Healthcare and patient costs of a proactive chlamydia screening programme: the Chlamydia Screening Studies project

BACKGROUND AND OBJECTIVE: Most economic evaluations of chlamydia screening do not include costs incurred by patients. The objective of this study was to estimate both the health service and private costs of patients who participated in proactive chlamydia screening, using mailed home-collected specimens as part of the Chlamydia Screening Studies project. METHODS: Data were collected on the administrative costs of the screening study, laboratory time and motion studies and patient-cost questionnaire surveys were conducted. The cost for each screening invitation and for each accepted offer was estimated. One-way sensitivity analysis was conducted to explore the effects of variations in patient costs and the number of patients accepting the screening offer. RESULTS: The time and costs of processing urine specimens and vulvo-vaginal swabs from women using two nucleic acid amplification tests were similar. The total cost per screening invitation was 20.37 pounds (95% CI 18.94 pounds to 24.83). This included the National Health Service cost per individual screening invitation 13.55 pounds (95% CI 13.15 pounds to 14.33) and average patient costs of 6.82 pounds (95% CI 5.48 pounds to 10.22). Administrative costs accounted for 50% of the overall cost. CONCLUSIONS: The cost of proactive chlamydia screening is comparable to those of opportunistic screening. Results from this study, which is the first to collect private patient costs associated with a chlamydia screening programme, could be used to inform future policy recommendations and provide unique primary cost data for economic evaluations.

Survey of public knowledge about Echinococcus multilocularis in four European countries: Need for proactive information

Background Public information about prevention of zoonoses should be based on the perceived problem by the public and should be adapted to regional circumstances. Growing fox populations have led to increasing concern about human alveolar echinococcosis, which is caused by the fox tapeworm Echinococcus multilocularis. In order to plan information campaigns, public knowledge about this zoonotic tapeworm was assessed. Methods By means of representative telephone interviews (N = 2041), a survey of public knowledge about the risk and the prevention of alveolar echinococcosis was carried out in the Czech Republic, France, Germany and Switzerland in 2004. Results For all five questions, significant country-specific differences were found. Fewer people had heard of E. multilocularis in the Czech Republic (14%) and France (18%) compared to Germany (63%) and Switzerland (70%). The same effect has been observed when only high endemic regions were considered (Czech Republic: 20%, France: 17%, Germany: 77%, Switzerland: 61%). In France 17% of people who knew the parasite felt themselves reasonably informed. In the other countries, the majority felt themselves reasonably informed (54–60%). The percentage that perceived E. multilocularis as a high risk ranged from 12% (Switzerland) to 43% (France). In some countries promising measures as deworming dogs (Czech Republic, Switzerland) were not recognized as prevention options. Conclusion Our results and the actual epidemiological circumstances of AE call for proactive information programs. This communication should enable the public to achieve realistic risk perception, give clear information on how people can minimize their infection risk, and prevent exaggerated reactions and anxiety.

Hope as a resource for self-directed career management: Investigatiing mediating effects on proactive career behaviors, life and job satisfaction

ABSTRACT Hope is increasingly recognized as an important psychological resource for career development, yet the empirical research on its functioning in this domain is sparse. This paper describes an investigation of how dispositional hope is related to career decidedness, career planning, and career self-efficacy beliefs and whether these more proximal career attitudes mediate the effects of hope on proactive career behaviors, life satisfaction, and job satisfaction. This investigation was conducted using two independent samples of university students (N = 1,334) and working professionals (N = 233). The results showed that in both samples, hope was significantly related but empirically distinct from career variables. In both samples, hope had a direct effect on proactive career behaviors, partially mediated by more career planning. Hope had significant direct and indirect effects on life satisfaction among students, mediated by the three career development attitudes. Although hope was significantly correlated with job satisfaction among employees, no direct effect of hope was found in the mediation model, but an indirect effect through career decidedness was found. The results suggest that hope is an important resource for proactive career development at different career stages and that the positive relation of hope to life and job satisfaction can partially be attributed to the positive relation between hope and favorable career development attitudes.

The Career Engagement Scale: Development and validation of a measure of proactive career behaviors

Careers today increasingly require engagement in proactive career behaviors; however, there is a lack of validated measures assessing the general degree to which somebody is engaged in such career behaviors. We describe the results of six studies with six independent samples of German university students (total N = 2,854), working professionals (total N = 561), and university graduates (N = 141) that report the development and validation of the Career Engagement Scale - a measure of the degree of which somebody is proactively developing her or his career as expressed by diverse career behaviors. The studies provide supprt for measurement invariance across gender and time. In support of convergent and discriminant validity, we find that career engagement is more prevalent among working professionals than among university students and that this scale has incremental validity above several specific career behaviors regarding its relation to vocational identity clarity and career self-efficacy beliefs among students and to job and career satisfaction among employees. In support of incremental predictive validity, beyond the effects of several more specific careeer behaviors, career engagement while at university predicts higher job and career satisfaction several months later after beginning work.

Career engagement: Investigating intraindividual predictors of weekly fluctuations in proactive career behaviors

The present study applies a micro‐level perspective on how within‐individual differenc motivational and social‐cognitive factors affect the weekly fluctuations of engageme proactive career behaviors among a group of 67 German university students. Career efficacy beliefs, perceived career barriers, experienced social career support, positive negative emotions, and career engagement were assessed weekly for 13 consecutive w Hierarchical linear regression analyses showed that above‐average levels of career engage within individuals were predicted by higher than average perceived social support and pos emotions during a given week. Conversely, within‐individual differences in self‐effi barriers, and negative emotions had no effect. The results suggest that career interven should provide boosts in social support and positive emotions.

Proactive motivation and engagement in career behaviors: Investigating direct, mediated, and moderated effects

Proactive career behaviors become increasingly important in today's career environment, but little is known about how and when motivational patterns affect individual differences. In a six-month longitudinal study among German university students (Study 1; N = 289) it was demonstrated that motivation in terms of “can do” (self-efficacy and context beliefs), “reason to” (autonomous career goals), and “energized to” (positive affect) significantly predicted career behaviors. Contrary to expectation, negative context beliefs had a positive effect when combined with other motivational states. Study 2 replicated and extended those results by investigating whether “can do” motivation mediates the effect of proactive personality and whether those effects are conditional upon the degree of career choice decidedness. We tested a moderated multiple mediation model with a unique sample of 134 German students, assessed three times, each interval being 6 weeks apart. The results showed that effects of proactivity were partially carried through higher self-efficacy beliefs but not context beliefs. Supporting a moderation model, indirect effects through self-efficacy beliefs were not present for students with very low decidedness.

Proactive aggression: A two part study

Aggressive behavior can be divided into the subtypes: reactive and proactive. Reactive aggressive acts occur in response to a stimulus or provocation. Proactive aggressive acts occur without provocation and are goal-directed. A number of findings have suggested that individuals displaying proactive aggression may be discerned from individuals not displaying proactive aggression on measures of personality, psychopathology and psychopathy, as well as on aggressive histories and type and severity of aggressive behaviors committed. The current study was conducted in two phases; phase 1 and 2. This was because phase 1 compared proactive aggressive, reactive aggressive and non-aggressive subjects on questionnaire measures, while phase 2 observed the acute effects of the benzodiazepine alprazolam on only proactive aggressive subjects. The phase 1 hypotheses were that proactive aggressive subjects would show greater numbers of personality disorders and have greater psychopathy relative to reactive and non-aggressive subjects. To verify these hypotheses subjects were recruited from the community and classified as proactive (n = 20), reactive (n = 20) or non-aggressive (n = 10) via laboratory behavioral testing. Classified subjects were administered a battery of questionnaires pertaining to personality disorders (SCID-II, OMNI-IV), psychopathy (PCL-R) and aggression history. The results of these questionnaire measures were subjected to statistical analyses, which confirmed the hypotheses. In the second phase, the acute effects of three doses of the benzodiazepine alprazolam were evaluated in proactive aggressive subjects on proactive aggressive responding in the computer-based Point Subtraction Aggression Paradigm (PSAP). In phase 2 it was hypothesized that alprazolam would produce dose dependent decreases in aggressive responding. Subjects were never provoked in this phase, and aggressive responding was classified as proactive. Studies of drugs acting on the GABA system have frequently found decreases in aggression in animals and humans, although there have also been findings of increased (paradoxical) aggression. The hypothesis was tested by statistical analysis of proactive aggressive responding under placebo vs. under alprazolam. The hypothesis was supported by six of seven subjects. Aggressive responding was significantly, decreased under alprazolam relative to placebo in six subjects. One subject showed increases in aggressive responding.^

Enhanced recommendations for e-learning authoring tools based on a proactive context-aware recommender

Authoring tools are powerful systems in the area of e-Learning that make easier for teachers to create new learning objects by reusing or editing existing educational resources coming from learning repositories or content providers. However, due to the overwhelming number of resources these tools can access, sometimes it is difficult for teachers to find the most suitable resources taking into account their needs in terms of content (e.g. topic) or pedagogical aspects (e.g. target level associated to their students). Recommender systems can take an important role trying to mitigate this problem. In this paper we propose a new model to generate proactive context-aware recommendations on resources during the creation process of a new learning object that a teacher carries out by using an authoring tool. The common use cases covered by the model for having recommendations in online authoring tools and details about the recommender model itself are presented.

Proactive and reactive thermal aware optimization techniques to minimize the environmental impact of data centers

Data centers are easily found in every sector of the worldwide economy. They are composed of thousands of servers, serving millions of users globally and 24-7. In the last years, e-Science applications such e-Health or Smart Cities have experienced a significant development. The need to deal efficiently with the computational needs of next-generation applications together with the increasing demand for higher resources in traditional applications has facilitated the rapid proliferation and growing of Data Centers. A drawback to this capacity growth has been the rapid increase of the energy consumption of these facilities. In 2010, data center electricity represented 1.3% of all the electricity use in the world. In year 2012 alone, global data center power demand grep 63% to 38GW. A further rise of 17% to 43GW was estimated in 2013. Moreover, Data Centers are responsible for more than 2% of total carbon dioxide emissions.

Proactive and reactive thermal aware optimization techniques to minimize the environmental impact of data centers

Los Centros de Datos se encuentran actualmente en cualquier sector de la economía mundial. Están compuestos por miles de servidores, dando servicio a los usuarios de forma global, las 24 horas del día y los 365 días del año. Durante los últimos años, las aplicaciones del ámbito de la e-Ciencia, como la e-Salud o las Ciudades Inteligentes han experimentado un desarrollo muy significativo. La necesidad de manejar de forma eficiente las necesidades de cómputo de aplicaciones de nueva generación, junto con la creciente demanda de recursos en aplicaciones tradicionales, han facilitado el rápido crecimiento y la proliferación de los Centros de Datos. El principal inconveniente de este aumento de capacidad ha sido el rápido y dramático incremento del consumo energético de estas infraestructuras. En 2010, la factura eléctrica de los Centros de Datos representaba el 1.3% del consumo eléctrico mundial. Sólo en el año 2012, el consumo de potencia de los Centros de Datos creció un 63%, alcanzando los 38GW. En 2013 se estimó un crecimiento de otro 17%, hasta llegar a los 43GW. Además, los Centros de Datos son responsables de más del 2% del total de emisiones de dióxido de carbono a la atmósfera. Esta tesis doctoral se enfrenta al problema energético proponiendo técnicas proactivas y reactivas conscientes de la temperatura y de la energía, que contribuyen a tener Centros de Datos más eficientes. Este trabajo desarrolla modelos de energía y utiliza el conocimiento sobre la demanda energética de la carga de trabajo a ejecutar y de los recursos de computación y refrigeración del Centro de Datos para optimizar el consumo. Además, los Centros de Datos son considerados como un elemento crucial dentro del marco de la aplicación ejecutada, optimizando no sólo el consumo del Centro de Datos sino el consumo energético global de la aplicación. Los principales componentes del consumo en los Centros de Datos son la potencia de computación utilizada por los equipos de IT, y la refrigeración necesaria para mantener los servidores dentro de un rango de temperatura de trabajo que asegure su correcto funcionamiento. Debido a la relación cúbica entre la velocidad de los ventiladores y el consumo de los mismos, las soluciones basadas en el sobre-aprovisionamiento de aire frío al servidor generalmente tienen como resultado ineficiencias energéticas. Por otro lado, temperaturas más elevadas en el procesador llevan a un consumo de fugas mayor, debido a la relación exponencial del consumo de fugas con la temperatura. Además, las características de la carga de trabajo y las políticas de asignación de recursos tienen un impacto importante en los balances entre corriente de fugas y consumo de refrigeración. La primera gran contribución de este trabajo es el desarrollo de modelos de potencia y temperatura que permiten describes estos balances entre corriente de fugas y refrigeración; así como la propuesta de estrategias para minimizar el consumo del servidor por medio de la asignación conjunta de refrigeración y carga desde una perspectiva multivariable. Cuando escalamos a nivel del Centro de Datos, observamos un comportamiento similar en términos del balance entre corrientes de fugas y refrigeración. Conforme aumenta la temperatura de la sala, mejora la eficiencia de la refrigeración. Sin embargo, este incremente de la temperatura de sala provoca un aumento en la temperatura de la CPU y, por tanto, también del consumo de fugas. Además, la dinámica de la sala tiene un comportamiento muy desigual, no equilibrado, debido a la asignación de carga y a la heterogeneidad en el equipamiento de IT. La segunda contribución de esta tesis es la propuesta de técnicas de asigación conscientes de la temperatura y heterogeneidad que permiten optimizar conjuntamente la asignación de tareas y refrigeración a los servidores. Estas estrategias necesitan estar respaldadas por modelos flexibles, que puedan trabajar en tiempo real, para describir el sistema desde un nivel de abstracción alto. Dentro del ámbito de las aplicaciones de nueva generación, las decisiones tomadas en el nivel de aplicación pueden tener un impacto dramático en el consumo energético de niveles de abstracción menores, como por ejemplo, en el Centro de Datos. Es importante considerar las relaciones entre todos los agentes computacionales implicados en el problema, de forma que puedan cooperar para conseguir el objetivo común de reducir el coste energético global del sistema. La tercera contribución de esta tesis es el desarrollo de optimizaciones energéticas para la aplicación global por medio de la evaluación de los costes de ejecutar parte del procesado necesario en otros niveles de abstracción, que van desde los nodos hasta el Centro de Datos, por medio de técnicas de balanceo de carga. Como resumen, el trabajo presentado en esta tesis lleva a cabo contribuciones en el modelado y optimización consciente del consumo por fugas y la refrigeración de servidores; el modelado de los Centros de Datos y el desarrollo de políticas de asignación conscientes de la heterogeneidad; y desarrolla mecanismos para la optimización energética de aplicaciones de nueva generación desde varios niveles de abstracción. ABSTRACT Data centers are easily found in every sector of the worldwide economy. They consist of tens of thousands of servers, serving millions of users globally and 24-7. In the last years, e-Science applications such e-Health or Smart Cities have experienced a significant development. The need to deal efficiently with the computational needs of next-generation applications together with the increasing demand for higher resources in traditional applications has facilitated the rapid proliferation and growing of data centers. A drawback to this capacity growth has been the rapid increase of the energy consumption of these facilities. In 2010, data center electricity represented 1.3% of all the electricity use in the world. In year 2012 alone, global data center power demand grew 63% to 38GW. A further rise of 17% to 43GW was estimated in 2013. Moreover, data centers are responsible for more than 2% of total carbon dioxide emissions. This PhD Thesis addresses the energy challenge by proposing proactive and reactive thermal and energy-aware optimization techniques that contribute to place data centers on a more scalable curve. This work develops energy models and uses the knowledge about the energy demand of the workload to be executed and the computational and cooling resources available at data center to optimize energy consumption. Moreover, data centers are considered as a crucial element within their application framework, optimizing not only the energy consumption of the facility, but the global energy consumption of the application. The main contributors to the energy consumption in a data center are the computing power drawn by IT equipment and the cooling power needed to keep the servers within a certain temperature range that ensures safe operation. Because of the cubic relation of fan power with fan speed, solutions based on over-provisioning cold air into the server usually lead to inefficiencies. On the other hand, higher chip temperatures lead to higher leakage power because of the exponential dependence of leakage on temperature. Moreover, workload characteristics as well as allocation policies also have an important impact on the leakage-cooling tradeoffs. The first key contribution of this work is the development of power and temperature models that accurately describe the leakage-cooling tradeoffs at the server level, and the proposal of strategies to minimize server energy via joint cooling and workload management from a multivariate perspective. When scaling to the data center level, a similar behavior in terms of leakage-temperature tradeoffs can be observed. As room temperature raises, the efficiency of data room cooling units improves. However, as we increase room temperature, CPU temperature raises and so does leakage power. Moreover, the thermal dynamics of a data room exhibit unbalanced patterns due to both the workload allocation and the heterogeneity of computing equipment. The second main contribution is the proposal of thermal- and heterogeneity-aware workload management techniques that jointly optimize the allocation of computation and cooling to servers. These strategies need to be backed up by flexible room level models, able to work on runtime, that describe the system from a high level perspective. Within the framework of next-generation applications, decisions taken at this scope can have a dramatical impact on the energy consumption of lower abstraction levels, i.e. the data center facility. It is important to consider the relationships between all the computational agents involved in the problem, so that they can cooperate to achieve the common goal of reducing energy in the overall system. The third main contribution is the energy optimization of the overall application by evaluating the energy costs of performing part of the processing in any of the different abstraction layers, from the node to the data center, via workload management and off-loading techniques. In summary, the work presented in this PhD Thesis, makes contributions on leakage and cooling aware server modeling and optimization, data center thermal modeling and heterogeneityaware data center resource allocation, and develops mechanisms for the energy optimization for next-generation applications from a multi-layer perspective.

Proactive and reactive inhibition during overt and covert actions. An electrical neuroimaging study.

Response inhibition is the ability to suppress inadequate but automatically activated, prepotent or ongoing response tendencies. In the framework of motor inhibition, two distinct operating strategies have been described: “proactive” and “reactive” control modes. In the proactive modality, inhibition is recruited in advance by predictive signals, and actively maintained before its enactment. Conversely, in the reactive control mode, inhibition is phasically enacted after the detection of the inhibitory signal. To date, ample evidence points to a core cerebral network for reactive inhibition comprising the right inferior frontal gyrus (rIFG), the presupplementary motor area (pre-SMA) and the basal ganglia (BG). Moreover, fMRI studies showed that cerebral activations during proactive and reactive inhibition largely overlap. These findings suggest that at least part of the neural network for reactive inhibition is recruited in advance, priming cortical regions in preparation for the upcoming inhibition. So far, proactive and reactive inhibitory mechanisms have been investigated during tasks in which the requested response to be stopped or withheld was an “overt” action execution (AE) (i.e., a movement effectively performed). Nevertheless, inhibitory mechanisms are also relevant for motor control during “covert actions” (i.e., potential motor acts not overtly performed), such as motor imagery (MI). MI is the conscious, voluntary mental rehearsal of action representations without any overt movement. Previous studies revealed a substantial overlap of activated motor-related brain networks in premotor, parietal and subcortical regions during overtly executed and imagined movements. Notwithstanding this evidence for a shared set of cerebral regions involved in encoding actions, whether or not those actions are effectively executed, the neural bases of motor inhibition during MI, preventing covert action from being overtly performed, in spite of the activation of the motor system, remain to be fully clarified. Taking into account this background, we performed a high density EEG study evaluating cerebral mechanisms and their related sources elicited during two types of cued Go/NoGo task, requiring the execution or withholding of an overt (Go) or a covert (MI) action, respectively. The EEG analyses were performed in two steps, with different aims: 1) Analysis of the “response phase” of the cued overt and covert Go/NoGo tasks, for the evaluation of reactive inhibitory control of overt and covert actions. 2) Analysis of the “preparatory phase” of the cued overt and covert Go/NoGo EEG datasets, focusing on cerebral activities time-locked to the preparatory signals, for the evaluation of proactive inhibitory mechanisms and their related neural sources. For these purposes, a spatiotemporal analysis of the scalp electric fields was applied on the EEG data recorded during the overt and covert Go/NoGo tasks. The spatiotemporal approach provide an objective definition of time windows for source analysis, relying on the statistical proof that the electric fields are different and thus generated by different neural sources. The analysis of the “response phase” revealed that key nodes of the inhibitory circuit, underpinning inhibition of the overt movement during the NoGo response, were also activated during the MI enactment. In both cases, inhibition relied on the activation of pre-SMA and rIFG, but with different temporal patterns of activation in accord with the intended “covert” or “overt” modality of motor performance. During the NoGo condition, the pre-SMA and rIFG were sequentially activated, pointing to an early decisional role of pre-SMA and to a later role of rIFG in the enactment of inhibitory control of the overt action. Conversely, a concomitant activation of pre-SMA and rIFG emerged during the imagined motor response. This latter finding suggested that an inhibitory mechanism (likely underpinned by the rIFG), could be prewired into a prepared “covert modality” of motor response, as an intrinsic component of the MI enactment. This mechanism would allow the rehearsal of the imagined motor representations, without any overt movement. The analyses of the “preparatory phase”, confirmed in both overt and covert Go/NoGo tasks the priming of cerebral regions pertaining to putative inhibitory network, reactively triggered in the following response phase. Nonetheless, differences in the preparatory strategies between the two tasks emerged, depending on the intended “overt” or “covert” modality of the possible incoming motor response. During the preparation of the overt Go/NoGo task, the cue primed the possible overt response programs in motor and premotor cortex. At the same time, through preactivation of a pre-SMA-related decisional mechanism, it triggered a parallel preparation for the successful response selection and/or inhibition during the subsequent response phase. Conversely, the preparatory strategy for the covert Go/NoGo task was centred on the goal-oriented priming of an inhibitory mechanism related to the rIFG that, being tuned to the instructed covert modality of the motor performance and instantiated during the subsequent MI enactment, allowed the imagined response to remain a potential motor act. Taken together, the results of the present study demonstrate a substantial overlap of cerebral networks activated during proactive recruitment and subsequent reactive enactment of motor inhibition in both overt and covert actions. At the same time, our data show that preparatory cues predisposed ab initio a different organization of the cerebral areas (in particular of the pre-SMA and rIFG) involved with sensorimotor transformations and motor inhibitory control for executed and imagined actions. During the preparatory phases of our cued overt and covert Go/NoGo tasks, the different adopted strategies were tuned to the “how” of the motor performance, reflecting the intended overt and covert modality of the possible incoming action.

The Proactive International Dimension and the Breakdown of Authoritarian Regimes

There is international consensus among scholars that democratic transitions are multicausal processes in which both internal and international variables are involved (Pridham 1991, 1995; Whitehead 1996; Schmitter 1996; Linz and Stepan 1996; Carothers 1999; Morlino and Magen 2008; Grilli di Cortona 2009). This chapter is limited, on the one hand, to the dependent variable consisting solely of the crisis/breakdown/transformation of non-democratic regimes in the Third Wave of democratization, and, on the other hand, to an independent variable identified solely with the international dimension of democratic transition. This factor, which can be termed the Proactive International Dimension (PID), specifically concerns that combination of actions or processes, produced by one or more international actors, that, intentionally or not, cause or contribute to the crisis/breakdown/transformation of a non-democratic regime.