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Over the past few decades, epidemiological evidence has accrued to establish variance in psychosis risk across both geographical locations and demographic characteristics such as the excess risk in migrants and their descendants. Yet, the causes of this variation in rates between places and ethnic groups are still unclear, and I aimed to address this in this thesis. I conducted a systematic review and meta-analyses to synthesise existing literature on psychosis incidence in the six countries included in the EUropean network of national schizophrenia networks studying Gene-Environment Interactions (EU-GEI) study: England, The Netherlands, Spain, France, Italy and Brazil. I subsequently analysed data from two parts of the EU-GEI study: a 17-centre service-based incidence study of psychosis, and a case-control arm utilising community volunteers. In the latter, I aimed to explain excess risk in ethnic and religious minorities using a theoretical sociocultural distance model I developed using literature from the social sciences. Here, I proposed that culturally distant minorities were particularly at risk of social exclusion, and this outsider experience led to increased psychosocial disempowerment (a lack of control over one’s life), which increased psychosis risk. I also explored if this model could explain any excess risk in those with increased genetic African ancestry in England. Incidence varied substantially between the studies included in the systematic review, although methodological differences could not be excluded as an explanation. The EU-GEI incidence study confirmed substantial variation by place, and demonstrated a higher incidence in ethnic minorities and for young men, as well as in areas characterised by a low percentage of owner-occupied housing. The sociocultural distance model could explain most of the excess psychosis risk in ethnic minorities, although some excess risk remained, particularly in the Black ethnic group. Social and cultural distance appeared to be more important predictors than psychosocial disempowerment, suggesting that chronic social injustices rather than acute stress play an important role. This model did not explain excess risk in religious minorities: those following any religion retained an excess risk. It could explain the excess risk in those with increased genetic African ancestry, although this was a small, exploratory sample and this will need replicating in larger studies. This thesis demonstrated, for the first time, that excess risk in ethnic minorities could be explained by the sociocultural distance model. Overall, the findings from this thesis confirm substantial variation in psychosis risk by person and place, and suggest that the social reality of the environment plays a crucial role in explaining this.

Computational modelling has been gaining an increasing amount of support from the neuroscience community as a tool to assay cognition and computational processes in the brain. Lately, scientists have started to apply computational methods from neuroscience to the study of psychiatry to gain further insight into the mechanisms leading to mental disorders. In fact, only recently has psychiatry started to move away from categorising illnesses using behavioural symptoms in an attempt for a more biologically driven diagnosis. To date, several neurobiological anomalies have been found in schizophrenia and led to a multitude of conceptual framework attempting to link the biology to the patients’ symptoms. Computational modelling can be applied to formalise these conceptual frameworks in an effort to test the validity or likelihood of each hypothesis. Recently, a novel conceptual model has been proposed to describe how positive symptoms (delusions, hallucinations and thought disorder) and cognitive symptoms (poor decision-making, i.e. “executive functioning”) might arise in schizophrenia. This framework however, has not been tested experimentally or against computational models. The focus of this thesis was to use a combination of behavioural experiments and computational models to independently assess the validity of each component that make up this framework. The first study of this thesis focused on the computational analysis of a disrupted prediction-error signalling and its implications for decision-making performances in complex tasks. Briefly, we used a reinforcement-learning model of a gambling task in rodents and disrupted the prediction-error signal known to be critical for learning. We found that this disruption can account for poor performances in decision-making due to an incorrect acquisition of the model of the world. This study illustrates how disruptions in prediction-error signalling (known to be present in schizophrenia) can lead to the acquisition of an incorrect world model which can lead to poor executive functioning or false beliefs (delusions) as seen in patients. The second study presented in this thesis addressed spatial working memory performances in chronic schizophrenia, bipolar disorder, first episode psychosis and family relatives of DISC1 translocation carriers. We build a probabilistic inference model to solve the working memory task optimally and then implemented various alterations of this model to test commonly debated hypotheses of cognitive deficiency in schizophrenia. Our goal was to find which of these hypotheses accounts best for the poor performance observed in patients. We found that while the performance at the task was significantly different for most patients groups in comparison to controls, this effect disappeared after controlling for IQ in one group. The models were nonetheless fitted to the experimental data and suggest that working memory maintenance is most likely to account for the poor performances observed in patients. We propose that the maintenance of information in working memory might have indirect implications for measures of general cognitive performance, as these rely on a correct filtering of information against distractions and cortical noise. Finally the third study presented in this thesis assessed the performance of medicated chronic schizophrenia patients in a statistical learning task of visual stimuli and measured how the acquired statistics influenced their perception. We find that patient with chronic schizophrenia appear to be unimpaired at statistical learning of visual stimuli. The acquired statistics however appear to induce less expectation-driven ‘hallucinations’ of the stimuli in the patients group than in controls. We find that this is in line with previous literature showing that patients are less susceptible to expectation-driven illusions than controls. This study highlights however the idea that perceptual processes during sensory integration diverge from this of healthy controls. In conclusion, this thesis suggests that impairments in reinforcement learning and Bayesian inference appear to be able to account for the positive and cognitive symptoms observed in schizophrenia, but that further work is required to merge these findings. Specifically, while our studies addressed individual components such as associative learning, working memory, implicit learning & perceptual inference, we cannot conclude that deficits of reinforcement learning and Bayesian inference can collectively account for symptoms in schizophrenia. We argue however that the studies presented in this thesis provided evidence that impairments of reinforcement learning and Bayesian inference are compatible with the emergence of positive and cognitive symptoms in schizophrenia.

Purpose: The purpose of this descriptive phenomenological study was to understand the lived experience of Black emerging adults with psychotic disorders who have community violence exposure (CVE). The aims included understanding how Black emerging adults with psychotic disorders described the experience of community violence in their lives. A secondary aim was to understand how these individuals described how their experience of community violence has impacted their ability to attain goals that are consistent with emerging adulthood.Background: CVE is a public health crisis. Black emerging adults are at an increased risk of CVE and having a psychotic disorder. CVE and psychotic disorders can cause an increased burden on life. While there is research examining the impact of CVE on mental health and research examining the effects of trauma on psychotic disorders, there is limited qualitative work in Black emerging adults with psychotic disorders and CVE. Method: This study was guided by Husserl's descriptive phenomenology philosophy, and Giorgi's descriptive psychological phenomenological approach guided data collection and analysis. Eleven participants were recruited through purposive sampling. Participants had to have a psychotic disorder, report CVE, identify as Black or African-American, and be between 18 and 29. Interviews were conducted individually with each participant to understand their experiences of CVE. Using bracketing, the data was coded and analyzed. Rigor and trustworthiness were ensured by using Lincoln and Guba's criteria for credibility, confirmability, dependability, and transferability. Results: The sample consisted of eleven participants, ranging in age from 21 to 28, with an average age of 24.6. Six identified as male, four identified as female, and one participant identified as transgender and non-binary/non-conforming. All participants identified as non-Hispanic Black/African-American and had a primary psychotic disorder. Four themes were identified: (1) CVE results in a range of emotional responses, (2) CVE results in a range of behavioral responses, (3) CVE causes disruptions in life and relationships, and (4) participants aspire for a better life without a clear pathway. These four themes represent the lived experiences of CVE in these Black emerging adults who have psychotic disorders in Boston, MA. The themes shed light on the consequences CVE had in their lives. Conclusion: Utilizing descriptive phenomenology created a comprehensive understanding of the experience of the phenomenon of CVE in Black emerging adults with a psychotic disorder. The results illuminated the complex nature CVE has on their life and mental health. Future research should focus on quantitative studies to explore the impact of CVE on various health, social, and psychological outcomes.

The construct of insight is considered highly relevant to mental health professionals who treat individuals with psychotic disorders. While empirical research on insight and its relationship to different levels of care has increased recently, the vast majority of previous research in this area has primarily focused on insight and its association with hospitalization-related outcomes. Research comparing insight to different levels of care (i.e., outpatient, hospitalization, and residential) is thus far nonexistent. The purpose of this study was to investigate whether insight differed among psychotic clients in an outpatient versus inpatient treatment setting, and whether degree of insight related to the need for an inpatient admission. One hundred seventy psychotic clients were administered the Scale to Assess Unawareness of Mental Disorder (SUMD) and the Functional assessment Rating Scale (FARS). One-way multivariate analysis of variance results indicated that there was a statistically significant difference in insight between clients in outpatient versus inpatient levels of care. A multiple regression analysis showed that insight into the need for treatment significantly predicted current need for an inpatient admission. Implications and recommendations for clinical practice, counselor education and supervision, and future research are outlined.