8,481 research outputs found

    An Exploration of the Suitability of Pharmacy Education in Saudi Arabia to Prepare Graduates to Meet Healthcare Needs: a Mixed-Methods Study

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    The key role of pharmacists within the health system, particularly in optimising safe, responsible and effective use of medicines, underpins the demand for a highly skilled and competent workforce. Therefore, developing the capacity of pharmacists to attain and maintain essential competencies relevant to the population’s health needs is required to ensure a high standard of patient care, thereby helping to improve patient and population health. In Saudi Arabia, little evidence exists regarding the assessment of national educational programmes’ structure and outcomes. Moreover, no national competency framework exists for pharmacists in any sector or stage of practice. In the absence of such core quality elements to inform pharmacy education assessment and development, the extent to which pharmacy schools in Saudi Arabia prepare competent pharmacists to address societal needs from pharmacy services is unclear. Therefore, this study aimed to explore the extent to which pharmacy education can prepare competent pharmacists to address the healthcare needs for pharmacy practice in Saudi Arabia. An exploratory sequential mixed methods research design was used to address the aim of this study in three phases: individual interviews and focus groups were employed with a purposively selected sample of pharmacy policy makers, pharmacists and the public to explore societal healthcare needs and the roles required of pharmacists to meet those needs; a national online survey of pharmacists and an online nominal group consensus method of pharmacy experts were used to identify competencies considered essential to develop a profession-wide national foundation level competency framework; and a case study in which curriculum mapping of two purposively selected Doctor of Pharmacy (PharmD) curricula was used to assess the extent to which the current pharmacy programme in Saudi Arabia meets the identified competencies of the developed national competency framework. Based on qualitative and quantitative analyses of societal healthcare needs, pharmacists’ roles, core competencies and curricular contents within the local context of Saudi Arabia, findings showed that there is a mismatch between initial education and real practice needs and expectations. While the country’s current needs from pharmacists are to optimise health system capacity and increase access to primary care services and medicines expertise in community pharmacies, the study indicated local education is product-oriented with a focus of curricular content and experiential training opportunities in most schools on preparing future pharmacists for hospital pharmacy practice. The study also identified several gaps between current initial education programmes and the competencies required to practise the expected roles, suggesting that current initial education might not prepare the students sufficiently to provide the full range of quality pharmaceutical services as per the country’s pharmacy practice needs. The study provided a new understanding of graduates’ readiness to practise as per the country’s pharmacy practice needs, the quality of educational programmes and pharmacists' professional development opportunities in Saudi Arabia. Findings maybe used to inform the development of competency-based education and maximise graduates’ capacity to deliver and develop pharmaceutical services effectively to best meet societal healthcare needs in Saudi Arabia

    The Impact of Attending Online Mindfulness Drop-In Sessions on Depression, Anxiety, Distress and Wellbeing in the General Population

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    Objectives: There is a lack of research into online mindfulness drop-in sessions (OMDIS) that have been offered freely to the public, especially during the Covid-19 pandemic. These sessions offer more flexibility than standard mindfulness-based interventions that run for a set number of sessions, as individuals can ‘drop in’ to as many sessions as and when they like. This research aimed to explore the impact of attending group facilitated OMDIS on psychological outcomes in the general population. Methods: A quantitative cross-sectional retrospective design was adopted in this study. Participants (n=112) were recruited online through OMDIS providers in the UK and internationally. Attendees were asked to complete an online survey with measures of depression, anxiety, distress and wellbeing, both for their current state and retrospectively for their state before attending any OMDIS. They also reported the number, duration and frequency of sessions attended, as well as their ease and accuracy of retrospective recall. Results: Paired T-tests and two-way repeated measures ANOVAs were conducted. Findings indicated that: OMDIS were efficacious in improving depression, anxiety, distress and wellbeing; attending more sessions, more frequently, for longer durations was not required to attain these benefits; and being on a psychology waitlist or having prior mindfulness experience did not lead to greater benefits, whereas having depression prior to attending OMDIS did lead to greater improvements in psychological outcomes. Conclusions: The current study is the first to explore and provide evidence for the efficacy of OMDIS on psychological outcomes. OMDIS are cost-effective and readily available and therefore could be offered to those on waiting lists for psychological interventions, who often wait prolonged periods without any support. Further research is needed to understand other factors that may impact efficacy in order to maximise the utility of OMDIS. Keywords: Online, mindfulness, drop-in, mental health, depression, anxiet

    On Transforming Reinforcement Learning by Transformer: The Development Trajectory

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    Transformer, originally devised for natural language processing, has also attested significant success in computer vision. Thanks to its super expressive power, researchers are investigating ways to deploy transformers to reinforcement learning (RL) and the transformer-based models have manifested their potential in representative RL benchmarks. In this paper, we collect and dissect recent advances on transforming RL by transformer (transformer-based RL or TRL), in order to explore its development trajectory and future trend. We group existing developments in two categories: architecture enhancement and trajectory optimization, and examine the main applications of TRL in robotic manipulation, text-based games, navigation and autonomous driving. For architecture enhancement, these methods consider how to apply the powerful transformer structure to RL problems under the traditional RL framework, which model agents and environments much more precisely than deep RL methods, but they are still limited by the inherent defects of traditional RL algorithms, such as bootstrapping and "deadly triad". For trajectory optimization, these methods treat RL problems as sequence modeling and train a joint state-action model over entire trajectories under the behavior cloning framework, which are able to extract policies from static datasets and fully use the long-sequence modeling capability of the transformer. Given these advancements, extensions and challenges in TRL are reviewed and proposals about future direction are discussed. We hope that this survey can provide a detailed introduction to TRL and motivate future research in this rapidly developing field.Comment: 26 page

    Inclusive Intelligent Learning Management System Framework - Application of Data Science in Inclusive Education

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    Dissertation presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Data ScienceBeing a disabled student the author faced higher education with a handicap which as experience studying during COVID 19 confinement periods matched the findings in recent research about the importance of digital accessibility through more e-learning intensive academic experiences. Narrative and systematic literature reviews enabled providing context in World Health Organization’s International Classification of Functioning, Disability and Health, legal and standards framework and information technology and communication state-of-the art. Assessing Portuguese higher education institutions’ web sites alerted to the fact that only outlying institutions implemented near perfect, accessibility-wise, websites. Therefore a gap was identified in how accessible the Portuguese higher education websites are, the needs of all students, including those with disabilities, and even the accessibility minimum legal requirements for digital products and the services provided by public or publicly funded organizations. Having identified a problem in society and exploring the scientific base of knowledge for context and state of the art was a first stage in the Design Science Research methodology, to which followed development and validation cycles of an Inclusive Intelligent Learning Management System Framework. The framework blends various Data Science study fields contributions with accessibility guidelines compliant interface design and content upload accessibility compliance assessment. Validation was provided by a focus group whose inputs were considered for the version presented in this dissertation. Not being the purpose of the research to deliver a complete implementation of the framework and lacking consistent data to put all the modules interacting with each other, the most relevant modules were tested with open data as proof of concept. The rigor cycle of DSR started with the inclusion of the previous thesis on Atlântica University Institute Scientific Repository and is to be completed with the publication of this thesis and the already started PhD’s findings in relevant journals and conferences

    Attaining climate justice through the adaptation of urban form to climate change: flood risks in Toronto

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    Empirical evidence points out that entrenched cost-benefit rationales behind urban form adaptations to climate change unequally exacerbate vulnerabilities and hazard exposures, engendering risk inequalities and triggering climate injustice. Specifically, adaptive interventions for managing climate change-induced floods, whether through green and blue infrastructure (GBI), land use planning, or urban design, prioritize the protection of high-value urban assets while excluding vulnerable groups. To redress climate injustice, some have called for the consideration of the three pillars of justice: distributive justice, i.e., the just spatial distribution of adaptation responses; procedural justice, i.e., the equality of decision-making processes; and recognitional justice, i.e., the legitimization of marginalized groups. To assess the extent of these pillars’ integration in the scholarship (theoretically and empirically), this dissertation conducted a systematic review of 136 peer-reviewed papers on urban climate justice vis-à-vis adaptation. The findings reveal a lack of theoretical and empirical connections between the three-pillared justice framework and climate adaptive interventions in urban form. The dissertation’s theoretical framework overcomes these omissions by using different theories/concepts in the literature as nexuses connecting climate justice pillars with urban form. It capitalizes on interconnections distributive justice has with differential vulnerabilities, flood exposures, and the adaptive capacity of urban form to identify areas that unequally experience flood risks and need to be prioritized in adaptation. It, furthermore, combined the three-pillared justice framework with epistemic justice and local experiential knowledge concept to explore how flood-adaptive GBI planning can address the root causes of vulnerabilities, hence facilitating justice-oriented transformative adaptation. Accordingly, the research developed a multi-criteria model including indicators and variables for measuring the spatial distribution of social vulnerabilities, exposure, and the adaptive capacity of urban form, whereby it proposes pathways for justice-oriented transformative adaptation of high-risk priority areas through GBI planning. The dissertation focuses on Toronto in Ontario, Canada, to test the theoretical framework, which can be applied in any city. The study in Toronto asks: “who” is unequally at-risk of flooding events, “where” are they located, “why” they are unequally vulnerable, and “how” we can engage the high-risk community in adaptive GBI planning to promote justice-oriented transformative adaptation. The methodology started with operationalizing the spatial multi-criteria model through weighted overlay analysis using ArcGIS and an online survey of 120 Toronto-based flooding experts, which yielded the identification of four priority neighborhoods at a disproportionate risk of floods. Focusing on one of the high-risk priority neighborhoods, Thorncliffe Park, I conducted 20 semi-structured interviews with flooding experts and local leaders and an online survey of residents to investigate whether the local experiential knowledge of residents has been recognized in adaptive GBI planning decisions. I furthermore performed an online participatory-mapping activity in this neighborhood during which participants marked, on the neighborhood map, locations that require GBI for socio-cultural benefits. I overlaid the resulting participatory maps with land uses’ run-off coefficients to propose sites for allocating GBI for both socio-cultural benefits and run-off management. The findings show the effectiveness of the theoretical framework in identifying priority neighborhoods and developing place-based adaptation solutions inside and outside Canada. All four high-risk neighborhoods are inner-city tower communities with old infrastructure and dense low-income, racialized, and migrant populations, typical tower blocks built after the second World War in several cities across North America and Europe. The findings in Thorncliffe Park, as the priority neighborhood, unveil the exclusion of residents from flood-adaptive GBI planning despite their vulnerabilities and exposure. This exclusion, as results indicate, is rooted in technocratic processes based on technical knowledge and cost-benefit rationales. The findings show four epistemic barriers that need to be addressed to facilitate climate justice in adaptation interventions within Thorncliffe Park: lack of social networks, citizenship rights, climate awareness opportunities, and communicational tools. The results also show that the industrial uses around the railway and residential-commercial sites around Overlea Boulevard in this neighborhood are in dire need of GBI for managing run-offs and socio-cultural benefits. I propose adopting inclusive processes to allocate small-scale adaptive GBI in these locations. Building on the findings, the dissertation proposes future theoretical and empirical studies to complement this study by proposing how to design GBI and other urban form adaptive interventions by changing the layout patterns, orientation, and geometry of streets, buildings, and blocks in the high-risk disenfranchised communities to advance climate justice. At the center of this proposition are developing new theories to expand the climate justice triad and devising new forms of inclusive and collaborative design

    A Qualitative Analysis of Common Practices in Annotations: A Taxonomy and Design Space

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    Annotations are a vital component of data externalization and collaborative analysis, directing readers' attention to important visual elements. Therefore, it is crucial to understand their design space for effectively annotating visualizations. However, despite their widespread use in visualization, we have identified a lack of a design space for common practices for annotations. In this paper, we present two studies that explore how people annotate visualizations to support effective communication. In the first study, we evaluate how visualization students annotate bar charts when answering high-level questions about the data. Qualitative coding of the resulting annotations generates a taxonomy comprising enclosure, connector, text, mark, and color, revealing how people leverage different visual elements to communicate critical information. We then extend our taxonomy by performing thematic coding on a diverse range of real-world annotated charts, adding trend and geometric annotations to the taxonomy. We then combine the results of these studies into a design space of annotations that focuses on the key elements driving the design choices available when annotating a chart, providing a reference guide for using annotations to communicate insights from visualizations
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