SACM - United Kingdom

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    The Knowledge of Autism Spectrum Disorder Among Male and Female Public Education Teachers in Jeddah, Saudi Arabia.
    (Nottingham Trent University, 0024-07) Alobaidi, Batool; Dillon, Gayle
    This study investigated teachers' knowledge of autism spectrum disorder (ASD) in Jeddah, Saudi Arabia, and examined what factors influenced the knowledge that teachers had. In Saudi Arabia, ASD is common but often diagnosed late (Hayat et al., 2019). This highlights the need to assess teachers' ASD knowledge, as they are well-positioned to notice signs of ASD. Understanding teachers' awareness can guide targeted training programs, improving early detection and support for students with ASD. Participants included 197 male and female teachers from public schools who completed the Autism Spectrum Knowledge Scale-General Population (ASKSG, 2019) and the Knowledge about Childhood Autism among Health Workers (KCAHW, 2008) scale. The findings revealed that participants demonstrated an average level of knowledge across both scales, scoring below average on the ASKSG but above average on the KCAHW, suggesting a potential gap in understanding ASD. Teachers with prior contact with individuals with ASD spectrum exhibited significantly higher ASD knowledge compared to those without such exposure, underscoring the impact of firsthand experience. Contrary to expectations, no significant differences in ASD knowledge were found based on gender, teaching experience, or school level taught between all educational levels, be it primary, secondary, or high school. The results aligned with previous regional studies (Alharbi et al.,2021; Otaif et al.,2019) documenting weak to moderate ASD knowledge among Saudi Arabian educators. Due to the findings from previous studies in Saudi Arabia until this study, which find that teachers' ASD knowledge has not improved, the study accentuates the pressing need for intensified and reinvigorated ASD training initiatives tailored to teachers, emphasising immersive, experiential learning modalities. By addressing the identified knowledge gaps and recognized limitations, further research efforts can help to provide a comprehensive understanding of teachers' knowledge of ASD. These studies will help to develop comprehensive and tailored programs to provide teachers with the knowledge needed to support children with ASD best.
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    THE IMPACT OF THE DEVELOPMENT OF PUBLIC TRANSPORTATION ON THE TOURISM SECTOR IN THE KINGDOM OF SAUDI ARABIA
    (Bournemouth University, 0024-05-24) Alrashdi, Mohammed Sulaiman; Shiva
    The research is based on the importance of public transportation development and its impact on the tourism industry of Saudi Arabia (SA). It highlights the impact of developing the transport facility that can help in attracting the potential tourist from the UK. SA has potential tourist destination in the country that makes it one of the major tourist spot for the visitors around the globe. The research questions have identified in the research that highlights various aspects of the research topic. In the theoretical framework, the innovation and future development process of SA’s public transportation system highlights the adoption of new technologies and scientific techniques. The developed strategies of public transportation in tourism contribute to enhance its profitability. The strategies of Tourism marketing follow and understand the needs and expectations of customers for online bookings, focusing on mobile, as well as optimized market. Sustainable tourism widely focuses on schemes to create a low carbon as well as encourage travel. Scientific Management Theory and Diffusion of Innovation Theory develop new ideas and practices of tourism key concepts. The research methodology introduces the concept and benefits of positivism research philosophy, deductive research approach, and descriptive research design. The data collection method is done through primary quantitative method from survey. Reliability and validity are used in research study for maintain accuracy and consistency of research study. Random sampling is used for collecting responses from 155 people working in Saudi Arabian tourism sector. Ethical considerations are used in research paper to protect it from any type of harm. Findings and discussion of the research topic is by conducting an online survey among 155 participants regarding the 11 questionnaires. Public Transport helps in reducing carbon emissions and traffic congestion in the country for tourist’s attraction that are environment conscious. The development of Saudi vision 2030 strategy focuses on developing the sector of tourists. The outcome of the research has been identified. It identifies that development and innovation of the PT system improves tourism comfort ability and safety. Some recommendations on the development of PT have also been given; the future scope and research limitation have also been identified here.
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    A Survey Assessing the Perceptions and Interpretations of Saudi Therapists on the Use of Virtual Reality Therapy for Patients with Spinal Cord Injury
    (Cardiff University, 0024-06-13) Alqarni, Rawabi; Williams, Alison
    Title: A Survey Assessing the Perceptions and Interpretations of Saudi Therapists on the Use of Virtual Reality Therapy for Patients with Spinal Cord Injury. Background: Virtual Reality (VR) has emerged as a promising tool for enhancing rehabilitation, particularly for individuals with spinal cord injuries (SCI) and neurological conditions. This study offered a comprehensive examination of VR-based interventions, encompassing the user experience (UX), game mechanics (GM), in-game assistance (IGA), and VR-induced symptoms and effects (VRISE). Methods: A descriptive survey with a self-developed questionnaire investigating the 31 Saudi therapist's perspectives that were based on patient feedback who were recruited via WhatsApp then filled up the questionnaire that contained 22 questions (both closed& opened-ended), providing a well-rounded assessment of the VR rehabilitation experience. Statistical outcomes, therapist involvement, and specific context were considered to identify areas for improvement and opportunities for further research. Results: The study highlighted the significance of enjoyment in fostering patient engagement and the need for customized VR setups aligned with patient preferences. Graphics and sound quality, while important, are not the sole determinants of engagement, emphasizing the importance of a holistic VR experience. GM and IGA show promise but require customization. Addressing VRISE through technological advancements is essential. Conclusion: This research underscored the continuous evolution of VR technology and design to better serve individuals with SCI and neurological conditions, emphasizing the importance of tailored approaches and ongoing advancements in VR-based rehabilitation.
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    Barriers and Facilitators to Accessing and Delivering Chronic Healthcare Services among Rural Areas in Makkah Region of Saudi Arabia: Perspectives of Rural Women and Healthcare Providers
    (The University of Sheffield, 0024-08-06) Albogame, Ashwaq; Thompson, Jill; Hinchliff, Sharron
    Background: Health disparities exist for rural residents, particularly women, due to multiple, complex barriers to accessing healthcare. Studies from around the world have identified factors influencing women's access to healthcare. Despite the Saudi Health Ministry’s efforts to reduce health disparities and provide comprehensive care for rural regions, Saudi Arabia (SA) still lacks comprehensive healthcare services for rural women. In recent years, the prevalence of chronic diseases has increased significantly in SA and people diagnosed with chronic conditions require continued medical attention and easy access to healthcare services. In SA, limited research has been conducted on the experiences of rural women with chronic conditions and their access to healthcare services. Aim: This PhD thesis aims to explore barriers and facilitators for accessing, receiving, and delivering healthcare services for rural women diagnosed with chronic diseases (Diabetes Mellitus (DM type 1 & 2) and/or Cardiovascular Diseases (CVD) in rural areas near Taif city in Saudi Arabia. Methods: A qualitative study, using semi-structured interviews, was conducted remotely. The participants included rural women (n = 13) living with chronic conditions and healthcare providers (n = 15). Participants were recruited from three different primary healthcare centres located in three rural areas and two secondary healthcare facilities located in Taif city. The responses from participants in the interviews were analysed using inductive-deductive thematic analysis guided by Levesque’s conceptual model of access to healthcare from the patient and the providers’ sides. Findings: Several barriers and facilitators were identified including health literacy, language barriers, cultural norms, transportation, and financial constraints which were all found to impact their access to, and experiences of, health services. Healthcare providers identified other barriers including communication difficulties, gender-related cultural norms, resource limitations, and fragmented referral systems. These barriers intersect to make access to healthcare services and management of rural patients’ chronic conditions difficult. Barriers can be minimized by facilitators such as family support, maximizing access to two levels of healthcare facilities - Primary Healthcare Centres (PHCCs) and Secondary Healthcare Facilities (SHCF), long work experience of HCPs, reforming the healthcare system and women’s rights. Conclusion: Despite international efforts to enhance women’s health, rural women still struggle to take advantage of improvements in the healthcare system. In the context of rural areas in SA, increasing distribution of PHCCs in rural areas and the provision of free services may not necessarily address the healthcare needs of rural women with chronic conditions. Researchers, policymakers, and rural community members need to work collaboratively to develop strategies to address barriers and prioritize rural dwellers’ needs. Improving healthcare access for rural women can help meet the country’s Vision 2030 objectives which include enhancing accessibility to healthcare services, health quality, and women's empowerment.
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    THE EFFECTIVENESS OF INSTAGRAM HIGHLIGHTS IN ENHANCING ATTENDEE ENGAGEMENT AND EVENT BRAND EQUITY
    (Bournemouth University, 0024-07-16) Alessa, Abdullah; Moital, Miguel
    The world of marketing in the 21st Century is a completely transformed one with the advent of the internet and social media. Today, companies and various brands are increasingly resorting to social networks to reach their prospective customers. This transformation is prompted by the level at which consumers are equally embracing digital media at the expense of legal media that is deemed outdated. This research presents a current study on the effectiveness of the Instagram Highlight feature in fostering enhanced attendee engagement and event brand equity. It utilizes a qualitative research methodology to collect primary data from a sample of social media experts working in various companies of relevance to the studied variables. The research performs a critical literature review of the existing scholarly work on the User Engagement Theory (UET). The research gap identified is the missing knowledge on the specific Instagram feature of the Highlights as used in the promotion of attendee engagement and event brand equity. To analyze data, the study uses both thematic analysis methods that are done along the identified themes within the area of study. The results are then presented in a simplified manner making specific quotations to indicate ethnicity of the same. Following a detailed discussion of the findings, the study highlights practical recommendations applicable by social media marketers seeking optimum performance for their Instagram Highlight posts. The study also highlights the typical limitations of qualitative research. It also declares no conflict of interest between the research and the subject under examination.
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    MEASURING THE IMPACT OF MEGA-EVENTS ON TOURISM AND ECONOMIC GROWTH IN SAUDI ARABIA
    (Leeds Beckett University, 0024-07-02) Alasseri, Reem; Cox, Perter
    The Kingdom of Saudi Arabia (KSA) recently announced its intention to expand its tourism sector as part of its economic diversification plans; a deliberate attempt to mitigate reliance on the petroleum industry. The KSA seeks to leverage the potential of the growing and expanding global tourism industry. The KSA has stated its clear intention to fully pursue this diversification, through its Vision 2030 programme, investments in developing tourism infrastructure, and deliberate efforts to host significant sporting events (mega-events). This paper evaluates whether the KSA’s aggressive approach of pouring billions of dollars into mega events and infrastructure helps the country’s bid to become one of the most favored tourist destinations in the world. It compares current efforts and previous approaches towards economic diversification used by different countries in the recent past, both those that succeeded and those that failed. This deliberate, systematic review predicts the KSA’s success if it leverages its greatest assets – the enormous wealth and investment capital provided by the sovereign wealth fund, its unique geopolitical position, a unifying branding strategy, and its budding young population. In doing so, however, the KSA needs to consider the cultural impacts of its tourist expansion efforts.
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    EXTRACTION OF TEMPORAL RELATIONSHIPS BETWEEN EVENTS FROM NEWS ARTICLES FOR TIMELINE GENERATION
    (University of Manchester, 0024-06-27) Alsayyahi, Sarah; Batista- Navarro, Riza
    Extracting temporal information from natural language texts is crucial for understanding the sequence and context of events, enhancing the accuracy of timeline generation and event analysis in various applications. However, within the NLP community, determining the temporal ordering of events has been recognised as a challenging task. This difficulty arises from the inherent vagueness of temporal information found in natural language texts like news articles. In Temporal Information Extraction (TIE), different datasets and methods have been proposed to extract various types of temporal entities, including events, temporal expressions, temporal relations, and the relative order of events. Some of these tasks have been considered easier than others in the field. For instance, extracting the temporal expressions or events is easier than determining the optimal order of a set of events. The complexity of determining the event order arises due to the requirement of commonsense and external knowledge, which is not readily accessible to computers. In contrast, humans can effortlessly identify this chronological order by relying on their external knowledge and understanding to establish the most appropriate sequence. In this thesis, our goal was to improve the performance of state-of-the-art methods for determining the temporal order of events in news articles. Accordingly, we present the following contributions: 1. We reviewed the literature by conducting a systematic survey, categorising tasks and datasets relevant to extracting the order of events mentioned in the news articles. We also identified existing findings and highlighted some research directions worth further investigation. 2. We proposed a novel annotation scheme with an unambiguous definition of the types of events and temporal relations of interest. Adopting this scheme, we developed a TIMELINE dataset, which annotates both verb and nominal events and considers the long-distance temporal relations between events separated by more than one sentence. 3. We integrated problem-related features with a neural-based method to improve the model's ability to extract temporal relations that involved nominal events and the temporal relations with small classes (e.g., EQUAL class). We found that integrating these features has significantly improved the performance of the neural baseline model and could achieve state-of-the-art results in two datasets in the literature. 4. We proposed a framework that uses local search algorithms (e.g., Hill Climbing and Simulated Annealing) to generate document-level timelines from a set of temporal relations. These algorithms have improved the performance of the current models and resolved the problem in less time than the state-of-the-art models.
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    Application Placement Approaches to Improve Quality of Service in Fog Computing
    (University of Manchester, 0024-06-25) Aljohani, Aisha; Sakellariou, Rizos
    Fog Computing (FC) addresses Cloud Computing's (CC) limitations by utilizing distributed computational devices, known as fog devices, near the Internet of Things (IoT) environment to support a wide range of IoT applications. In FC, to ensure Quality of Service (QoS), users need to specify a placement plan for distributing IoT applications among fog devices for processing; this is known as the application placement problem (APP). With a potentially huge number of fog devices and applications, solving the APP can be decentralized, i.e., independent optimization can be performed in parallel for different clusters of fog devices, thus mitigating the networking and computing overhead and enhancing the QoS consequently. In this approach, clusters lacking sufficient fog devices may propagate undeployed applications to other clusters, potentially leading to uncertain fulfillment of QoS constraints, i.e., delay bounds on response time. Moreover, deploying applications based on available resources at the placement decision time might result in an increased number of propagated applications among clusters. Additionally, the heterogeneity in fog devices' capabilities and the variations in IoT application characteristics, such as computing and networking intensity, and delay sensitivity, pose challenges in choosing competent applications for powerful fog devices. Assigning specific applications to these powerful devices may result in delay violations for other applications on less powerful ones, potentially leading to propagating the latter ones to other clusters. A raise in the number of propagated applications, especially those with data streams, might lead to increased networking congestion, resulting in extended response time and potential violation in delays, particularly for delay-sensitive applications. This thesis proposes three approaches aiming to improve the QoS of IoT applications, i.e., delays. First, an improved application placement approach through parallel collaboration (ParColl) is proposed to increase the probability of placing propagated applications within their delays, incorporating algorithms to enable parallel searching and manage the searching process. Second, an improved application placement approach through postponement (PostP) is proposed to maximize the number of non-propagated applications meeting their delays, employing algorithms to postpone placement of undeployed applications, instead of propagating them, if such postponement ensures their delays. Third, an application placement approach maximizing response times for applications while meeting delays through cluster-wide resource selection CWRS) is proposed. CWRS ensures that powerful fog devices are reserved for applications needing them to meet their delays, minimizing violations on other devices whenever possible. Experimental results of implementing the proposed approaches in iFogSim show an improvement in the percentage of applications processed within their QoS constraints and a reduction in average delay violation times compared to existing approaches.
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    Enhancing Chemical Adherence Testing through Pharmacokinetics and Pharmacogenetics Insights and Mass Spectrometry Advancements.
    (University of Leicester, 0024-05-18) Alghamdi, Randah; Gupta, Pankaj
    This thesis addresses the pressing issue of medication non-adherence with a focus on hypertension. Non-adherence is common and significantly elevates the risk of hospitalisation and mortality. The study investigates chemical adherence tests to assess medication adherence, employing liquid chromatography with tandem mass spectrometry (LC-MS/MS) as a robust method. The introduction highlights the complexities of adherence measurement and outlines potential limitations, including the influence of pharmacokinetics (PK) and pharmacogenetics on medication detection and the time-consuming nature of chemical adherence testing (CAT) processes. The central hypothesis underpinning this research is that the pharmacokinetics and pharmacogenetics of antihypertensive medications do not significantly affect medication detection or, consequently, the results of CAT by LC-MS/MS. This hypothesis is explored through a series of specific aims, including establishing PK parameters for the 20 most commonly prescribed antihypertensive medications through a comprehensive literature review. Additionally, the study aims to determine whether these PK parameters have any bearing on the outcomes of CAT using LC-MS/MS. A systematic review is conducted to identify genetic polymorphisms related to the effects of cardiovascular medications within the Biology Study to Tailored Treatment in Chronic Heart Failure (BIOSTAT-CHF) cohort, and the subsequent investigation focuses on the association between genetic polymorphisms and medication detection rates in the same cohort. Furthermore, the study strives to develop and partial validate an improved and more efficient CAT method for quantitating various cardiometabolic medications using LC-QQTO MS, a crucial step in ensuring accurate adherence assessments. The findings of this research reveal several critical insights. Chapter 3, which reviews the PK parameters of commonly prescribed antihypertensive medications, demonstrates no significant correlation between these parameters and adherence scores. This observation holds for multiple parameters, including bioavailability, urine excretion, clearance, volume of distribution (VD), half-life, peak time, and peak concentrations. Logistic regression analysis confirms that PK parameters do not predict non-adherence, even when considering additional factors such as age, sex, the number of medications, and creatinine levels. In Chapter 4, the systematic review uncovers various genetic polymorphisms associated with cardiovascular medication effects in the BIOSTAT-CHF cohort. However, these genetic variations do not exhibit a substantial correlation with non-adherence to prescribed cardiovascular drugs and encompass a wide range of effects, including PK influences, adverse drug reactions, metabolic responses, therapeutic outcomes, and risk-related impacts. Additionally, a non-directed genome wide association study (GWAS) showed weak associations with some potential polymorphisms, but none met the usual threshold of significance. Chapter 5 focuses on the development and partial validation of LC-QTOF-MS methods for the quantitation of cardiometabolic medications. Due to the distinct challenges posed by the COVID-19 pandemic, the objective was modified to conduct a partial validation assessment. The analysis time was reduced by 10 times from the previous method. The optimization of conditions for both positive and negative modes of LC-QTOF-MS is detailed, covering parameters such as capillary voltage, energy settings, and mobile phase selection. The validation results underscore the importance of tailored approaches for different pharmaceutical compounds, emphasising the significance of meticulous method development and validation in pharmaceutical analysis. In conclusion, this thesis proves the central hypothesis that the pharmacokinetics and pharmacogenetics of antihypertensive medications do not significantly affect medication detection and, therefore, do not influence the outcomes of CAT by LC-MS/MS. These findings offer valuable insights into improving medication adherence assessment and management in cardiometabolic diseases, highlighting the need for a multifaceted approach that considers pharmacokinetics and pharmacogenetics. Notably, my thesis had to adapt to the challenges posed by the COVID-19 crisis. The research shifted its focus from the initial plan of conducting PK profiles of antihypertensive medications in healthy volunteers to the plan of undertaking a systematic review of genetic polymorphisms associated with various effects of cardiovascular medications within the BIOSTAT-CHF cohort study.
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    Analysing Scientific Collaboration Networks Using Network Science Techniques to Study Covid-19 preprint papers/articles in UK and USA
    (University of Exeter, 0024-03-11) Asiri, Najat; Saunders, Owen
    The COVID-19 pandemic has instigated an unparalleled surge in scientific research, necessitating extensive collaboration among researchers, institutions, and nations. In this study, we employ advanced network science techniques, including centrality and betweenness measures, to conduct a comprehensive analysis of scientific collaboration networks within the context of COVID-19 research. The focus is specifically on preprint papers and articles sourced from Kaggle databases in the UK and USA. The research methodology involves collecting and analyzing over 50 million preprint papers and articles to provide a robust foundation for the analysis. Building upon existing research, we utilize bibliometric analyses and network science methodologies to unveil the intricate dynamics of collaboration. By mapping and quantifying evolving collaboration patterns, this research aims to identify key players and uncover research hotspots. The inclusion of network science methods such as centrality and betweenness enriches the analysis, providing a nuanced understanding of the collaborative landscape. The findings not only present a comprehensive view of collaborative dynamics within the scientific community but also shed light on key network metrics, including centrality and betweenness, highlighting pivotal contributors and facilitating efficient information flow. The paper contributes to the ongoing discourse on global health crises, offering valuable insights into the collaborative responses to the pandemic. The study, encompassing 32 papers over the period 2020 to 2023, represents a significant and timely addition to the existing body of knowledge. As the global scientific community continues to grapple with the complexities of COVID-19, this research serves as an essential guide for informed decision-making by policymakers, researchers, and institutions involved in shaping strategies for both current and future pandemics. The incorporation of new results further enhances the relevance and applicability of the findings, positioning this study as a crucial contribution to the understanding of collaborative networks in the face of global health challenges.
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