Associations of living arrangements with symptoms and functioning in schizophrenia

Prediction of Clinical Outcomes in Psychotic Disorders Using Artificial Intelligence Methods: A Scoping Review

BACKGROUND

Psychotic disorders are major psychiatric disorders that can impact multiple domains including physical, social, and psychological functioning within individuals with these conditions. Being able to better predict the outcomes of psychotic disorders will allow clinicians to identify illness subgroups and optimize treatment strategies in a timely manner.

OBJECTIVE

In this scoping review, we aimed to examine the accuracy of the use of artificial intelligence (AI) methods in predicting the clinical outcomes of patients with psychotic disorders as well as determine the relevant predictors of these outcomes.

METHODS

This review was guided by the PRISMA Guidelines for Scoping Reviews. Seven electronic databases were searched for relevant published articles in English until 1 February 2024.

RESULTS

Thirty articles were included in this review. These studies were mainly conducted in the West (63%) and Asia (37%) and published within the last 5 years (83.3%). The clinical outcomes included symptomatic improvements, illness course, and social functioning. The machine learning models utilized data from various sources including clinical, cognitive, and biological variables such as genetic, neuroimaging measures. In terms of main machine learning models used, the most common approaches were support vector machine, random forest, logistic regression, and linear regression models. No specific machine learning approach outperformed the other approaches consistently across the studies, and an overall range of predictive accuracy was observed with an AUC from 0.58 to 0.95. Specific predictors of clinical outcomes included demographic characteristics (gender, socioeconomic status, accommodation, education, and employment); social factors (activity level and interpersonal relationships); illness features (number of relapses, duration of relapses, hospitalization rates, cognitive impairments, and negative and disorganization symptoms); treatment (prescription of first-generation antipsychotics, high antipsychotic doses, clozapine, use of electroconvulsive therapy, and presence of metabolic syndrome); and structural and functional neuroimaging abnormalities, especially involving the temporal and frontal brain regions.

CONCLUSIONS

The current review highlights the potential and need to further refine AI and machine learning models in parsing out the complex interplay of specific variables that contribute to the clinical outcome prediction of psychotic disorders.

Caregiving experiences of family caregivers of patients with schizophrenia in a community: a qualitative study in Beijing

OBJECTIVES

This study aims to understand the caregiving experiences of family caregivers of people with schizophrenia in a community.

DESIGN

A qualitative study based on phenomenological analysis was conducted through in-depth interviews.

SETTING

This study was carried out from May to June 2023 in two community health service centres in urban Beijing, China.

PARTICIPANTS

We selected 16 family caregivers for interviews using purposive sampling method.

RESULTS

Four themes and 10 subthemes were identified: (1) psychosocial distress of family caregivers (feeling unprepared and helpless at the beginning, confronting negative emotions in long-term care and straying away from social life); (2) adverse impacts on the whole family (poor cooperation within the family, insufficient family involvement in professional care); (3) coping with family caregiving (accepting the reality of the patients' illness, struggling with family life balance and having realistic expectations); (4) concerns about future care (daily living support, physical health management).

CONCLUSION

Family caregivers experienced psychosocial distress and family stress in the process of caregiving. They had to cope with caregiving stress and were concerned about the long-term care of people with schizophrenia. These findings provide implications for intervention programmes to strengthen social support, family involvement, and active coping for caregivers and develop long-term care mechanisms for people with schizophrenia.

Examining associations, moderators and mediators between childhood maltreatment, social functioning, and social cognition in psychotic disorders: a systematic review and meta-analysis

Childhood maltreatment (CM) has been related to social functioning and social cognition impairment in people with psychotic disorders (PD); however, evidence across different CM subtypes and social domains remains less clear. We conducted a systematic review and meta-analysis to quantify associations between CM, overall and its different subtypes (physical/emotional/sexual abuse, physical/emotional neglect), and domains of social functioning and social cognition in adults with PD. We also examined moderators and mediators of these associations. A PRISMA-compliant systematic search was performed on 24 November 2022 (PROSPERO CRD42020175244). Fifty-three studies (N = 13 635 individuals with PD) were included in qualitative synthesis, of which 51 studies (N = 13 260) with 125 effects sizes were pooled in meta-analyses. We found that CM was negatively associated with global social functioning and interpersonal relations, and positively associated with aggressive behaviour, but unrelated to independent living or occupational functioning. There was no meta-analytic evidence of associations between CM and social cognition. Meta-regression analyses did not identify any consistent moderation pattern. Narrative synthesis identified sex and timing of CM as potential moderators, and depressive symptoms and maladaptive personality traits as possible mediators between CM and social outcomes. Associations were of small magnitude and limited number of studies assessing CM subtypes and social cognition are available. Nevertheless, adults with PD are at risk of social functioning problems after CM exposure, an effect observed across multiple CM subtypes, social domains, diagnoses and illness stages. Maltreated adults with PD may thus benefit from trauma-related and psychosocial interventions targeting social relationships and functioning.

Social Networks and Residential Status in Community-Dwelling Older Adults With Schizophrenia: Compensation by Reconfiguration?

OBJECTIVE

To address the paucity of data on the structure and content of social networks of older adults with schizophrenia (OAS).

METHODS

The OAS group comprised 249 persons aged 55 and older with early-onset schizophrenia living in supportive housing (SS; n = 151), independently (SI; n = 70), or with family (SF; n = 28). The community comparison (CC) group comprised 113 individuals. Social network analysis was used. Multinomial logistic regression with p ≤0.001 and p ≤0.05 was used for overall and pairwise comparisons, respectively.

RESULTS

Each OAS subgroup had more total, nonkin, and formal linkages than the CC group. The SS and SI subgroups had fewer kin linkages than the CC group. The CC group had more confidants than the SS subgroup, more reliable linkages than the SS and SI subgroups, and more sustenance linkages than each of the OAS subgroups. Nearly everyone in the CC, SI, and SF subgroups had a confidant, a reliable contact, and a sustenance linkage; 33% of the SS subgroup had no confidants. The SS subgroup displayed more psychiatric symptoms than the SI and SF subgroups. There were no differences in loneliness or relationship satisfaction between the CC and the schizophrenia subgroups.

CONCLUSION

Networks were expressed differentially across residential arrangements and differences may reflect dissimilarities in psychiatric functioning. OAS generally had ample levels of companionship and emotional and instrumental support, often comparable to their age peers. Whereas social networks typically decline at illness onset and may be predominantly family-focused, later life may be a time of network reconfiguration and reconstitution.

Cariprazine's Potential in Improving Social Dysfunction in Patients With Schizophrenia: A Perspective

Social dysfunction is one of the most debilitating aspects of schizophrenia. Treatment of this complex phenomenon, constituted by negative, cognitive, and affective symptoms, has been difficult with the available pharmacological agents, hence it represents an unmet medical need. Cariprazine, a novel, third-generation antipsychotic with a unique mechanism of action has been proven to sufficiently alleviate negative, cognitive, and affective symptoms of schizophrenia. These characteristics make this compound a valid candidate for addressing social dysfunction too. In this perspective, we argue that cariprazine can be viewed as a "socializing drug" that has the ability to improve the patient's functionality and ultimately their quality of life. Data from animal research, clinical trials, an observational study, and patient cases are provided.