Psychiatric and non-psychiatric patients during the midst of Covid-19: Pandemic distress, psychosis and the belief in conspiracy theories

BACKGROUND

The COVID-19 pandemic was associated with increased levels of psychological distress in the general population, at the same time providing a perfect breeding ground for conspiracy beliefs. Psychiatric patients are considered as a population with an increased vulnerability for stressful events, and conspiracy beliefs show overlaps with paranoid ideations. The aim of the present study was to investigate if psychiatric patients experienced higher levels of pandemic distress than non-psychiatric patients, if they were more prone to conspiracy beliefs and if pandemic distress as well as other mental health variables were associated with believing in conspiracy theories.

METHODS

Indicators for mental health (pandemic distress, depressive symptoms, general anxiety symptoms, perceived stress) and indicators for believing in conspiracy theories were assessed within psychiatric (n = 73) and non-psychiatric patients (n = 29) during the midst of the pandemic.

RESULTS

Psychiatric patients reported higher levels of pandemic distress than non-psychiatric patients. Conspiracy measurements correlated positively with pandemic distress, but not with anxiety and depression. No differences were found between psychiatric patients with or without psychotic disorder and non-psychiatric patients in regard to conspiracy measurements.

CONCLUSION

Our findings suggest a higher susceptibility of psychiatric patients to pandemic distress, but not an increased level of believing in conspiracy theories. The common notion that people suffering from psychosis are more likely to believe in conspiracy theories was not supported. Furthermore, distress caused by a specific event and not anxiety per se seems to be related to the degree of conspiracy beliefs.

Multisensor hyperspectral imaging approach for the microchemical analysis of ultramarine blue pigments

This work presents a multisensor hyperspectral approach for the characterization of ultramarine blue, a valuable historical pigment, at the microscopic scale combining the information of four analytical techniques at the elemental and molecular levels. The hyperspectral images collected were combined in a single hypercube, where the pixels of the various spectral components are aligned on top of each other. Selected spectral descriptors have been defined to reduce data dimensionality before applying unsupervised chemometric data analysis approaches. Lazurite, responsible for the blue color of the pigment, was detected as the major mineral phase present in synthetic and good quality pigments. Impurities like pyrite were detected in lower quality samples, although the clear identification of other mineral phases with silicate basis was more difficult. There is no correlation between the spatial distribution of the bands arising in the Raman spectra of natural samples in the region 1200-1850 cm-1 and any of the transition metals or rare earth elements (REE). With this information, the previous hypothesis (based on bulk analysis) attributing these bands to luminescence emissions due to impurities of these elements must be revised. We propose the consideration of CO2 molecules trapped in the cages of the aluminosilicate structure of sodalite-type. Additionally, correlation between certain Raman features and the combined presence of Ca, P, and REE, in particular Nd, was detected for the lowest quality pigment. Our results highlight the usefulness of fusing chemical images obtained via different imaging techniques to obtain relevant information on chemical structure and properties.

Auditory top-down control and affective theory of mind in schizophrenia with and without hallucinations

Social cognitive impairments may represent a core feature of schizophrenia and above all are a strong predictor of positive psychotic symptoms. Previous studies could show that reduced inhibitory top-down control contributes to deficits in theory of mind abilities and is involved in the genesis of hallucinations. The current study aimed to investigate the relationship between auditory inhibition, affective theory of mind and the experience of hallucinations in patients with schizophrenia. In the present study, 20 in-patients with schizophrenia and 20 healthy controls completed a social cognition task (the Reading the Mind in the Eyes Test) and an inhibitory top-down Dichotic Listening Test. Schizophrenia patients with greater severity of hallucinations showed impaired affective theory of mind as well as impaired inhibitory top-down control. More dysfunctional top-down inhibition was associated with poorer affective theory of mind performance, and seemed to mediate the association between impairment to affective theory of mind and severity of hallucinations. The findings support the idea of impaired theory of mind as a trait marker of schizophrenia. In addition, dysfunctional top-down inhibition may give rise to hallucinations and may further impair affective theory of mind skills in schizophrenia.

Nucleation and Growth of Uniform m-ZRO2

Hydrothermal treatment of zirconyl salt solutions produces uniform m-ZrO2 powder on the order of 80 nm. This powder is porous, has a 3-nm crystallite size, and exhibits an unusually high degree of crystallographic alignment within particles. The generation of this powder occurs via a complex process involving nucleation, growth, and controlled agglomeration of primary particles. Particle formation, crystallographic alignment and particulate uniformity are explained in terms of solution reactions and colloidal behavior.

Preparation of A12O3-ZrO2 Composites by Adjustment of Surface Chemical Behavior

Aqueous colloidal routes for processing binary suspensions containing Al 2 O 3 and ZrO2 were designed and tested in order to achieve homogeneous microstructures. Effects of particle size and size ratio of each component, pH, and electrolyte concentration of composite suspensions on sedimentation, green density, and ZrO2 distribution in sintered microstructures were examined. The pH conditions for inhibiting differential sedimentation without impairing green density were optimized. Overall suspension and coagulation behavior for these composite systems were explained using the DLVO approach. Optimum balance of colloidal and gravitational forces occurred when the secondary minimum heterocoagulation was maximized.

Theoretical considerations of monitor unit calculations for intensity modulated beam treatment planning

A treatment planning system to compute intensity modulated radiotherapy (IMRT) treatments using inverse planning was investigated. The system was designed to optimize the intensity patterns required to treat a specified target volume with specified normal structure constraints. A beam model that uses the convolution of pencil beams was used to compute the dose distributions. A multileaf collimator leaf-setting sequence intended to produce the intensity pattern was computed along with the monitor units required to deliver each of a number of fixed-gantry modulated fields. Computer calculations are commonly verified using an independent manual procedure. It is difficult to calculate treatment delivery monitor units for this variant of IMRT using manual methods. Since manual calculations are not feasible, it is important both to understand and to verify the calculation of treatment monitor units by the planning system algorithm. A formal analysis was made of the dose calculation model and the monitor unit calculation embedded in the algorithm. Experimental verification of the dose delivered by plans computed with the methodology demonstrated an agreement of better than 4% between the dose model and measurements.

Breast tissue classification using diagnostic ultrasound and pattern recognition techniques: I. Methods of pattern recognition

This paper discusses the application of statistical pattern recognition techniques to problems in diagnostic ultrasound. Using our own system as an example, we describe the concepts and specific methods that we have applied to a problem involving the computer-aided classification of breast tissue in vivo. Topics include feature generation, feature selection and classification, as well as a method which estimates the probability of error on classifying future data. An accompanying paper applies these methods to the classification of backscattered RF signals from normal and diseased breast tissue.