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BackgroundCo-occurrence of common mental disorders (CMD) with psychotic experiences is well-known. There is little research on the public mental health relevance of concurrent psychotic experiences for service use, suicidality, and poor physical health. We aim to: (1) describe the distribution of psychotic experiences co-occurring with a range of non-psychotic psychiatric disorders [CMD, depressive episode, anxiety disorder, probable post-traumatic stress disorder (PTSD), and personality dysfunction], and (2) examine associations of concurrent psychotic experiences with secondary mental healthcare use, psychological treatment use for CMD, lifetime suicide attempts, and poor self-rated health.MethodsWe linked a prospective cross-sectional community health survey with a mental healthcare provider database. For each non-psychotic psychiatric disorder, patients with concurrent psychotic experiences were compared to those without psychotic experiences on use of secondary mental healthcare, psychological treatment for CMD, suicide attempt, physical functioning, and a composite multimorbidity score, using logistic regression and Cox regressions.ResultsIn all disorders except for anxiety disorder, concurrent psychotic experiences were accompanied by a greater odds of all outcomes (odds ratios) for a unit change in composite multimorbidity score ranged between 2.21 [95% confidence interval (CI) 1.49–3.27] and 3.46 (95% CI 1.52–7.85). Hazard ratios for secondary mental health service use for non-psychotic disorders with concurrent psychotic experiences, ranged from 0.53 (95% CI 0.15–1.86) for anxiety disorders with psychotic experiences to 4.99 (95% CI 1.22–20.44) among those with PTSD with psychotic experiences.ConclusionsCo-occurring psychotic experiences indicate greater public mental health burden, suggesting psychotic experiences could be a marker for future preventive strategies improving public mental health.

BackgroundAssessment of risks of illnesses has been an important part of medicine for decades. We now have hundreds of ‘risk calculators’ for illnesses, including brain disorders, and these calculators are continually improving as more diverse measures are collected on larger samples.MethodsWe first replicated an existing psychosis risk calculator and then used our own sample to develop a similar calculator for use in recruiting ‘psychosis risk’ enriched community samples. We assessed 632 participants age 8–21 (52% female; 48% Black) from a community sample with longitudinal data on neurocognitive, clinical, medical, and environmental variables. We used this information to predict psychosis spectrum (PS) status in the future. We selected variables based on lasso, random forest, and statistical inference relief; and predicted future PS using ridge regression, random forest, and support vector machines.ResultsCross-validated prediction diagnostics were obtained by building and testing models in randomly selected sub-samples of the data, resulting in a distribution of the diagnostics; we report the mean. The strongest predictors of later PS status were the Children's Global Assessment Scale; delusions of predicting the future or having one's thoughts/actions controlled; and the percent married in one's neighborhood. Random forest followed by ridge regression was most accurate, with a cross-validated area under the curve (AUC) of 0.67. Adjustment of the model including only six variables reached an AUC of 0.70.ConclusionsResults support the potential application of risk calculators for screening and identification of at-risk community youth in prospective investigations of developmental trajectories of the PS.

Background.Recent randomized controlled trials suggest some efficacy for focused interventions in subjects at high risk (HR) for psychosis. However, treating HR subjects within the real-world setting of prodromal services is hindered by several practical problems that can significantly make an impact on the effect of focused interventions.Method.All subjects referred to Outreach and Support in South London (OASIS) and diagnosed with a HR state in the period 2001–2012 were included (n = 258). Exposure to focused interventions was correlated with sociodemographic and clinical characteristics at baseline. Their association with longitudinal clinical and functional outcomes was addressed at follow-up.Results.In a mean follow-up time of 6 years (s.d. = 2.5 years) a transition risk of 18% was observed. Of the sample, 33% were treated with cognitive behavioural therapy (CBT) only; 17% of subjects received antipsychotics (APs) in addition to CBT sessions. Another 17% of subjects were prescribed with antidepressants (ADs) in addition to CBT. Of the sample, 20% were exposed to a combination of interventions. Focused interventions had a significant relationship with transition to psychosis. The CBT + AD intervention was associated with a reduced risk of transition to psychosis, as compared with the CBT + AP intervention (hazards ratio = 0.129, 95% confidence interval 0.030–0.565, p = 0.007).Conclusions.There were differential associations with transition outcome for AD v. AP interventions in addition to CBT in HR subjects. These effects were not secondary to baseline differences in symptom severity.

BackgroundCannabis use is associated with an increased risk of developing a psychotic disorder but the temporal relationship between cannabis use and onset of illness is unclear. The objective of this study was to assess prospectively the influence of cannabis use on transition to psychosis in people at ultra-high risk (UHR) for the disorder.MethodLifetime and continued cannabis use was assessed in a consecutively ascertained sample of 182 people (104 male, 78 female) at UHR for psychosis. Individuals were then followed clinically for 2 years to determine their clinical outcomes.ResultsLifetime cannabis use was reported by 134 individuals (73.6%). However, most of these individuals had stopped using cannabis before clinical presentation (n = 98, 73.1%), usually because of adverse effects. Among lifetime users, frequent use, early-onset use and continued use after presentation were all associated with an increase in transition to psychosis. Transition to psychosis was highest among those who started using cannabis before the age of 15 years and went on to use frequently (frequent early-onset use: 25%; infrequent or late-onset use: 5%; χ21 = 10.971, p = 0.001). However, within the whole sample, cannabis users were no more likely to develop psychosis than those who had never used cannabis (cannabis use: 12.7%; no use: 18.8%; χ21 = 1.061, p = 0.303).ConclusionsIn people at UHR for psychosis, lifetime cannabis use was common but not related to outcome. Among cannabis users, frequent use, early-onset use and continued use after clinical presentation were associated with transition to psychosis.

BackgroundThe past two decades have seen exponential clinical and research interest in help-seeking individuals presenting with potentially prodromal symptoms for psychosis. However, the epidemiological validity of this paradigm has been neglected, limiting future advancements in the field.MethodWe undertook a critical review of core epidemiological issues underlying the clinical high-risk (HR) state for psychosis and which model of prodromal intervention is best suited for mental health.ResultsThe HR state for psychosis model needs refining, to bring together population-based findings of high levels of psychotic experiences (PEs) and clinical expression of risk. Traditionally, outcome has been attributed to ‘HR criteria’ alone rather than taking into account sampling strategies. Furthermore, the exclusive focus on variably defined ‘transition’ obscures true variation in the slow and non-linear progression across stages of psychopathology. Finally, the outcome from HR states is variable, indicating that the underlying paradigm of ‘schizophrenia light progressing to schizophrenia’ is inadequate.ConclusionsIn the general population, mixed and non-specific expression of psychosis, depression, anxiety and subthreshold mania is common and mostly transitory. When combined with distress, it may be considered as the first, diagnostically neutral stage of potentially more severe psychopathology, which only later may acquire a degree of diagnostic specificity and possible relative resistance to treatment. Therefore, rather than creating silos of per-disorder ultra-HR syndromes, an early intervention focus on the broad syndrome of early mental distress, requiring phase-specific interventions, may be more profitable.

BackgroundInterpersonal sensitivity is a personality trait described as excessive awareness of both the behaviour and feelings of others. Although interpersonal sensitivity has been found to be one of the vulnerability factors to depression, there has been little interest in its relationship with the prodromal phase of psychosis. The aims of this study were to examine the level of interpersonal sensitivity in a sample of individuals with an at-risk mental state (ARMS) for psychosis and its relationship with other psychopathological features.MethodMethod.Sixty-two individuals with an ARMS for psychosis and 39 control participants completed a series of self-report questionnaires, including the Interpersonal Sensitivity Measure (IPSM), the Prodromal Questionnaire (PQ), the Ways of Coping Questionnaire (WCQ) and the Depression and Anxiety Stress Scale (DASS).ResultsIndividuals with an ARMS reported higher interpersonal sensitivity compared to controls. Associations between interpersonal sensitivity, positive psychotic symptoms (i.e. paranoid ideation), avoidant coping and symptoms of depression, anxiety and stress were also found.ConclusionsThis study suggests that being ‘hypersensitive’ to interpersonal interactions is a psychological feature of the putatively prodromal phase of psychosis. The relationship between interpersonal sensitivity, attenuated positive psychotic symptoms, avoidant coping and negative emotional states may contribute to long-term deficits in social functioning. We illustrate the importance, when assessing a young client with a possible ARMS, of examining more subtle and subjective symptoms in addition to attenuated positive symptoms.

BackgroundAlthough individuals vulnerable to psychosis show brain volumetric abnormalities, structural alterations underlying different probabilities for later transition are unknown. The present study addresses this issue by means of voxel-based morphometry (VBM).MethodWe investigated grey matter volume (GMV) abnormalities by comparing four neuroleptic-free groups: individuals with first episode of psychosis (FEP) and with at-risk mental state (ARMS), with either long-term (ARMS-LT) or short-term ARMS (ARMS-ST), compared to the healthy control (HC) group. Using three-dimensional (3D) magnetic resonance imaging (MRI), we examined 16 FEP, 31 ARMS, clinically followed up for on average 3 months (ARMS-ST, n=18) and 4.5 years (ARMS-LT, n=13), and 19 HC.ResultsThe ARMS-ST group showed less GMV in the right and left insula compared to the ARMS-LT (Cohen's d 1.67) and FEP groups (Cohen's d 1.81) respectively. These GMV differences were correlated positively with global functioning in the whole ARMS group. Insular alterations were associated with negative symptomatology in the whole ARMS group, and also with hallucinations in the ARMS-ST and ARMS-LT subgroups. We found a significant effect of previous antipsychotic medication use on GMV abnormalities in the FEP group.ConclusionsGMV abnormalities in subjects at high clinical risk for psychosis are associated with negative and positive psychotic symptoms, and global functioning. Alterations in the right insula are associated with a higher risk for transition to psychosis, and thus may be related to different transition probabilities.

BackgroundMany research groups have attempted to predict which individuals with an at-risk mental state (ARMS) for psychosis will later develop a psychotic disorder. However, it is difficult to predict the course and outcome based on individual symptoms scores.MethodData from 318 ARMS individuals from two specialized services for ARMS subjects were analysed using latent class cluster analysis (LCCA). The score on the Comprehensive Assessment of At-Risk Mental States (CAARMS) was used to explore the number, size and symptom profiles of latent classes.ResultsLCCA produced four high-risk classes, censored after 2 years of follow-up: class 1 (mild) had the lowest transition risk (4.9%). Subjects in this group had the lowest scores on all the CAARMS items, they were younger, more likely to be students and had the highest Global Assessment of Functioning (GAF) score. Subjects in class 2 (moderate) had a transition risk of 10.9%, scored moderately on all CAARMS items and were more likely to be in employment. Those in class 3 (moderate–severe) had a transition risk of 11.4% and scored moderately severe on the CAARMS. Subjects in class 4 (severe) had the highest transition risk (41.2%), they scored highest on the CAARMS, had the lowest GAF score and were more likely to be unemployed. Overall, class 4 was best distinguished from the other classes on the alogia, avolition/apathy, anhedonia, social isolation and impaired role functioning.ConclusionsThe different classes of symptoms were associated with significant differences in the risk of transition at 2 years of follow-up. Symptomatic clustering predicts prognosis better than individual symptoms.

BackgroundImpaired spatial working memory (SWM) is a robust feature of schizophrenia and has been linked to the risk of developing psychosis in people with an at-risk mental state (ARMS). We used functional magnetic resonance imaging (fMRI) to examine the neural substrate of SWM in the ARMS and in patients who had just developed schizophrenia.MethodfMRI was used to study 17 patients with an ARMS, 10 patients with a first episode of psychosis and 15 age-matched healthy comparison subjects. The blood oxygen level-dependent (BOLD) response was measured while subjects performed an object–location paired-associate memory task, with experimental manipulation of mnemonic load.ResultsIn all groups, increasing mnemonic load was associated with activation in the medial frontal and medial posterior parietal cortex. Significant between-group differences in activation were evident in a cluster spanning the medial frontal cortex and right precuneus, with the ARMS groups showing less activation than controls but greater activation than first-episode psychosis (FEP) patients. These group differences were more evident at the most demanding levels of the task than at the easy level. In all groups, task performance improved with repetition of the conditions. However, there was a significant group difference in the response of the right precuneus across repeated trials, with an attenuation of activation in controls but increased activation in FEP and little change in the ARMS.ConclusionsAbnormal neural activity in the medial frontal cortex and posterior parietal cortex during an SWM task may be a neural correlate of increased vulnerability to psychosis.

BackgroundWe conducted a systematic review to assess the evidence for specific effects of cannabis on brain structure and function. The review focuses on the cognitive changes associated with acute and chronic use of the drug.MethodWe reviewed literature reporting neuroimaging studies of chronic or acute cannabis use published up until January 2009. The search was conducted using Medline, EMBASE, LILACS and PsycLIT indexing services using the following key words: cannabis, marijuana, delta-9-tetrahydrocannabinol, THC, cannabidiol, CBD, neuroimaging, brain imaging, computerized tomography, CT, magnetic resonance, MRI, single photon emission tomography, SPECT, functional magnetic resonance, fMRI, positron emission tomography, PET, diffusion tensor MRI, DTI-MRI, MRS and spectroscopy.ResultsSixty-six studies were identified, of which 41 met the inclusion criteria. Thirty-three were functional (SPECT/PET/fMRI) and eight structural (volumetric/DTI) imaging studies. The high degree of heterogeneity across studies precluded a meta-analysis. The functional studies suggest that resting global and prefrontal blood flow are lower in cannabis users than in controls. The results from the activation studies using a cognitive task are inconsistent because of the heterogeneity of the methods used. Studies of acute administration of THC or marijuana report increased resting activity and activation of the frontal and anterior cingulate cortex during cognitive tasks. Only three of the structural imaging studies found differences between users and controls.ConclusionsFunctional neuroimaging studies suggest a modulation of global and prefrontal metabolism both during the resting state and after the administration of THC/marijuana cigarettes. Minimal evidence of major effects of cannabis on brain structure has been reported.

We read with great interest the article by Navari & Dazzan (2009) recently published in Psychological Medicine. These authors found that antipsychotic treatment may contribute to brain structural changes observed in psychosis and that antipsychotics act regionally rather than globally on the brain, with specific effects on different brain structures. In an own systematic review on the effects of antipsychotics on the brain (Smieskova et al. in press) we summarized findings from structural imaging studies of schizophrenia. We focused on studies investigating schizophrenia patients using neuroimaging techniques according to antipsychotic medication and studies considering the differences in medication either in various antipsychotic medications or over the time or in various groups of patients. Overall, we found that patients with schizophrenia receiving treatment with antipsychotics had reduced grey matter (GM) volume, particularly in frontal and temporal lobes. Medication with typical antipsychotics also leads to increased volume of the basal ganglia, while atypical antipsychotics reversed the effect after switching. Studies with typical antipsychotics have reported increased GM volume in cingulate cortex, in contrast to atypical antipsychotics with the excess more often seen in thalamus volume.