The purpose of this study was to explore and describe the perceptions of registered nurses about patient-friendly health services rendered within an ambulatory care setting in the King Abdulaziz Medical City, Riyadh (KAMC-R), Kingdom of Saudi Arabia. A qualitative, explorative, descriptive and contextual design was used. Fifteen registered nurses (one male and 14 female) voluntarily participated in this study. The data collection process comprised of semi-structured individual interviews with the participants to explore what they perceived to be patient-friendly health services. The obtained data were analysed using Van Mannen’s thematic analysis method. The emerging empirical data identified four themes, three categories and nine subcategories; a literature control was incorporated to validate the findings. The study findings revealed that the participants identified cultural differences as a quintessential obstacle in rendering patient-friendly health services in the study context. Professional yet patient-friendly communication proved to be a challenge as did ambulatory care flow. This had the potential to compromise patient-friendly health services. Meeting the patients’ needs was acknowledged. However, the needs, goals and values of patientfriendly healthcare services were perceived differently by the patients on the one hand and the registered nurses on the other and this affected the process of interaction and delivery of patient-friendly care. Despite the fact that the registered nurses daily experienced ongoing challenges which compromised patient-friendly health services, they were aware and committed to deliver patient-friendly health services. The process of scientific inquiry concluded with the limitations of the study and recommendations were made based on the findings. / Health Studies / M.A. (Heath Studies)

Developments in technology have influenced all areas of life, including education and in particular, language learning and teaching. The computer has become very advantageous in the teaching of foreign languages, especially with the augmentation of hardware, software and the World Wide Web. Computer-assisted language learning (CALL) is beneficial, since it helps teachers to enhance their teaching and gives students the opportunity to learn in an authentic and interesting environment. The impact of CALL has led many researchers to carry out studies to explore the significance of CALL and the factors that could enhance or reduce the integration of CALL into language learning and teaching. Although CALL could be beneficial to the enhancement of English proficiency among Saudi Arabian students, the integration of CALL is still narrow in terms of quantity and quality among EFL teachers in public female secondary schools in Riyadh. So, this study aims to explore the current integration of CALL among these teachers. Furthermore, this study aims to explore some of the factors that contribute to the integration of CALL, those being computer literacy and the computer training that is available for both pre-service and in-service teachers. In addition, the study focuses on the kind of training that is vital to enhance teachers' use of CALL. Also, this study revolves around the teachers' roles when using CALL, their barriers to the integration of CALL, as well as their attitudes toward CALL. The first step in this study is a background of the history of language teaching methods, starting with the traditional methods and ending with the integration of CALL. The literature review follows in order to substantiate this study with relevant studies that have been conducted in this area and to provide the theoretical background of the study. After that, the methods that are used to carry out the study are indicated; including the questionnaire, follow-up interviews and two focus groups. Lastly, an analysis of the results is done in order to come up with the findings. The findings of the study suggest that the current levels of computer use and computer literacy among EFL teachers are still insufficient. The available computer training is inadequate for both pre-service and in-service teachers and there are no computer courses facilitated by the Ministry of Education. Moreover, in-service teachers still need ongoing computer training courses to keep them up to date with recent developments in educational technology. Recommendations to increase teachers’ computer literacy and to enhance their use of CALL are considered as well as recommendations for further Saudi Arabian studies on CALL. / Dissertation (MA)--University of Pretoria, 2013. / gm2014 / Afrikaans / unrestricted

This thesis aims to explore how the urban form specifically sprawl affects travel behavior and travel distance in Riyadh. Since the city is expanding and the travel time gets longer, the first mode option is the car. The research question that reframes this thesis is, how does the urban form 'sprawl' affect travel behavior and distance in Riyadh specifically 'Al-Narjis and Al-Malaz' based on their density and land use. In order to respond to the thesis question, a qualitative research design including mixed qualitative methods has been used. This study conducted a web survey for Riyadh citizens, this survey got 6312 respondents. In addition, this study conducted in-depth online interviews including travel itinerary diaries with six participants, three from each of the two neighborhoods in the study area. The interviews' outputs were visualized through QGIS by producing six maps. The results indicate that travel behavior and travel distance in Riyadh are affected negatively by sprawl. This effect could be seen in the high dependency on automobiles that resulted from land use and city planning, longer trips due to disconnected streets, and poor service accessibility. As well as less usage of other transportation such as walking and cycling due to the lack of pedestrian infrastructure.

Today’s world is characterised by considerable inconsistency. In some parts of the world people are living in starvation and malnutrition, while in some other parts of the same world, about 1.3 billion tons of food is wasted every year. We do not know enough about what contributes to food waste. However, there seems to be an emergent pattern of behaviour around sharing food. This hermeneutic phenomenological research will explore how food sharing might reduce food waste in a cultural and community-based society like Saudi Arabia through the lived experiences of restaurants and food bank employees. Research data were collected through a face-to-face semi-structured interview method from 15 participants from selected restaurants and food bank in Riyadh. Using the theory of planned behaviour (TPB) as the theoretical lens, a conceptual framework was proposed to elicit underlying behavioural and cultural factors impeding food waste reduction and the inefficiency of food sharing. Using Paul Colaizzi’s approach, the collected interview data were reviewed, analysed, and seventeen themes were elicited for further discussion. The findings suggest that culture through an affluent way of life and the show-off lifestyle of hosts continue to contribute to more food wastage. The strictly business nature of restaurants operation leads to edible food fit for human consumption ending up in the garbage. The revised conceptual framework provides insight into the factors hindering food waste reduction and food sharing. With supporting regulations and policies, food leftovers can either be distributed to people in need or put to an alternative use.

This dissertation resituates C. A. Doxiadis in Post-War urban design history with a detailed examination of how urban growth and change was addressed by urban design strategies as applied in the master plan for Riyadh Saudi Arabia, undertaken between 1968 and 1972. The Riyadh master plan commission is important within Doxiadis' career, occurring in the midst of his prolific writing projects and approximately eight years after he completed the Islamabad master plan, his most renowned project. Most Post-War architects focused on the socio-spatial components of urban life, elaborating architectural projects that intertwined transportation, infrastructure, and concentrated on mass housing strategies. This dissertation argues that Doxiadis' contribution to urban design theory and practice during the Post-War period was to define a rational scientific methodology for urban design that would restructure settlements to enable urban expansion and change while addressing issues of community building, governance and processes of development. The applied urban design for Riyadh Saudi Arabia strongly exemplifies Doxiadis' rational strategy and methodology as outlined in Ekistics theory and the conceptual model of Dynapolis. The comparative analysis examines how Doxiadis applies the Dynapolis model in the urban spatial planning of Riyadh to organize urban territory at the macro and local urban scales, define neighborhood communities, and connect the new master plan to the existing spatial territory of the city. The longitudinal analysis contrasts the Doxiadis master plan, Riyadh's first urban development strategy, to the most recent comprehensive approach MEDSTAR to understand how the Doxaidis' urban design has sustained its spatial continuity over time. This dissertation makes two significant contributions. The first is to broaden knowledge of Post-War urban design specific to the spatial problem of urban expansion and change, and second to resituate Doxiadis within the Post-War history of urban design specifically revealing his previously unrecognized project of the Riyadh master plan undertaken from 1968-1972.

This study examined the perception of managers in the Institute of Public Administration (IPA), Riyadh, Saudi Arabia as to the way public relations is practiced within Saudi Arabia based on a comparison with Grunig's four models of public relations. Out of a population of 38 directors and director generals, 30 participated in a personal interview for a 79 percent response rate.A Q-sort analysis revealed two perceptions of public relations performance in the Institute. Perceptions differed based on educational experience, and managerial levels. Top managers with Ph.Ds tended to view performance as related to Grunig's Press Agentry and One-Way Information models. Fewer level employees saw performance related to the Two-Way Asymmetrical and Symmetrical models. The researcher concluded that the more higher educated level managers had a better understanding of the reality of performance of public relations in IPA. Main attitudes from the sorts of the participants showing a significantly and different attitude in how directors generals and directors perceived public relations was being practiced in the IPA. The directors generals and directors strongly held different views concerning the practice of public relations in the IPA. / Department of Journalism

The selection of the most appropriate traffic control actions to solve non-recurrent traffic congestion is a complex task which requires significant expert knowledge and experience. In this thesis we develop and investigate the application of an intelligent traffic control decision support system for road traffic management to assist the human operator to identify the most suitable control actions in order to deal with non-recurrent and non-predictable traffic congestion in a real-time situation. Our intelligent system employs a Fuzzy Neural Networks (FNN) Tool that combines the capabilities of fuzzy reasoning in measuring imprecise and dynamic factors and the capabilities of neural networks in terms of learning processes. In this work we present an effective learning approach with regard to the FNN-Tool, which consists of three stages: initializing the membership functions of both input and output variables by determining their centres and widths using self-organizing algorithms; employing an evolutionary Genetic Algorithm (GA) based learning method to identify the fuzzy rules; tune the derived structure and parameters using the back-propagation learning algorithm. We evaluate experimentally the performance and the prediction capability of this three-stage learning approach using well-known benchmark examples. Experimental results demonstrate the ability of the learning approach to identify all relevant fuzzy rules from the training data. A comparative analysis shows that the proposed learning approach has a higher degree of predictive capability than existing models. We also address the scalability issue of our intelligent traffic control decision support system by using a multi-agent based approach. The large network is divided into sub-networks, each of which has its own associated agent. Finally, our intelligent traffic control decision support system is applied to a number of road traffic case studies using the traffic network in Riyadh, in Saudi Arabia. The results obtained are promising and show that our intelligent traffic control decision support system can provide an effective support for real-time traffic control.

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The selection of the most appropriate traffic control actions to solve non-recurrent traffic congestion is a complex task which requires significant expert knowledge and experience. In this thesis we develop and investigate the application of an intelligent traffic control decision support system for road traffic management to assist the human operator to identify the most suitable control actions in order to deal with non-recurrent and non-predictable traffic congestion in a real-time situation. Our intelligent system employs a Fuzzy Neural Networks (FNN) Tool that combines the capabilities of fuzzy reasoning in measuring imprecise and dynamic factors and the capabilities of neural networks in terms of learning processes. In this work we present an effective learning approach with regard to the FNN-Tool, which consists of three stages: initializing the membership functions of both input and output variables by determining their centres and widths using self-organizing algorithms; employing an evolutionary Genetic Algorithm (GA) based learning method to identify the fuzzy rules; tune the derived structure and parameters using the back-propagation learning algorithm. We evaluate experimentally the performance and the prediction capability of this three-stage learning approach using well-known benchmark examples. Experimental results demonstrate the ability of the learning approach to identify all relevant fuzzy rules from the training data. A comparative analysis shows that the proposed learning approach has a higher degree of predictive capability than existing models. We also address the scalability issue of our intelligent traffic control decision support system by using a multi-agent based approach. The large network is divided into sub-networks, each of which has its own associated agent. Finally, our intelligent traffic control decision support system is applied to a number of road traffic case studies using the traffic network in Riyadh, in Saudi Arabia. The results obtained are promising and show that our intelligent traffic control decision support system can provide an effective support for real-time traffic control.