3,448 research outputs found

    The biochemical, physiological, and metabolic evaluation of human subjects wearing pressure suits and on a diet of precooked freeze dehydrated foods

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    Biochemical, physiological and metabolic evaluation of human subjects wearing pressure suits and on diet of precooked frozen dehydrated food

    Biochemical and physiological evaluation of human subjects in a life support systems evaluator

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    Biochemical and physiological evaluation of human nutritional requirements under simulated aerospace condition

    Boosting clinical performance: The impact of enhanced final year placements.

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    BACKGROUND: This study follows on from a study that investigated how to develop effective final year medical student assistantship placements, using multidisciplinary clinical teams in planning and delivery. AIMS: This study assessed the effects on objective structured clinical examination (OSCE) performance of the in-course enhanced "super-assistantship" placement introduced to a randomly selected sample of 2013-14 final year medical students at Leeds medical school. METHODS: Quantitative data analysis was used to compare the global grades of OSCE stations between students who undertook this placement against those who did not. RESULTS: There was a small overall improvement in the "super-assistantship" student scores across the whole assessment (effect size = 0.085). "Pre-op Capacity", "Admissions Prescribing" and "Hip Pain" stations had small-medium effect sizes (0.226, 0.215, and 0.214) in favor of the intervention group. Other stations had small effect sizes (0.107-0.191), mostly in favor of the intervention group. CONCLUSIONS: The "super-assistantship" experience characterized by increasing student responsibility on placement can help to improve competence and confidence in clinical decision-making "in a simulated environment". The clinical environment and multidisciplinary team must be ready and supported to provide these opportunities effectively. Further in-course opportunities for increasing final year student responsibility should be developed

    The biochemical, physiological, and metabolic evaluation of human subjects in a life support systems evaluator and on a liquid food diet Final report, 12 Jun. 1964 - 23 Feb. 1965

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    Biochemical, physiological, and metabolic analysis of subjects in life support system on liquid food diets during space environment simulatio

    Mapping maternity services in Australia: Location, classification and services

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    Objective. To describe maternity services available to Australian women and, in particular, the location, classification of services and support services available. Design. A descriptive study was conducted using an online survey that was emailed to eligible hospitals. Inclusion criteria for the study included public and private maternity units with greater than 50 births per year. In total, 278 maternity units were identified. Units were asked to classify their level of acuity (Levels 26). Results. A total of 150 (53%) maternity units responded. Those who responded were reasonably similar to those who did not respond, and were representative of Australian maternity units. Almost three-quarters of respondents were from public maternity units and almost 70% defined themselves as being in a rural or remote location. Maternity units with higher birth rates were more likely to classify themselves as providing higher acuity services, that is, Levels 5 and 6. Private maternity units were more likely to have higher acuity classifications. Interventions such as induction of labour, either using an artificial rupture of membranes (ARM) and oxytocin infusion or with prostaglandins, were common across most units. Although electronic fetal monitoring (EFM) was also widely available, access to fetal scalp pH monitoring was low. Conclusion. Maternity service provision varies across the country and is defined predominately by location and annual birth rate. What is known about the topic? In 2007, over 99% of the 289496 women who gave birth in Australia did so in a hospital. It is estimated that there are more than 300 maternity units in the country, ranging from large tertiary referral centres in major cities to smaller maternity units in rural towns, some of which only provide postnatal care with the woman giving birth at a larger facility. Geographical location, population and ability to attract a maternity workforce determine the number of maternity units within a region, although the means of determining the number of maternity units within a region is often unclear. In recent years, a large number of small maternity units have closed, particularly in rural areas, often due to difficulties securing an adequate workforce, particularly midwives and general practitioner obstetricians. There is a lack of understanding about the nature of maternity service provision in Australia and considerable differences across states and territories. What does this paper add? This paper provides a description of the geographic distribution and level of maternity services, the demand on services, the available obstetric interventions, the level of staffing (paediatric and anaesthetic) and support services available and the private and public mix of maternity units. The paper also provides an exploration of the different interventions and discusses whether these are appropriate, given the level of acuity and access to emergency Caesarean section services. What are the implications for practitioners? This study provides useful information particularly for policy-makers, managers and practitioners. This is at a time when considerable maternity reform is underway and changes at a broader level to the health system are planned. Understanding the nature of maternity services is critical to this debate and ongoing planning decisions. © 2011 AHHA

    Quantifying error in OSCE standard setting for varying cohort sizes: A resampling approach to measuring assessment quality

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    Background: The use of the borderline regression method (BRM) is a widely accepted standard setting method for OSCEs. However, it is unclear whether this method is appropriate for use with small cohorts (e.g. specialist post-graduate examinations). Aims and methods: This work uses an innovative application of resampling methods applied to four pre-existing OSCE data sets (number of stations between 17 and 21) from two institutions to investigate how the robustness of the BRM changes as the cohort size varies. Using a variety of metrics, the ‘quality’ of an OSCE is evaluated for cohorts of approximately n=300 down to n=15. Estimates of the standard error in station-level and overall pass marks, R2 coefficient, and Cronbach’s alpha are all calculated as cohort size varies. Results and conclusion: For larger cohorts (n>200), the standard error in the overall pass mark is small (less than 0.5%), and for individual stations is of the order of 1-2%. These errors grow as the sample size reduces, with cohorts of less than 50 candidates showing unacceptably large standard error. Alpha and R2 also become unstable for small cohorts. The resampling methodology is shown to be robust and has the potential to be more widely applied in standard setting and medical assessment quality assurance and research
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