Dis-sociality (DS) reflects the impairment of social experience in people with schizophrenia; it encompasses both negative features (disorder of attunement, inability to grasp the meaning of social contexts, the vanishing of social shared knowledge) and positive features (a peculiar set of values, ruminations not oriented to reality), reflecting the existential arrangement of people with schizophrenia. DS is grounded on the notion of schizophrenic autism as depicted by continental psychopathology. A rating scale has been developed, providing an experiential phenotype. Here we present the Autism Rating Scale for Schizophrenia - Revised English version (ARSS-Rev), developed on the Italian version of the scale. The scale is provided by a structured interview to facilitate the assessment of the phenomena investigated here. ARSS-Rev is composed of 16 distinctive items grouped into 6 categories: hypo-attunement, invasiveness, emotional flooding, algorithmic conception of sociality, antithetical attitude toward sociality, and idionomia. For each item and category, an accurate description is provided. Different intensities of phenomena are assessed through a Likert scale by rating each item according to its quantitative features (frequency, intensity, impairment, and need for coping). The ARSS-Rev has been able to discriminate patients with remitted schizophrenia from euthymic patients with psychotic bipolar disorder. This instrument may be useful in clinical/research settings to demarcate the boundaries of schizophrenia spectrum disorders from affective psychoses.
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http://dx.doi.org/10.1159/000530588 | DOI Listing |
J Perianesth Nurs
January 2025
Department of Anaesthesia, Intensive Care and Pain Medicine, General Hospital Maria Middelares, Ghent, East Flanders, Belgium.
Purpose: The aim of this study was to assess the correlation between the Visual Analog Scale (VAS), Numeric Rating Scale (NRS), and Verbal Rating Scale (VRS). Additionally, the study aimed to determine NRS threshold values for both mild analgesic administration (= without risk of nausea and vomiting [NV] side effects) and strong analgesic administration (= with risk of NV side effects) in the postanaesthetic care unit (PACU).
Design: Prospective, observational study design.
J Voice
January 2025
Department of Surgery, UMONS Research Institute for Health Sciences and Technology, University of Mons (UMons), Mons, Belgium; Division of Laryngology and Bronchoesophagology, Department of Otolaryngology Head Neck Surgery, EpiCURA Hospital, Baudour, Belgium; Department of Otolaryngology-Head and Neck Surgery, Foch Hospital, School of Medicine, UFR Simone Veil, Université Versailles Saint-Quentin-en-Yvelines (Paris Saclay University), Paris, France; Department of Otolaryngology, Elsan Hospital, Paris, France. Electronic address:
Background: Voice analysis has emerged as a potential biomarker for mood state detection and monitoring in bipolar disorder (BD). The systematic review aimed to summarize the evidence for voice analysis applications in BD, examining (1) the predictive validity of voice quality outcomes for mood state detection, and (2) the correlation between voice parameters and clinical symptom scales.
Methods: A PubMed, Scopus, and Cochrane Library search was carried out by two investigators for publications investigating voice quality in BD according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statements.
Chin J Traumatol
January 2025
Road Traffic Injury Research Center, Tabriz University of Medical Sciences, Tabriz, Iran. Electronic address:
Purpose: Attention-deficit/hyperactivity disorder (ADHD) increases the risk of road traffic injuries through various mechanisms including higher risky driving behaviors. Therefore, drivers with ADHD are shown to be more prone to road traffic injuries. This study was conducted in a community-based sample of drivers to determine how ADHD affects driving behavior components.
View Article and Find Full Text PDFJ Affect Disord
January 2025
Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA; Department of Medicine, Duke University, Durham, NC, USA; Duke Institute of Brain Sciences, Duke University, Durham, NC, USA. Electronic address:
Metabolomics provides powerful tools that can inform about heterogeneity in disease and response to treatments. In this exploratory study, we employed an electrochemistry-based targeted metabolomics platform to assess the metabolic effects of three randomly-assigned treatments: escitalopram, duloxetine, and Cognitive-Behavioral Therapy (CBT) in 163 treatment-naïve outpatients with major depressive disorder. Serum samples from baseline and 12 weeks post-treatment were analyzed using targeted liquid chromatography-electrochemistry for metabolites related to tryptophan, tyrosine metabolism and related pathways.
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