4 resultados para Dropouts

em QUB Research Portal - Research Directory and Institutional Repository for Queen's University Belfast


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Inhibition of histone deacetylases may be an important target in patients with myeloproliferative neoplasms. This investigator-initiated, non-randomized, open-label phase II multi-centre study included 63 patients (19 essential thrombocythaemia, 44 polycythaemia vera) from 15 centres. The primary objective was to evaluate if vorinostat was followed by a decline in clonal myeloproliferation as defined by European Leukaemia Net. Thirty patients (48%) completed the intervention period (24 weeks of therapy). An intention-to-treat response rate of 35% was identified. Pruritus was resolved [19% to 0% (P = 0·06)] and the prevalence of splenomegaly was lowered from 50% to 27% (P = 0·03). Sixty-five per cent of the patients experienced a decrease in JAK2 V617F allele burden (P = 0·006). Thirty-three patients (52% of patients) discontinued study drug before end of intervention due to adverse events (28 patients) or lack of response (5 patients). In conclusion, vorinostat showed effectiveness by normalizing elevated leucocyte and platelet counts, resolving pruritus and significantly reducing splenomegaly. However, vorinostat was associated with significant side effects resulting in a high discontinuation rate. A lower dose of vorinostat in combination with conventional and/or novel targeted therapies may be warranted in future studies.

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The current worldwide nursing shortage and high attrition of nursing students remain a challenge for the nursing profession. The aim of this paper was to investigate how key psychological attributes and constructions differentiate between completers and non-completers of nursing education. A questionnaire including measures of gender role identity and perceived gender appropriateness of careers was administered to 384 students early in the first year of the course. At the end of the programme attrition rates were obtained. The findings indicate that males were more likely to leave the course than females. Furthermore, those who completed the course tended to view nursing as more appropriate for women, in contrast to the non-completers who had less gender typed views. The female-dominated nature of nursing, prevalent stereotypes and gender bias inherent in nursing education seem to make this an uncomfortable place for males and those with less gendered typed views. Whilst it is acknowledged that attrition is undoubtedly a complex issue with many contributing factors, the nursing profession need to take steps to address this bias to ensure their profession is open equally to both female and male recruits.

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Aim: This paper is a report of a study to examine the role of personality and self-efficacy in predicting academic performance and attrition in nursing students.

Background: Despite a considerable amount of research investigating attrition in nursing students and new nurses, concerns remain. This particular issue highlights the need for a more effective selection process whereby those selected are more likely to complete their preregistration programme successfully, and remain employed as Registered Nurses.

Method: A longitudinal design was adopted. A questionnaire, which included measures of personality and occupational and academic self-efficacy, was administered to 384 students early in the first year of the study. At the end of the programme, final marks and attrition rates were obtained from university records for a total of 350 students. The data were collected from 1999 to 2002.

Findings: Individuals who scored higher on a psychoticism scale were more likely to withdraw from the programme. Occupational self-efficacy was revealed to be a statistically significant predictor of final mark obtained, in that those with higher self-efficacy beliefs were more likely to achieve better final marks. Extraversion was also shown to negatively predict academic performance in that those with higher extraversion scores were more likely to achieve lower marks.

Conclusion: More research is needed to explore the attributes of successful nursing students and the potential contribution of psychological profiling to a more effective selection process.

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In this brief, a hybrid filter algorithm is developed to deal with the state estimation (SE) problem for power systems by taking into account the impact from the phasor measurement units (PMUs). Our aim is to include PMU measurements when designing the dynamic state estimators for power systems with traditional measurements. Also, as data dropouts inevitably occur in the transmission channels of traditional measurements from the meters to the control center, the missing measurement phenomenon is also tackled in the state estimator design. In the framework of extended Kalman filter (EKF) algorithm, the PMU measurements are treated as inequality constraints on the states with the aid of the statistical criterion, and then the addressed SE problem becomes a constrained optimization one based on the probability-maximization method. The resulting constrained optimization problem is then solved using the particle swarm optimization algorithm together with the penalty function approach. The proposed algorithm is applied to estimate the states of the power systems with both traditional and PMU measurements in the presence of probabilistic data missing phenomenon. Extensive simulations are carried out on the IEEE 14-bus test system and it is shown that the proposed algorithm gives much improved estimation performances over the traditional EKF method.