175 resultados para Information needs – representation
Resumo:
Background Maternity care reform plans have been proposed at state and national levels in Australia, but the extent to which these respond to maternity care consumers’ expressed needs is unclear. This study examines open-text survey comments to identify women’s unmet needs and priorities for maternity care. It is then considered whether these needs and priorities are addressed in current reform plans. Methods Women who had a live single or multiple birth in Queensland, Australia, in 2010 (n 3,635) were invited to complete a retrospective self-report survey. In addition to questions about clinical and interpersonal maternity care experiences from pregnancy to postpartum, women were asked an open-ended question “Is there anything else you’d like to tell us about having your baby?” This paper describes a detailed thematic analysis of open-ended responses from a random selection of 150 women (10% of 1,510 who responded to the question). Results Four broad themes emerged relevant to improving women’s experiences of maternity care: quality of care (interpersonal and technical); access to choices and involvement in decision-making; unmet information needs; and dissatisfaction with the care environment. Some of these topics are reflected in current reform goals, while others provide evidence of the need for further reforms. Conclusions The findings reinforce the importance of some existing maternity reform objectives, and describe how these might best be met. Findings affirm the importance of information provision to enable informed choices; a goal of Queensland and national reform agendas. Improvement opportunities not currently specified in reform agendas were also identified, including the quality of interpersonal relationships between women and staff, particular unmet information needs (e.g., breastfeeding), and concerns regarding the care environment (e.g., crowding and long waiting times).
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Culturally, philosophically and religiously diverse medical systems including Western medicine, Traditional Chinese Medicine, Ayurvedic Medicine and Homeopathic Medicine, once situated in places and times relatively unconnected from each other, currently co-exist to a point where patients must choose which system to consult. These decisions require comparative analyses, yet the divergence in key underpinning assumptions is so great that comparisons cannot easily be made. However, diverse medical systems can be meaningfully juxtaposed for the purpose of making practical decisions if relevant information is presented appropriately. Information regarding privacy provisions inherent in the typical practice of each medical system is an important element in this juxtaposition. In this paper the information needs of patients making decisions regarding the selection of a medical system are examined.
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This thesis is a qualitative study of the influence of social media on the university and course decision making process of international students. It examines the role of social media in influencing international students' decisions on course and university selection and the role of social media in meeting their information needs. It also gathered inputs on how universities could engage, collaborate and communicate using social media communities and channels for more effective recruitment strategies.
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For traditional information filtering (IF) models, it is often assumed that the documents in one collection are only related to one topic. However, in reality users’ interests can be diverse and the documents in the collection often involve multiple topics. Topic modelling was proposed to generate statistical models to represent multiple topics in a collection of documents, but in a topic model, topics are represented by distributions over words which are limited to distinctively represent the semantics of topics. Patterns are always thought to be more discriminative than single terms and are able to reveal the inner relations between words. This paper proposes a novel information filtering model, Significant matched Pattern-based Topic Model (SPBTM). The SPBTM represents user information needs in terms of multiple topics and each topic is represented by patterns. More importantly, the patterns are organized into groups based on their statistical and taxonomic features, from which the more representative patterns, called Significant Matched Patterns, can be identified and used to estimate the document relevance. Experiments on benchmark data sets demonstrate that the SPBTM significantly outperforms the state-of-the-art models.
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Objective The objective of this study was to evaluate weight-related risk perception in early pregnancy and to compare this perception between women commencing pregnancy healthy weight and overweight. Study design Pregnant women (n=664) aged 29±5 (mean±s.d.) years were recruited from a metropolitan teaching hospital in Australia. A self-administered questionnaire was completed at around 16 weeks of gestation. Height measured at baseline and self-reported pre-pregnancy weight were used to calculate body mass index. Cross-sectional analysis was conducted. Differences between groups were assessed using chi-squared tests for categorical variables and t-tests or Mann–Whitney U tests for continuous variables depending on distribution. Result Excess gestational weight gain (GWG) during pregnancy was more important in leading to health problems for women or their child compared with pre-pregnancy weight. Personal risk perception for complications was low for all women, although overweight women had slightly higher scores than healthy-weight women (2.4±1.0 vs 2.9±1.0; P<0.001). All women perceived their risk for complications to be below that of an average pregnant woman. Conclusion Women should be informed of the risk associated with their pre-pregnancy weight (in the case of maternal overweight) and excess GWG. If efforts to raise risk awareness are to result in preventative action, this information needs to be accompanied by advice and appropriate support on how to reduce risk.
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Bug fixing is a highly cooperative work activity where developers, testers, product managers and other stake-holders collaborate using a bug tracking system. In the context of Global Software Development (GSD), where software development is distributed across different geographical locations, we focus on understanding the role of bug trackers in supporting software bug fixing activities. We carried out a small-scale ethnographic fieldwork in a software product team distributed between Finland and India at a multinational engineering company. Using semi-structured interviews and in-situ observations of 16 bug cases, we show that the bug tracker 1) supported information needs of different stake holder, 2) established common-ground, and 3) reinforced issues related to ownership, performance and power. Consequently, we provide implications for design around these findings.
Resumo:
Objective The objectives of this study were to investigate (1) the attitudes and behaviours of Australian consumers in antibiotic use, and (2) their understanding of antibiotic resistance. Methods Semi-structured interviews were conducted with consumers in May/June 2015. Convenience sampling was used to recruit consumers between 18–54 years old. Thirty-two consumers were interviewed. Transcripts were analysed to identify themes. Lessons Learned Dominant themes for attitudes and behaviours regarding antibiotics were (a) avoidance of antibiotic use unless clinically warranted; (b) antibiotics were useful but “weakened the body”; and (c) use of complementary medicines as adjuncts to antibiotics or to strengthen the immune system. Key information needs were (a) unambiguous instructions from GPs when prescribed antibiotics, to avoid inappropriate medicine-taking behaviour; (b) rationale for antibiotic selection; and (c) treatment duration. Antibiotic resistance was conceptualised in three ways: as a property of the body (body becomes resistant to antibiotics); the medication (antibiotic no longer effective); and the bacteria (bacteria is resistant). Antibiotic resistance was perceived as an issue that would only affect the wider community in the future, although most recognised that it is a current challenge for hospitals. Personal good health and/or avoidance of antibiotics were perceived as insurance against being adversely affected by antibiotic resistance. Implications A structured survey (discrete choice experiment) will be developed from these findings to investigate how consumers trade-off on factors influencing antibiotic use. Public health campaigns promoting conservation of antibiotics can benefit from these findings.
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Recommender systems assist users in finding what they want. The challenging issue is how to efficiently acquire user preferences or user information needs for building personalized recommender systems. This research explores the acquisition of user preferences using data taxonomy information to enhance personalized recommendations for alleviating cold-start problem. A concept hierarchy model is proposed, which provides a two-dimensional hierarchy for acquiring user preferences. The language model is also extended for the proposed hierarchy in order to generate an effective recommender algorithm. Both Amazon.com book and music datasets are used to evaluate the proposed approach, and the experimental results show that the proposed approach is promising.
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Recovering position from sensor information is an important problem in mobile robotics, known as localisation. Localisation requires a map or some other description of the environment to provide the robot with a context to interpret sensor data. The mobile robot system under discussion is using an artificial neural representation of position. Building a geometrical map of the environment with a single camera and artificial neural networks is difficult. Instead it would be simpler to learn position as a function of the visual input. Usually when learning images, an intermediate representation is employed. An appropriate starting point for biologically plausible image representation is the complex cells of the visual cortex, which have invariance properties that appear useful for localisation. The effectiveness for localisation of two different complex cell models are evaluated. Finally the ability of a simple neural network with single shot learning to recognise these representations and localise a robot is examined.
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This paper reports the findings of a qualitative study which investigated 25 international students’ use of online information resources for study purposes at two Australian universities. Using an expanded critical incident approach, the study viewed international students through an information literacy lens, as information-using learners. The findings are presented in two complementary parts: as a word picture that describes their whole experience of using online information resources to learn; and as a tabulated set of critical findings that summarises their associated information literacy learning needs. The word picture shows international students’ resource use as a complex interplay of eight inter-related elements: students; information-learning environment; interactions (with online resources); strengths-challenges; learning-help; affective responses; reflective responses; cultural-linguistic dimensions. In using online resources, the international students experience an array of strengths and challenges, and an apparent information literacy imbalance between their more developed information skills and less developed critical information use. The critical findings about information literacy needs provide a framework for developing an inclusive informed learning approach that responds to international students’ complex information using experiences and needs. While the study is situated in Australia, the findings are of potential interest to educators, information professionals and researchers worldwide who seek to support learning in culturally diverse higher education contexts.
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Background: High levels of distress and need for self-care information by patients commencing chemotherapy suggest that current prechemotherapy education is suboptimal. We conducted a randomised, controlled trial of a prechemotherapy education intervention (ChemoEd) to assess impact on patient distress, treatment-related concerns, and the prevalence and severity of and bother caused by six chemotherapy side-effects. Patients and methods: One hundred and ninety-two breast, gastrointestinal, and haematologic cancer patients were recruited before the trial closing prematurely (original target 352). ChemoEd patients received a DVD, question-prompt list, self-care information, an education consultation ≥24 h before first treatment (intervention 1), telephone follow-up 48 h after first treatment (intervention 2), and a face-to-face review immediately before second treatment (intervention 3). Patient outcomes were measured at baseline (T1: pre-education) and immediately preceding treatment cycles 1 (T2) and 3 (T3). Results: ChemoEd did not significantly reduce patient distress. However, a significant decrease in sensory/psychological (P = 0.027) and procedural (P = 0.03) concerns, as well as prevalence and severity of and bother due to vomiting (all P = 0.001), were observed at T3. In addition, subgroup analysis of patients with elevated distress at T1 indicated a significant decrease (P = 0.035) at T2 but not at T3 (P = 0.055) in ChemoEd patients. Conclusions: ChemoEd holds promise to improve patient treatment-related concerns and some physical/psychological outcomes; however, further research is required on more diverse patient populations to ensure generalisability.
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Building information models are increasingly being utilised for facility management of large facilities such as critical infrastructures. In such environments, it is valuable to utilise the vast amount of data contained within the building information models to improve access control administration. The use of building information models in access control scenarios can provide 3D visualisation of buildings as well as many other advantages such as automation of essential tasks including path finding, consistency detection, and accessibility verification. However, there is no mathematical model for building information models that can be used to describe and compute these functions. In this paper, we show how graph theory can be utilised as a representation language of building information models and the proposed security related functions. This graph-theoretic representation allows for mathematically representing building information models and performing computations using these functions.