4,395 research outputs found
Exploring the Validity of Script Concordance Testing to Assess the Clinical Reasoning of Medical Students
Assessment of clinical reasoning is often challenging, as it is a complex process of thinking and decision making. Script Concordance Testing (SCT), using authentic clinical scenarios with diagnostic or management uncertainties, has been developed to assess clinical reasoning. As SCT is a relatively new assessment modality, more empirical evidence is needed to support the validity of SCT scores.
This thesis examines key aspects of the validity of SCT scores in the assessment of the clinical reasoning ability of medical undergraduates. A review of the current literature informs the use, design and standard setting of SCT, as well as evidence for its reliability and validity. Exploration of the response patterns of 5 cohorts of graduate-entry medical students in an Australian Medical School showed deliberate avoidance of extreme responses by the lowest quartile students. A post-hoc simulation study, testing the hypothesis that test-wise candidates’ SCT scores were inflated through deliberate avoidance of extreme response-options and selection of neutral response-options, generated an approach to optimising and balancing SCT items for improved SCT score validity.
In response to the paucity of empirical studies on the construct validity for SCT scores, the next study showed evidence of progression in SCT scores from medical students, to junior registrars, to experienced general practitioners. Finally, an investigation of candidates’ response process, using a ‘think-aloud’ approach, supported the response process validity of SCT scores.
In conclusion, this thesis has demonstrated that: 1) thoughtful design and balance of SCT items can mitigate some of the validity threats to medical student SCT scores; 2) the tendency of SCT scores to progress with increasing levels of clinical practice experience further supports the construct validity of SCT scores; and 3) use of the ‘think-aloud’ approach to explore students’ response process may enhance the utility and educational benefits of SCT. The research supports the validity of SCT in assessing clinical reasoning in undergraduate medical education, and presents practical approaches to enhance the design of the assessment instrument
Multiple Cue Based Vehicle Detection and Tracking for Road Safety
With the rise in accident related fatalities on roads, the researchers around the world are looking for solutions including integrating intelligence to vehicles. One cruicial aspects of it is the robust detection and tracking of other vehicles in the visinity. In this paper, we have proposed a probabilistic way of incorporation of several visual cues in vehicle detection and a particle filter based tracking strategy. Visual cues used are, lane markings, symmetry, entropy and shadows. Combination of visual cues provided us with robust results when compared with their individual counterparts. The definition of a region of interest lowers the computational requirements with improved robustness. Experimental results of the algorithm in Sydney urban areas are presente
Peritoneal computed tomography: A diagnostic tool for genital oedema in patients on peritoneal dialysis
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A systematic review and meta-analysis of prophylactic central neck dissection on short-term locoregional recurrence in papillary thyroid carcinoma after total thyroidectomy
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Off-Street Vehicular Fog for Catering Applications in 5G/B5G: A Trust-based Task Mapping Solution and Open Research Issues
One of the key enablers in serving the applications requiring stringent latency in 5G networks is fog computing as it is situated closer to the end users. With the technological advancement of vehicles’ on-board units, their computing capabilities are becoming robust, and considering the underutilization of the off-street vehicles, we envision that the off-street vehicles can be an enormously useful computational source for the fog computing. Additionally, clustering the vehicles would be advantageous in order to improve the service availability. As the vehicles become highly connected, trust is needed especially in distributed environments. However, vehicles are made from different manufacturers, and have different platforms, security mechanisms, and varying parking duration. These lead to the unpredictable behavior of the vehicles where quantifying trust value of vehicles would be difficult. A trust-based solution is necessary for task mapping as a task has a set of properties including expected time to complete, and trust requirements that need to be met. However, the existing metrics used for trust evaluation in the vehicular fog computing such as velocity and direction are not applicable in the off-street vehicle fog environments. In this paper, we propose a framework for quantifying the trust value of off-street vehicle fog computing facilities in 5G networks and forming logical clusters of vehicles based on the trust values. This allows tasks to be shared with multiple vehicles in the same cluster that meets the tasks’ trust requirements. Further, we propose a novel task mapping algorithm to increase the vehicle resource utilization and meet the desired trust requirements while maintaining imposed latency requirements of 5G applications. Results obtained using iFogSim simulator demonstrate that the proposed solution increases vehicle resource utilization and reduces task drop noticeably. This paper presents open research issues pertaining to the study to lead..
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