The 2017 Regional Election in Catalonia: An attempt to understand the pro-independence vote

This paper tries to unveil the main factors behind the triumph of the proindependence vote in the 2017 Regional Election in Catalonia. The empirical analysis, which is carried out at the county level and by using a spatial econometric model, reveals that geographical location matters. The estimation results also suggest that the pro-independence vote is mainly linked to the birthplace of individuals. More specifically, it shows that the independence feeling is weaker the higher the share of citizens born outside Catalonia. On the other side, young and highly educated people are more prone to independence. Additionally, it is shown that people working in the public sector are more likely to vote for a political party in favor of Catalonia remaining in Spain, while the opposite happens for those voters working in construction. Finally, the results seem to dispel some myths associated with the role played by the county’s size and level of income on the proindependence vote

Interference-induced gain in Autler-Townes doublet of a V-type atom in a cavity

We study the Autler-Townes spectrum of a V-type atom coupled to a single-mode, frequency-tunable cavity field at finite termperature, with a pre-selected polarization in the bad cavity limit, and show that, when the mean number of thermal photons $N\gg 1$ and the excited sublevel splitting is very large (the same order as the cavity linewidth), the probe gain may occur at either sideband of the doublet, depending on the cavity frequency, due to the cavity-induced interference.Comment: Minor changes are mad

A brief history of learning classifier systems: from CS-1 to XCS and its variants

© 2015, Springer-Verlag Berlin Heidelberg. The direction set by Wilson’s XCS is that modern Learning Classifier Systems can be characterized by their use of rule accuracy as the utility metric for the search algorithm(s) discovering useful rules. Such searching typically takes place within the restricted space of co-active rules for efficiency. This paper gives an overview of the evolution of Learning Classifier Systems up to XCS, and then of some of the subsequent developments of Wilson’s algorithm to different types of learning

Prescription Medicines and the Risk of Road Traffic Crashes: A French Registry-Based Study

Using three nationwide databases in France, Ludivine Orriols, Emmanuel Lagarde, and colleagues provide evidence that prescribed medicines contribute to the risk of experiencing a road traffic crash

Information and feedback to improve occupational physicians’ reporting of occupational diseases: a randomised controlled trial

To assess the effectiveness of supplying occupational physicians (OPs) with targeted and stage-matched information or with feedback on reporting occupational diseases to the national registry in the Netherlands. In a randomized controlled design, 1076 OPs were divided into three groups based on previous reporting behaviour: precontemplators not considering reporting, contemplators considering reporting and actioners reporting occupational diseases. Precontemplators and contemplators were randomly assigned to receive stage-matched, stage-mismatched or general information. Actioners were randomly assigned to receive personalized or standardized feedback upon notification. Outcome measures were the number of OPs reporting and the number of reported occupational diseases in a 180-day period before and after the intervention. Precontemplators were significantly more male and self-employed compared to contemplators and actioners. There was no significant effect of stage-matched information versus stage-mismatched or general information on the percentage of reporting OPs and on the mean number of notifications in each group. Receiving any information affected reporting more in contemplators than in precontemplators. The mean number of notifications in actioners increased more after personalized feedback than after standardized feedback, but the difference was not significant. This study supports the concept that contemplators are more susceptible to receiving information but could not confirm an effect of stage-matching this information on reporting occupational diseases to the national registr

Predictors for patient knowledge and reported behaviour regarding driving under the influence of medicines: a multi-country survey

<p>Abstract</p> <p>Background</p> <p>Reports on the state of knowledge about medicines and driving showed an increased concern about the role that the use of medicines might play in car crashes. Much of patient knowledge regarding medicines comes from communications with healthcare professionals. This study, part of the DRUID (Driving Under the Influence of Drugs, alcohol and medicines) project, was carried out in four European countries and attempts to define predictors for knowledge of patients who use driving-impairing medicines. The influence of socio-demographic variables on patient knowledge was investigated as well as the influence of socio-demographic factors, knowledge and attitudes on patients' reported behaviour regarding driving under the influence of medicines.</p> <p>Methods</p> <p>Pharmacists handed out questionnaires to patients who met the inclusion criteria: 1) prevalent user of benzodiazepines, antidepressants or first generation antihistamines for systemic use; 2) age between 18 and 75 years old and 3) actual driver of a motorised vehicle. Factors affecting knowledge and reported behaviour towards driving-impairing medicines were analysed by means of multiple linear regression analysis and multiple logistic regression analysis, respectively.</p> <p>Results</p> <p>A total of 633 questionnaires (out of 3.607 that were distributed to patients) were analysed. Patient knowledge regarding driving under the influence of medicines is better in younger and higher educated patients. Information provided to or accessed by patients does not influence knowledge. Patients who experienced side effects and who have a negative attitude towards driving under the influence of impairing medicines are more prone to change their driving frequency behaviour than those who use their motorised vehicles on a daily basis or those who use anti-allergic medicines.</p> <p>Conclusions</p> <p>Changes in driving behaviour can be predicted by negative attitudes towards driving under the influence of medicines but not by patients' knowledge regarding driving under the influence of medicines. Future research should not only focus on information campaigns for patients but also for healthcare providers as this might contribute to improve communications with patients regarding the risks of driving under the influence of medicines.</p

A comparison of pharmacoepidemiological study designs in medication use and traffic safety research

In order to explore how the choice of different study designs could influence the risk estimates, a case–crossover and case–time–control study were carried out and their outcomes were compared with those of a traditional case–control study design that evaluated the association between the exposure to psychotropic medications and the risk of having a motor vehicle accident (MVA). A record-linkage database availing data for 3,786 cases and 18,089 controls during the period 2000–2007 was used. The study designs (i.e., case–crossover and case–time–control) were derived from published literature, and the following psychotropic medicines were examined: antipsychotics, anxiolytics, hypnotics and sedatives, and antidepressants, stratified in the two groups selective serotonin reuptake inhibitors (SSRIs) and other antidepressants. Moreover, in order to further investigate the effects of frequency of psychoactive medication exposure on the outcomes of the case–crossover analysis, the data were also stratified by the number of defined daily doses (DDDs) and days of medication use in the 12 months before the motor vehicle accident. Three-thousand seven-hundred fifty-two cases were included in this second part of the case–crossover analysis. The case–crossover design did not show any statistically significant association between psychotropic medication exposure and MVA risk [e.g., SSRIs—Adj. OR = 1.00 (95 % CI: 0.69–1.46); Anxiolytics—Adj. OR = 0.95 (95 % CI: 0.68–1.31)]. The case–time–control design only showed a borderline statistically significant increased traffic accident risk in SSRI users [Adj. OR = 1.16 (95 % CI: 1.01–1.34)]. With respect to the stratifications by the number of DDDs and days of medication use, the analyses showed no increased traffic accident risk associated with the exposure to the selected medication groups [e.g., SSRIs, <20 DDDs—Adj. OR = 0.65 (95 % CI: 0.11–3.87); SSRIs, 16–150 days—Adj. OR = 0.55 (95 % CI: 0.24–1.24)]. In contrast to the above-mentioned results, our recent case–control study found a statistically significant association between traffic accident risk and exposure to anxiolytics [Adj. OR = 1.54 (95 % CI: 1.11–2.15)], and SSRIs [Adj. OR = 2.03 (95 % CI: 1.31–3.14)]. Case–crossover and case–time–control analyses produced different results than those of our recent case–control study (i.e., case–crossover and case–time–control analyses did not show any statistically significant association whereas the case–control analysis showed an increased traffic accident risk in anxiolytic and SSRI users). These divergent results can probably be explained by the differences in the study designs. Given that the case–crossover design is only appropriate for short-term exposures and the case–time–control design is an elaboration of this latter, it can be concluded that, probably, these two approaches are not the most suitable ones to investigate the relation between MVA risk and psychotropic medications, which, on the contrary, are often use chronically

Mortality Risk of Hypnotics: Strengths and Limits of Evidence

Sleeping pills, more formally defined as hypnotics, are sedatives used to induce and maintain sleep. In a review of publications for the past 30 years, descriptive epidemiologic studies were identified that examined the mortality risk of hypnotics and related sedative-anxiolytics. Of the 34 studies estimating risk ratios, odds ratios, or hazard ratios, excess mortality associated with hypnotics was significant (p &lt; 0.05) in 24 studies including all 14 of the largest, contrasted with no studies at all suggesting that hypnotics ever prolong life. The studies had many limitations: possibly tending to overestimate risk, such as possible confounding by indication with other risk factors; confusing hypnotics with drugs having other indications; possible genetic confounders; and too much heterogeneity of studies for meta-analyses. There were balancing limitations possibly tending towards underestimates of risk such as limited power, excessive follow-up intervals with possible follow-up mixing of participants taking hypnotics with controls, missing dosage data for most studies, and over-adjustment of confounders. Epidemiologic association in itself is not adequate proof of causality, but there is proof that hypnotics cause death in overdoses; there is thorough understanding of how hypnotics euthanize animals and execute humans; and there is proof that hypnotics cause potentially lethal morbidities such as depression, infection, poor driving, suppressed respiration, and possibly cancer. Combining these proofs with consistent evidence of association, the great weight of evidence is that hypnotics cause huge risks of decreasing a patient's duration of survival