Medical Students' views of a career in Geriatric Medicine; Multi-Centre Qualitative Analysis

Medical students frequently have negative preconceptions of a career in Geriatric Medicine. In ta qualitative analysis of the free text from 789 response from Medical students in Scotland and Northern Ireland, we show that clinical attachment seffectively challenge negative student views and more positive statements about future careers in Geriatric Medicine emerged at the end of the attachment.

ASR emotional speech: Clarifying the issues and enhancing performance

There are multiple reasons to expect that recognising the verbal content of emotional speech will be a difficult problem, and recognition rates reported in the literature are in fact low. Including information about prosody improves recognition rate for emotions simulated by actors, but its relevance to the freer patterns of spontaneous speech is unproven. This paper shows that recognition rate for spontaneous emotionally coloured speech can be improved by using a language model based on increased representation of emotional utterances. The models are derived by adapting an already existing corpus, the British National Corpus (BNC). An emotional lexicon is used to identify emotionally coloured words, and sentences containing these words are recombined with the BNC to form a corpus with a raised proportion of emotional material. Using a language model based on that technique improves recognition rate by about 20%. (c) 2005 Elsevier Ltd. All rights reserved.

Does first aid have a place in the medical curriculum? A survey of medical students

Introduction: When a medical emergency occurs in the prehospital environment, there is an expectation from the general public for medical students to offer assistance with a similar level of competence as qualified doctors. However, the question is raised; do medical students have sufficient training in first aid skills to fulfil the role expected of them?

Prior to the publication of the latest version of Tomorrow’s Doctors by the UK General Medical Council, a student selected component (SSC) in first aid was delivered at the medical school in Queen’s University Belfast (QUB), Northern Ireland. The overwhelming popularity of this SSC prompted a desire to investigate and understand students’ experiences of first aid.

Aim: To identify first and second year medical students’ knowledge of, and attitudes towards, first aid and their expectations of the medical curriculum.

Methods: A questionnaire was delivered using TurningPoint Audience Response System® during the second semester of the 2008 - 2009 academic year to all first and second year medical students at QUB.

Results: Less than half of the students felt that they had a good level of first aid knowledge, a third would feel confident helping in an emergency and only 10% would be confident leading an emergency situation. The vast majority of students believed first aid is beneficial, that the general public expect medical students to have the knowledge to handle an emergency situation, and that a full first aid course should be included in the core medical curriculum at an early stage. They did not believe it should be a pre-requisite for medical school.

Conclusion: Only a small proportion believed their first aid knowledge adequate. An overwhelming proportion believed that first aid training is beneficial and that the public expect competency in managing emergencies. This study clearly demonstrates students’ need and desire for first aid training in the core medical curriculum at an early stage and to the highest training level possible.

Characteristics and Treatment of Medical Device Related Infections

Medical device related infections are becoming an increasing prevalent area of infectious disease. They can be attributed to a multitude of factors from an increasing elderly population with reduced immunological status to increasing microbial resistance and evolution. Of greatest significance is the failure of standard antimicrobial regimens to eradicate biomaterial-related infections due to the formation of microbial biofilms consisting of extracellular polymeric substances. Biofilms form and thrive at the abiotic device surface where nutrients are more concentrated and symbiotic colonies can be formed. The formation of a biofilm matrix occurs in a series of steps beginning with reversible attachment of bacteria to the surface of the substrate and terminating in dispersion of mature biofilm microcolonies that aim to colonise fresh surfaces high in nutrients. Mature biofilms can resist 10-1000 times the concentrations of standard antibiotic regimens that are required to kill genetically equivalent planktonic forms. The extent of the infection and the pathogen(s) present can be attributed to both the form and location of the device. It is important that preventative measures and treatment strategies relate to combating the causative microorganisms. Preventative measures include: the use of anti-infective biomaterials that can be coated or incorporated with standard or innovative antimicrobials; modified anti-adhesive medical devices; environmental sterilisation protocols and prophylactic drug therapy. Treatment of established infection may require removal of the device or if deemed possible the device may be salvageable through the initiation of antimicrobial therapy. The increasing spectre of antibiotic resistance and medical device related infections are a large and increasing burden on health care systems and the patient’s quality of life and long term prognosis. As an infectious disease it represents one of the most difficult challenges facing modern science and healthcare.

Creating a spontaneous conversational speech corpus

Speech recognition and language analysis of spontaneous speech arising in naturally spoken conversations are becoming the subject of much research. However, there is a shortage of spontaneous speech corpora that are freely available for academics. We therefore undertook the building of a natural conversation speech database, recording over 200 hours of conversations in English by over 600 local university students. With few exceptions, the students used their own cell phones from their own rooms or homes to speak to one another, and they were permitted to speak on any topic they chose. Although they knew that they were being recorded and that they would receive a small payment, their conversations in the corpus are probably very close to being natural and spontaneous. This paper describes a detailed case study of the problems we faced and the methods we used to make the recordings and control the collection of these social science data on a limited budget.

CLOSE—A Data-Driven Approach to Speech Separation

This paper studies single-channel speech separation, assuming unknown, arbitrary temporal dynamics for the speech signals to be separated. A data-driven approach is described, which matches each mixed speech segment against a composite training segment to separate the underlying clean speech segments. To advance the separation accuracy, the new approach seeks and separates the longest mixed speech segments with matching composite training segments. Lengthening the mixed speech segments to match reduces the uncertainty of the constituent training segments, and hence the error of separation. For convenience, we call the new approach Composition of Longest Segments, or CLOSE. The CLOSE method includes a data-driven approach to model long-range temporal dynamics of speech signals, and a statistical approach to identify the longest mixed speech segments with matching composite training segments. Experiments are conducted on the Wall Street Journal database, for separating mixtures of two simultaneous large-vocabulary speech utterances spoken by two different speakers. The results are evaluated using various objective and subjective measures, including the challenge of large-vocabulary continuous speech recognition. It is shown that the new separation approach leads to significant improvement in all these measures.