Abnormal illness behavior and Internet addiction severity: The role of disease conviction, irritability, and alexithymia

While the association between health anxiety and maladaptive Internet use is a well-established finding, no studies have been performed to examine the possible effect of abnormal illness behavior (AIB). AIB is a maladaptive manner of experiencing, evaluating, or acting in response to health and illness that is disproportionate to evident pathology. The aim of this study was to investigate the association between AIB and Internet addiction (IA) severity in a sample of Italian University students. The possible effect of alexithymia, anxiety, and depression was also taken into account. Methods Participants were 115 men and 163 women (mean age = 23.62 ± 4.38 years); AIB was measured via the Illness Behavior Questionnaire (IBQ), and IA severity by the Internet Addiction Test (IAT). Results The most powerful IBQ factor predicting IA severity scores was disease conviction. Irritability was the only emotional IBQ factor associated with IA severity. Nevertheless, disease conviction and alexithymia remained the only significant predictors of IAT scores when hierarchical regression analysis was executed. Discussion and conclusions Our results support previous findings showing that those characterized by health anxiety are more prone to an excessive and maladaptive use of Internet. Moreover, this study showed that irritability was the only emotional aspect of AIB predicting IA severity. This finding is consistent with the cognitive model of hypochondria, which states that cognitive factors (dysfunctional beliefs and assumptions) play a major role in the explanation of this psychopathological condition

Accuracy of invasive arterial pressure monitoring in cardiovascular patients: An observational study

INTRODUCTION: Critically ill patients and patients undergoing high-risk and major surgery, are instrumented with intra-arterial catheters and invasive blood pressure is considered the “gold standard” for arterial pressure monitoring. Nonetheless, artifacts due to inappropriate dynamic response of the fluid-filled monitoring systems may lead to clinically relevant differences between actual and displayed pressure values. We sought to analyze the incidence and causes of resonance/underdamping phenomena in patients undergoing major vascular and cardiac surgery. METHODS: Arterial pressures were measured invasively and, according to the fast-flush Gardner’s test, each patient was attributed to one of two groups depending on the presence (R-group) or absence (NR-group) of resonance/underdamping. Invasive pressure values were then compared with the non-invasive ones. RESULTS: A total of 11,610 pulses and 1,200 non-invasive blood pressure measurements were analyzed in 300 patients. Ninety-two out of 300 (30.7%) underdamping/resonance arterial signals were found. In these cases (R-group) systolic invasive blood pressure (IBP) average overestimation of non-invasive blood pressure (NIBP) was 28.5 (15.9) mmHg (P <0.0001) while in the NR-group the overestimation was 4.1(5.3) mmHg (P <0.0001). The mean IBP-NIBP difference in diastolic pressure in the R-group was −2.2 (10.6) mmHg and, in the NR-group −1.1 (5.8) mmHg. The mean arterial pressure difference was 7.4 (11.2) mmHg in the R-group and 2.3 (6.4) mmHg in the NR-group. A multivariate logistic regression identified five parameters independently associated with underdamping/resonance: polydistrectual arteriopathy (P =0.0023; OR = 2.82), history of arterial hypertension (P =0.0214; OR = 2.09), chronic obstructive pulmonary disease (P =0.198; OR = 2.61), arterial catheter diameter (20 vs. 18 gauge) (P <0.0001; OR = 0.35) and sedation (P =0.0131; OR = 0.5). The ROC curve for the maximal pressure–time ratio, showed an optimum selected cut-off point of 1.67 mmHg/msec with a specificity of 97% (95% CI: 95.13 to 99.47%) and a sensitivity of 77% (95% CI: 67.25 to 85.28%) and an area under the ROC curve by extended trapezoidal rule of 0.88. CONCLUSION: Physicians should be aware of the possibility that IBP can be inaccurate in a consistent number of patients due to underdamping/resonance phenomena. NIBP measurement may help to confirm/exclude the presence of this artifact avoiding inappropriate treatments

Duration of Untreated Disorder and Cannabis Use: An Observational Study on a Cohort of Young Italian Patients Experiencing Psychotic Experiences and Dissociative Symptoms

© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).Background: The Duration of Untreated Psychosis (DUP) is the time between the first-episode psychosis (FEP) and the initiation of antipsychotic treatment. It is an important predictor of several disease-related outcomes in psychotic disorders. The aim of this manuscript is investigating the influence of cannabis on the DUP and its clinical correlates. Methods: During years 2014−2019, sixty-two FEP patients with and without cannabis use disorder (CUD) were recruited from several Italian psychiatric hospitals. The subjects were then divided into two groups based on the duration of the DUP and assessed at the beginning of the antipsychotic treatment and after 3 and 6 months, using the Positive and Negative Syndrome Scale (PANSS), the Global Assessment of Functioning (GAF) scale, and the Dissociative Experiences Scale (DES-II). Results: As expected, a longer DUP was associated with worse symptoms and cannabis use did not seem to affect the DUP, but both were related with more dissociative symptoms at onset and over time. Discussion: According to our study, cannabis use can be a predictor of FEP and DUP, and of disease outcome. However, several factors might influence the relationship between cannabis use and DUP. Preventing cannabis use and early diagnosis of psychotic disorders might impact the disease by reducing the persistence of symptoms and limiting dissociative experiences.Peer reviewedFinal Published versio

A Prediction Modelling and Pattern Detection Approach for the First-Episode Psychosis Associated to Cannabis Use

Over the last two decades, a significant body of research has established a link between cannabis use and psychotic outcomes. In this study, we aim to propose a novel symbiotic machine learning and statistical approach to pattern detection and to developing predictive models for the onset of first-episode psychosis. The data used has been gathered from real cases in cooperation with a medical research institution, and comprises a wide set of variables including demographic, drug-related, as well as several variables specifically related to the cannabis use. Our approach is built upon several machine learning techniques whose predictive models have been optimised in a computationally intensive framework. The ability of these models to predict first-episode psychosis has been extensively tested through large scale Monte Carlo simulations. Our results show that Boosted Classification Trees outperform other models in this context, and have significant predictive ability despite a large number of missing values in the data. Furthermore, we extended our approach by further investigating how different patterns of cannabis use relate to new cases of psychosis, via association analysis and Bayesian techniques

Association of extent of cannabis use and psychotic like intoxication experiences in a multi-national sample of first episode psychosis patients and controls

BackgroundFirst episode psychosis (FEP) patients who use cannabis experience more frequent psychotic and euphoric intoxication experiences compared to controls. It is not clear whether this is consequent to patients being more vulnerable to the effects of cannabis use or to their heavier pattern of use. We aimed to determine whether extent of use predicted psychotic-like and euphoric intoxication experiences in patients and controls and whether this differs between groups.MethodsWe analysed data on patients who had ever used cannabis (n = 655) and controls who had ever used cannabis (n = 654) across 15 sites from six countries in the EU-GEI study (2010–2015). We used multiple regression to model predictors of cannabis-induced experiences and to determine if there was an interaction between caseness and extent of use.ResultsCaseness, frequency of cannabis use and money spent on cannabis predicted psychotic-like and euphoric experiences (p ⩽ 0.001). For psychotic-like experiences (PEs) there was a significant interaction for caseness × frequency of use (p 0.5).ConclusionsFEP patients are particularly sensitive to increased psychotic-like, but not euphoric experiences, at higher levels of cannabis use compared to controls. This suggests a specific psychotomimetic response in FEP patients related to heavy cannabis use. Clinicians should enquire regarding cannabis related PEs and advise that lower levels of cannabis use are associated with less frequent PEs

Daily use of high-potency cannabis is associated with more positive symptoms in first-episode psychosis patients: the EU-GEI case-control study.

BACKGROUND: Daily use of high-potency cannabis has been reported to carry a high risk for developing a psychotic disorder. However, the evidence is mixed on whether any pattern of cannabis use is associated with a particular symptomatology in first-episode psychosis (FEP) patients. METHOD: We analysed data from 901 FEP patients and 1235 controls recruited across six countries, as part of the European Network of National Schizophrenia Networks Studying Gene-Environment Interactions (EU-GEI) study. We used item response modelling to estimate two bifactor models, which included general and specific dimensions of psychotic symptoms in patients and psychotic experiences in controls. The associations between these dimensions and cannabis use were evaluated using linear mixed-effects models analyses. RESULTS: In patients, there was a linear relationship between the positive symptom dimension and the extent of lifetime exposure to cannabis, with daily users of high-potency cannabis having the highest score (B = 0.35; 95% CI 0.14-0.56). Moreover, negative symptoms were more common among patients who never used cannabis compared with those with any pattern of use (B = -0.22; 95% CI -0.37 to -0.07). In controls, psychotic experiences were associated with current use of cannabis but not with the extent of lifetime use. Neither patients nor controls presented differences in depressive dimension related to cannabis use. CONCLUSIONS: Our findings provide the first large-scale evidence that FEP patients with a history of daily use of high-potency cannabis present with more positive and less negative symptoms, compared with those who never used cannabis or used low-potency types.The work was supported by: Clinician Scientist Medical Research Council fellowship (project reference MR/M008436/1) to MDF; the National Institute for Health Research (NIHR) Collaboration for Leadership in Applied Health Research and Care South London at King's College Hospital NHS Foundation Trust to DQ; DFG Heisenberg professorship (no. 389624707) to UR. National Institute for Health Research (NIHR) Biomedical Research Centre for Mental Health at South London and Maudsley NHS Foundation Trust and King’s College London. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care. The EU-GEI Project is funded by the European Community’s Seventh Framework Programme under grant agreement No. HEALTH-F2-2010-241909 (Project EU-GEI). The Brazilian study was funded by the São Paulo Research Foundation under grant number 2012/0417-0

The continuity of effect of schizophrenia polygenic risk score and patterns of cannabis use on transdiagnostic symptom dimensions at first-episode psychosis: findings from the EU-GEI study.

Diagnostic categories do not completely reflect the heterogeneous expression of psychosis. Using data from the EU-GEI study, we evaluated the impact of schizophrenia polygenic risk score (SZ-PRS) and patterns of cannabis use on the transdiagnostic expression of psychosis. We analysed first-episode psychosis patients (FEP) and controls, generating transdiagnostic dimensions of psychotic symptoms and experiences using item response bi-factor modelling. Linear regression was used to test the associations between these dimensions and SZ-PRS, as well as the combined effect of SZ-PRS and cannabis use on the dimensions of positive psychotic symptoms and experiences. We found associations between SZ-PRS and (1) both negative (B = 0.18; 95%CI 0.03-0.33) and positive (B = 0.19; 95%CI 0.03-0.35) symptom dimensions in 617 FEP patients, regardless of their categorical diagnosis; and (2) all the psychotic experience dimensions in 979 controls. We did not observe associations between SZ-PRS and the general and affective dimensions in FEP. Daily and current cannabis use were associated with the positive dimensions in FEP (B = 0.31; 95%CI 0.11-0.52) and in controls (B = 0.26; 95%CI 0.06-0.46), over and above SZ-PRS. We provide evidence that genetic liability to schizophrenia and cannabis use map onto transdiagnostic symptom dimensions, supporting the validity and utility of the dimensional representation of psychosis. In our sample, genetic liability to schizophrenia correlated with more severe psychosis presentation, and cannabis use conferred risk to positive symptomatology beyond the genetic risk. Our findings support the hypothesis that psychotic experiences in the general population have similar genetic substrates as clinical disorders

Treated Incidence of Psychotic Disorders in the Multinational EU-GEI Study

Importance: Psychotic disorders contribute significantly to the global disease burden, yet the latest international incidence study of psychotic disorders was conducted in the 1980s. Objectives: To estimate the incidence of psychotic disorders using comparable methods across 17 catchment areas in 6 countries and to examine the variance between catchment areas by putative environmental risk factors. Design, Setting, and Participants: An international multisite incidence study (the European Network of National Schizophrenia Networks Studying Gene-Environment Interactions) was conducted from May 1, 2010, to April 1, 2015, among 2774 individuals from England (2 catchment areas), France (3 catchment areas), Italy (3 catchment areas), the Netherlands (2 catchment areas), Spain (6 catchment areas), and Brazil (1 catchment area) with a first episode of nonorganic psychotic disorders (International Statistical Classification of Diseases and Related Health Problems, Tenth Revision [ICD-10] codes F20-F33) confirmed by the Operational Criteria Checklist. Denominator populations were estimated using official national statistics. Exposures: Age, sex, and racial/ethnic minority status were treated as a priori confounders. Latitude, population density, percentage unemployment, owner-occupied housing, and single-person households were treated as catchment area-level exposures. Main Outcomes and Measures: Incidence of nonorganic psychotic disorders (ICD-10 codes F20-F33), nonaffective psychoses (ICD-10 codes F20-F29), and affective psychoses (ICD-10 codes F30-F33) confirmed by the Operational Criteria Checklist. Results: A total of 2774 patients (1196 women and 1578 men; median age, 30.5 years [interquartile range, 23.0-41.0 years]) with incident cases of psychotic disorders were identified during 12.9 million person-years at risk (crude incidence, 21.4 per 100 000 person-years; 95% CI, 19.4-23.4 per 100 000 person-years). A total of 2183 patients (78.7%) had nonaffective psychotic disorders. After direct standardization for age, sex, and racial/ethnic minority status, an 8-fold variation was seen in the incidence of all psychotic disorders, from 6.0 (95% CI, 3.5-8.6) per 100 000 person-years in Santiago, Spain, to 46.1 (95% CI, 37.3-55.0) per 100 000 person-years in Paris, France. Rates were elevated in racial/ethnic minority groups (incidence rate ratio, 1.6; 95% CI, 1.5-1.7), were highest for men 18 to 24 years of age, and were lower in catchment areas with more owner-occupied homes (incidence rate ratio, 0.8; 95% CI, 0.7-0.8). Similar patterns were observed for nonaffective psychoses; a lower incidence of affective psychoses was associated with higher area-level unemployment (incidence rate ratio, 0.3; 95% CI, 0.2-0.5). Conclusions and Relevance: This study confirmed marked heterogeneity in risk for psychotic disorders by person and place, including higher rates in younger men, racial/ethnic minorities, and areas characterized by a lower percentage of owner-occupied houses.The European Network of National Schizophrenia Networks Studying Gene-Environment Interactions (EU-GEI) Project is funded by grant agreement HEALTH-F2-2010-241909 (Project EU-GEI) from the European Community’s Seventh Framework Programme. The Brazilian study was funded by grant 2012/0417-0 from the São Paulo Research Foundation. Dr Kirkbride is funded by the Wellcome Trust and grant 101272/Z/13/Z from the Royal Society. Ms Jongsma and Dr Jones are funded by the National Institute of Health Research Collaboration of Leadership in Applied Health Research and Care East of England

Genetic and psychosocial stressors have independent effects on the level of subclinical psychosis: findings from the multinational EU-GEI study

Aims: Gene x environment (G×E) interactions, i.e. genetic modulation of the sensitivity to environmental factors and/or environmental control of the gene expression, have not been reliably established regarding aetiology of psychotic disorders. Moreover, recent studies have shown associations between the polygenic risk scores for schizophrenia (PRS-SZ) and some risk factors of psychotic disorders, challenging the traditional gene v. environment dichotomy. In the present article, we studied the role of GxE interaction between psychosocial stressors (childhood trauma, stressful life-events, self-reported discrimination experiences and low social capital) and the PRS-SZ on subclinical psychosis in a population-based sample. Methods: Data were drawn from the EUropean network of national schizophrenia networks studying Gene-Environment Interactions (EU-GEI) study, in which subjects without psychotic disorders were included in six countries. The sample was restricted to European descendant subjects (n = 706). Subclinical dimensions of psychosis (positive, negative, and depressive) were measured by the Community Assessment of Psychic Experiences (CAPE) scale. Associations between the PRS-SZ and the psychosocial stressors were tested. For each dimension, the interactions between genes and environment were assessed using linear models and comparing explained variances of 'Genetic' models (solely fitted with PRS-SZ), 'Environmental' models (solely fitted with each environmental stressor), 'Independent' models (with PRS-SZ and each environmental factor), and 'Interaction' models (Independent models plus an interaction term between the PRS-SZ and each environmental factor). Likelihood ration tests (LRT) compared the fit of the different models. Results: There were no genes-environment associations. PRS-SZ was associated with positive dimensions (β = 0.092, R2 = 7.50%), and most psychosocial stressors were associated with all three subclinical psychotic dimensions (except social capital and positive dimension). Concerning the positive dimension, Independent models fitted better than Environmental and Genetic models. No significant GxE interaction was observed for any dimension. Conclusions: This study in subjects without psychotic disorders suggests that (i) the aetiological continuum hypothesis could concern particularly the positive dimension of subclinical psychosis, (ii) genetic and environmental factors have independent effects on the level of this positive dimension, (iii) and that interactions between genetic and individual environmental factors could not be identified in this sample

The EUropean Network of National Schizophrenia Networks Studying Gene-Environment Interactions (EU-GEI): Incidence and First-Episode Case-Control Programme.

PURPOSE: The EUropean Network of National Schizophrenia Networks Studying Gene-Environment Interactions (EU-GEI) study contains an unparalleled wealth of comprehensive data that allows for testing hypotheses about (1) variations in incidence within and between countries, including by urbanicity and minority ethnic groups; and (2) the role of multiple environmental and genetic risk factors, and their interactions, in the development of psychotic disorders. METHODS: Between 2010 and 2015, we identified 2774 incident cases of psychotic disorders during 12.9 million person-years at risk, across 17 sites in 6 countries (UK, The Netherlands, France, Spain, Italy, and Brazil). Of the 2774 incident cases, 1130 cases were assessed in detail and form the case sample for case-control analyses. Across all sites, 1497 controls were recruited and assessed. We collected data on an extensive range of exposures and outcomes, including demographic, clinical (e.g. premorbid adjustment), social (e.g. childhood and adult adversity, cannabis use, migration, discrimination), cognitive (e.g. IQ, facial affect processing, attributional biases), and biological (DNA via blood sample/cheek swab). We describe the methodology of the study and some descriptive results, including representativeness of the cohort. CONCLUSIONS: This resource constitutes the largest and most extensive incidence and case-control study of psychosis ever conducted.The EU-GEI Study is funded by grant agreement HEALTH-F2-2010-241909 (Project EU-GEI) from the European Community’s Seventh Framework Programme, and grant 2012/0417-0 from the São Paulo Research Foundatio