Using plan analysis in psychotherapeutic case formulation of borderline personality disorder.

A comprehensive understanding of the patient's problems is essential for a constructive therapeutic behaviour, especially in borderline personality disorder (BPD) where difficult interpersonal patterns are persistent. In these circumstances, the use of an integrative case formulation approach such as Plan Analysis, developed by K. Grawe and F. Caspar, can be of help for therapy planning. The focus here is on instrumental relations between behaviours and the hypothetical Plans and motives 'behind' those behaviours. The present qualitative study aimed at setting a prototypical Plan structure for n = 15 patients presenting a Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, diagnosis of BPD using Plan Analysis. The first psychotherapeutic session of every outpatient was video-taped and evaluated according to the Plan Analysis procedure. Inter-rater reliability was established between two independent raters and was considered sufficient. The detailed prototypical Plan structure of BPD showed two main tendencies: first, the important presence of support-seeking among these patients and second, the will to be in control and to protect oneself. This study confirms the existence of several core similarities in the functioning of patients with BPD. These findings are in line with earlier studies and expand the latter with the aim of contributing to the understanding of BPD psychopathology. Clinical implications are discussed. Copyright © 2011 John Wiley & Sons, Ltd. KEY PRACTITIONER MESSAGE: Plan Analysis can especially be of help with patients who have difficult interpersonal patterns, as those presenting with BPD. Two tendencies were found within BPD patients: (1) support-seeking and (2) control and self-protecting Plans. Further research using Plan Analysis should focus on the identification and detail of emotions within BPD.

Predictive analysis and mapping of indoor radon concentrations in Switzerland

It is estimated that around 230 people die each year due to radon (222Rn) exposure in Switzerland. 222Rn occurs mainly in closed environments like buildings and originates primarily from the subjacent ground. Therefore it depends strongly on geology and shows substantial regional variations. Correct identification of these regional variations would lead to substantial reduction of 222Rn exposure of the population based on appropriate construction of new and mitigation of already existing buildings. Prediction of indoor 222Rn concentrations (IRC) and identification of 222Rn prone areas is however difficult since IRC depend on a variety of different variables like building characteristics, meteorology, geology and anthropogenic factors. The present work aims at the development of predictive models and the understanding of IRC in Switzerland, taking into account a maximum of information in order to minimize the prediction uncertainty. The predictive maps will be used as a decision-support tool for 222Rn risk management. The construction of these models is based on different data-driven statistical methods, in combination with geographical information systems (GIS). In a first phase we performed univariate analysis of IRC for different variables, namely the detector type, building category, foundation, year of construction, the average outdoor temperature during measurement, altitude and lithology. All variables showed significant associations to IRC. Buildings constructed after 1900 showed significantly lower IRC compared to earlier constructions. We observed a further drop of IRC after 1970. In addition to that, we found an association of IRC with altitude. With regard to lithology, we observed the lowest IRC in sedimentary rocks (excluding carbonates) and sediments and the highest IRC in the Jura carbonates and igneous rock. The IRC data was systematically analyzed for potential bias due to spatially unbalanced sampling of measurements. In order to facilitate the modeling and the interpretation of the influence of geology on IRC, we developed an algorithm based on k-medoids clustering which permits to define coherent geological classes in terms of IRC. We performed a soil gas 222Rn concentration (SRC) measurement campaign in order to determine the predictive power of SRC with respect to IRC. We found that the use of SRC is limited for IRC prediction. The second part of the project was dedicated to predictive mapping of IRC using models which take into account the multidimensionality of the process of 222Rn entry into buildings. We used kernel regression and ensemble regression tree for this purpose. We could explain up to 33% of the variance of the log transformed IRC all over Switzerland. This is a good performance compared to former attempts of IRC modeling in Switzerland. As predictor variables we considered geographical coordinates, altitude, outdoor temperature, building type, foundation, year of construction and detector type. Ensemble regression trees like random forests allow to determine the role of each IRC predictor in a multidimensional setting. We found spatial information like geology, altitude and coordinates to have stronger influences on IRC than building related variables like foundation type, building type and year of construction. Based on kernel estimation we developed an approach to determine the local probability of IRC to exceed 300 Bq/m3. In addition to that we developed a confidence index in order to provide an estimate of uncertainty of the map. All methods allow an easy creation of tailor-made maps for different building characteristics. Our work is an essential step towards a 222Rn risk assessment which accounts at the same time for different architectural situations as well as geological and geographical conditions. For the communication of 222Rn hazard to the population we recommend to make use of the probability map based on kernel estimation. The communication of 222Rn hazard could for example be implemented via a web interface where the users specify the characteristics and coordinates of their home in order to obtain the probability to be above a given IRC with a corresponding index of confidence. Taking into account the health effects of 222Rn, our results have the potential to substantially improve the estimation of the effective dose from 222Rn delivered to the Swiss population.

Antiretroviral therapy during pregnancy and premature birth: analysis of Swiss data.

BACKGROUND: There is an ongoing debate as to whether combined antiretroviral treatment (cART) during pregnancy is an independent risk factor for prematurity in HIV-1-infected women. OBJECTIVE: The aim of the study was to examine (1) crude effects of different ART regimens on prematurity, (2) the association between duration of cART and duration of pregnancy, and (3) the role of possibly confounding risk factors for prematurity. METHOD: We analysed data from 1180 pregnancies prospectively collected by the Swiss Mother and Child HIV Cohort Study (MoCHiV) and the Swiss HIV Cohort Study (SHCS). RESULTS: Odds ratios for prematurity in women receiving mono/dual therapy and cART were 1.8 [95% confidence interval (CI) 0.85-3.6] and 2.5 (95% CI 1.4-4.3) compared with women not receiving ART during pregnancy (P=0.004). In a subgroup of 365 pregnancies with comprehensive information on maternal clinical, demographic and lifestyle characteristics, there was no indication that maternal viral load, age, ethnicity or history of injecting drug use affected prematurity rates associated with the use of cART. Duration of cART before delivery was also not associated with duration of pregnancy. CONCLUSION: Our study indicates that confounding by maternal risk factors or duration of cART exposure is not a likely explanation for the effects of ART on prematurity in HIV-1-infected women.

Analyse critique des résultats de biopsies musculaires et de la méthodologie utilisée dans 889 cas d'affections neuromusculaires [Critical analysis of the results of muscle biopsies and of the methods used in 889 cases of neuromuscular disorders]

The contribution of muscle biopsies to the diagnosis of neuromuscular disorders and the indications of various methods of examination are investigated by analysis of 889 biopsies from patients suffering from myopathic and/or neurogenic disorders. Histo-enzymatic studies performed on frozen material as well as immunohistochemistry and electron microscopy allowed to provide specific diagnoses in all the neurogenic disorders (polyneuropathies and motor neuron diseases), whereas one third of myopathies remained uncertain. Confrontation of neuropathological data with the clinical indications for histological investigations shows that muscle biopsies reveal the diagnosis in 25% of the cases (mainly in congenital and metabolic myopathies) and confirm and/or complete the clinical diagnosis in 50%. In the remaining cases with non specific abnormalities neuropathological investigations may help the clinician by excluding well defined neuromuscular disorders. Analysis of performed studies and results of investigations show the contribution and specificity of each method for the diagnosis. Statistical evaluation of this series indicates that cryostat sectioning for histo- and immunochemical and electron microscopy increases the rate of diagnoses of neuromuscular diseases: full investigation was necessary for the diagnosis in 30% of the cases. The interpretation of the wide range of pathological reactions in muscles requires a close cooperation with the clinician.

Optimization of HS-SPME/GC-MS analysis and its use in the profiling of illicit ecstasy tablets (Part 1)

A headspace solid-phase microextraction procedure (HS-SPME) was developed for the profiling of traces present in 3,4-methylenedioxymethylampethamine (MDMA). Traces were first extracted using HS-SPME and then analyzed by gas chromatography-mass spectroscopy (GC-MS). The HS-SPME conditions were optimized using varying conditions. Optimal results were obtained when 40 mg of crushed MDMA sample was heated at 80 °C for 15 min, followed by extraction at 80 °C for 15 min with a polydimethylsiloxane/divinylbenzene coated fibre. A total of 31 compounds were identified as traces related to MDMA synthesis, namely precursors, intermediates or by-products. In addition some fatty acids used as tabletting materials and caffeine used as adulterant, were also detected. The use of a restricted set of 10 target compounds was also proposed for developing a screening tool for clustering samples having close profile. 114 seizures were analyzed using an SPME auto-sampler (MultiPurpose Samples MPS2), purchased from Gerstel GMBH & Co. (Germany), and coupled to GC-MS. The data was handled using various pre-treatment methods, followed by the study of similarities between sample pairs based on the Pearson correlation. The results show that HS-SPME, coupled with the suitable statistical method is a powerful tool for distinguishing specimens coming from the same seizure and specimens coming from different seizures. This information can be used by law enforcement personnel to visualize the ecstasy distribution network as well as the clandestine tablet manufacturing.

Critical values of nitrogen indices in tomato plants grown in soil and nutrient solution determined by different statistical procedures

The objective of this study was to establish critical values of the N indices, namely soil-plant analysis development (SPAD), petiole sap N-NO3 and organic N in the tomato leaf adjacent to the first cluster (LAC), under soil and nutrient solution conditions, determined by different statistical approaches. Two experiments were conducted in randomized complete block design with four repli-cations. Tomato plants were grown in soil, in 3 L pot, with five N rates (0, 100, 200, 400 and 800 mg kg-1) and in solution at N rates of 0, 4, 8, 12 and 16 mmol L-1. Experiments in nutrient solution and soil were finished at thirty seven and forty two days after transplanting, respectively. At those times, SPAD index and petiole sap N-NO3 were evaluated in the LAC. Then, plants were harvested, separated in leaves and stem, dried at 70ºC, ground and weighted. The organic N was determined in LAC dry matter. Three statistical procedures were used to calculate critical N values. There were accentuated discrepancies for critical values of N indices obtained with plants grown in soil and nutrient solution as well as for different statistical procedures. Critical values of nitrogen indices at all situations are presented.

Analysis of variance of primary data on plant growth analysis

Plant growth analysis presents difficulties related to statistical comparison of growth rates, and the analysis of variance of primary data could guide the interpretation of results. The objective of this work was to evaluate the analysis of variance of data from distinct harvests of an experiment, focusing especially on the homogeneity of variances and the choice of an adequate ANOVA model. Data from five experiments covering different crops and growth conditions were used. From the total number of variables, 19% were originally homoscedastic, 60% became homoscedastic after logarithmic transformation, and 21% remained heteroscedastic after transformation. Data transformation did not affect the F test in one experiment, whereas in the other experiments transformation modified the F test usually reducing the number of significant effects. Even when transformation has not altered the F test, mean comparisons led to divergent interpretations. The mixed ANOVA model, considering harvest as a random effect, reduced the number of significant effects of every factor which had the F test modified by this model. Examples illustrated that analysis of variance of primary variables provides a tool for identifying significant differences in growth rates. The analysis of variance imposes restrictions to experimental design thereby eliminating some advantages of the functional growth analysis.

Heterogeneity and event dependence in the analysis of sickness absence

Sickness absence (SA) is an important social, economic and public health issue. Identifying and understanding the determinants, whether biological, regulatory or, health services-related, of variability in SA duration is essential for better management of SA. The conditional frailty model (CFM) is useful when repeated SA events occur within the same individual, as it allows simultaneous analysis of event dependence and heterogeneity due to unknown, unmeasured, or unmeasurable factors. However, its use may encounter computational limitations when applied to very large data sets, as may frequently occur in the analysis of SA duration. To overcome the computational issue, we propose a Poisson-based conditional frailty model (CFPM) for repeated SA events that accounts for both event dependence and heterogeneity. To demonstrate the usefulness of the model proposed in the SA duration context, we used data from all non-work-related SA episodes that occurred in Catalonia (Spain) in 2007, initiated by either a diagnosis of neoplasm or mental and behavioral disorders. As expected, the CFPM results were very similar to those of the CFM for both diagnosis groups. The CPU time for the CFPM was substantially shorter than the CFM. The CFPM is an suitable alternative to the CFM in survival analysis with recurrent events,especially with large databases.

A statistical procedure for testing social reciprocity at group, dyadic and individual levels

This paper examines statistical analysis of social reciprocity, that is, the balance between addressing and receiving behaviour in social interactions. Specifically, it focuses on the measurement of social reciprocity by means of directionality and skew-symmetry statistics at different levels. Two statistics have been used as overall measures of social reciprocity at group level: the directional consistency and the skew-symmetry statistics. Furthermore, the skew-symmetry statistic allows social researchers to obtain complementary information at dyadic and individual levels. However, having computed these measures, social researchers may be interested in testing statistical hypotheses regarding social reciprocity. For this reason, it has been developed a statistical procedure, based on Monte Carlo sampling, in order to allow social researchers to describe groups and make statistical decisions.

Statistical modeling of bowing control applied to violin sound synthesis

Excitation-continuous music instrument control patterns are often not explicitly represented in current sound synthesis techniques when applied to automatic performance. Both physical model-based and sample-based synthesis paradigmswould benefit from a flexible and accurate instrument control model, enabling the improvement of naturalness and realism. Wepresent a framework for modeling bowing control parameters inviolin performance. Nearly non-intrusive sensing techniques allow for accurate acquisition of relevant timbre-related bowing control parameter signals.We model the temporal contour of bow velocity, bow pressing force, and bow-bridge distance as sequences of short Bézier cubic curve segments. Considering different articulations, dynamics, and performance contexts, a number of note classes are defined. Contours of bowing parameters in a performance database are analyzed at note-level by following a predefined grammar that dictates characteristics of curve segment sequences for each of the classes in consideration. As a result, contour analysis of bowing parameters of each note yields an optimal representation vector that is sufficient for reconstructing original contours with significant fidelity. From the resulting representation vectors, we construct a statistical model based on Gaussian mixtures suitable for both the analysis and synthesis of bowing parameter contours. By using the estimated models, synthetic contours can be generated through a bow planning algorithm able to reproduce possible constraints caused by the finite length of the bow. Rendered contours are successfully used in two preliminary synthesis frameworks: digital waveguide-based bowed stringphysical modeling and sample-based spectral-domain synthesis.

Chances and limits of method restriction: a detailed analysis of suicide methods in Switzerland.

The objective of this study was to estimate the potential of method restriction as a public health strategy in suicide prevention. Data from the Swiss Federal Statistical Office and the Swiss Institutes of Forensic Medicine from 2004 were gathered and categorized into suicide submethods according to accessibility to restriction of means. Of suicides in Switzerland, 39.2% are accessible to method restriction. The highest proportions were found in private weapons (13.2%), army weapons (10.4%), and jumps from hot-spots (4.6%). The presented method permits the estimation of the suicide prevention potential of a country by method restriction and the comparison of restriction potentials between suicide methods. In Switzerland, reduction of firearm suicides has the highest potential to reduce the total number of suicides.

EEG windowed statistical wavelet scoring for evaluation and discrimination of muscular artifacts

EEG recordings are usually corrupted by spurious extra-cerebral artifacts, which should be rejected or cleaned up by the practitioner. Since manual screening of human EEGs is inherently error prone and might induce experimental bias, automatic artifact detection is an issue of importance. Automatic artifact detection is the best guarantee for objective and clean results. We present a new approach, based on the time–frequency shape of muscular artifacts, to achieve reliable and automatic scoring. The impact of muscular activity on the signal can be evaluated using this methodology by placing emphasis on the analysis of EEG activity. The method is used to discriminate evoked potentials from several types of recorded muscular artifacts—with a sensitivity of 98.8% and a specificity of 92.2%. Automatic cleaning ofEEGdata are then successfully realized using this method, combined with independent component analysis. The outcome of the automatic cleaning is then compared with the Slepian multitaper spectrum based technique introduced by Delorme et al (2007 Neuroimage 34 1443–9).

Statistical modeling of violin bowing parameter contours

We present a framework for modeling right-hand gestures in bowed-string instrument playing, applied to violin. Nearly non-intrusive sensing techniques allow for accurate acquisition of relevant timbre-related bowing gesture parameter cues. We model the temporal contour of bow transversal velocity, bow pressing force, and bow-bridge distance as sequences of short segments, in particular B´ezier cubic curve segments. Considering different articulations, dynamics, andcontexts, a number of note classes is defined. Gesture parameter contours of a performance database are analyzed at note-level by following a predefined grammar that dictatescharacteristics of curve segment sequences for each of the classes into consideration. Based on dynamic programming, gesture parameter contour analysis provides an optimal curve parameter vector for each note. The informationpresent in such parameter vector is enough for reconstructing original gesture parameter contours with significant fidelity. From the resulting representation vectors, weconstruct a statistical model based on Gaussian mixtures, suitable for both analysis and synthesis of bowing gesture parameter contours. We show the potential of the modelby synthesizing bowing gesture parameter contours from an annotated input score. Finally, we point out promising applicationsand developments.

Analysis of preharvest sprouting in three Brazilian wheat populations

The objective of this work was to evaluate the possibility of obtaining recombinant inbred wheat lines more resistant to preharvest sprouting, independently of colour genes, in three red-grained Brazilian wheat populations. The results showed statistical significance among lines within all populations, which presented a normal distribution and transgressive segregation for preharvest sprouting. The normal distribution of the lines from all red-grained populations suggests that sprouting, excluding the genes expressing seed coat pigmentation, is, probably, controlled by many genes. These findings also indicate that it may be possible to improve resistance to preharvest sprouting, independently of the colour genes.