Modelling the longitudinal dynamics of paranoia in psychosis: A temporal network analysis over 20 years.

BACKGROUND: Paranoia is a key feature of psychosis that can be highly debilitating. Theories of paranoia mostly interface with short-scale or cross-sectional data models, leaving the longitudinal course of paranoia underspecified. METHODS: We develop an empirical characterisation of two aspects of paranoia - persecutory and referential delusions - in individuals with psychosis over 20 years. We examine delusional dynamics by applying a Graphical Vector Autoregression Model to data collected from the Chicago Follow-up Study (n = 135 with a range of psychosis-spectrum diagnoses). We adjusted for age, sex, IQ, and antipsychotic use. RESULTS: We found that referential and persecutory delusions are central themes, supported by other primary delusions, and are strongly autoregressive - the presence of referential and persecutory delusions is predictive of their future occurrence. In a second analysis we demonstrate that social factors influence the severity of referential, but not persecutory, delusions. IMPLICATIONS: We suggest that persecutory delusions represent central, resistant states in the cognitive landscape, whereas referential beliefs are more flexible, offering an important window of opportunity for intervention. Our data models can be collated with prior biological, computational, and social work to contribute toward a more complete theory of paranoia and provide more time-dependent evidence for optimal treatment targets.

Using network analysis to examine links between individual depressive symptoms, inflammatory markers, and covariates.

BACKGROUND: Studies investigating the link between depressive symptoms and inflammation have yielded inconsistent results, which may be due to two factors. First, studies differed regarding the specific inflammatory markers studied and covariates accounted for. Second, specific depressive symptoms may be differentially related to inflammation. We address both challenges using network psychometrics. METHODS: We estimated seven regularized Mixed Graphical Models in the Netherlands Study of Depression and Anxiety (NESDA) data (N = 2321) to explore shared variances among (1) depression severity, modeled via depression sum-score, nine DSM-5 symptoms, or 28 individual depressive symptoms; (2) inflammatory markers C-reactive protein (CRP), interleukin 6 (IL-6), and tumor necrosis factor α (TNF-α); (3) before and after adjusting for sex, age, body mass index (BMI), exercise, smoking, alcohol, and chronic diseases. RESULTS: The depression sum-score was related to both IL-6 and CRP before, and only to IL-6 after covariate adjustment. When modeling the DSM-5 symptoms and CRP in a conceptual replication of Jokela et al., CRP was associated with 'sleep problems', 'energy level', and 'weight/appetite changes'; only the first two links survived covariate adjustment. In a conservative model with all 38 variables, symptoms and markers were unrelated. Following recent psychometric work, we re-estimated the full model without regularization: the depressive symptoms 'insomnia', 'hypersomnia', and 'aches and pain' showed unique positive relations to all inflammatory markers. CONCLUSIONS: We found evidence for differential relations between markers, depressive symptoms, and covariates. Associations between symptoms and markers were attenuated after covariate adjustment; BMI and sex consistently showed strong relations with inflammatory markers.

[Chronic Disease Self-management Support for People with a Migrant Background: towards a Peer-led Group Program to Improve Equity in Health]. / Selbstmanagementförderung bei chronischer Krankheit für Menschen mit Migrationshintergrund ­ ein Gruppenkurs mit Peer-Ansatz als Beitrag zu gesundheitlicher Chancengerechtigkeit.

AIM: Limited health literacy and language skills are barriers for people with a migrant background (PMB) to access health information and healthcare services, in particular for those living with chronic conditions. During the introduction of a peer-led Stanford chronic disease self-management course in Switzerland, special interest in the program as well as motivation of PMB was observed. In response, we examined if the program can be implemented in German for people with limited language skills. METHODS: This explorative study is part of the evaluation study on introducing the adapted Stanford program in Switzerland and German-speaking Europe. Following the principles of Grounded Theory, semi-structured focus group and individual interviews were conducted with course participants, leaders and coordinators (n=30) and analyzed thematically. The focus was on the feasibility, satisfaction and course content. RESULTS: In principle, the program seems to have positive value for PMB, may work for them in German, have high relevance for everyday life and give an impetus for social integration. CONCLUSION: The need for and extent of modification of the program for PMB has to be further explored in order to make it more accessible for vulnerable groups.

How predictable are symptoms in psychopathological networks? A reanalysis of 18 published datasets.

BACKGROUND: Network analyses on psychopathological data focus on the network structure and its derivatives such as node centrality. One conclusion one can draw from centrality measures is that the node with the highest centrality is likely to be the node that is determined most by its neighboring nodes. However, centrality is a relative measure: knowing that a node is highly central gives no information about the extent to which it is determined by its neighbors. Here we provide an absolute measure of determination (or controllability) of a node - its predictability. We introduce predictability, estimate the predictability of all nodes in 18 prior empirical network papers on psychopathology, and statistically relate it to centrality. METHODS: We carried out a literature review and collected 25 datasets from 18 published papers in the field (several mood and anxiety disorders, substance abuse, psychosis, autism, and transdiagnostic data). We fit state-of-the-art network models to all datasets, and computed the predictability of all nodes. RESULTS: Predictability was unrelated to sample size, moderately high in most symptom networks, and differed considerable both within and between datasets. Predictability was higher in community than clinical samples, highest for mood and anxiety disorders, and lowest for psychosis. CONCLUSIONS: Predictability is an important additional characterization of symptom networks because it gives an absolute measure of the controllability of each node. It allows conclusions about how self-determined a symptom network is, and may help to inform intervention strategies. Limitations of predictability along with future directions are discussed.

[Self-responsibility in health care using the example of medication management from the chronically ill patient's perspective]. / Selbstverantwortung im Gesundheitswesen, diskutiert am Medikamentenmanagement aus Sicht chronisch kranker Patienten.

With rising costs in health care, especially in the area of pharmaceuticals, patients are expected to be more involved in managing their care. Concepts such as shared decision-making or self-management support in chronic illness have been suggested as a way to facilitate this process and to empower patients. It is unclear however, whether the self-responsible patient role outlined in these concepts aligns with the patient's needs. The aim of this paper is to examine this proposed self-responsible role with regard to the patient's medication management needs and to discuss whether self-responsibility and autonomy are suitable concepts when illness-related challenges become difficult or complex. Selected findings from a qualitative longitudinal study on medication management from the perspective of people with chronic conditions are presented. Results from interviews with 27 patients indicate that both the patient's view and the challenges people with chronic conditions face in everyday life remain a 'blind spot' in health care. Providing information to improve health literacy may not be enough; there is a need to systematically support patients in developing skills to adequately (self-)manage a chronic condition.

[Incidence and prevalence of postoperative acute confusion in heart surgery patients after coronary artery bypass and heart valve replacement surgeries]. / Inzidenz und Prävalenz postoperativer akuter Verwirrtheit kardiochirurgischer Patienten nach Bypassoperationen sowie Herzklappenersatz.

Compared to foreign countries, Germany does not have data about the occurrence of acute confusion following heart-surgery. However, the occurrence of acute confusion does extend the hospital length of stay for up to 13 days. Thus, this phenomenon is of high relevance to nursing. This prevalence/incidence study was implemented with the goal of obtaining exact information on the incidence rate of acute postoperative confusion after a heart surgery through a multicenter evaluation. The data evaluation took place in the form of a convenience sample survey in three different German clinics specializing on heart surgeries. The observation period lasted from the day of the surgery up to the fifth postoperative day. In the context of this prospective Cohort-study all patients aged 18 and older who had heart surgery between February 1st and April 30th, 2000, were considered suitable as participants in the study. In the end, 860 patients were included in this study. 152 patients (17.4%) showed symptoms of acute confusion (confidence interval 14-20%). Certain circumstances seemed to predispose patients to acute confusion. A widespread occurrence could be observed particularly at night. Patients aged 81-91 were mainly affected. A confusion rate of 43.5% could be determined for this group. These results confirm the clinical importance and suggest interdisciplinary approaches for solution.