A systematic review and meta-analysis of the
psychosis continuum: evidence for a psychosis
proneness–persistence–impairment model of
psychotic disorder
J. van Os
1
,
2
*, R. J. Linscott
1
,
3
, I. Myin-Germeys
1
, P. Delespaul
1
and L. Krabbendam
1
1
Department of Psychiatry and Neuropsychology, South Limburg Mental Health Research and Teaching Network, EURON, Maastricht
University, Maastricht, The Netherlands
2
Division of Psychological Medicine, Institute of Psychiatry, London, UK
3
Department of Psychology, University of Otago, Dunedin, New Zealand
A systematic review of all reported incidence and prevalence studies of population rates of subclinical psychotic
experiences reveals a median prevalence rate of around 5 % and a median incidence rate of around 3 %. A meta-
analysis of risk factors reveals associations with developmental stage, child and adult social adversity, psychoactive
drug use, and also male sex and migrant status. The small difference between prevalence and incidence rates,
together with data from follow-up studies, indicates that approximately 75–90% of developmental psychotic
experiences are transitory and disappear over time. There is evidence, however, that transitory developmental
expression of psychosis (psychosis proneness) may become abnormally persistent (persistence) and subsequently
clinically relevant (impairment), depending on the degree of environmental risk the person is additionally exposed
to. The psychosis proneness–persistence–impairment model considers genetic background factors impacting on a
broadly distributed and transitory population expression of psychosis during development, poor prognosis of which,
in terms of persistence and clinical need, is predicted by environmental exposure interacting with genetic risk.
Received 12 November 2007 ; Revised 12 May 2008 ; Accepted 12 May 2008
Key words : Epidemiology, psychosis, schizophrenia, schizotypy, treatment.
The psychosis continuum
Psychiatric morbidity in a population may be seen as a
function of the degree to which the distribution of a
continuous phenotype, measurable in both healthy
and ill individuals, is shifted towards higher values
(Fig. 1). There is a long-standing notion that the psy-
chosis phenotype is expressed at levels well below its
clinical manifestation, commonly referred to as psy-
chosis proneness, psychotic experiences, schizotypy or
at-risk mental states (Meehl, 1962 ; Siever et al. 1993;
Chapman et al. 1994 ; Claridge, 1997; Crow, 1998;
Kwapil, 1998; Verdoux et al. 1998a; van Os et al. 2000;
Stefanis et al. 2002; Vollema et al. 2002 ; Yung et al.
2003). A psychosis continuum implies that the same
symptoms that are seen in patients with psychotic dis-
orders can be measured in non-clinical populations.
The assumption of this approach is that experiencing
symptoms of psychosis such as delusions and hal-
lucinations is not inevitably associated with the pres-
ence of disorder. The latter is thought to be dependent
on symptom factors such as intrusiveness, frequency
and psychopathological co-morbidities on the one
hand, and personal and cultural factors such as coping,
illness behaviour, societal tolerance and the degree of
associated developmental impairment on the other
(Johns & van Os, 2001). Thus, even though the preva-
lence of the clinical disorder is low, the prevalence of
the symptoms can conceivably be much higher.
What constitutes proof for a psychosis continuum?
Distributional validity: a simulation
Although the distinction between health and illness
makes intuitive sense, it can be readily shown that
most common illnesses cannot be entirely dichot-
omous in nature. Diseases caused by a single domi-
nant gene defect that is fully penetrant may exist as a
* Address for correspondence : Dr J. van Os, Department of
Psychiatry and Neuropsychology, South Limburg Mental Health
Research and Teaching Network, EURON, Maastricht University,
PO Box 616 (DRT 10), 6200 MD Maastricht, The Netherlands.
(Email : j.vanos@sp.unimaas.nl)
Psychological Medicine, Page 1 of 17. f 2008 Cambridge University Press
doi:10.1017/S0033291708003814 Printed in the United Kingdom
INVITED REVIEW
truly dichotomous phenomenon. If nothing else influ-
ences the expression of the genetic defect, the disease
in question will have the same distribution as the
genetic defect itself (Fig. 2b). However, in the case of
multi-factorial diseases, such as psychiatric disorders,
where multiple interacting causes contribute to the
phenotypic distribution, it can be shown, using stat-
istical simulations (available on request), that the most
likely distribution is half-normal (Fig. 2c). It may be
argued that it would still be possible that multiple
interacting factors contribute to an underlying con-
tinuous biological abnormality that, when a certain
threshold is reached, gives rise to a dichotomous be-
havioural phenotype. Although this may be possible,
it is unlikely given the fact that the biological and cog-
nitive abnormalities associated with (the genetics of)
schizophrenia have all been demonstrated to behave
as linear risk indicators without evidence of threshold
effects (Jones et al. 1994a, b).
Psychopathological validity
The vast majority of patients with non-affective psy-
chotic disorder meet criteria for other DSM-IV
psychiatric disorders (Kessler et al. 2005). Psychotic
symptoms outside psychotic disorder show a similar
pattern of ‘co-morbidity’ (van Os et al. 2000), sug-
gesting continuity in terms of psychopathological
associations. Psychotic disorders can be usefully re-
presented as variation in several correlated psycho-
pathological dimensions, in particular dimensions of
positive, negative and affective symptoms (Kitamura
et al. 1995 ; McGorry et al. 1998). Interestingly, sub-
clinical psychotic experiences and the related concept
of schizotypy show a similar pattern. Thus, subclinical
positive psychotic experiences are strongly associated
with the negative symptoms within the psychosis
phenotype (van Os et al. 2000), and emerging work
in general population samples suggests the existence
of similar correlated affective and non-affective
dimensions of the psychosis phenotype at the sub-
clinical level (Stefanis et al. 2002; Krabbendam et al.
2004). Similarly, it has been observed that in studies
using variably defined schizotypy scales to measure
the subclinical manifestations of the psychosis
phenotype, the dimensions of subclinical psychosis
closely resemble those that have been identified in
schizophrenia, thus suggesting psychopathological
continuity between the clinical and subclinical
phenotypes (Vollema & van den Bosch, 1995;
Gruzelier, 1996; Vollema & Hoijtink, 2000; Mata et al.
2003; Lewandowski et al. 2006).
Epidemiological validity
Epidemiological validity refers to the notion that evi-
dence with respect to the distribution of a construct of
interest within a population should be consistent with
the propositions that stem from the theoretical model
of that construct. A categorical model of psychosis
does not predict that the symptoms of psychosis are
more common than the clinical disorder. By contrast, a
continuum model accommodates high-prevalence and
high-incidence rates of psychotic and psychosis-like
experiences. To address this contrast, we systemati-
cally reviewed evidence on the prevalence and inci-
dence of psychotic symptoms and experiences in the
general population.
Methods
We searched entries in the Medline database, with
publication years from 1950 to (7 August) 2007, to
identify the intersection of two sets of publications:
(1) those papers identified using the truncated key-
word search terms ‘delus’, ‘ hallucinat’, ‘paranoi ’,
‘psychos ’, ‘ psychot’, ‘schizophr’ or ‘schizotyp ’; and
(2) those papers identified using the keyword search
terms ‘incidence’, ‘prevalence’, ‘sensitivity’ or ‘ speci-
ficity’. This intersection set, containing 17 363 articles,
was then reduced to those that were limited to human
research and included one or more of the following
key phrases:
‘general population ’
‘normal population’, ‘ normal individuals ’, ‘ normal
sample’
‘healthy population’, ‘healthy individuals ’, ‘ healthy
sample’
‘community individuals ’, ‘community sample ’
‘nonpsychotic ’, ‘survival ’, ‘screening ’, ‘subclinical ’
This yielded 2442 potentially relevant papers. We then
searched each of these papers, first by reading the title
and subsequently, as necessary, the abstract and the
paper itself to identify papers that described studies
Values of population A are shifted to the right compared to population B
Low score High score
Frequency
Disorder threshold
Mean population A
Mean population B
Fig. 1. Relationship between continuous phenotype and
dichotomous disorder. The difference in prevalence of a
psychotic disorder between population A (high prevalence)
and population B (low prevalence) is shown in the graph as a
function of differences between A and B in the population
mean value of a continuous phenotype.
2 J. van Os et al.
of symptoms of psychosis in the general population.
The following inclusion and exclusion criteria were
applied:
Papers included in the meta-analysis were those
that: (a) reported a study of a general population
sample with complete data on at least 100 partici-
pants; (b) reported exact incidence or prevalence rates
(or count data or scores from which rates could be
determined) for dichotomous (at item or instrument
level) psychosis outcomes (symptoms or experience of
or resembling hallucinations, delusions, or both) ; and
(c) were published as original research in or since 1950.
We searched citations within papers meeting these
criteria to identify other potentially eligible studies.
We excluded studies for which: (a) participants were
recruited through secondary or tertiary health services
(e.g. ophthalmology services), prisons, or aged-care
facilities; (b) there was insufficient information to de-
termine a prevalence or incidence rate, a sample size,
or that inclusion criteria were met ; (c) more than 20%
of the participants were (likely to have been) aged
o65 years; (d) outcome measures conflated psychosis
outcomes with other outcomes, such as hypomania or
depersonalization; and (e) psychosis outcomes were
sleep-related (hypnopompic and hypnagogic) halluci-
nations.
From each article, we recorded a cohort name and
its characteristics (sampling population, recruitment
strategy, response rate, the actual or eligible age range
of participants, the mean age and its standard devi-
ation, the proportion of participants aged o65 years,
the proportion of males in the sample, and significant
inclusion and exclusion criteria), the key outcome
phenotype and the criteria used to determine outcome
[the name of the measurement instrument, the ad-
ministration format (self-report, lay interview, pro-
fessional interview, observer ratings); the number
of items of the instrument that were used ; classes of
excluded experience (reports attributed to misunder-
standing, experience judged as realistic or plausible,
experience attributed to drugs or general medical
conditions, experiences judged to be inconsequential) ;
the number of affirmative responses required to reach
study threshold for outcome presence; any frequency,
severity, or likelihood criterion required to reach
study threshold for outcome presence; for composite
phenotype outcomes, such as those collapsing out-
comes across items measuring hallucinations and
delusions, the number of items representing each
phenotype in the measure; the outcome interval];
how outcome data were handled (whether rates were
weighted to compensate for the sampling strategy or
not, whether the rate was of any affirmative response
or a mean item endorsement frequency), the rate de-
nominator, and the rate itself. We recorded as many
rates as possible for each paper and cohort, provided
these were not derived under identical conditions. The
psychosis outcomes were hallucinations, delusions,
and the combined or unsegregated reporting of these.
Analysis
Of the papers we searched, 47 met the inclusion and
exclusion criteria. These 47 articles reported data from
analyses of 35 participant cohorts and yielded 217 es-
timates of the prevalence or 1-year incidence of the
phenotypes (Table 1). The highest number of estimates
yielded by a single paper or cohort was 36 from the
Zurich Study of Young Adults (Ro
¨
ssler et al. 2007), a
longitudinal study with rates of three types of exper-
ience (hallucinations, delusions, and unsegregated) for
two severity levels (at least moderate, at least a little
bit), across six waves of data collection spanning 20
years. By contrast, nine cohorts provided a single
prevalence or incidence estimate. The median number
of rates per cohort was 4.
To summarize rate data, we adopted the graphical
approach to the analysis of epidemiological findings
that Saha et al. (2008) proposed. This approach does
not yield a summary meta-analytic or weighted mean
rate but has the advantage of conveying full infor-
mation about the variability in findings. It also has the
(a)(b)(c)
Phenotypic value
Frequency
Fig. 2. Expected phenotypic distribution of a disorder of multi-factorial interactive aetiology. (a) Shows a continuous and
normal distribution of a trait in the general population, much as would be expected in the case of, for example, weight or IQ.
(b) Shows a clear bimodal distribution, with the great majority of the population having negligible values of the trait, whereas
a very small proportion has extremely high values. (c) Depicts a continuous but only half-normal distribution, with the
majority of the population having very low values but a significant proportion also having progressively higher values.
A systematic review and meta-analysis of the psychosis continuum 3
Table 1. Cohorts and data sources included in the analysis of epidemiological validity
Cohort name or description Source(s) Index
Observed or median rate (n)
H D H/D
Aichi prefecture schoolchildren, Japan Yoshizumi et al. (2004) P 0.213 (1)
Christchurch Health and Development Study, New Zealand Fergusson et al. (2003) P 0.018 (2) 0.100 (2) 0.091 (2)
DSM-IV Symptoms Driven Diagnosis System for Primary
Care validation study
Olfson et al. (1996) P 0.012 (1) 0.009 (1) 0.010 (1)
Dunedin Multidisciplinary
Child Health and Development Study
McGee et al. (2000) P 0.106 (2) 0.162 (2) 0.082 (2)
Poulton et al. (2000) I 0.113 (1) 0.149 (2)
Early Developmental Stages of Psychopathology, Munich Spauwen et al. (2003, 2006a) P 0.046 (1) 0.157 (1) 0.165 (2)
I 0.078 (2)
Epidemiological Catchment Area Program, USA Eaton et al. (1991) P 0.083 (4) 0.029 (2) 0.034 (2)
Tien (1991) I 0.030 (2) 0.009 (1) 0.010 (3)
Tien & Anthony (1990)
Tien & Eaton (1992)
Greek National Basic Airforce Training Centre Stefanis et al. (2004) P 0.032 (1) 0.054 (1) 0.048 (1)
Icelandic birth cohort Lı
´
ndal et al. (1994) P 0.117 (2)
Israeli young adult cohort Stueve & Link (1998) P 0.403 (2)
Liverpool University students, UK Bentall & Slade (1985) P 0.153 (2)
Manhattan primary care survey Olfson et al. (2002) P 0.100 (1) 0.063 (1) 0.134 (8)
Mexican American Prevalence and Services Survey, Fresno, USA Vega et al. (2006) P 0.044 (1) 0.047 (2) 0.125 (4)
Murray State University students, USA Barrett & Etheridge (1992) P 0.225 (1)
Murray State University students, USA Posey & Losch (1983) P 0.228 (1)
National Psychiatric Morbidity Surveys of Great Britain Brugha et al. (2005) P 0.006 (2) 0.003 (2)
[Second] National Survey of Psychiatric Morbidity in Great Britain Johns et al. (2004) P 0.025 (2) 0.087 (2) 0.079 (4)
Wiles et al. (2006) I 0.006 (2) 0.025 (2) 0.029 (5)
[Fourth] National Survey of Ethnic Minorities, England and Wales Johns et al. (2002) P 0.026 (8)
National Survey of Mental Health and Well-Being, Australia Degenhardt & Hall (2001) P 0.017 (8)
Scott et al. (2006)
Netherlands Mental Health Survey and Incidence Study Bak et al. (2005) P 0.033 (1) 0.017 (1) 0.040 (5)
Hanssen et al. (2005) I 0.020 (1)
van Os et al. (2000)
North Florida household survey Schwab (1977) P 0.110 (1)
Pamplona cohort Lo
´
pez-Ilundain et al. (2006) P 0.177 (1)
Peters et al. Delusions Inventory, standardization study Peters et al. (1999a) P 0.252 (1)
Peters et al. Delusions Inventory – 21-item version, standardization study Peters et al. (2004) P 0.298 (1)
Sleep epidemiology survey across five nations Ohayon & Schatzberg (2002) P 0.016 (1)
4 J. van Os et al.
benefit of allowing the inclusion of more than one rate
per cohort. That is, because there is no requirement
that synthesized rates be independent, multiple rates
derived from non-identical conditions within a single
cohort (e.g. the observed rates of hallucinations across
different thresholds or assessment periods) can be in-
cluded in the graphical analysis.
Results
Estimates of the prevalence and 1-year incidence of
psychotic symptoms and experiences vary substan-
tially across cohorts and studies (Fig. 3 ; Tables 1 and
2). The median prevalence, overall, was 5.3%, but the
interquartile range (IQR) was 1.9–14.4 %. For inci-
dence, the median rate was 3.1% and the IQR was
Southeast London schoolchildren Laurens et al. (2007) P 0.286 (1) 0.177 (1) 0.589 (1)
State of Victoria schoolchildren, Australia McGorry et al. (1995) P 0.255 (2) 0.302 (2)
The Zurich Study (of Young Adults), Switzerland Ro
¨
ssler et al. (2007) P 0.006 (12) 0.151 (12) 0.140 (12)
Thuringia schoolchildren, Germany Wolfradt & Straube (1998) P 0.391 (1)
United States National Comorbidity Survey Kendler et al. (1996) P 0.071 (1) 0.049 (1) 0.094 (7)
Shevlin et al. (2007)
United States National Comorbidity Survey Replication Kessler et al. (2005) P 0.049 (5) 0.005 (5) 0.086 (5)
United States National Household Survey on Drug Abuse Mojtabi (2006) P 0.021 (1) 0.009 (1) 0.032 (2)
University of Lie
`
ge students, Belgium Laroi et al. (2004) P 0.203 (2)
Utrecht University students, The Netherlands Aleman et al. (2001) P 0.129 (2)
Winnipeg Dissociative Experiences Study Ross & Joshi (1992) P 0.062 (4) 0.054 (1) 0.040 (10)
Ross et al. (1990)
Zuid-Holland Erasmus Medical Centre/Sophia Children’s Dhossche et al. (2002) P 0.031 (8)
Hospital, The Netherlands Ferdinand et al. (2004) I 0.034 (1)
H, Hallucinations ; D, delusions ; H/D, unsegregated ; P, prevalence ; I, annual incidence.
1.0
0.8
0.6
0.4
0.2
0.0
Cumulative relative frequency
0.60.50.40.30.20.10.0
Rate (proportion)
Prevalence
Incidence (one year)
(
a
)
1.0
0.8
0.6
0.4
0.2
0.0
Cumulative relative frequency
0.60.50.40.30.20.10.0
Rate (proportion)
Hallucinations
Delusions
Unsegregated
(
b
)
Fig. 3. Cumulative relative frequencies of (a) prevalences
(n=195) and 1-year incidence (n=22) rates, collapsed across
phenotypes and other variables, and (b) prevalence rates for
phenotypes hallucinations (n=72), delusions (n=54), and for
unsegregated hallucinations, delusions, or both (n=69).
A systematic review and meta-analysis of the psychosis continuum 5
