ArticleSchizophrenia bulletin2018
Distress, Impairment and the Extended Psychosis Phenotype: A Network Analysis of Psychotic Experiences in an US General Population Sample.
Article in Schizophrenia bulletin, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
17 citing papers in PubMed, 1 synthesis or guideline pooled it, 44 citations in OpenAlex.
- A systematic review of studies using network analysis to assess dynamics of psychotic-like experiences in community samples.Psychological medicine · 2025Pooled it
- Social-spatial residence patterns and adolescent mental health: Investigating the influences of residential segregation, neighborhood social cohesion, and race on persistent, distressing psychotic-like experiences in the United States.Social science & medicine (1982) · 2025Article
- Salience network segregation and symptom profiles in psychosis risk subgroups among youth and early adults.Schizophrenia (Heidelberg, Germany) · 2025Article
- Annual Research Review: Psychosis in children and adolescents: key updates from the past 2 decades on psychotic disorders, psychotic experiences, and psychosis risk.Journal of child psychology and psychiatry, and allied disciplines · 2025Review
- A longitudinal network of psychotic-like experiences, depressive and anxiety symptoms, and adverse life events: a cohort study of 3,358 college students.Epidemiology and psychiatric sciences · 2024Article
- Sexual abuse and psychotic phenomena: a directed acyclic graph analysis of affective symptoms using English national psychiatric survey data.Psychological medicine · 2023Article
- Impact of conspiracist ideation and psychotic-like experiences in patients with schizophrenia during the COVID-19 crisis.Journal of psychiatric research · 2022Article
- Insight-related beliefs and controllability appraisals contribute little to hallucinated voices: a transdiagnostic network analysis study.European archives of psychiatry and clinical neuroscience · 2021Article
- Network analysis of trauma in patients with early-stage psychosis.Scientific reports · 2021Article
- Network Structure of Callous-Unemotional Traits and Conduct Disorder Symptoms Among At-Risk Youth: Multi-Informant Reports and Gender Differences.Research on child and adolescent psychopathology · 2021Article
- The network structure of schizotypy in the general population.European archives of psychiatry and clinical neuroscience · 2021Article
- Toward a Complex Network of Risks for Psychosis: Combining Trauma, Cognitive Biases, Depression, and Psychotic-like Experiences on a Large Sample of Young Adults.Schizophrenia bulletin · 2021Article
- Network study of responses to unusualness and psychological stress during the COVID-19 outbreak in Korea.PloS one · 2021Article
- Network Structures of Social Functioning Domains in Schizophrenia and Bipolar Disorder: A Preliminary Study.Clinical psychopharmacology and neuroscience : the official scientific journal of the Korean College of Neuropsychopharmacology · 2020Article
- Beyond Clinical High-Risk State for Psychosis: The Network Structure of Multidimensional Psychosis Liability in Adolescents.Frontiers in psychiatry · 2019Article
- Psychotic Experiences and Related Distress: A Cross-national Comparison and Network Analysis Based on 7141 Participants From 13 Countries.Schizophrenia bulletin · 2018Article
- The Network Structure of Schizotypal Personality Traits.Schizophrenia bulletin · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
It has been proposed that subclinical psychotic experiences (PEs) may causally impact on each other over time and engage with one another in patterns of mutual reinforcement and feedback. This subclinical network of experiences in turn may facilitate the onset of psychotic disorder. PEs, however, are not inherently distressing, nor do they inevitably lead to impairment. The question arises therefore, whether nondistressing PEs, distressing PEs, or both, meaningfully inform an extended psychosis phenotype. The current study first aimed to exploit valuable ordinal data that captured the absence, occurrence and associated impairment of PEs in the general population to construct a general population based severity network of PEs. The study then aimed to partition the available ordinal data into 2 sets of binary data to test whether an occurrence network comprised of PE data denoting absence (coded 0) and occurrence/impairment (coded 1) was comparable to an impairment network comprised of binary PE data denoting absence/occurrence (coded 0) and impairment (coded 1). Networks were constructed using state-of-the-art regularized pairwise Markov Random Fields (PMRF). The severity network revealed strong interconnectivity between PEs and nodes denoting paranoia were among the most central in the network. The binary PMRF impairment network structure was similar to the occurrence network, however, the impairment network was characterized by significantly stronger PE interconnectivity. The findings may help researchers and clinicians to consider and determine how, when, and why an individual might transition from experiences that are nondistressing to experiences that are more commonly characteristic of psychosis symptomology in clinical settings.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.