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.
Background: Temporal patterns of affective functioning such as emotional inertia and instability may indicate changes in emotion regulation that predict depression. However, affect dynamics’ incremental validity over affect intensity and exposure to stressors in predicting depression has been questioned.Methods: We collected longitudinal data regarding momentary affective states (measured multiple times a day), perceived stressors and depressive symptoms (measured every three days) from a general population sample during the COVID-19 pandemic’s first wave in Hungary. The final dataset included 7165 affective states surveys from 125 participants, which were aggregated in 464 three-day measurement windows. Using multilevel models, we explored the unique effects of within-person changes in mean level, inertia, and instability of negative affective states (NA), and stressor-exposure on two domains of depression (anhedonia and negative mood and thoughts) within the three-day windows.Results: Within-person increases in NA inertia and NA instability showed significant positive associations with negative mood and thoughts. These effects did not remain significant after adjusting for mean levels of NA. Multilevel mediation analysis revealed that within individuals, NA inertia and instability indirectly predicted negative mood and thoughts through elevated NA mean.Limitations: The application of self-report questionnaires might bias the results, and the overrepresentation of female participants could limit the generalizability of the findings.Conclusions: Specific patterns of temporal affective functioning are indirect predictors of depressive symptoms at the within-individual level. Our findings may facilitate automated depression risk assessment on the basis of simple affective time series.
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 = 11807) 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, normalized 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.
BackgroundAssociations between impaired cognitive control and maladaptive emotion regulation have been extensively explored across individuals. However, whether this relationship also holds within individuals is an open question. In this study, we tested the assumption that momentary within-person fluctuation in cognitive control (working memory updating and response inhibition) predicts emotional reactivity in everyday life.MethodsWe conducted an experience sampling study (8 two-hourly prompts daily for max. 28 days) where participants repeatedly performed short 2-back and Go-Nogo tasks using their own devices in daily life. We also assessed negative, and positive affective states and the perceived pleasantness of a recent significant event to capture emotional reactivity, as an indicator of effective emotion regulation. We analyzed two overlapping samples: a Go-Nogo (N[participants] = 161, N[observations] = 2494, M[age] = 41.7, SD[age] = 14.5) and a 2-back dataset (N[Participants] = 158, N[observations] = 2641, M[age] = 41.8, SD[age] = 14.5).ResultsHigher 2-back performance predicted more intense negative emotional reactivity within individuals: when individuals’ momentary working memory updating was better than their average, they demonstrated higher negative emotional reactivity. However, better cognitive control performance predicted decreased negative affect if perceived distress was constant. Better Go/no-go performance predicted lower negative emotionality but not reactivity. Cognitive control performance did not predict positive emotional reactivity.ConclusionsThe relationship between cognitive control and affectivity is determined by perceived distress within individuals. This implies that cognitive control training alone may not necessarily contribute to adaptive emotion regulation since the relationship between cognitive control and negative emotionality is context-dependent.
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