169 resultados para 147-895E


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Purpose: The purpose of this study was to improve the retention of primary healthcare (PHC) nurses through exploring and assessing their quality of work life (QWL) and turnover intention. Design and methods: A cross-sectional survey design was used in this study. Data were collected using a questionnaire comprising four sections (Brooks’ survey of Quality of Nursing Work Life [QNWL], Anticipated Turnover Intention, open-ended questions and demographic characteristics). A convenience sample was recruited from 143 PHC centres in Jazan, Saudi Arabia. A response rate of 87% (n = 508/585) was achieved. The SPSS v17 for Windows and NVivo 8 were used for analysis purposes. Procedures and tests used in this study to analyse the quantitative data were descriptive statistics, t-test, ANOVA, General Linear Model (GLM) univariate analysis, standard multiple regression, and hierarchical multiple regression. Qualitative data obtained from responses to the open-ended questions were analysed using the NVivo 8. Findings: Quantitative findings suggested that PHC nurses were dissatisfied with their work life. Respondents’ scores ranged between 45 and 218 (mean = 139.45), which is lower than the average total score on Brooks’ Survey (147). Major influencing factors were classified under four dimensions. First, work life/home life factors: unsuitable working hours, lack of facilities for nurses, inability to balance work with family needs and inadequacy of vacations’ policy. Second, work design factors: high workload, insufficient workforce numbers, lack of autonomy and undertaking many non-nursing tasks. Third, work context factors: management practices, lack of development opportunities, and inappropriate working environment in terms of the level of security, patient care supplies and unavailability of recreation room. Finally, work world factors: negative public image of nursing, and inadequate payment. More positively, nurses were notably satisfied with their co-workers. Conversely, 40.4% (n = 205) of the respondents indicated that they intended to leave their current employment. The relationships between QWL and demographic variables of gender, age, marital status, dependent children, dependent adults, nationality, ethnicity, nursing tenure, organisational tenure, positional tenure, and payment per month were significant (p < .05). The eta squared test for these demographics indicates a small to medium effect size of the variation in QWL scores. Using the GLM univariate analysis, education level was also significantly related to the QWL (p < .05). The relationships between turnover intention and demographic variables including gender, age, marital status, dependent children, education level, nursing tenure, organisational tenure, positional tenure, and payment per month were significant (p < .05). The eta squared test for these demographics indicates a small to moderate effect size of the variation in the turnover intention scores. Using the GLM univariate analysis, the dependent adults’ variable was also significantly related to turnover intention (p < .05). Turnover intention was significantly related to QWL. Using standard multiple regression, 26% of the variance in turnover intention was explained by the QWL F (4,491), 43.71, p < .001, with R² = .263. Further analysis using hierarchical multiple regression found that the total variance explained by the model as a whole (demographics and QWL) was 32.1%, F (17.433) = 12.04, p < .001. QWL explained an additional 19% of the variance in turnover intention, after controlling for demographic variables, R squared change =.19, F change (4, 433) = 30.190, p < .001. The work context variable makes the strongest unique contribution (-.387) to explain the turnover intention, followed by the work design dimension (-.112). The qualitative findings reaffirmed the quantitative findings in terms of QWL and turnover intention. However, the home life/work life and work world dimensions were of great important to both QWL and turnover intention. The qualitative findings revealed a number of new factors that were not included in the survey questionnaire. These included being away from family, lack of family support, social and cultural aspects, accommodation facilities, transportation, building and infrastructure of PHC, nature of work, job instability, privacy at work, patients and community, and distance between home and workplace. Conclusion: Creating and maintaining a healthy work life for PHC nurses is very important to improve their work satisfaction, reduce turnover, enhance productivity and improve nursing care outcomes. Improving these factors could lead to a higher QWL and increase retention rates and therefore reinforcing the stabilisation of the nursing workforce. Significance of the research: Many countries are examining strategies to attract and retain the health care workforce, particularly nurses. This study identified factors that influence the QWL of PHC nurses as well as their turnover intention. It also determined the significant relationship between QWL and turnover intention. In addition, the present study tested Brooks’ survey of QNWL on PHC nurses for the first time. The qualitative findings of this study revealed a number of new variables regarding QWL and turnover intention of PHC nurses. These variables could be used to improve current survey instruments or to develop new research surveys. The study findings could be also used to develop and appropriately implement plans to improve QWL. This may help to enhance the home and work environments of PHC nurses, improve individual and organisational performance, and increase nurses’ commitment. This study contributes to the existing body of research knowledge by presenting new data and findings from a different country and healthcare system. It is the first of its kind in Saudi Arabia, especially in the field of PHC. It has examined the relationship between QWL and turnover intention of PHC nurses for the first time using nursing instruments. The study also offers a fresh explanation (new framework) of the relationship between QWL and turnover intention among PHC nurses, which could be used or tested by researchers in other settings. Implications for further research: Review of the extant literature reveals little in-depth research on the PHC workforce, especially in terms of QWL and organisational turnover in developing countries. Further research is required to develop a QWL tool for PHC nurses, taking into consideration the findings of the current study along with the local culture. Moreover, the revised theoretical framework of the current study could be tested in further research in other regions, countries or healthcare systems in order to identify its ability to predict the level of PHC nurses’ QWL and their intention to leave. There is a need to conduct longitudinal research on PHC organisations to gain an in-depth understanding of the determents of and changes in QWL and turnover intention of PHC nurses at various points of time. An intervention study is required to improve QWL and retention among PHC nurses using the findings of the current study. This would help to assess the impact of such strategies on reducing turnover of PHC nurses. Focusing on the location of the current study, it would be valuable to conduct another study in five years’ time to examine the percentage of actual turnover among PHC nurses compared with the reported turnover intention in the current study. Further in-depth research would also be useful to assess the impact of the local culture on the perception of expatriate nurses towards their QWL and their turnover intention. A comparative study is required between PHC centres and hospitals as well as the public and private health sector agencies in terms of QWL and turnover intention of nursing personnel. Findings may differ from sector to sector according to variations in health systems, working environments and the case mix of patients.

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Adopting a model of job enrichment we report on a longitudinal case investigating the perceived impact of an Enterprise Resource Planning (ERP) system on user job design characteristics. Our results indicated that in the context of an ERP geared towards centralisation and standardisation the extent to which users perceived an increase or decrease in job enrichment was associated with aspects such as formal authority and the nature of their work role. Experienced operational employees proficient in the original legacy system perceived ERP system protocols to constrain their actions, limit training and increase dependence on others in the workflow. Conversely, managerial users reported a number of benefits relating to report availability, improved organisational transparency and increased overall job enrichment. These results supported our argument concerning the relationship between ERPs with a standardisation intent and positive job enrichment outcomes for managerial users and negative job-related outcomes for operational users.

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Introduction:  Smoking status in outpatients with chronic obstructive pulmonary disease (COPD) has been associated with a low body mass index (BMI) and reduced mid-arm muscle circumference (Cochrane & Afolabi, 2004). Individuals with COPD identified as malnourished have also been found to be twice as likely to die within 1 year compared to non-malnourished patients (Collins et al., 2010). Although malnutrition is both preventable and treatable, it is not clear what influence current smoking status, another modifiable risk factor, has on malnutrition risk. The current study aimed to establish the influence of smoking status on malnutrition risk and 1-year mortality in outpatients with COPD. Methods:  A prospective nutritional screening survey was carried out between July 2008 and May 2009 at a large teaching hospital (Southampton General Hospital) and a smaller community hospital within Hampshire (Lymington New Forest Hospital). In total, 424 outpatients with a diagnosis of COPD were routinely screened using the ‘Malnutrition Universal Screening Tool’, ‘MUST’ (Elia, 2003); 222 males, 202 females; mean (SD) age 73 (9.9) years; mean (SD) BMI 25.9 (6.4) kg m−2. Smoking status on the date of screening was obtained for 401 of the outpatients. Severity of COPD was assessed using the GOLD criteria, and social deprivation determined using the Index of Multiple Deprivation (Nobel et al., 2008). Results:  The overall prevalence of malnutrition (medium + high risk) was 22%, with 32% of current smokers at risk (who accounted for 19% of the total COPD population). In comparison, 19% of nonsmokers and ex-smokers were likely to be malnourished [odds ratio, 1.965; 95% confidence interval (CI), 1.133–3.394; P = 0.015]. Smoking status remained an independent risk factor for malnutrition even after adjustment for age, social deprivation and disease-severity (odds ratio, 2.048; 95% CI, 1.085–3.866; P = 0.027) using binary logistic regression. After adjusting for age, disease severity, social deprivation, smoking status, malnutrition remained a significant predictor of 1-year mortality [odds ratio (medium + high risk versus low risk), 2.161; 95% CI, 1.021–4.573; P = 0.044], whereas smoking status did not (odds ratio for smokers versus ex-smokers + nonsmokers was 1.968; 95% CI, 0.788–4.913; P = 0.147). Discussion:  This study highlights the potential importance of combined nutritional support and smoking cessation in order to treat malnutrition. The close association between smoking status and malnutrition risk in COPD suggests that smoking is an important consideration in the nutritional management of malnourished COPD outpatients. Conclusions:  Smoking status in COPD outpatients is a significant independent risk factor for malnutrition and a weaker (nonsignificant) predictor of 1-year mortality. Malnutrition significantly predicted 1 year mortality. References:  Cochrane, W.J. & Afolabi, O.A. (2004) Investigation into the nutritional status, dietary intake and smoking habits of patients with chronic obstructive pulmonary disease. J. Hum. Nutr. Diet.17, 3–11. Collins, P.F., Stratton, R.J., Kurukulaaratchym R., Warwick, H. Cawood, A.L. & Elia, M. (2010) ‘MUST’ predicts 1-year survival in outpatients with chronic obstructive pulmonary disease. Clin. Nutr.5, 17. Elia, M. (Ed) (2003) The ‘MUST’ Report. BAPEN. http://www.bapen.org.uk (accessed on March 30 2011). Nobel, M., McLennan, D., Wilkinson, K., Whitworth, A. & Barnes, H. (2008) The English Indices of Deprivation 2007. http://www.communities.gov.uk (accessed on March 30 2011).

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Mesenchymal stem/stromal cells (MSC) are rapidly becoming a leading candidate for use in tissue regeneration, with first generation of therapies being approved for use in orthopaedic repair applications. Capturing the full potential of MSC will likely require the development of novel in vitro culture techniques and devices. Herein we describe the development of a straightforward surface modification of an existing commercial product to enable the efficient study of three dimensional (3D) human bone marrow-derived MSC osteogenic differentiation. Hundreds of 3D microaggregates, of either 42 or 168 cells each, were cultured in osteogenic induction medium and their differentiation was compared with that occurring in traditional two dimensional (2D) monolayer cultures. Osteogenic gene expression and matrix composition was significantly enhanced in the 3D microaggregate cultures. Additionally, BMP-2 gene expression was significantly up-regulated in 3D cultures at day 3 and 7 by approximately 25- and 30-fold, respectively. The difference in BMP-2 gene expression between 2D and 3D cultures was negligible in the more mature day 14 osteogenic cultures. These data support the notion that BMP-2 autocrine signalling is up-regulated in 3D MSC cultures, enhancing osteogenic differentiation. This study provides both mechanistic insight into MSC differentiation, as well as a platform for the efficient generation of microtissue units for further investigation or use in tissue engineering applications.

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Effective, statistically robust sampling and surveillance strategies form an integral component of large agricultural industries such as the grains industry. Intensive in-storage sampling is essential for pest detection, Integrated Pest Management (IPM), to determine grain quality and to satisfy importing nation’s biosecurity concerns, while surveillance over broad geographic regions ensures that biosecurity risks can be excluded, monitored, eradicated or contained within an area. In the grains industry, a number of qualitative and quantitative methodologies for surveillance and in-storage sampling have been considered. Primarily, research has focussed on developing statistical methodologies for in storage sampling strategies concentrating on detection of pest insects within a grain bulk, however, the need for effective and statistically defensible surveillance strategies has also been recognised. Interestingly, although surveillance and in storage sampling have typically been considered independently, many techniques and concepts are common between the two fields of research. This review aims to consider the development of statistically based in storage sampling and surveillance strategies and to identify methods that may be useful for both surveillance and in storage sampling. We discuss the utility of new quantitative and qualitative approaches, such as Bayesian statistics, fault trees and more traditional probabilistic methods and show how these methods may be used in both surveillance and in storage sampling systems.

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Background Post traumatic stress disorder (PTSD) and depressive disorder are over represented in combat veterans. Veterans with both disorders have an increased risk of suicide. The nitric oxide synthase 1 adaptor protein (NOS1AP) gene, which modulates stress-evoked N-methyl-D-aspartate (NMDA) activity, was investigated in combat veterans. Methods A comprehensive genetic analysis of NOS1AP and its association with PTSD was investigated in Vietnam combat veterans with PTSD (n=121) and a group of healthy control individuals (n=237). PTSD patients were assessed for symptom severity and level of depression using the Mississippi Scale for Combat-Related PTSD and the Beck Depression Inventory-II (BDI). Results The G allele of NOS1AP SNP rs386231 was significantly associated with PTSD (p = 0.002). Analysis of variance revealed significant differences in BDI-II and Mississippi scores between genotypes for rs386231 with the GG genotype associated with increased severity of depression (p = 0.002 F = 6.839) and higher Mississippi Scale for Combat-Related PTSD scores (p = 0.033). Haplotype analysis revealed that the C/G haplotype (rs451275/rs386231) was significantly associated with PTSD (p = 0.001). Limitations The sample sizes in our study were not sufficient to detect SNP associations with very small effects. In addition the study was limited by its cross sectional design. Conclusions This is the first study reporting that a variant of the NOS1AP gene is associated with PTSD. Our data also suggest that a genetic variant in NOS1AP may increase the susceptibility to severe depression in patients with PTSD and increased risk for suicide.

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KPNA3 is a gene that has been linked to schizophrenia susceptibility. In this study we investigated the possible association between KPNA3 variation and schizophrenia. To investigate a wider role of KPNA3 across psychiatric disorders we also analysed major depression, PTSD, nicotine dependent, alcohol dependent and opiate dependent cohorts. Using a haplotype block-based gene-tagging approach we genotyped six KPNA3 single nucleotide polymorphisms (SNPs) in 157 schizophrenia patients, 121 post-traumatic stress disorder patients, 120 opiate dependent patients, 231 alcohol dependent patients, 147 nicotine dependent patients and 266 major depression patients. One SNP rs2273816 was found to be significantly associated with schizophrenia, opiate dependence and alcohol dependence at the genotype and allele level. Major depression was also associated with rs2273816 but only at the allele level. Our study suggests that KPNA3 may contribute to the genetic susceptibility to schizophrenia as well as other psychiatric disorders.

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Preventive Maintenance (PM) is often applied to improve the reliability of production lines. A Split System Approach (SSA) based methodology is presented to assist in making optimal PM decisions for serial production lines. The methodology treats a production line as a complex series system with multiple (imperfect) PM actions over multiple intervals. The conditional and overall reliability of the entire production line over these multiple PM intervals are hierarchically calculated using SSA, and provide a foundation for cost analysis. Both risk-related cost and maintenance-related cost are factored into the methodology as either deterministic or random variables. This SSA based methodology enables Asset Management (AM) decisions to be optimised considering a variety of factors including failure probability, failure cost, maintenance cost, PM performance, and the type of PM strategy. The application of this new methodology and an evaluation of the effects of these factors on PM decisions are demonstrated using an example. The results of this work show that the performance of a PM strategy can be measured by its Total Expected Cost Index (TECI). The optimal PM interval is dependent on TECI, PM performance and types of PM strategies. These factors are interrelated. Generally, it was found that a trade-off between reliability and the number of PM actions needs to be made so that one can minimise Total Expected Cost (TEC) for asset maintenance.

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This chapter is a tutorial that teaches you how to design extended finite state machine (EFSM) test models for a system that you want to test. EFSM models are more powerful and expressive than simple finite state machine (FSM) models, and are one of the most commonly used styles of models for model-based testing, especially for embedded systems. There are many languages and notations in use for writing EFSM models, but in this tutorial we write our EFSM models in the familiar Java programming language. To generate tests from these EFSM models we use ModelJUnit, which is an open-source tool that supports several stochastic test generation algorithms, and we also show how to write your own model-based testing tool. We show how EFSM models can be used for unit testing and system testing of embedded systems, and for offline testing as well as online testing.

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This article focuses on the evaluation of thesis supervision and highlights the vast range of problem areas presently documented as significant areas of concern for both graduate students and their supervisors. Additionally, the authors report on a study completed in 1995, which surveyed all Australian universities about current evaluative practices in postgraduate supervision. The conclusion of this study was that the conduct of such evaluations appears to be minimal and is primarily designed to obtain an indicator of the general “health” of a university's postgraduate supervision rather than to foster improved supervisory practices. As part of the same study, the authors conducted University faculty-based student and supervisor focus groups. Key issues emerging from these focus groups were: (1) the importance of relational aspects of supervision as the student communicates over the long term with one or more supervisors; (2) the importance of systematic feedback, monitoring, and evaluation to the supervisory process; and (3) the lack of strategies to facilitate this evaluative feedback process. On the basis of these findings, the authors designed evaluative strategies to facilitate regular ongoing feedback between students and supervisors.