160 research outputs found

    Autistic Symptoms and Social Functioning in Psychosis:A Network Approach

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    Psychotic and autistic symptoms are related to social functioning in individuals with psychotic disorders (PD). The present study used a network approach to (1) evaluate the interactions between autistic symptoms, psychotic symptoms, and social functioning, and (2) investigate whether relations are similar in individuals with and without PD. We estimated an undirected network model in a sample of 504 PD, 572 familial risk for psychosis (FR), and 337 typical comparisons (TC), with a mean age of 34.9 years. Symptoms were assessed with the Autism Spectrum Quotient (AQ; 5 nodes) and the Community Assessment of Psychic Experiences (CAPE; 9 nodes). Social functioning was measured with the Social Functioning Scale (SFS; 7 nodes). We identified statistically significant differences between the FR and PD samples in global strength (P < .001) and network structure (P < .001). Our results show autistic symptoms (social interaction nodes) are negatively and more closely related to social functioning (withdrawal, interpersonal behavior) than psychotic symptoms. More and stronger connections between nodes were observed for the PD network than for FR and TC networks, while the latter 2 were similar in density (P = .11) and network structure (P = .19). The most central items in strength for PD were bizarre experiences, social skills, and paranoia. In conclusion, specific autistic symptoms are negatively associated with social functioning across the psychosis spectrum, but in the PD network symptoms may reinforce each other more easily. These findings emphasize the need for increased clinical awareness of comorbid autistic symptoms in psychotic individuals

    Pathways from speech illusions to psychotic symptoms in subjects at Ultra-High Risk for psychosis: combining an experimental measure of aberrant experiences with network analysis

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    Background One of the oldest and most influential theories of psychosis formation states that delusions arise in an attempt to explain unusual experiences, including perceptual aberrations. The White Noise Task by Galdos et al (2011) was developed as an experimental task to assess the tendency to attribute meaning to random perceptual stimuli: speech illusions in white noise. Studies to date have demonstrated that speech illusions as assessed with the White Noise Task are associated with a composite measure of positive symptoms in patients with psychotic disorders (Galdos et al, 2011; Catalan et al, 2014). However, findings in non-clinical samples have been inconsistent: one study found an association with a composite measure of subclinical positive symptoms, including support for a relation with familial psychosis liability (Galdos et al, 2011), whereas other studies did not find any association in non-clinical samples or only partly (Catalan et al, 2014; Rimvall et al, 2016; Pries et al, 2017). The current study aims to further examine whether speech illusions as assessed with the White Noise Task are indicative of psychosis liability and to explore specific symptomatic pathways. Methods We conducted symptom-based network analyses in Ultra-High Risk (UHR) subjects participating in the European network of national networks studying gene-environment interactions in schizophrenia project (EU-GEI, 2014; www.eu-gei.eu). Psychotic symptoms were assessed with the Brief Psychiatric Rating Scale (BPRS). Transition to clinical psychosis was assessed with the Comprehensive Assessment of At Risk Mental State (CAARMS). We used a conservative measure of speech illusions, as described in Catalan et al (2014). Results The current sample consisted of 339 UHR subjects, of which 9.1% (N=31) experienced speech illusions. Preliminary network analyses in cross-sectional baseline data showed potential pathways from speech illusions to delusional ideation, through hallucinatory experiences. We also found evidence of prospective relations between speech illusions at baseline and transition to clinical psychosis. Pathways ran via baseline psychotic symptoms and affective symptoms, as well as a ‘direct’ pathway. Discussion As far as we are aware, this is the first study combining an experimental measure of aberrant experiences with symptom-based network analysis. Although the current reported findings are preliminary and exploratory, they tentatively support a relation between speech illusions as assessed with the White Noise Task and psychosis liability. This relation may be dependent on sample composition, and not generalizable to the general population as a whole. Future studies may benefit from focusing on more detailed trajectories of both susceptibility to speech illusions and course of (sub)clinical psychotic symptom severity in subjects with increased risk for psychosis, with use of more frequent, short assessment periods and inclusion of environmental risk factors for transition to clinical disorder

    Insight, personality, and symptoms among individuals with psychosis:Cross-sectional and longitudinal relationships

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    BACKGROUND: Reports on the relationship between clinical insight and psychotic symptoms have shown inconsistent results, and the association between clinical insight and personality has rarely been addressed. The aim of this study was to examine whether personality is correlated cross-sectionally with insight level, and longitudinally with change in insight, beyond symptoms. METHODS: Participants were a sub-sample of the Dutch Genetic Risk and Outcome of Psychosis (GROUP) project. Two hundred and eleven participants diagnosed with non-affective psychotic disorders took part in the cross-sectional part of the study, of whom 136 took part in the three-year follow-up assessment. They were administered with self-report Birchwood insight scale and NEO-Five Factor Inventory, and clinicians assessed them according to PANSS and CDS symptoms scales. RESULTS: Cross-sectional analysis showed baseline self-report insight was positively related to neuroticism and agreeableness and negatively related to extraversion. Longitudinal analysis showed change in level of self-reported insight was predicted by baseline-insight and change in symptoms of disorganization. Personality factors did not predict insight change (as measured either by self-report or by clinician assessment). DISCUSSION: The cross-sectional findings showed self-report insight (as opposed to clinician-rated) is associated with personality traits, suggesting negative affect is related to higher level of insight and that having insight may be influenced by the wish to comply with views of professionals, or a tendency to cover up problems. The longitudinal findings imply that not personality but change in severity of symptoms of disorganization, and possibly other variables, predicts change in insight

    Impact of coping styles on substance use in persons with psychosis, siblings, and controls

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    BACKGROUND: Substance use is overrepresented in patients with psychosis. Maladaptive coping has been proposed as one of the mechanisms which might underlie this high prevalence. Patients are known to apply more maladaptive coping compared to the healthy population. However, it is unknown whether coping is associated with the use of different substances across those with different vulnerability for psychosis, and whether coping mediates the possible association between life events and substance use. METHODS: In this multicenter, cohort study, 429 patients, 504 siblings, and 220 controls were included. We determined whether coping was associated with tobacco smoking, cannabis use, or alcohol consumption. Multivariable logistic regression models were applied whilst correcting for potential confounders. We performed post-hoc analyses to explore the association between negative life events, tobacco smoking, and the role of coping as a mediator in patients with psychosis. RESULTS: A positive association was found in patients between passive coping and tobacco smoking (fully adjusted OR 1.65, 95% CI 1.18-2.31). Tobacco smoking patients experienced more negative life events compared to non-smoking patients and passive coping mediated this association. In siblings and controls, none of the coping strategies were associated with substance use. CONCLUSIONS: The coping style of patients with psychosis is associated with tobacco smoking and mediates the association between negative events and tobacco smoking. No significant associations were found in siblings, controls or concerning other substance use. Future research is required to examine whether enhancing healthy coping strategies decreases tobacco use in patients with psychosis

    The Association Between Exposure to COVID-19 and Mental Health Outcomes Among Healthcare Workers

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    Due to the unprecedented impact of the COVID-19 pandemic on health care systems, there has been great interest in the mental wellbeing of healthcare workers. While most studies investigated mental health outcomes among frontline vs. non-frontline healthcare workers, little is known about the impact of various work-related variables. The present study aimed to examine the association between work-related [i.e., having contact with COVID-19 patients, being redeployed due to the pandemic and availability of sufficient personal protective equipment (PPE)] and subjective (i.e., worries about getting infected or infecting others) exposures and self-reported mental health outcomes (i.e., psychological distress, depressive symptoms, and posttraumatic stress symptoms). Between February and May 2021, 994 healthcare workers employed at a variety of healthcare settings in the Netherlands filled out an online survey as part of the COVID-19 HEalth caRe wOrkErS (HEROES) study. Mental health outcomes were measured using the General Health Questionnaire-12, the Patient Health Questionnaire-9, and the Primary Care PTSD Screen for DSM-5. Approximately 13% reported depressive symptoms, 37% experienced psychological distress, and 20% reported posttraumatic stress symptoms. Multilevel linear models consisted of three levels: individual (work-related and subjective exposures), healthcare center (aggregated redeployment and availability of sufficient PPE), and regional (cumulative COVID-19 infection and death rates). Worries about infection were associated with all three mental health outcomes, whereas insufficient PPE was associated with psychological distress and depressive symptoms. There were no differences in outcomes between healthcare centers or provinces with different COVID-19 infection and death rates. Our findings highlight the importance of adequate PPE provision and the subjective experience of the COVID-19 pandemic. These factors should be part of interventions aimed at mitigating adverse mental health outcomes among healthcare workers during the COVID-19 pandemic

    The association between smoking behaviour, social cognition and social functioning in patients with a non-affective psychotic disorder:A prospective follow-up study

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    INTRODUCTION: In patients with psychotic disorders, both tobacco smoking and deficits in social cognition and social functioning are highly prevalent. However, little is known about their relationship in psychosis. The authors sought to evaluate the multi-cross-sectional and longitudinal associations between tobacco smoking, social cognition and social functioning in a large prospective study. METHODS: This study was performed within the Genetic Risk and Outcome of Psychosis (GROUP) Study, a cohort study conducted in patients with non-affective psychosis (N = 1074), their unaffected siblings (N = 1047) and healthy controls (N = 549). At baseline, three years and six years of follow-up, data on tobacco smoking (using the Composite International Diagnostic Review), social cognition (emotion processing and theory of mind) and social functioning were collected. To assess associations between tobacco smoking and social cognition or social functioning, multivariate linear mixed-effects models and multiple linear regression models were used. Bonferroni correction for multiple testing was applied. RESULTS: A significant positive association was found between smoking and emotion processing (as part of social cognition) in the patient group (estimate = 1.96, SE = 0.6, p = 0.003). However, smoking was significantly negatively associated with participating in pro-social activities compared with smoking (estimate = 2.55, SE = 0.9, p = 0.004). Change in smoking behaviour was not associated with social cognition or social functioning in the longitudinal analyses. CONCLUSION: Findings indicate that smoking patients with a non-affective psychotic disorder slightly outperformed their non-smoking peers on a task on social cognition, but participated less in pro-social activities. Commencement or cessation of smoking was not related to social cognition or functioning

    Associations between genetic liabilities to smoking behavior and schizophrenia symptoms in patients with a psychotic disorder, their siblings and healthy controls

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    It is unknown how smoking behavior polygenic scores (PRS) relate to psychosis and psychotic symptoms. To elucidate this, genotype and phenotype data were collected from patients with schizophrenia, their unaffected siblings, and healthy controls in a six-year follow-up prospective cohort study. Associations between smoking behaviors, PRS and schizophrenia symptoms were explored using linear mixed-effect models. The mean number of cigarettes smoked per day were 18 for patients, 13 for siblings and 12 for controls. In the overall sample, PRSs-smoking initiation (i.e., ever smoking as a binary phenotype, PRS-SI) were positively associated with positive symptoms, negative symptoms, and depressive symptoms, whereas PRSs-AI (age at regular smoking initiation) were negatively associated with all symptom dimensions, with similar effect sizes. When considering groups separately, PRS were only associated with psychotic symptoms in siblings and controls. In conclusion, unaffected siblings show smoking behaviors at an intermediate level between patients and healthy controls. Additionally, PRS-SI and PRS-AI are associated with all symptom dimensions only in unaffected siblings and healthy controls, possibly owing to the dominant role of other (genetic) risk factors in patients. Future studies may examine mechanisms via which genetic risk for smoking affects mental health symptoms.</p

    The Community Assessment of Psychic Experiences:Optimal cut-off scores for detecting individuals with a psychotic disorder

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    OBJECTIVES: The need for a brief screening tool for psychosis is widely recognized. The Community Assessment of Psychic Experiences (CAPE) is a popular self‐report measure of psychosis, but a cut‐off score that can detect those most likely to fulfill diagnostic criteria for psychotic disorder is not established. METHODS: A case–control sample from the Genetic Risk and Outcome of Psychosis Project study (N = 1375, healthy individuals, n = 507, and individuals with a psychotic disorder, n = 868), was used to examine cut‐off scores of the CAPE with receiver operating curve analyses. We examined 27 possible cut‐off scores computed from a combination of scores from the frequency and distress scales of the various factors of the CAPE. RESULTS: The weighted severity positive symptom dimension was most optimal in detecting individuals with a psychotic disorder (>1.75 cut‐off; area under the curve = 0.88; sensitivity, 75%; specificity, 88%), which correctly identified 80% of the sample as cases or controls with a diagnostic odds ratio of 22.69. CONCLUSIONS: The CAPE can be used as a first screening tool to detect individuals who are likely to fulfill criteria for a psychotic disorder. The >1.75 cut‐off of the weighted severity positive symptom dimension provides a better prediction than all alternatives tested so far

    A Cross-sectional Conceptual Replication and Longitudinal Evaluation of the PANSS-Autism-Severity-Score Measure Suggests it Does Not Capture Autistic Traits in Individuals With Psychosis

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    Background Autism and psychosis co-occur at elevated rates, with implications for clinical outcomes, functioning, and suicidality. The PANSS-Autism-Severity-Score (PAUSS) is a measure of autism trait severity which has not yet been validated externally or longitudinally. Study Design Participants were derived from the GROUP and SCOPE datasets. Participants included 1448 adults with schizophrenia spectrum disorder (SSD), 800 SSD-siblings, 103 adults diagnosed with an autistic spectrum condition (ASC), and 409 typically-developing controls (TC). Analyses from the original validation study were conducted with SSD participants, and extended into ASC, SSD-sibling, and TC participants. Test–retest reliability of the PAUSS at 2-weeks and long-term stability 3 and 6-years was also examined. Study Results Results differed in important ways from the original validation. SSD participants reported higher PAUSS scores than other groups, with only a fraction of ASC participants scoring as “PAUSS-Autistic.” Cronbach’s alpha was acceptable for the SSD cohort only. Two-week stability of the PAUSS was fair to good for all PAUSS scores. Long-term stability was poor for most PAUSS items but fair for total PAUSS score. Conclusions Results suggest that the PAUSS does not appear appropriate for assessing autism, with the low rate of PAUSS-Autistic in the ASC population suggesting the PAUSS may not accurately reflect characteristics of autism. The relative lack of long-term stability is cause for concern and suggestive that the PAUSS is capturing features of psychosis rather than autism traits

    Polygenic risk score for schizophrenia was not associated with glycemic level (HbA1c) in patients with non-affective psychosis: Genetic Risk and Outcome of Psychosis (GROUP) cohort study

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    Introduction: Type 2 diabetes (T2D) is a common comorbidity in patients with schizophrenia (SCZ). The underlying pathophysiologic mechanisms are yet to be fully elucidated, although it can be argued that shared genes, environmental factors or their interaction effect are involved. This study investigated the association between polygenic risk score of SCZ (PRSSCZ) and glycated haemoglobin (HbA1c) while adjusting for polygenic risk score of T2D (PRST2D), and clinical and demographic covariables. Methods: Genotype, clinical and demographic data of 1129 patients with non-affective psychosis were extracted from Genetic Risk and Outcome of Psychosis (GROUP) cohort study. The glycated haemoglobin (HbA1c) was the outcome. PRS was calculated using standard methods. Univariable and multivariable linear regression analyses were applied to estimate associations. Additionally, sensitivity analysis based on multiple imputation was done. After correction for multiple testing, a two-sided p-value ≤.003 was considered to discover evidence for an association. Results: Of 1129 patients, 75.8% were male with median age of 29 years. The mean (standard deviation) HbA1c level was 35.1 (5.9) mmol/mol. There was no evidence for an association between high HbA1c level and increased PRSSCZ (adjusted regression coefficient (aβ) = 0.69, standard error (SE) = 0.77, p-value =.37). On the other hand, there was evidence for an association between high HbA1c level and increased PRST2D (aβ = 0.93, SE = 0.32, p-value =.004), body mass index (aβ = 0.20, SE = 0.08, p-value =.01), diastolic blood pressure (aβ = 0.08, SE = 0.04, p-value =.03), late age of first psychosis onset (aβ = 0.19, SE = 0.05, p-value =.0004) and male gender (aβ = 1.58, SE = 0.81, p-value =.05). After multiple testing correction, there was evidence for an association between high HbA1c level and late age of first psychosis onset. Evidence for interaction effect between PRSscz and antipsychotics was not observed. The multiple imputation-based sensitivity analysis provided consistent results with complete case analysis. Conclusions: Glycemic dysregulation in patients with SCZ was not associated with PRSSCZ. This suggests that the mechanisms of hyperglycemia or diabetes are at least partly independent from genetic predisposition to SCZ. Our findings show that the change in HbA1c level can be caused by at least in part due to PRST2D, late age of illness onset, male gender, and increased body mass index and diastolic blood pressure
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