Understanding Lifelong Factors and Prediction Models of Social Functioning After Psychosis Onset Using the Large-Scale GROUP Cohort Study

Shaping tomorrow's support: baseline clinical characteristics predict later social functioning and quality of life in schizophrenia spectrum disorder

PURPOSE

We aimed to explore the multidimensional nature of social inclusion (mSI) among patients diagnosed with schizophrenia spectrum disorder (SSD), and to identify the predictors of 3-year mSI and the mSI prediction using traditional and data-driven approaches.

METHODS

We used the baseline and 3-year follow-up data of 1119 patients from the Genetic Risk and Outcome in Psychosis (GROUP) cohort in the Netherlands. The outcome mSI was defined as clusters derived from combined analyses of thirteen subscales from the Social Functioning Scale and the brief version of World Health Organization Quality of Life questionnaires through K-means clustering. Prediction models were built through multinomial logistic regression (ModelMLR) and random forest (ModelRF), internally validated via bootstrapping and compared by accuracy and the discriminability of mSI subgroups.

RESULTS

We identified five mSI subgroups: "very low (social functioning)/very low (quality of life)" (8.58%), "low/low" (12.87%), "high/low" (49.24%), "medium/high" (18.05%), and "high/high" (11.26%). The mSI was robustly predicted by a genetic predisposition for SSD, premorbid adjustment, positive, negative, and depressive symptoms, number of met needs, and baseline satisfaction with the environment and social life. The ModelRF (61.61% [54.90%, 68.01%]; P =0.013) was cautiously considered outperform the ModelMLR (59.16% [55.75%, 62.58%]; P =0.994).

CONCLUSION

We introduced and distinguished meaningful subgroups of mSI, which were modestly predictable from baseline clinical characteristics. A possibility for early prediction of mSI at the clinical stage may unlock the potential for faster and more impactful social support that is specifically tailored to the unique characteristics of the mSI subgroup to which a given patient belongs.

Moving from supported to independent living: what are the barriers and facilitators for individuals with psychosis?

PURPOSE

Living independently, as opposed to in sheltered housing or with caregivers, is an important aim in the recovery of individuals with psychosis, but the transition to independence can be challenging. This study aims to investigate how individuals with psychosis move between living arrangements and to identify the barriers and facilitators of moving towards independence.

METHODS

The living arrangements of 1119 individuals with non-affective psychosis from the Genetic Risk and Outcome of Psychosis study were assessed at baseline, at three- and six-year follow-ups and further categorized as either supported (sheltered housing or with parents) or independent (single or with partner/family). We estimated the probabilities of transitioning between the living statuses and investigated the influence of demographic characteristics, symptomatology, cognition, social support, and premorbid social adjustment on transition using Markov chain modelling.

RESULTS

The majority of individuals living in supported housing remained there during the six-year follow-up period (~ 60%). The likelihood of moving from supported to independent living was twice as high for participants who were younger, five-to-six times higher for women, twice as high for individuals with better overall cognition, and five times higher for those with a course of low positive symptoms.

CONCLUSION

This study highlights that a large group of individuals with psychosis in supported housing is unlikely to move to independent living. Older men with cognitive impairments and who show continuous severe positive symptoms are the least likely to move living independently. Tailored interventions for these at-risk individuals could increase their chances of moving to independent living.

Bane or boon regarding urbanicity and psychotic spectrum disorders: a scoping review of current evidence

PURPOSE OF REVIEW

This review aims to provide an update on the association between urbanization and psychotic spectrum disorders, focusing on specific aspects of the urban environment that could be a bane or boon for the risk of psychosis.

RECENT FINDINGS

Majority of the included studies support previous evidence suggesting that urbanization is linked to a higher risk of psychotic experiences and psychotic spectrum disorders. A small minority, however, have also found specific factors in the urban environment that could give rise to positive outcomes, such as better social functioning and lower mortality rates in psychotic spectrum disorders, or mitigate the risks associated with urbanization. The perception of the urban environment was also an important factor that increased or mitigated stress levels in patients with psychosis, which in turn affected their susceptibility to psychotic symptoms.

SUMMARY

Specific aspects of the urban environment such as the availability and density of greenspaces are crucial for mitigating the effect of urbanization on risk of psychotic spectrum disorders, and should be incorporated into urban planning. At the same time, there is a need to further explore how modifiable risk factors of the urban environment such as air and noise pollution can be minimized to allow for more liveable cities in the context of psychotic spectrum conditions.

Deep Clinical Phenotyping of Schizophrenia Spectrum Disorders Using Data-Driven Methods: Marching towards Precision Psychiatry

Heterogeneity is the main challenge in the traditional classification of mental disorders, including schizophrenia spectrum disorders (SSD). This can be partly attributed to the absence of objective diagnostic criteria and the multidimensional nature of symptoms and their associated factors. This article provides an overview of findings from the Genetic Risk and Outcome of Psychosis (GROUP) cohort study on the deep clinical phenotyping of schizophrenia spectrum disorders targeting positive and negative symptoms, cognitive impairments and psychosocial functioning. Three to four latent subtypes of positive and negative symptoms were identified in patients, siblings and controls, whereas four to six latent cognitive subtypes were identified. Five latent subtypes of psychosocial function-multidimensional social inclusion and premorbid adjustment-were also identified in patients. We discovered that the identified subtypes had mixed profiles and exhibited stable, deteriorating, relapsing and ameliorating longitudinal courses over time. Baseline positive and negative symptoms, premorbid adjustment, psychotic-like experiences, health-related quality of life and PRSSCZ were found to be the strong predictors of the identified subtypes. Our findings are comprehensive, novel and of clinical interest for precisely identifying high-risk population groups, patients with good or poor disease prognosis and the selection of optimal intervention, ultimately fostering precision psychiatry by tackling diagnostic and treatment selection challenges pertaining to heterogeneity.