampling, and SMOTEENN for up and down sampling) and three feature selection methods (LASSO, RFE, and PCA). The resulting datasets were then trained on four machine learning models (Logistic Regression, Random Forest, XGBoost, and Neural Network). Model performance was evaluated with AUC and accuracy, and interpretation used SHapley Addictive exPlanations.</p><p dir="ltr">Using data balancing methods improved the prediction performances of the machine learning models, but feature selection did not remove any features or affect performance. With all models having a high accuracy (78.6% to 99.9%), interpretation on all four models yielded the most holistic view. For recurrent stroke, SHAP values indicated that treatment combinations of occupational therapy, physical therapy, antidepressants, non-medical intervention for pain, therapeutic diet, anticoagulants, and diuretics contributed more to reducing recurrent stroke risk in the model when compared to individual treatments. For post-infection seizure, SHAP values indicated that therapy (speech, physical, occupational, and respiratory), independence (activities of daily living for walking, mobility, eating, dressing, and toilet use), and mood (severity score, anti-anxiety medications, antidepressants, and antipsychotics) features contributed the most. Meaning, stroke survivors who received fewer therapy hours, were less independent, and had a worse overall mood were at a greater risk of having a post-infection seizure.</p><p dir="ltr">The development of a tool to predict recurrent stroke and post-infection seizure in stroke survivors can be interpreted by providers to guide treatment and rehabilitation to prevent complications long-term. This promotes individualized plans that can increase the quality of resident care.</p>