Exploring the Interactions Between Psychotic Symptoms, Cognition, and Environmental Risk Factors: A Bayesian Analysis of Networks.

BACKGROUND AND HYPOTHESIS: Psychotic disorders (PDs) have huge personal and societal impact, and efforts to improve outcomes in patients are continuously needed. Environmental risk factors (ERFs), especially modifiable risk factors, are important to study because they pose a target for intervention and prevention. No studies have investigated ERFs, cognition, and psychotic symptoms together in a network approach. STUDY DESIGN: We explored interactions between 3 important ERFs (tobacco smoking, cannabis use, and childhood trauma), 6 cognitive domains, and 3 dimensions of symptoms in psychosis. From the Genetic Risk and Outcome of Psychosis (GROUP) cohort, we used data from patients, siblings, and healthy controls to construct networks using Bayesian analyses of all 12 variables. We constructed networks of the combined sample and of patients and siblings separately. STUDY RESULTS: We found that tobacco smoking was directly associated with cognition and psychotic symptoms. The cognitive variable processing speed was the most central node, connecting clusters of psychotic symptoms and substance use through the variables of positive symptoms and tobacco smoking. Comparing the networks of patients and siblings, we found that networks were relatively similar between patients and siblings. CONCLUSIONS: Our results support a potential central role of processing speed deficits in PDs. Findings highlight the importance of integrating tobacco smoking as potential ERFs in the context of PDs and to broaden the perspective from cannabis discontinuation to smoking cessation programs in patients or people at risk of PDs.

Quantifying the evidence for the absence of the job demands and job control interaction on workers' well-being: A Bayesian meta-analysis.

Central to many influential theories in the occupational health and stress literature is that job resources reduce the negative effects of job demands on workers' well-being. However, empirical investigations testing this supposition have produced inconsistent findings. This study evaluates the interaction between job demands and job control on workers' well-being through a systematic literature search and using a Bayesian meta-analytic approach. Both aggregated study findings and raw participant-level data were included in the study, resulting in 104 effect sizes of aggregate-level data and 14 participant-level data sets. Overall, the data provided strong evidence for the absence of an interaction between job demands and job control. Longitudinal and nonlinear research designs were also examined but did not alter this overall conclusion. Contrary to the postulations of widespread theories, job control does not reduce the negative impact of job demands on workers' well-being. Alternative theoretical approaches and the need for more consistent and rigorous research standards, like open science practices, are discussed. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Corrigendum: The interplay between quality of life and resilience factors in later life: a network analysis.

[This corrects the article DOI: 10.3389/fpsyg.2021.752564.].

The Interplay Between Quality of Life and Resilience Factors in Later Life: A Network Analysis.

Age-related challenges and transitions can have considerable social, psychological, and physical consequences that may lead to significant changes in quality of life (QoL). As such, maintaining high levels of QoL in later life may crucially depend on the ability to demonstrate resilience (i.e., successful adaptation to late-life challenges). The current study set out to explore the interplay between several resilience factors, and how these contribute to the realization and maintenance of (different facets of) QoL. Based on the previous work, we identified behavioral coping, positive appraisal, self-management ability, and physical activity as key resilience factors. Their interplay with (various facets of) QoL, as measured with the WHOQOL-OLD, was established through network analysis. In a sample of community-dwelling older adults (55+; N=1,392), we found that QoL was most strongly (and directly) related to positive appraisal style and self-management ability. Among those, taking care of multifunctional resources (i.e., yielding various benefits at the same time) seemed to be crucial. It connected directly to "satisfaction with past, present, and future activities," a key facet of QoL with strong interconnections to other QoL facets. Our analysis also identified resilience factor(s) with the potential to promote QoL when targeted by training, intervention, or other experimental manipulation. The appropriate set of resilience factors to manipulate may depend on the goal and/or facet of QoL that one aims to improve.