Latent profile analysis of psychosis liability in a community‐derived sample of adolescents: Links with mental health difficulties, suicidal ideation, bipolar‐like experiences and psychotic‐like experiences

Fonseca‐Pedrero, Eduardo; Ortuño‐Sierra, Javier; Muñiz, José; Bobes, Julio

doi:10.1111/eip.12741

Cited by 13 publications

(17 citation statements)

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“…They found that schizotypal features were highly overlapped with depressive symptoms. Furthermore, the results found here are congruent with those studies that show that PLEs during adolescence are associated, among other, with emotional and behavioural problems, suicidality, and depression (Armando et al, 2010;Bolhuis et al, 2018;Fonseca-Pedrero et al, 2019;Kelleher et al, 2013;Schimanski, Mouat, Billinghurst, & Linscott, 2017;Yung et al, 2006). Overall, the results add empirical support to the extended psychosis phenotype indicating that PLEs (occurrence and associated distress) are directly associated with emotional dysregulation and psychopathology in adolescent populations.…”

Section: Discussionsupporting

confidence: 89%

“…At a phenotypic level, the link between psychotic experiences and a later psychotic disorder, may be stronger depending on the concomitant presence of affective dysregulation, family history of a mental disorder, and lower socio-economic status (Klrll et al, 2019;Pries et al, 2018;van os & Linscott, 2012). In addition, previous research has shown that PLEs are also associated bidirectionally, among others, with emotional and behavioural problems, suicidality, non-suicidal self-injury, depression, and substance use (Armando et al, 2010;Bolhuis et al, 2018;Fonseca-Pedrero, Ortuño-Sierra, Muñiz, & Bobes, 2019;Yung et al, 2006). In this sense, evidence suggests that the combination of well-known risk factors such as cannabis use, psychopathology, childhood adversity, and urbanicity, in interaction with proxy measures of genetic risk, may facilitate the onset of psychosis (eg, Radhakrishnan et al, 2019).…”

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confidence: 99%

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Network structure of psychotic‐like experiences in adolescents: Links with risk and protective factors

Fonseca‐Pedrero

Muñiz

Gacía‐Portilla

et al. 2020

Early Intervention Psych

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Aim: The main goal was to analyse the network structure of psychotic-like experiences (PLEs) in a large sample of adolescents. In addition, the network structure between PLEs and putative risk (mental health difficulties, suicidal behaviour, depression symptoms) and protective factors (prosocial behaviour, subjective well-being, self-esteem) for psychosis was analysed. Methods:The sample compromised a total of 1790 adolescents (M=15.7 years; SD=1.26), 816 men (45.6%), selected by stratified random cluster sampling. Various tools were used to measure PLEs, general psychopathology, suicide ideation and behaviour, depression symptoms, prosocial behaviour, subjective well-being, and self-esteem. The Gaussian graphical model for continuous variables and Ising model for binary variables were used for network estimation. Results: The PLEs estimated network was strongly interconnected. Unusual perceptual experiences were among the most central nodes. The average predictability of this network was 16.41%. The PLEs and risk and protective factors estimated network showed a high degree of interconnectedness between PLEs and psychopathology domains. PLEs, behavioural problems, and emotional symptoms were among the most central nodes. The mean predictability of this network was 43.46%. The results of the stability and accuracy analysis indicated that networks were accurately estimated. Conclusions: At population level, extended psychosis phenotype can be conceptualized as a network of interacting cognitive, emotional, and behavioural features. The network model allows us to understand psychosis risk, at the same time opening new lines of study in the mental health arena. K E Y W O R D S extended psychosis phenotype, network analyses, network model psychotic-like experiences, psychosis risk 1 | INTRODUCTION Psychotic-like experiences (PLEs) are often viewed as phenotypic indicators of the diathesis for psychotic disorders (Linscott & van Os, 2013). Previous follow-up studies have showed that adolescents and young adults who report subclinical expressions of psychosis phenotype (eg, PLEs, schizotypal traits) have a greater probability of clinical outcome, mainly non-affective psychoses (Debbané

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Section: Discussionsupporting

confidence: 89%

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confidence: 99%

Network structure of psychotic‐like experiences in adolescents: Links with risk and protective factors

Fonseca‐Pedrero

Muñiz

Gacía‐Portilla

et al. 2020

Early Intervention Psych

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“…The adolescents in the true schizotypy latent class reported more psychological distress and family history of psychosis, compared to the other classes. In other study, Fonseca-Pedrero et al [31], using a representative sample of adolescents, found four latent profiles (positive schizotypy, low schizotypy, social disorganization schizotypy, and high schizotypy), where the high schizotypy class scored higher on psychopathology indicators relative to the other three clusters.…”

Section: Introductionmentioning

confidence: 87%

“…There is an increasing interest in finding homogenous groups of potentially at-risk individuals based on psychotic-spectrum phenomena [31,32]. A novel mixture model called latent class analysis (LCA) (dichotomous outcome) or latent profile analysis (LPA) (continuous outcome) [33] was recently used for this purpose.…”

Section: Introductionmentioning

confidence: 99%

Identifying extended psychosis phenotypes at school: Associations with socio-emotional adjustment, academic, and neurocognitive outcomes

et al. 2020

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The main goal of the present study was to explore the latent structure of extended psychosis phenotypes in a representative sample of adolescents. Moreover, associations with socioemotional adjustment, academic achievement, and neurocognition performance across the latent profiles were compared. Participants were 1506 students, 667 males (44.3%), derived from random cluster sampling. Various tools were used to measure psychosis risk, subjective well-being, academic performance, and neurocognition. Based on three psychometric indicators of psychosis risk (schizotypal traits, psychotic-like experiences, and bipolar-like experiences), four latent classes were found: non-risk, low-risk, high reality distortion experiences, and high psychosis liability. The high-risk latent groups scored significantly higher on mental health difficulties, and negative affect, and lower on positive affect and well-being, compared to the two non-risk groups. Moreover, these high-risk groups had a significantly higher number of failed academic subjects compared to the non-risk groups. In addition, no statistically significant differences in efficiency performance were found in the neurocognitive domains across the four latent profiles. This study allows us to improve the early identification of adolescents at risk of serious mental disorder in school settings in order to prevent the incidence and burden associated with these kinds of mental health problems.

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“…For instance, Meng et al conducted an LPA on a sample of 2158 participants and found a best-fitting model with three classes: ‘low group anxiety, moderate group anxiety and high group anxiety’ 9. Fonseca-Pedrero et al using LPA identified four latent classes: ‘positive schizotypy’, ‘low schizotypy’ and ‘high schizotypy’ and their findings can facilitate prevention of psychotic-spectrum disorder and mental health problems 17…”

Section: Introductionmentioning

confidence: 99%

Latent profile analysis of anxiety disorder among left-behind children in rural Southern China: a cross-sectional study

Liao

Pan

et al. 2019

BMJ Open

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ObjectivesPrevious studies have used latent profile analysis (LPA) to examine rural left-behind children’s anxiety. Further study is needed to identify the heterogeneous characteristics of rural left-behind children’s anxiety and explore the related factors.SettingA cross-sectional survey using a school-based sample was conducted in January 2018 in Qingxin district, Qingyuan city, Guangdong province.Participants1026 left-behind children (effective response rate of the questionnaire: 95.39%).Main outcome measuresProfile latent classes (LC) and anxiety disorder.ResultsThe LPA identified three anxiety LC: ‘low anxiety’ (56.6%), ‘medium anxiety’ (34.8%) and ‘severe anxiety’ (8.6%). The multinomial logistic regression model was used to predict the relationship between personal, family, school factors and anxiety. We found that the variables directly related to lower anxiety classes included age (12–14 years), harmonious or fair relationship with classmates, no neglect, harmonious parental relationship and the duration of mother migration <6 months.ConclusionsThese findings suggested the need for careful consideration of differences in anxieties among rural left-behind children. Identifying latent subgroups may provide an empirical basis for teachers and public health practitioners to implement anxiety intervention efforts.

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Latent profile analysis of psychosis liability in a community‐derived sample of adolescents: Links with mental health difficulties, suicidal ideation, bipolar‐like experiences and psychotic‐like experiences

Cited by 13 publications

References 62 publications

Network structure of psychotic‐like experiences in adolescents: Links with risk and protective factors

Network structure of psychotic‐like experiences in adolescents: Links with risk and protective factors

Identifying extended psychosis phenotypes at school: Associations with socio-emotional adjustment, academic, and neurocognitive outcomes

Latent profile analysis of anxiety disorder among left-behind children in rural Southern China: a cross-sectional study

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