The network structure of schizotypy in the general population

Abstract

Schizotypal personality traits show similarity with schizophrenia at various levels of analysis. It is generally agreed that schizotypal personality is multidimensional; however, it is still debated whether impulsive nonconformity should be incorporated into theories and measurement of schizotypy. In addition, relatively little is known about the network structure of the four-dimensional model of schizotypal personality. To estimate the network structure of schizotypy, we used data from participants recruited from the community (N = 11,807) who completed the short version of the Oxford-Liverpool Inventory of Feelings and Experiences, a widespread self-report instrument that assesses the positive, negative, disorganised and impulsive domains of schizotypy. We performed community detection, then examined differences between communities in terms of centralities and compared the strength of edges within and between communities. We found communities that almost perfectly corresponded to the a priori-defined subscales (93% overlap, normalised mutual information = 0.74). Items in the disorganisation community had higher closeness centrality relative to items in the other communities (Cliff's Δs ranged from 0.55 to 0.83) and weights of edges within the disorganisation community were stronger as compared to the negative schizotypy and impulsive nonconformity communities (Cliff's Δs = 0.33). Our findings imply that the inclusion of impulsive nonconformity items does not dilute the classical three-factor structure of positive, negative and disorganised schizotypy. The high closeness centrality of disorganisation concurs with theories positing that cognitive slippage and associative loosening are core features of the schizophrenic phenotype.

Cross-modal auditory priors drive the perception of bistable visual stimuli with reliable differences between individuals [preprint]

“…Interestingly, individuals showing high levels of schizotypy were less likely to respond slower on ambiguous trials and to make more errors on unambiguous trials, which may indicate increased reliance on priors and reduced sensory precision. As all dimensions of schizotypy showed these associations, one may speculate that this tendency is related to disorganisation, a core feature of the psychosisspectrum phenotype (Polner et al, 2019). On a related note, disorganisation has been linked to a deficit of visual perceptual organisation, probably indicating impaired modulation by contextual expectations (Uhlhaas et al, 2005).…”

Home confinement during the COVID-19: day-to-day associations of sleep quality with rumination, psychotic-like experiences and somatic symptoms

“…Since our aim was to include only healthy participants free from severe psychological conditions in our prospective study, we excluded individuals showing clinically relevant signs of depressive symptoms. Nevertheless, we retained and included in our models the scores of PTSD-like symptoms and cognitive disorganization as proxies of psychopathological conditions that were consistently linked to impaired sleep quality 54-57 , negative emotionality and reduced resilience [47][48][49][50] . This way, by controlling the effects of the levels of more general psychopathological traits, we could disentangle the associations of sleep quality with daytime reports that reflect rather specific mental experiences such as rumination, psychotic-like experiences, and somatic complaints during the confinement.…”

“…Likewise, we examined the inverse direction, i.e., whether daytime rumination, psychotic-like experiences, and somatization could predict worse sleep quality the following night. Additionally, we reasoned that trait-like characteristics such as proneness for a dysregulated stress-response after exposure to a stressor (as reflected by PTSD-like symptoms 47,48 ) and difficulties in controlling thoughts and attention (as reflected by cognitive disorganization 49,50 ) would be predictive of increased maladaptation during the pandemic. Therefore, we examined the association of these retrospectively assessed psychopathological indices with daytime functioning over and above the hypothesized association with sleep.…”

The Network Structure of Schizotypy in the General Population

“…Analyses were performed in R [61] [v3.5.0] using RStudio [62] [v1.1.423]. All code and data to reproduce the analyses are provided here: osf.io/epfvq [63]. In order to estimate the network from the binary sO-LIFE data, we applied the eLasso methodology [for details see 64] implemented in the IsingFit package [65] which are more densely connected to each other, as compared to nodes in different communities [69].…”