The American population is aging; by 2030, people over the age of 65 may comprise as much as 20% of the population (Niedert, 2006). As many as 80% of the people in this age group live with at least one chronic illness, and 4.5% of elderly persons in the United States live in nursing homes (Boyle & Holben, 2006). As individuals age into late adulthood, they may experience lessening abilities to think clearly and to move as dexterously as well as a decline in bodily functions that may inhibit their ability to perform tasks of daily living (Boyle & Holben, 2006). These experiences also hinder nutrient intake.

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Persistence to program completion is critical for online students. Retaining online students is a struggle in higher education with online persistence rates being significantly lower than nononline students. In this qualitative case study the perceptions of female graduates who persisted in a fully online allied health program at a career college were investigated. Using Tinto's theory of student departure and self-determination theory, the characteristics, attitudes, and motivations of female online learners explored to discern their perceived success in the online classroom. The research questions focused on participants' perceptions, skills, and attitudes that contribute to their success, experiences with support services, and a review of archival documents to examine existing systems to support this population to gain insight into possible methods to support persistence challenges by designing meaningful learning experiences, to strengthen student persistence and develop faculty for online teaching. Notes from document reviews and semistructured interviews with 12 participants were analyzed and coded using an inductive approach to identify themes in the data. Results of the research indicated that participants used a variety of strategies for success, connected to the campus community, were prepared for online learning, and engaged with learning materials to support persisting to graduation. The findings of this study will influence social change by providing administrators and faculty a 3-day professional development program to strengthen faculties' understanding of online students' needs thereby improving online student support, persistence to degree completion, and graduation. Degree completion will improve career opportunities resulting in a higher quality of life.

This study aims to understand the use of a computer during GP consultations and to enable the development of EPR systems which are easier to review, enter data into, use to take action, and is more sensitive to the clinical context. This thesis reports the development of a multi-channel video and data capture toolkit, the ALFA (Activity Log File Aggregation) because existing observation techniques have limitations. None of the existing tools are designed to assess human-computer interaction in the context of the clinical consultation, where the social interaction is the prime focus. The ALFA tool-kit has been used to observe and study 163 live primary care consultations supported by computer systems with four different designs. A detailed analysis of consultation interactions was then performed focusing on doctor-patient communication and the integration of the computer into the consultation workflow. The data collection elements of the ALFA supported recording of consultation activities by providing rating techniques attuned with the characteristics of those interactions. The Log File Aggregation (LFA) component of the ALFA toolkit aggregated those multitudes of data files into a single navigable output that can be studied both quantitatively and qualitatively. A set of Unified Modelling Language (UML) sequence diagrams were then created as they could be used by software engineers to develop better systems. This research proposes a framework with three elements to analyse the computerised clinical consultation; (1) the overview of the context within which the consultation was carried out, (2) time taken to perform key consultation tasks and (3) the process used. Traditional analysis with its emphasis on the technology often misses crucial features of the complex work environments in which the technology is implemented. Direct observation could inform software designers in developing systems that are more readily integrated into clinical workflow. Direct observation of the consultation, using the ALFA toolkit is acceptable to patients; captures the context of the consultation the precise timing and duration of key tasks; and produces an output a software engineer can understand. ALFA offers a range of possibilities for research in the consulting room. The computer should be considered as an active element of the consultation; room layout and consultation models should let the computer in, while software engineers take in the capacity to sustain patient centred social interactions as a core facet of their design agenda.

Pulmonary embolism (PE) is an obstruction within the pulmonary arterial tree and in the majority of cases arises from a thrombosis that has travelled to the lungs via the venous system. Pulmonary embolism (PE) is a fatal condition which affects all age groups and is the third most common cause of death in the US. Computed tomographic angiography (CTA) imaging has recently emerged as an accurate method in the diagnosis of pulmonary embolism. Each CTA scan contains hundreds of CT images, so the accuracy and efficiency of interpreting such a large image data set is complicated due to various PE look-alikes and human factors such as attention span and eye fatigue. Moreover, manual reading and interpreting a large number of slices is time consuming and it is difficult to find all the pulmonary embolisms (PE) in a data set. Consequently, it is highly desirable to have a computer aided detection (CAD) system to assist radiologists in detecting and characterizing emboli in an accurate, efficient and reproducible manner. A computer aided detection (CAD) system for detection of pulmonary embolism is proposed in CTA images. Our approach is performed in three stages: firstly the pulmonary artery tree is extracted in the region of the lung and heart in order to reduce the search area (PE occurs inside the pulmonary artery) and aims to reduce the false detection rate. The pulmonary artery is separated from the surrounding organs by analyzing the second derivative of the Hessian matrix and then a hybrid method based on region growing and a new customized level set is used to extract the pulmonary artery (PA). In the level set implementation algorithm, a new stopping criterion is applied, a consideration often neglected in many level set implementations. In the second stage, pulmonary embolism candidates are detected inside the segmented pulmonary artery, by an analysis of three dimensional features inside the segmented artery. PE detection in the pulmonary artery is implemented using five detectors. Each detector responds to different properties of PE. In the third stage, filtering is used to exclude false positive detections associated with the partial volume effect on the artery boundary, flow void, lymphoid tissue, noise and motion artifacts. Soft tissue between the bronchial wall and the pulmonary artery is a common cause of false positive detection in CAD systems. A new feature, based on location is used to reduce false positives caused by soft tissue. The method was tested on 55 data scans (20 training data scans and 35 additional data scans for evaluation containing a total of 195 emboli). The system provided a segmentation of the PA up to the 6th division, which includes the sub-segmental level. Resulting performance gave 94% detection sensitivity with an average 4.1 false positive detections per scan. We demonstrated that the proposed CAD system can improve the performance of a radiologist, detecting 19 (11 %) extra PE which were not annotated by the radiologist.

Thesis (MGeront)--University of South Australia, 1998

Thesis (M.Ed.)--University of Adelaide, Dept. of Education, 1999. / Errata inserted facing title page. Bibliography: leaves 124-135.