Identification of core competencies for primary care of allergy patients using a modified Delphi technique.

BACKGROUND: The majority of allergy patients who seek medical advice are seen in primary care. In-service training of professionals in general practice is needed in order to increase knowledge among primary care clinicians about allergy. Therefore it is important to establish a consensus about what primary care professionals should be able to do, and what the public can expect. We sought to identify core competencies for good practice amongst primary care providers with respect to diagnosis and therapy of allergic diseases and to outline learning objectives for a postgraduate training programme in this field. METHODS: The study involved three rounds, involving a total of 43 expert panellists. In the first round, a panel was asked to indicate competencies (knowledge, diagnostics, therapy and communication) necessary for primary care providers. The second and third rounds were answered by primary care physicians (26) and nurses (10). A Likert scale 1-4 was applied in the second round and two choices ("agree"/"disagree") in the third round, with a criterion of 75% being adopted. RESULTS: The second round included 80 competencies and the third 50. The third round selected a consensus of 46 competencies defining nine learning outcomes for in-service medical training. CONCLUSIONS: The competencies in the field of allergy recommended in this study may serve as a reference of what can be expected from primary care providers

“I Try to be Modern” – Identity Formation Between Tradition and Modernity Among Young Women in Hanoi

Since 1986, the Vietnamese socialist state has gradually opened towards the global market. Subsequently, socialist modernity may increasingly be outrivaled by the individualistic culture associated with global capitalism which is now gaining ground in Vietnam, especially among the urban middle-class who can easily access it. Proceeding from a post-colonial feminist framework, this thesis aims to investigate how development and globalization affect identity formation in Vietnam. This issue is approached by looking at how young women are navigating between competing discourses, through exploring how their perceptions of the women’s role are influenced by constructions of “modernity” and “tradition”. The empirical analysis is founded upon semi-structured interviews with young unmarried and university educated women living in Hanoi. The study has a constructivist grounded theory approach, thus the empirical material has continuously been guiding the direction of the research. The findings show that the participants understand modernity as related to individualism, development and globalization. Simultaneously, tradition is understood as an obstacle to development, in line with colonial discourse. This may be considered problematic since the participants are identifying as both modern and traditional, hence regards one part of their identity as unsolicited within the globalized capitalist modernity. This notion illustrates that the colonial constructions which are enforced in contemporary development discourse are interfering with the participants’ understanding of their role and possibilities. However, identity formation between contrasting discourses may open a space for agency and resistance, as the women have the possibility to renegotiate their respective subject-positions through accessing a variety of discourses and thereby create new understandings of what “modernity” might be

Mental disorder labelling as an extralegal variable in mock jury deliberations

Previous research has shown that a number of characteristics of trial participants (extralegal variables) can and do influence juror’s judgements. This is of importance as only the legally relevant facts of the case should be considered during a trial. The present study investigates the influence of victim characteristics on the juror decision making process during deliberation and the judgements made about the victim, crime and defendant in a mock jury setting, as well as investigating mock juror gender differences. A representative sample of people eligible for jury duty in Western Australia viewed a video vignette depicting a trial, in which the mental disorder label (no label, schizophrenia, depression, intellectual disability) was varied. Deliberations were videotaped and subject to an analysis in conjunction with pre and post test questionnaire measuring victim characteristics. A 4x2x2 repeated measures ANOVA was used to analyse the data, in addition to the analysis of the deliberations. The qualitative findings suggest that mock jurors invested relatively much time in some mental disorder labels may function as extralegal variables. This inference is supported by the quantitative findings in this study. The mental disorder label assigned to the victim had an impact on mock jurors’ perception of the likeability, reliability and honesty of the victim, the responsibility for the crime and the guilt of the defendant, often interacting with mock juror gender and deliberation. However, no clear pattern of bias against or in favour of any specific victim could be discerned. There was slightly more evidence of a negative bias than a positive bias towards the no label and schizophrenia victims, while the opposite was true for the depression and intellectual disability victims

Machine Intelligence in Automated Performance Test Analysis

Software testing is a large part of development and especially important for projects that practice Continuous Integration. In order to reduce the burden of testing and make the process more efficient, as much as possible is automated. In this thesis, a design science approach is used to investigate how machine intelligence can be used to improve the automation of the analysis of non-functional testing. A prototype is created in order to demonstrate the ability of machine intelligence methods to provide useful information about the relationships between different test cases and their histories. This prototype was found to be fairly accurate in its predictions of test results, could identify most related degradations across test cases, and was positively received by the testers. Based on the results of this thesis, machine intelligence was found to have great potential in dealing with the large amount of data created during testing