Reducing patient mortality in hospitals:the role of human resource management

Developing effective health care organizations is increasingly complex as a result of demographic changes, globalization, and developments in medicine. This study examines the potential contribution of organizational behavior theory and research by investigating the relationship between systems of human resource management (HRM) practices and effectiveness of patient care in hospitals. Relatively little research has been conducted to explore these issues in health care settings. In a sample of 52 hospitals in England, we examine the relationship between the HRM system and health care outcome. Specifically, we study the association between high performance HRM policies and practices and standardized patient mortality rates. The research reveals that, after controlling for prior mortality and other potentially confounding factors such as the ratio of doctors to patients, greater use of a complementary set of HRM practices has a statistically and practically significant relationship with patient mortality. The findings suggest that managers and policy makers should focus sharply on improving the functioning of relevant HR management systems in health care organizations as one important means by which to improve patient care. Copyright © 2006 John Wiley & Sons, Ltd.

The role of prior exposure on the capture of attention by items in working memory

The Biased Competition Model (BCM) suggests both top-down and bottom-up biases operate on selective attention (e.g., Desimone & Duncan, 1995). It has been suggested that top-down control signals may arise from working memory. In support, Downing (2000) found faster responses to probes presented in the location of stimuli held vs. not held in working memory. Soto, Heinke, Humphreys, and Blanco (2005) showed the involuntary nature of this effect and that shared features between stimuli were sufficient to attract attention. Here we show that stimuli held in working memory had an influence on the deployment of attentional resources even when: (1) It was detrimental to the task, (2) there was equal prior exposure, and (3) there was no bottom-up priming. These results provide further support for involuntary top-down guidance of attention from working memory and the basic tenets of the BCM, but further discredit the notion that bottom-up priming is necessary for the effect to occur.

'I like this interview; I get cakes and cats!':the effect of prior relationships on interview talk

Research interviews are a form of interaction jointly constructed by the interviewer and interviewee, what Silverman (2001: 104) calls 'interview-as-local-accomplishment'. From this perspective, interviews are an interpretative practice in which what is said is inextricably tied to where it is said, how it is said and, importantly, to whom it is said (Holstein and Gubrium, 2004). The relationship between interviewer and interviewee, then, is fundamental in research interviews. But what happens when the relationship between interviewer and interviewee is not only that of researcher-informant but also involves other roles such as colleague and friend? In this article we will show how prior relationships are invoked and made relevant by both parties during educational research interviews and how these prior relationships therefore contribute to the 'generation' (Baker, 2004: 163) of interview data. © 2010 The Author(s).

Web based expert elicitation of uncertainties in environmental model inputs

When constructing and using environmental models, it is typical that many of the inputs to the models will not be known perfectly. In some cases, it will be possible to make observations, or occasionally physics-based uncertainty propagation, to ascertain the uncertainty on these inputs. However, such observations are often either not available or even possible, and another approach to characterising the uncertainty on the inputs must be sought. Even when observations are available, if the analysis is being carried out within a Bayesian framework then prior distributions will have to be specified. One option for gathering or at least estimating this information is to employ expert elicitation. Expert elicitation is well studied within statistics and psychology and involves the assessment of the beliefs of a group of experts about an uncertain quantity, (for example an input / parameter within a model), typically in terms of obtaining a probability distribution. One of the challenges in expert elicitation is to minimise the biases that might enter into the judgements made by the individual experts, and then to come to a consensus decision within the group of experts. Effort is made in the elicitation exercise to prevent biases clouding the judgements through well-devised questioning schemes. It is also important that, when reaching a consensus, the experts are exposed to the knowledge of the others in the group. Within the FP7 UncertWeb project (http://www.uncertweb.org/), there is a requirement to build a Webbased tool for expert elicitation. In this paper, we discuss some of the issues of building a Web-based elicitation system - both the technological aspects and the statistical and scientific issues. In particular, we demonstrate two tools: a Web-based system for the elicitation of continuous random variables and a system designed to elicit uncertainty about categorical random variables in the setting of landcover classification uncertainty. The first of these examples is a generic tool developed to elicit uncertainty about univariate continuous random variables. It is designed to be used within an application context and extends the existing SHELF method, adding a web interface and access to metadata. The tool is developed so that it can be readily integrated with environmental models exposed as web services. The second example was developed for the TREES-3 initiative which monitors tropical landcover change through ground-truthing at confluence points. It allows experts to validate the accuracy of automated landcover classifications using site-specific imagery and local knowledge. Experts may provide uncertainty information at various levels: from a general rating of their confidence in a site validation to a numerical ranking of the possible landcover types within a segment. A key challenge in the web based setting is the design of the user interface and the method of interacting between the problem owner and the problem experts. We show the workflow of the elicitation tool, and show how we can represent the final elicited distributions and confusion matrices using UncertML, ready for integration into uncertainty enabled workflows.We also show how the metadata associated with the elicitation exercise is captured and can be referenced from the elicited result, providing crucial lineage information and thus traceability in the decision making process.

Data visualisation and exploration with prior knowledge

Visualising data for exploratory analysis is a major challenge in many applications. Visualisation allows scientists to gain insight into the structure and distribution of the data, for example finding common patterns and relationships between samples as well as variables. Typically, visualisation methods like principal component analysis and multi-dimensional scaling are employed. These methods are favoured because of their simplicity, but they cannot cope with missing data and it is difficult to incorporate prior knowledge about properties of the variable space into the analysis; this is particularly important in the high-dimensional, sparse datasets typical in geochemistry. In this paper we show how to utilise a block-structured correlation matrix using a modification of a well known non-linear probabilistic visualisation model, the Generative Topographic Mapping (GTM), which can cope with missing data. The block structure supports direct modelling of strongly correlated variables. We show that including prior structural information it is possible to improve both the data visualisation and the model fit. These benefits are demonstrated on artificial data as well as a real geochemical dataset used for oil exploration, where the proposed modifications improved the missing data imputation results by 3 to 13%.

Placement year academic benefit revisited:effects of demographics, prior achievement and degree programme

Investigations of whether students taking undergraduate work placements show greater academic improvement than those who do not have shown inconsistent results. In most studies, sample sizes have been relatively small and few studies have taken into account pre-existing student differences.Here data from over 6000 students at one university over six cohorts and a range of programmes are analysed. Consistent academic benefit from placement experience, regardless of ethnicity, gender, socioeconomic background and subject is shown. However the impact of demographic factors on both achievement and on the probability of taking a placement suggests that future research should take these factors into account. The role of placements in promoting employability is contextualised as a secondary benefit to the primary goal of educating the mind in the Newman (1852) tradition. Possible causes of, and further research into, the improved academic performance identified are discussed.

Prior action execution has no effect on corticospinal facilitation during action observation

Transcranial magnetic stimulation (TMS) has been used widely in research investigating corticospinal (CS) excitability during action observation. Generally, this work has shown that observation of an action performed by others, in the absence of overt movement, modulates the excitability of the CS pathway in humans. Despite the extent of the literature exploring action observation effects, however, there has been little research to date that has compared observation with the combination of observation and execution directly. Here, we report a single-pulse TMS study that investigated whether CS excitability during action observation was modulated by actions performed by the observers prior to viewing a ball pinching action. The results showed that CS excitability during action observation increased when compared to observation of a static hand, but that there was no additional motor facilitation when participants performed the same action prior to observing it. Our findings highlight the importance of action observation and its consequences on the CS system, whilst also illustrating the limited effect of prior action execution on the CS pathway for a simple action task.

Efficacy of Adding 2% (w/v) Chlorhexidine Gluconate to 70% (v/v) Isopropyl Alcohol for Skin Disinfection Prior to Peripheral Venous Cannulation

We undertook a clinical trial to compare the efficacy of 2% (w/v) chlorhexidine gluconate in 70% (v/v) isopropyl alcohol with the efficacy of 70% (v/v) isopropyl alcohol alone for skin disinfection to prevent peripheral venous catheter colonization and contamination. We found that the addition of 2% chlorhexidine gluconate reduced the number of peripheral venous catheters that were colonized or contaminated. © 2008 by The Society for Healthcare Epidemiology of America. All rights reserved.

Incorporating sentiment prior knowledge for weakly supervised sentiment analysis

This article presents two novel approaches for incorporating sentiment prior knowledge into the topic model for weakly supervised sentiment analysis where sentiment labels are considered as topics. One is by modifying the Dirichlet prior for topic-word distribution (LDA-DP), the other is by augmenting the model objective function through adding terms that express preferences on expectations of sentiment labels of the lexicon words using generalized expectation criteria (LDA-GE). We conducted extensive experiments on English movie review data and multi-domain sentiment dataset as well as Chinese product reviews about mobile phones, digital cameras, MP3 players, and monitors. The results show that while both LDA-DP and LDAGE perform comparably to existing weakly supervised sentiment classification algorithms, they are much simpler and computationally efficient, rendering themmore suitable for online and real-time sentiment classification on the Web. We observed that LDA-GE is more effective than LDA-DP, suggesting that it should be preferred when considering employing the topic model for sentiment analysis. Moreover, both models are able to extract highly domain-salient polarity words from text.

The effects of prior moves on job relocation stress

This study examines the relationship between the number of prior moves, time living in an area and psychological reactions of employees undergoing job relocation. Relocating employees from a single organization completed questionnaires on average six weeks before and 10 weeks after their move. Results show that the greater the number of prior moves the lower was the reported stress following the move. However, the relationship between number of prior moves and well-being also followed a quadratic trend such that those with few and those with many prior moves reported the greatest stress. Furthermore, the longer the relocator had lived in the area prior to moving, the greater was the general stress and the job-related anxiety and depression following the move.

Impact of suspected food allergy on emotional distress and family life of parents prior to allergy diagnosis

Background: Food allergy is associated with psychological distress in both child and parent. It is unknown whether parental distress is present prior to clinical diagnosis or whether experiences at clinic can reduce any distress present. This study aimed to assess anxiety and depression in parents and the impact of suspected food allergy on the lives of families before and after a visit to an allergy clinic. Methods: One hundred and twenty-four parents visiting an allergy clinic for the first time to have their child assessed for food allergy completed a study-specific questionnaire and the Hospital Anxiety and Depression Scale; 50 parents completed these 4-6 wk later in their own home. Results: Most parents (86.4%) reported suspected food allergy had an impact on their family life prior to clinic attendance; 76% had made changes to their child's diet. 32.5% of parents had mild-to-severe anxiety before their clinic visit; 17.5% had mild-to-moderate depression. Post-clinic, 40% had mild-to-severe anxiety; 13.1% had mild-to-moderate depression. There were no significant differences in anxiety (p = 0.34) or depression scores (p = 0.09) before and after the clinic visit. Conclusions: Anxiety and depression is present in a small proportion of parents prior to diagnosis of food allergy in their child and this does not reduce in the short term after the clinic visit. Identification of parents at risk of suffering from distress is needed and ways in which we communicate allergy information before and at clinic should be investigated to see if we can reduce distress. © 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Emotions and a Prior Knowledge Representation in Artificial General Intelligence

In this paper a prior knowledge representation for Artificial General Intelligence is proposed based on fuzzy rules using linguistic variables. These linguistic variables may be produced by neural network. Rules may be used for generation of basic emotions – positive and negative, which influence on planning and execution of behavior. The representation of Three Laws of Robotics as such prior knowledge is suggested as highest level of motivation in AGI.

Observation of Matthew effects in Sina Weibo microblogger

This paper researches on Matthew Effect in Sina Weibo microblogger. We choose the microblogs in the ranking list of Hot Microblog App in Sina Weibo microblogger as target of our study. The differences of repost number of microblogs in the ranking list between before and after the time when it enter the ranking list of Hot Microblog app are analyzed. And we compare the spread features of the microblogs in the ranking list with those hot microblogs not in the list and those ordinary microblogs of users who have some microblog in the ranking list before. Our study proves the existence of Matthew Effect in social network. © 2013 IEEE.

Predicting posttraumatic stress reactions in children prior to traumatic exposure

The present study examined the relations among previously identified risk and protective variables associated with traumatic exposure and evaluated a model of resilience to traumatic events among Latino youth prior to traumatic exposure using structural equation modeling. Model tests were pursued in the context of Full Information Maximum Likelihood (FIML) methods as implemented in Mplus. The model evaluated the role of the following variables: (a) intervening life events; (b) child characteristics; (c) social support from significant others; and (d) children's coping. Data were collected from 181 Latino youth (M age = 9.22, SD = 1.38; 49.0% female) participants. Data analyses revealed that children's perceived available social support and use of coping strategies predicted low state anxiety following exposure to cues of disaster. Life events and preexisting depression symptoms did not significantly predict social support and coping, whereas preexisting anxiety was a significant predictor of perceived social support. This study represents an important initial step towards establishing and empirically evaluating a resilience model. Implications for preparedness interventions and a framework for the etiology of resilient reactions to disaster exposure are discussed.