Abstract
Purpose
Some studies suggest that positive symptoms of psychosis—clinical and sub-clinical alike—reflect a single, continuously distributed dimension in the population. It is unknown, however, whether such a spectrum of positive psychotic experiences is non-linearly related to outcomes such as daily functioning. This work aims to characterize the relationship between positive psychosis and impairment.
Methods
Data from the Office of National Statistics National Psychiatric Morbidity Surveys of Great Britain were used to establish measurement models of psychosis and impairment. Competing linear and nonlinear models of the relationship between the two latent variables were evaluated using mixture structural equation models.
Results
Positive psychosis is best modeled by a continuous, normal distribution. Increases in positive psychosis correlate with roughly linear increases in impairment.
Conclusions
Positive psychotic symptoms occur throughout the population without a discrete, pathological threshold. Functional deficits are linearly associated with the psychosis at all points along the continuum, and a significant portion of the population experiences subclinical psychosis.
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References
Ruscio J, Ruscio AM (2000) Informing the continuity controversy: a taxometric analysis of depression. J Abnorm Psychol 109(3):473–487
Oord EJC, Pickles A, Waldman ID (2003) Normal variation and abnormality: an empirical study of the liability distributions underlying depression and delinquency. J Child Psychol Psychiatry 44(2):180–192
Markon KE, Krueger RF (2005) Categorical and continuous models of liability to externalizing disorders: a direct comparison in NESARC. Arch Gen Psychiatry 62(12):1352–1359
Schmitt JE, Mehta PD, Aggen SH, Kubarych TS, Neale MC (2006) Semi-nonparametric methods for detecting latent non-normality: a fusion of latent trait and ordered latent class modeling. Multivar Behav Res 41:427–443
Haslam N, Holland E, Kuppens P (2011) Categorical versus dimensions in personality and psychopathology: a quantitative review of taxometric research. Psychol Med 41(11):1–18
Shevlin M, Adamson G, Vollebergh W, de Graaf R, van Os J (2007) An application of item response mixture modeling to psychosis indicators in two large community samples. Soc Psychiatry Psychiatr Epidemiol 42(10):771–779
Daneluzzo E, Stratta P, Di Tommaso S, Pacifico R, Riccardi I, Rossi A (2009) Dimensional, non-taxonic latent structure of psychotic symptoms in a student sample. Soc Psychiatry Psychiatr Epidemiol 44(11):911–916
Linscott RJ, van Os J (2010) Systematic reviews of categorical versus continuum models in psychosis: evidence for discontinuous subpopulations underlying a psychometric continuum. Implications for DSM-V, DSM-VI, and DSM-VII. Annu Rev Clin Psychol 6:391–419
Flett GL, Vredenburg K, Krames L (1997) The continuity of depression in clinical and nonclinical samples. Psychol Bull 121:395–416
Pickles A, Angold A (2003) Natural categories or fundamental dimensions: on carving nature at the joints and the rearticulation of psychopathology. Dev Psychopathol 15(03):529–551
Jenkins R, Bebbington P, Brugha T, Farrell M, Gill B, Lewis G, Meltzer H, Petticrew M (1997) The national psychiatric morbidity surveys of Great Britain—strategy and methods. Psychol Med 27(04):765–774
Jenkins R, Bebbington P, Brugha T, Farrell M, Gill B, Lewis G, Meltzer H, Petticrew M (2003) The national psychiatric morbidity surveys of Great Britain—strategy and methods. Int Rev Psychiatry (Abingdon, England) 15:5–13
Singleton N, Bumpstead R, O’Brien M, Lee A, Meltzer H (2003) Psychiatric morbidity among adults living in private households, 2000. Int Rev Psychiatry 15(1–2):65–73
McManus S, Meltzer H, Brugha T, Bebbington P, Jenkins R (2009) Adult psychiatric morbidity in England, 2007: results of a household survey. The NHS Centre for Health and Social care, UK
Bebbington P, Nayani T (1995) The psychosis screening questionnaire. Int J Methods Psychiatr Res 5(1):11–19
Pincus T, Summey JA, Soraci JRSA, Wallston KA, Hummon NP (1983) Assessment of patient satisfaction in activities of daily living using a modified Stanford health assessment questionnaire. Arthr Rheum 26(11):1346–1353
Ware J Jr, Kosinski M, Keller SD (1996) A 12-item short-form health survey: construction of scales and preliminary tests of reliability and validity. Med Care 34(3):220–233
Muthen BO, Muthen L (2007) MPlus user’s guide, 5th edn. Muthen & Muthen, Los Angeles
Muthén BO, Tihomir A (2002) Latent variable analysis with categorical outcomes: multiple-group and growth modeling in Mplus. Mplus Web Notes 4(5):1–22
Wirth RJ, Edwards MC (2007) Item factor analysis: current approaches and future directions. Psychol Methods 12(1):58–79
Klein A, Moosbrugger H (2000) Maximum likelihood estimation of latent interaction effects with the LMS method. Psychometrika 65(4):457–474
Lee S-Y, Zhu H-T (2002) Maximum likelihood estimation of nonlinear structural equation models. Psychometrika 67(2):189–210
Wall MM, Amemiya Y (2000) Estimation for polynomial structural equation models. J Am Stat Assoc 95(451):929–940
Bauer D (2005) A semiparametric approach to modeling nonlinear relations among latent variables. Struct Equ Model Multidiscip J 12(4):513–535
Markon KE (2010) How things fall apart: understanding the nature of internalizing through its relationship with impairment. J Abnorm Psychol 119(3):447–458
Schwarz G (1978) Estimating the dimension of a model. Ann Stat 6(2):461–464
Biernacki C, Celeux G, Govaert G (1998) Assessing a mixture model for clustering with the integrated classification likelihood. Institut National de Recherche en Informatique et en Automatique: Unite de Recherche Rhone-Alpes 14802(a):27
Akaike H (1981) Likelihood of a model and information criteria. J Econom 16:3–14
Henson JM, Reise SP, Kim KH (2007) Detecting mixtures from structural model differences using latent variable mixture modeling: a comparison of relative model fit statistics. Struct Equ Model Multidiscip J 14(2):202–226
Nylund KL, Asparouhov T, Muthen BO (2007) Deciding on the number of classes in latent class analysis and growth mixture modeling: a Monte Carlo simulation study. Struct Equ Model 14(4):535–569
Lo Y, Mendell NR, Rubin DB (2001) Testing the number of components in a normal mixture. Biometrika 88(3):767–778
Vuong QH (1989) Likelihood ratio tests for model selection and non-nested hypotheses. Econometrica 57(2):307–333
Pek J, Sterba SK, Kok BE, Bauer DJ (2009) Estimating and visualizing nonlinear relations among latent variables: a semiparametric approach. Multivar Behav Res 44(4):407–436
Murphy J, Shevlin M, Adamson G (2007) A latent class analysis of positive psychosis symptoms based on the British Psychiatric Morbidity Survey. Pers Individ Differ 42(8):1491–1502
Raftery A (1995) Bayesian model selection in social research. Sociol Methodol 25:111–163
van Os J, Hanssen M, Bijl RV, Ravelli A (2000) Strauss (1969) revisited: a psychosis continuum in the general population? Schizophr Res 45(1–2):11–20
Stefanis NC, Hanssen M, Smirnis NK, Avramopoulos DA, Evdokimidis IK, Stefanis CN, Verdoux H, van Os J (2002) Evidence that three dimensions of psychosis have a distribution in the general population. Psychol Med 32(02):347–358
Kelleher I, Cannon M (2011) Psychotic-like experiences in the general population: characterizing a high-risk group for psychosis. Psychol Med 41(01):1–6
Claridge G (1994) Single indicator of risk for schizophrenia: probable fact or likely myth? Schizophr Bull 20(1):151–168
Walker E, Kestler L, Bollini A, Hochman KM (2004) Schizophrenia: etiology and Course. Annu Rev Psychol 55(1):401–430
Nuevo R, Chatterji S, Verdes E, Naidoo N, Arango C, Ayuso-Mateos JL (2012) The continuum of psychotic symptoms in the general population: a cross-national study. Schizophr Bull 38(3):475–485
Kessler RC, Birnbaum H, Demler O et al (2005) The prevalence and correlates of nonaffective psychosis in the National Comorbidity Survey Replication (NCS-R). Biol Psychiatry 58(8):668–676
Kendler KS, Gallagher TJ, Abelson JM, Kessler RC (1996) Lifetime prevalence, demographic risk factors, and diagnostic validity of nonaffective psychosis as assessed in a US community sample: the national comorbidity survey. Arch Gen Psychiatry 53(11):1022–1031
Lasalvia A, Boggian I, Bonetto C, Saggioro V, Piccione G, Zanoni C, Cristofalo D, Lamonaco D (2012) Multiple perspectives on mental health outcome: needs for care and service satisfaction assessed by staff, patients and family members. Soc Psychiatry Psychiatr Epidemiol 47(7):1035–1045
Nierop M, van Os J, Gunther N, Myin-Germeys I, de Graaf R, ten Have M, van Dorsselaer S, Bak M, van Winkel R (2012) Phenotypically continuous with clinical psychosis, discontinuous in need for care: evidence for an extended psychosis phenotype. Schizophr Bull 38(2):231–238
Arndt S, Andreasen NC, Flaum M, Miller D, Nopoulos P (1995) A longitudinal study of symptom dimensions in schizophrenia: prediction and patterns of change. Archives of general psychiatry. Arch Gen Psychiatry 52(5):352–360
Eaton WW, Thara R, Federman B, Melton B, Liang K (1995) Structure and course of positive and negative symptoms in schizophrenia. Arch Gen Psychiatry 52(2):127–134
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Jonas, K.G., Markon, K.E. A model of psychosis and its relationship with impairment. Soc Psychiatry Psychiatr Epidemiol 48, 1367–1375 (2013). https://doi.org/10.1007/s00127-012-0642-2
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DOI: https://doi.org/10.1007/s00127-012-0642-2