741 resultados para clinical learning environment
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While CPD is now a mandatory requirement for Australian pharmacists, there has been little research to identify preferred learning resources, or barriers and motivators for continuing education and CPD participation. This study aimed to identify post-registration learning trends of community pharmacists in western Australia, as well as their opinions on post-registration learning.
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Objective. To determine whether copper incorporated into hospital ward furnishings and equipment can reduce their surface microbial load. Design. A crossover study. Setting. Acute care medical ward with 19 beds at a large university hospital. Methods. Fourteen types of frequent-touch items made of copper alloy were installed in various locations on an acute care medical ward. These included door handles and push plates, toilet seats and flush handles, grab rails, light switches and pull cord toggles, sockets, overbed tables, dressing trolleys, commodes, taps, and sink fittings. Their surfaces and those of equivalent standard items on the same ward were sampled once weekly for 24 weeks. The copper and standard items were switched over after 12 weeks of sampling to reduce bias in usage patterns. The total aerobic microbial counts and the presence of indicator microorganisms were determined. Results. Eight of the 14 copper item types had microbial counts on their surfaces that were significantly lower than counts on standard materials. The other 6 copper item types had reduced microbial numbers on their surfaces, compared with microbial counts on standard items, but the reduction did not reach statistical significance. Indicator microorganisms were recovered from both types of surfaces; however, significantly fewer copper surfaces were contaminated with vancomycin-resistant enterococci, methicillin-susceptible Staphylococcus aureus, and coliforms, compared with standard surfaces. Conclusions. Copper alloys (greater than or equal to 58% copper), when incorporated into various hospital furnishings and fittings, reduce the surface microorganisms. The use of copper in combination with optimal infection-prevention strategies may therefore further reduce the risk that patients will acquire infection in healthcare environments.
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This dissertation investigates the very important and current problem of modelling human expertise. This is an apparent issue in any computer system emulating human decision making. It is prominent in Clinical Decision Support Systems (CDSS) due to the complexity of the induction process and the vast number of parameters in most cases. Other issues such as human error and missing or incomplete data present further challenges. In this thesis, the Galatean Risk Screening Tool (GRiST) is used as an example of modelling clinical expertise and parameter elicitation. The tool is a mental health clinical record management system with a top layer of decision support capabilities. It is currently being deployed by several NHS mental health trusts across the UK. The aim of the research is to investigate the problem of parameter elicitation by inducing them from real clinical data rather than from the human experts who provided the decision model. The induced parameters provide an insight into both the data relationships and how experts make decisions themselves. The outcomes help further understand human decision making and, in particular, help GRiST provide more accurate emulations of risk judgements. Although the algorithms and methods presented in this dissertation are applied to GRiST, they can be adopted for other human knowledge engineering domains.
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Scholarship in learning and teaching.
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Adults participate in communities of practice (COP) in diverse environments. As the number of US citizens 55 years or older increases, so might the number residing in adult living environments. COP research would be valuable in such settings.
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Peer reviewed
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In any environment, group dynamics would exist. How we deal with it in a competitive work environment defines who we are using transformative learning. This paper provides useful information from a number of theorists who share perspectives on the complex nature of groups.
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This thesis focused on medical students’ language learning strategies for patient encounters. The research questions concerned the types of learning strategies that medical students use and the differences between the preclinical students and the clinical students, two groups who have had varying amounts of experience with patients. Additionally, strategy use was examined through activity systems to gain information on the context of language learning strategy use in order to learn language for patient encounters. In total, 130 first-year medical students (preclinical) and 39 fifth-year medical students (clinical) participated in the study by filling in a questionnaire on language learning strategies. In addition, two students were interviewed in order to create activity systems for the medical students at different stages of their studies. The study utilised both quantitative and qualitative research methods; the analysis of the results relies on Oxford’s Strategic Self-Regulation Model in the quantitative part and on activity theory in the qualitative part. The theoretical sections of the study introduced earlier research and theories regarding English for specific purposes, language learning strategies and activity theory. The results indicated that the medical students use affective, sociocultural-interactive and metasociocultural-interactive strategies often and avoid using negative strategies, which hinder language learning or cease communication altogether. Slight differences between the preclinical and clinical students were found, as clinical students appear to use affective and metasociocultural-interactive strategies more frequently compared to the preclinical students. The activity systems of the two students interviewed were rather similar. The students were at different stages of their studies, but their opinions were very similar. Both reported the object of learning to be mutual understanding between the patient and the doctor, which in part explains the preference for strategies that support communication and interaction. The results indicate that the nature of patient encounters affects the strategy use of the medical students at least to some extent.
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An economy of effort is a core characteristic of highly skilled motor performance often described as being effortless or automatic. Electroencephalographic (EEG) evaluation of cortical activity in elite performers has consistently revealed a reduction in extraneous associative cortical activity and an enhancement of task-relevant cortical processes. However, this has only been demonstrated under what are essentially practice-like conditions. Recently it has been shown that cerebral cortical activity becomes less efficient when performance occurs in a stressful, complex social environment. This dissertation examines the impact of motor skill training or practice on the EEG cortical dynamics that underlie performance in a stressful, complex social environment. Sixteen ROTC cadets participated in head-to-head pistol shooting competitions before and after completing nine sessions of skill training over three weeks. Spectral power increased in the theta frequency band and decreased in the low alpha frequency band after skill training. EEG Coherence increased in the left frontal region and decreased in the left temporal region after the practice intervention. These suggest a refinement of cerebral cortical dynamics with a reduction of task extraneous processing in the left frontal region and an enhancement of task related processing in the left temporal region consistent with the skill level reached by participants. Partitioning performance into ‘best’ and ‘worst’ based on shot score revealed that deliberate practice appears to optimize cerebral cortical activity of ‘best’ performances which are accompanied by a reduction in task-specific processes reflected by increased high-alpha power, while ‘worst’ performances are characterized by an inappropriate reduction in task-specific processing resulting in a loss of focus reflected by higher high-alpha power after training when compared to ‘best’ performances. Together, these studies demonstrate the power of experience afforded by practice, as a controllable factor, to promote resilience of cerebral cortical efficiency in complex environments.
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Background: Tertiary pediatric hospitals usually provide excellent clinical services, but such centers have a lot to do for educational perfection. Objectives: This study was performed to address under-graduate educational deficits and find feasible solutions. Patients and Methods: This cross-sectional study was done in a target population of 77 sixth year undergraduate medical students (response rate = 78%) who spent their 3-month pediatric rotation in the Children’s Medical Center, the Pediatrics Center of Excellence in Tehran, Iran. The Dundee ready educational environment measure (DREEM) instrument was used for assessing educational environment of this subspecialized pediatric hospital. Results: Among 60 students who answered the questionnaires, 24 were male (40%). Participants’ age ranged from 23 to 24 years. The mean total score was 95.8 (48%). Comparison of scores based on students’ knowledge showed no significant difference. Problematic areas were learning, academic self-perception, and social self-perception. Conclusions: Having an accurate schedule to train general practitioner, using new teaching methods, and providing a non-stressful atmosphere were suggested solutions.
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Isolation of Mycobacterium avium complex (MAC) organisms from clinical samples may occur in patients without clinical disease, making the interpretation of results difficult. The clinical relevance of MAC isolates from different types of clinical samples (n = 47) from 39 patients in different sections of a hospital was assessed by comparison with environmental isolates (n = 17) from the hospital. Various methods for identification and typing (commercial probes, phenotypic characteristics, PCR for detection of IS1245 and IS901, sequencing of the hsp65 gene, and pulsed-field gel electrophoresis) were evaluated. The same strain was found in all the environmental isolates, 21 out of 23 (91.3%) of the isolates cultured from urine samples, and 5 out of 19 (26.3%) isolates from respiratory specimens. This strain did not cause disease in the patients. Testing best characterized the strain as M. avium subsp. hominissuis, with the unusual feature that 81.4% of these isolates lacked the IS1245 element. Contamination of certain clinical samples with an environmental strain was the most likely event; therefore, characterization of the environmental mycobacteria present in health care facilities should be performed to discard false-positive isolations in nonsterile samples, mainly urine samples. Molecular techniques applied in this study demonstrated their usefulness for this purpose.
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Clinical and omics data are a promising field of application for machine learning techniques even though these methods are not yet systematically adopted in healthcare institutions. Despite artificial intelligence has proved successful in terms of prediction of pathologies or identification of their causes, the systematic adoption of these techniques still presents challenging issues due to the peculiarities of the analysed data. The aim of this thesis is to apply machine learning algorithms to both clinical and omics data sets in order to predict a patient's state of health and get better insights on the possible causes of the analysed diseases. In doing so, many of the arising issues when working with medical data will be discussed while possible solutions will be proposed to make machine learning provide feasible results and possibly become an effective and reliable support tool for healthcare systems.
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At the intersection of biology, chemistry, and engineering, biosensors are a multidisciplinary innovation that provide a cost-effective alternative to traditional laboratory techniques. Due to their advantages, biosensors are used in medical diagnostics, environmental monitoring, food safety and many other fields. The first part of the thesis is concerned with learning the state of the art of paper-based immunosensors with bioluminescent (BL) and chemiluminescent (CL) detection. The use of biospecific assays combined with CL detection and paper-based technology offers an optimal approach to creating analytical tools for on-site applications and we have focused on the specific areas that need to be considered more in order to ensure a future practical implementation of these methods in routine analyses. The subsequent part of the thesis addresses the development of an autonomous lab-on-chip platform for performing chemiluminescent-based bioassays in space environment, exploiting a CubeSat platform for astrobiological investigations. An origami-inspired microfluidic paper-based analytical device has been developed with the purpose of assesses its performance in space and to evaluate its functionality and the resilience of the (bio)molecules when exposed to a radiation-rich environment. Subsequently, we designed a paper-based assay to detect traces of ovalbumin in food samples, creating a user-friendly immunosensing platform. To this purpose, we developed an origami device that exploits a competitive immunoassay coupled with chemiluminescence detection and magnetic microbeads used to immobilize ovalbumin on paper. Finally, with the aim of exploring the use of biomimetic materials, an hydrogel-based chemiluminescence biosensor for the detection of H2O2 and glucose was developed. A guanosine hydrogel was prepared and loaded with luminol and hemin, miming a DNAzyme activity. Subsequently, the hydrogel was modified by incorporating glucose oxidase enzyme to enable glucose biosensing. The emitted photons were detected using a portable device equipped with a smartphone's CMOS (complementary metal oxide semiconductor) camera for CL emission detection.