The effect of overweight/obesity on cognitive function in euthymic individuals with bipolar disorder

Background. - Persistent impairment in cognitive function has been described in euthymic individuals with bipolar disorder. Collective work indicates that obesity is associated with reduced cognitive function in otherwise healthy individuals. This sub-group post-hoc analysis preliminarily explores and examines the association between overweight/obesity and cognitive function in euthymic individuals with bipolar disorder. Methods. - Euthymic adults with DSM-IV-TR-defined bipolar I or II disorder were enrolled. Subjects included in this post-hoc analysis (n = 67) were divided into two groups (normal weight, body mass index [BMI] of 18.5-24.9 kg/m(2); overweight/obese, BMI >= 25.0 kg/m(2)). Demographic and clinical information were obtained at screening. At baseline, study participants completed a comprehensive cognitive battery to assess premorbid IQ, verbal learning and memory, attention and psychomotor processing speed, executive function, general intellectual abilities, recollection and habit memory, as well as self-perceptions of cognitive failures. Results. - BMI was negatively correlated with attention and psychomotor processing speed as measured by the Digit Symbol Substitution Test (P < 0.01). Overweight and obese bipolar individuals had a significantly lower score on the Verbal Fluency Test when compared to normal weight subjects (P < 0.05). For all other measures of cognitive function, non-significant trends suggesting a negative association with BMI were observed, with the exception of measures of executive function (i.e. Trail Making Test B) and recollection memory (i.e. process-dissociation task). Conclusion. - Notwithstanding the post-hoc methodology and relatively small sample size, the results of this study suggest a possible negative effect of overweight/obesity on cognitive function in euthymic individuals with bipolar disorder. Taken together, these data provide the impetus for more rigorous evaluation of the mediational role of overweight/obesity (and other medical co-morbidity) on cognitive function in psychiatric populations. (C) 2011 Elsevier Masson SAS. All rights reserved.

The Role of Consciousness in Memory

Conscious events interact with memory systems in learning, rehearsal and retrieval (Ebbinghaus 1885/1964; Tulving 1985). Here we present hypotheses that arise from the IDA computional model (Franklin, Kelemen and McCauley 1998; Franklin 2001b) of global workspace theory (Baars 1988, 2002). Our primary tool for this exploration is a flexible cognitive cycle employed by the IDA computational model and hypothesized to be a basic element of human cognitive processing. Since cognitive cycles are hypothesized to occur five to ten times a second and include interaction between conscious contents and several of the memory systems, they provide the means for an exceptionally fine-grained analysis of various cognitive tasks. We apply this tool to the small effect size of subliminal learning compared to supraliminal learning, to process dissociation, to implicit learning, to recognition vs. recall, and to the availability heuristic in recall. The IDA model elucidates the role of consciousness in the updating of perceptual memory, transient episodic memory, and procedural memory. In most cases, memory is hypothesized to interact with conscious events for its normal functioning. The methodology of the paper is unusual in that the hypotheses and explanations presented are derived from an empirically based, but broad and qualitative computational model of human cognition.

An examination of learning processes during critical incident training: Implications for the development of adaptable trainees

Three experiments are reported that examined the process by which trainees learn decision-making skills during a critical incident training program. Formal theories of category learning were used to identify two processes that may be responsible for the acquisition of decision-making skills: rule learning and exemplar learning. Experiments I and 2 used the process dissociation procedure (L. L. Jacoby, 1998) to evaluate the contribution of these processes to performance. The results suggest that trainees used a mixture of rule and exemplar learning. Furthermore, these learning processes were influenced by different aspects of training structure and design. The goal of Experiment 3 was to develop training techniques that enable trainees to use a rule adaptively. Trainees were tested on cases that represented exceptions to the rule. Unexpectedly, the results suggest that providing general instruction regarding the kinds of conditions in which a decision rule does not apply caused them to fixate on the specific conditions mentioned and impaired their ability to identify other conditions in which the rule might not apply. The theoretical, methodological, and practical implications of the results are discussed.

Information system planning in drug service:a case study

The development of an information system in Caribbean public sector organisations is usually seen as a matter of installing hardware and software according to a directive from senior management, without much planning. This causes huge investment in procuring hardware and software without improving overall system performance. Increasingly, Caribbean organisations are looking for assurances on information system performance before making investment decisions not only to satisfy the funding agencies, but also to be competitive in this dynamic and global business world. This study demonstrates an information system planning approach using a process-reengineering framework. Firstly, the stakeholders for the business functions are identified along with their relationships and requirements. Secondly, process reengineering is carried out to develop the system requirements. Accordingly, information technology is selected through detailed system requirement analysis. Thirdly, cost-benefit analysis, identification of critical success factors and risk analysis are carried out to strengthen the selection. The entire methodology has been demonstrated through an information system project in the Barbados drug service, a public sector organisation in the Caribbean.

Robust automatic mapping algorithms in a network monitoring scenario

Automatically generating maps of a measured variable of interest can be problematic. In this work we focus on the monitoring network context where observations are collected and reported by a network of sensors, and are then transformed into interpolated maps for use in decision making. Using traditional geostatistical methods, estimating the covariance structure of data collected in an emergency situation can be difficult. Variogram determination, whether by method-of-moment estimators or by maximum likelihood, is very sensitive to extreme values. Even when a monitoring network is in a routine mode of operation, sensors can sporadically malfunction and report extreme values. If this extreme data destabilises the model, causing the covariance structure of the observed data to be incorrectly estimated, the generated maps will be of little value, and the uncertainty estimates in particular will be misleading. Marchant and Lark [2007] propose a REML estimator for the covariance, which is shown to work on small data sets with a manual selection of the damping parameter in the robust likelihood. We show how this can be extended to allow treatment of large data sets together with an automated approach to all parameter estimation. The projected process kriging framework of Ingram et al. [2007] is extended to allow the use of robust likelihood functions, including the two component Gaussian and the Huber function. We show how our algorithm is further refined to reduce the computational complexity while at the same time minimising any loss of information. To show the benefits of this method, we use data collected from radiation monitoring networks across Europe. We compare our results to those obtained from traditional kriging methodologies and include comparisons with Box-Cox transformations of the data. We discuss the issue of whether to treat or ignore extreme values, making the distinction between the robust methods which ignore outliers and transformation methods which treat them as part of the (transformed) process. Using a case study, based on an extreme radiological events over a large area, we show how radiation data collected from monitoring networks can be analysed automatically and then used to generate reliable maps to inform decision making. We show the limitations of the methods and discuss potential extensions to remedy these.

Illusions of team working in health care

Purpose: The ubiquity and value of teams in healthcare are well acknowledged. However, in practice, healthcare teams vary dramatically in their structures and effectiveness in ways that can damage team processes and patient outcomes. The aim of this paper is to highlight these characteristics and to extrapolate several important aspects of teamwork that have a powerful impact on team effectiveness across healthcare contexts. Design/methodology/approach: The paper draws upon the literature from health services management and organisational behaviour to provide an overview of the current science of healthcare teams. Findings: Underpinned by the input-process-output framework of team effectiveness, team composition, team task, and organisational support are viewed as critical inputs that influence key team processes including team objectives, leadership and reflexivity, which in turn impact staff and patient outcomes. Team training interventions and care pathways can facilitate more effective interdisciplinary teamwork. Originality/value: The paper argues that the prevalence of the term "team" in healthcare makes the synthesis and advancement of the scientific understanding of healthcare teams a challenge. Future research therefore needs to better define the fundamental characteristics of teams in studies in order to ensure that findings based on real teams, rather than pseudo-like groups, are accumulated. © Emerald Group Publishing Limited.

Evaluating Applicability of E-Service Quality in Online Hotel Bookings

This study evaluates applicability of E-service quality measurements in the context of online hotel bookings. Data was collected from an online survey of undergraduate college students at two universities in the United States. The Transaction Process-based Framework (eTransQual) conceptualized by Bauer et al. (2006) was adapted, and the dimensionality of e-service quality was identified. The study identified process/reliability as the most important factor influencing overall quality of booking websites.

Proportion dominance in valuing lives: The role of deliberative thinking

Proportion responding (PR) is the preference for proportionally higher gains, such that the same absolute quantity is valued more as the reference group decreases. This research investigated this kind of proportion PR in decisions about saving lives (e.g., saving 10/10 lives is preferred to saving 10/100 lives). The results of two studies suggest that PR does not stem from an overall tendency to choose higher proportions, but rather from faulty deliberative reasoning. In particular, people who display PR are less likely to engage in deliberative reflection as measured by response time, the Process Dissociation Procedure, the Cognitive Reflection Test, a numeracy test, and a task assessing denominator neglect. This association between faulty deliberation and PR was observed only when choosing the highest proportion was non-normative because it came at the expense of absolute gains (e.g., saving 10/10 lives is preferred to saving 11/100 lives). These results help to make sense of discrepant findings in previous research, pertaining to how PR relates to biased reasoning and decision making.

Analytic and heuristic processes in the detection and resolution of conflict

Previous research with the ratio-bias task found larger response latencies for conflict trials where the heuristic- and analytic-based responses are assumed to be in opposition (e.g., choosing between 1/10 and 9/100 ratios of success) when compared to no-conflict trials where both processes converge on the same response (e.g., choosing between 1/10 and 11/100). This pattern is consistent with parallel dualprocess models, which assume that there is effective, rather than lax, monitoring of the output of heuristic processing. It is, however, unclear why conflict resolution sometimes fails. Ratio-biased choices may increase because of a decline in analytical reasoning (leaving heuristic-based responses unopposed) or to a rise in heuristic processing (making it more difficult for analytic processes to override the heuristic preferences). Using the process-dissociation procedure, we found that instructions to respond logically and response speed affected analytic (controlled) processing (C), leaving heuristic processing (H) unchanged, whereas the intuitive preference for large nominators (as assessed by responses to equal ratio trials) affected H but not C. These findings create new challenges to the debate between dual-process and singleprocess accounts, which are discussed.

An empirical framework for studying desistance as a process

Recent reviews of the desistance literature have advocated studying desistance as a process, yet current empirical methods continue to measure desistance as a discrete state. In this paper, we propose a framework for empirical research that recognizes desistance as a developmental process. This approach focuses on changes in the offending rare rather than on offending itself We describe a statistical model to implement this approach and provide an empirical example. We conclude with several suggestions for future research endeavors that arise from our conceptualization of desistance.

Customer Lifetime Value: a framework for application in the insurance industry - Building a Business Process to Generate and Maintain an Automatic Estimation Agent

Research Project submited as partial fulfilment for the Master Degree in Statistics and Information Management

Step towards multiplatform framework for supporting pediatric and neonatology care unit decision process

Children are an especially vulnerable population, particularly in respect to drug administration. It is estimated that neonatal and pediatric patients are at least three times more vulnerable to damage due to adverse events and medication errors than adults are. With the development of this framework, it is intended the provision of a Clinical Decision Support System based on a prototype already tested in a real environment. The framework will include features such as preparation of Total Parenteral Nutrition prescriptions, table pediatric and neonatal emergency drugs, medical scales of morbidity and mortality, anthropometry percentiles (weight, length/height, head circumference and BMI), utilities for supporting medical decision on the treatment of neonatal jaundice and anemia and support for technical procedures and other calculators and widespread use tools. The solution in development means an extension of INTCare project. The main goal is to provide an approach to get the functionality at all times of clinical practice and outside the hospital environment for dissemination, education and simulation of hypothetical situations. The aim is also to develop an area for the study and analysis of information and extraction of knowledge from the data collected by the use of the system. This paper presents the architecture, their requirements and functionalities and a SWOT analysis of the solution proposed.

Framework Agreement between the Minister for Health and the Irish Medical Organisation in respect of a process for engagement concerning the GMS/GP Contract

Minister of State with responsibility for Primary Care, Alex White TD, today (4 June 2014) concluded a series of meetings with the Irish Medical Organisation (IMO) with the signing of the Framework Agreement between the Minister of Health, the HSE and the Irish Medical Organisation (IMO) setting out a process for engagement concerning the GMS/GP contract and other publicly funded contracts involving General Practitioners (GPs). Download document here

Gaussian process framework for pervasive estimation of swimming velocity with body-worn IMU

Presented is an accurate swimming velocity estimation method using an inertial measurement unit (IMU) by employing a simple biomechanical constraint of motion along with Gaussian process regression to deal with sensor inherent errors. Experimental validation shows a velocity RMS error of 9.0 cm/s and high linear correlation when compared with a commercial tethered reference system. The results confirm the practicality of the presented method to estimate swimming velocity using a single low-cost, body-worn IMU.