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Chapter 7

Detecting patients at high risk of developing psychosis: the usual suspects

and beyond

Authors: Judith Rietdijk, Helga K. Ising, Sara Dragt, Rianne M.C. Klaassen, Dorien H. Nieman, Lex Wunderink, Pim Cuijpers, Don H. Linszen, Mark van der Gaag.

Submitted

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People at ultra high risk for psychosis

Abstract

Background: Many patients with at-risk mental states for developing psychosis seek help in secondary mental health care services. Knowledge about symptom profiles and associations between risk symptoms and non-psychotic psychopathology is needed in order to improve the early detection in help-seeking populations. Method: From February 2008 to February 2010 baseline data were collected from 201 help-seeking subjects (age 14-35 yrs) who met criteria for At Risk Mental States for developing psychosis. The association of the different criteria for at-risk mental states with psychopathological profiles, gender and previously assigned diagnoses were explored. Results: All patients showed high scores on depression and anxiety, independent of their previously assigned diagnosis. No distinct symptom profiles were found for different risk symptoms. The included population consisted of a higher proportion of women and older subjects than other ultra high risk populations. Women and men had comparable scores on positive as well as negative symptoms and cognitive impairment, but women showed higher scores on affective symptoms. Discussion: The presence of depressive symptoms was found to be associated with having an at risk mental state for developing psychosis. All patients scored high on the Beck Depression Inventory, which implies that the presence of depressive symptoms is independent of the assigned diagnosis in secondary mental health services.

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Background

The first psychotic episode is, in retrospect, generally preceded by a prodromal phase. This phase has been coined the at risk mental state (ARMS)-phase in prospective studies. Research has focused on the development of reliable and valid criteria to detect these ARMS-patients at an early stage, in order to prevent or delay the onset of imminent psychosis or to reduce the duration of untreated psychosis (Miller et al., 2003; Yung et al., 2003; Yung et al., 2005; Yung et al., 2008). The development of psychopathology has been found to be a prodromal sign for the development of psychotic disorders in many cases (Addington, Van Mastrigt, Hutchington & Addington, 2002; Bota, Munro & Sagduyu, 2005; Häfner, et al., 2003; Krabbendam & Van Os, 2005; Yung & McGorry, 1996). A retrospective study in a cohort of 1,753 first episode psychotic patients has shown that there are different help-seeking pathways to psychosis (Rietdijk, et al., 2011a). About 44% came in contact with the mental health care settings after the onset of psychosis. The other 56% of the patients sought help from secondary mental health care services for non-psychotic mental disorders prior to the onset of psychosis. They developed a psychotic disorder later on. In other retrospective studies of schizophrenia patients, 40-75% sought help in the prodromal phase (Addington et al., 2002; Bota et al., 2005). Especially the development of mood- and anxiety disorders have been found to be a prodromal sign for the development of psychotic disorders in many help-seeking cases (Addington et al., 2002; Bota et al., 2005; Häfner et al., 2003; Krabbendam & Van Os, 2005). Recognizing those help-seeking patients that go on to develop psychosis may be particularly challenging as the early symptoms present themselves as the early symptoms of depression or anxiety (Häfner et al., 2005a; Häfner et al., 2005b). A recent review showed that the pathways to psychosis are also gender dependent. Negative symptoms and cognitive impairments are more often associated with the onset of psychotic disorders in males, while affective symptoms and help-seeking characterize the development of psychosis in females (Van Os, Kenis & Rutten, 2010). Non-trained community health caretakers are largely unaware of the at risk mental state for developing psychosis. As a result, many of these patients, especially women, are underrepresented in the traditional referral process to the specialized clinical research settings (Rietdijk et al., 2011b). It would be helpful to have better knowledge of the symptom profiles in ARMS-patients in order to improve early detection strategies in help-seeking populations. The findings described above put forward a set of hypotheses tested with baseline

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characteristics of help-seeking patients included in the Dutch Early Detection and Intervention Evaluation psychosis prevention study (EDIE-NL; Rietdijk et al., 2010). First, we hypothesize that the presence of ARMS is associated with help-seeking for distressing mood- and anxiety disorders. Second, that ARMS-symptoms are accompanied by high scores for depression and anxiety. This might imply a dose-response relationship between the two. Therefore, our third hypothesis is that the presence of more than one ARMS-symptom is associated with increased scores on depression and anxiety. Fourth, ARMS in men is associated with negative symptoms and cognitive impairment. And fifth, ARMS in women is characterized by affective symptoms.

Method

EDIE-NL is a longitudinal randomized controlled trial that compared treatment as usual (TAU) to an add-on cognitive behavioral therapy targeting psychosis-risk symptoms (CBT+TAU). A comprehensive description of the study, its aims, protocol etc. have been described elsewhere (Rietdijk et al., 2010). The design of this study has been approved by the Netherlands Association of Medical Research Ethics Committees (NVMETC) for mental health organizations. The trial was conducted in compliance with the ‘Declaration of Helsinki’ (amendment of Edinburgh, 2000). The trial is registered at Current Controlled trials as trial number ISRCTN21353122.Informed consent was obtained in writing from all EDIE-participants. The parents gave written informed consent for subjects younger than 18 years of age.

SubjectsBaseline data were collected from 201 help-seeking patients who met the At Risk Mental States (ARMS)-criteria as defined by the PACE-clinic (Yung & McGorry, 1996) and entered secondary and tertiary mental health care between February 2008 and February 2010. Two recruitment strategies were used. The consecutive help-seeking populations entering four mental health services (PsyQ The Hague and PsyQ Amsterdam aged 18-35; and GGz Friesland and ABC Utrecht aged 14-35 years) were prescreened with the Prodomal Questionnaire (PQ; Loewy, Bearden, Johnson, Raine & Cannon, 2005). Subjects that scored above the cut-off score of 18 on the relevant items of the PQ and below 65 on the Global Assessment of Functioning (GAF; APA; Endicott, Spitzer, Fleiss & Cohen, 1976) were assessed with the Comprehensive Assessment of At Risk Mental States (CAARMS; Yung et al.,

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2005) interview. In addition, all referrals to the diagnostic center of the Academic Medical Center in Amsterdam and GGz Rivierduinen (aged 14-35 yrs), who were suspected of a development towards florid psychosis or a first psychotic episode of schizophrenia spectrum disorders, and agreed to participate in the study, were assessed with both the PQ (in this case not used as a screening method) and the CAARMS. The ARMS population consists of three different groups defined by the PACE-criteria (Yung & McGorry, 1996):1) patients with a schizotypal personality disorder or a first degree relative with

psychosis (genetic risk group); 2) patients experiencing attenuated positive symptoms (APS), such as ideas of

reference, odd beliefs, magical thinking, or unusual perceptual experiences; and

3) patients experiencing a brief psychotic episode of less than one week in duration that resolves without antipsychotic medication (Brief Limited Intermittent Psychotic Symptoms: BLIPS).

In addition, in all groups social functioning as assessed with the Social and Occupational Functional Assessment Scale (SOFAS; Goldman, Skodol & Lave, 1992) had to be impaired, defined as a SOFAS score of 50 or less over the last year and/or a drop in the SOFAS score of 30%.Exclusion criteria were: 1) current or previous usage of a cumulative dose of antipsychotic medication of in total more than 15 mg Haloperidol equivalent (e.g. maximum of five days of 3 mg); 2) severe learning impairment; 3) psychiatric symptoms due to an known somatic condition; 4) insufficient competence in the Dutch language; 5) a history of psychosis.

InstrumentsA complete description of the instruments used has been published elsewhere (Rietdijk et al., 2010).In short, prodromal symptoms were assessed with the Prodromal Questionnaire (Loewy et al., 2005; PQ, authorized Dutch translation by M. van der Gaag, R. Klaassen and L. Wunderink and named ‘Experiences list’). The PQ is a 92-item self-report questionnaire that assesses the presence of lifetime prodromal symptoms on a two-point scale (true/false). In a pilot-study we have set the cut-off at the score of 18 on the 45 positive symptom items.At-risk mental state was assessed with the Comprehensive Assessment of At Risk Mental States (CAARMS; Yung et al., 2005), including Social and Occupational

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Functioning Assessment Scale (SOFAS; Goldman et al., 1992). The CAARMS is a semi-structured interview that was conducted to determine the presence, severity, frequency and type of ARMS-symptoms. This instrument uses the severity and frequency of positive symptoms (i.e.: unusual thought content, non-bizarre ideas, perceptual abnormalities and disorganized speech) to discriminate between ARMS, psychosis or neither of both with high reliability and validity (86% sensitivity, 91% specificity). Dr. Alison Yung, the main CAARMS developer, extensively trained the researchers. Reliability checks of the Dutch version of the CAARMS were performed approximately every three months during the study. The pair-wise inter-rater concordance of the CAARMS was .97.Negative symptoms were assessed with the negative symptom scales included in the CAARMS (i.e. alogia, apathy and anhedonia).Semantic verbal fluency was assessed with the verbal fluency test (animal category) in which the participants had to name as many animals as possible in 60 seconds (Luteijn & Van der Ploeg, 1983). The performance measure is the number of words.Depression was assessed with both the Dutch translation of the Beck Depression Inventory second edition (BDI-II-NL; Van der Does, 2002) and the Calgary Depression Scale (CDS; Addington, Addington & Schissel, 1990). The CDS is a 9-item interview that assesses depressive symptoms separately of the negative symptoms of schizophrenia.Social anxiety was measured with the Social Interaction Anxiety Scale (SIAS; Mattick & Clarke, 1998). This is a 20-item self-report questionnaire measuring social phobia and social anxiety disorder. Experiences in social situations are rated on a 5-point scale from 0 (not at all characteristic of me) to 4 (extremely characteristic of me). A cut-off score of 43 is indicative for social anxiety.Subjective appraisal of the illness was assessed with the Personal Beliefs about Illness Questionnaire-Revised (PBIQ-R; Birchwood, Mason, MacMillan, & Healy, 1993), a self-rating questionnaire. The subjective quality of life was measured with the Manchester Short Assessment of Quality of Life (MANSA; Priebe, Huxley, Knight & Evans, 1999).DSM-IV diagnoses were assigned by professional caregivers (psychologists and psychiatrists) during intake at the mental health services. Social demographic characteristics were assessed by a demographic questionnaire, designed by the researchers. Variables were chosen on the basis of previous research and known risk factors for psychotic disorders.

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AnalysesBaseline characteristics were explored using the Statistical Package for the Social Sciences (SPSS 18.0 Statistics UK). Multivariate Analyses of Variance (MANOVA) were used to explore differences between both sexes on ARMS-symptoms, negative symptoms and non-psychotic psychopathology. MANOVA corrects for Error Type I and II associated with multivariate testing. Two-tailed Chi-square analyses were performed to assess the association between scores on the ARMS-symptoms and intake diagnosis. A MANOVA explored the association of ARMS-symptoms (i.e. unusual thought content vs. non-bizarre ideas vs. perceptual abnormalities vs. disorganized speech) with psychopathological profiles. MANOVA was also used to explore differences on psychopathology for subgroups who were included on the basis of ARMS- scores on none (genetic risk group only), one, two and three inclusion items. When differences were found, post-hoc tests were used for further examination of these differences.

Results

The study sample included 201 ARMS-patients. Socio-demographic characteristics are presented in table 7.1.

Table 7.1. Socio-demographic characteristics of the EDIE.NL sample. Figures are numbers with percentages in parentheses, unless otherwise indicated

Mean age, sd (range) 22.7, sd = 5.52 (14-35)Years of full-time education, median (range) 13,(0-26)Female 102 (50.7%)Ethnicity N (%)Dutch 119 (59.2)Moroccan 22 (10.9)Turkish 13 (6.5)Surinamese 16 (8)Other non-western 15 (7.5)Other 16 (8)Marital status N (%)Married 44 (21.9)Never married 149 (74.1)Divorced 8 (4)Living situation N (%)Living alone 36 (17.9)With parents 93 (46.3)With partner/kids 55 (27.4)Residential Care 2 (15)Other 15 (7.5)

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Urban Environment in number of inhabitants of the city N (%)< 10,000 14 (7)10,000 – 100,000 66 (32.8)100,000 – 250,000 15 (7.5)250,000 – 500,000 73 (36.3)>500,000 33 (16.4)Attending school 72 (35.8)In paid employment 82 (40.8)Maternal problems N (%)Medication during pregnancy 16 (8)Alcohol during pregnancy 13 (6.5)Smoking during pregnancy 47 (23.4)Undesired pregnancy 38 (18.9)Breastfed 122 (60.7)Head injury 51 (25.4)Previously assigned diagnosis N (%)Adjustment disorder 22 (10.9)Anxiety disorder 47 (23.4)Depressive disorder 51 (25.4)Eating disorder 10 (5.0)Personality disorder 15 (7.5)Posttraumatic stress disorder 10 (5.0)Relationship problems 6 (3.0)Psychosomatic 3 (1.5)Substance abuse 11 (5.5)No DiagnosisUnknown

14 (6.9)12 (5.9)

CAARMS entry route N (%)Genetic risk group only 7 (3.5)APS only 163 (81.1)BLIPS only 3 (1.5)Genetic risk + APS 27(13.4)APS + BLIPS 1 (.5)

Legend table 7.1: APS = attenuated psychotic symptoms; BLIPS = brief limited and intermittent psychotic symptoms.

Figure 7.1 shows the overlap in ARMS-scores on the positive items scale (unusual thought content, non-bizarre ideas, perceptual abnormalities and disorganized speech) of the CAARMS in number of patients. 92 Patients were included on the basis of one positive symptom CAARMS-item; 79 met the criteria of two positive symptom CAARMS-items; and 23 met the criteria of three positive CAARMS-items. Seven patients did not at all meet ARMS-scores on the positive items; they were included merely on the basis of their genetic liability plus decline in functioning (see figure 7.1).

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Perceptual AbnormalitiesPerceptual Abnormalities

Non-bizarre ideas

Unusual thought content

Disorganized speech

41

24

33

2

19

1

17

1 2

1 2 2

25

Genetic vulnerability

7

24

Figure 7.1: Overlap in CAARMS inclusion scales in number of patients

ARMS-symptoms and psychopathologyThe fi rst hypothesis examined the association of ARMS with mood- and anxiety disorders. Table 7.1 shows that 94.1% of the patients was previously diagnosed with an Axis 1 or 2 disorder. As expected the most prevalent disorders appeared to be mood- and anxiety disorders. Two-tailed chi-square analyses found no diff erences between previously assigned diagnoses and the intensity, frequency and experienced distress of the positive symptoms on the CAARMS.Secondly, we analyzed whether ARMS was associated with symptoms of mood and anxiety disorders. Of the patients 17.6% did not meet criteria for depression on the BDI, 15.1% reported a marginal depression, 13.5% reported mild depression, 29.2% reported major depression and 24.6% suff ered from severe depression on the BDI. A total of 28.1% of the patients scored above the cut-off score of 43 for social anxiety on the SIAS. Patients diagnosed with personality disorders scored signifi cantly higher (m= 29, sd= 2.12) on the BDI than patients diagnosed with other disorders (X2(48, N= 199)= 65.43, p= .048). No signifi cant diff erences were found for anxiety scores (SIAS) between diff erent previously assigned diagnoses.

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Thirdly, patients who met criteria for more than one positive symptom, scored higher on psychopathology (see table 7.2). However, these differences were only significant for scores on the Personal Beliefs About Illness Questionnaire. Posthoc-tests revealed that the more sub-clinical symptoms present, the more negative the personal beliefs about illness.

Table 7.2: Severity of psychopathology in patients meeting none, one, two or three CAARMS criteria.

Meets No CAARMS criterion

Meets One CAARMS criterion

Meets Two CAARMS criteria

meets three CAARMS criteria

Mean(st. error)

Mean(st. error)

Mean(st. error)

Mean(st. error)

F-value Df p

SOFAS 46.7 (1.9) 46.1 (.5) 45.6 (.6) 45.1 (1.1) .37 3, 185 .78BDI 13.8 (4.7) 21.6 (1.3) 22.9 (1.5) 23.7 (2.8) 1.29 3, 185 .28SIAS 27.4 (6.4) 30.6 (1.8) 33.6 (2.0) 35.4 (3.8) .83 3, 185 .48PBIQ 64.4 (6.0) 73.2 (1.7) 75.2 (1.9) 83 (3.6) 3.05 3, 185 .03MANSA 61.3 (4.7) 52.2 (1.3) 50.4 (1.5) 50.0 (2.8) 1.81 3, 185 .15CDS 3.5 (1.8) 6.2 (.5) 6.5 (.6) 6.8 (1.1) .87 3, 185 .46Verbal Fluency 23.4 (2.3) 22.4 (.6) 21.7 (.7) 21.1 (1.3) .45 3, 185 .71Legend: CAARMS = Comprehensive Assessment of At Risk Mental States; SOFAS = Social and Occupational Functioning Assessment Scale; BDI = Beck Depression Inventory; SIAS = Social Interactions Anxiety Scale; PBIQ = Personal Beliefs About Illness Questionnaire; MANSA = Manchester Short Assessment of Quality of Life; CDS = Calgary Depression Scale.

Table 7. 3 displays the mean scores and standard errors for psychopathology, negative symptoms and the intensity, frequency and experienced distress of the positive symptoms of the CAARMS for both sexes. No differences were found for both sexes on intensities or frequencies of CAARMS-positive symptoms. MANOVA did not show higher mean scores for negative symptoms and cognitive impairments in men (hypothesis 4). Women reported significantly higher scores on depression, social anxiety, personal beliefs about illness and distress caused by non-bizarre ideas and perceptual abnormalities (hypothesis 5).

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Table 7.3: Baseline symptom profiles and differences across both sexes

TotalN=201

MaleN= 99

FemaleN= 102

Mean(st. error)

Mean(st. error)

Mean(st. error)

F-value Df p

SOFAS 46.0 (.35) 45.4 (.52) 46.3 (.52) 1.70 1, 184 .19BDI 21.6 (.85) 18.9 (1.21) 24.4 (1.20) 7.74 1, 184 .01SIAS 31.7 (1.18) 28.9 (1.69) 43.5 (1.67) 4.40 1, 184 .04PBIQ 74.7 (1.19) 71.6 (1.68) 77.7 (1.65) 6.80 1, 184 .01MANSA 51.6 (.92) 52.8 (1.31) 50.5 (1.29) 1.64 1, 184 .20CDS 6.2 (.35) 4.97 (.49) 7.49 (.48) 13.63 1, 184 .000Verbal Fluency 22.0 (.44) 21.5 (.63) 22.5 (.62) 1.37 1, 184 .24Total negative symptoms 7.13 (.26) 7.05 (.37) 7.21 (.37) .091 1, 184 .76UTC Intensity 2.86 (.12) 2.90 (.16) 2.81 (.16) 0.32 1, 184 .57UTC Frequency 3.10 (.13) 3.24 (.17) 3.00 (.17) 1.24 1, 184 .27UTC Distress 44.5 (2.39) 40.9 (3.22) 48.0 (3.17) 1.97 1, 184 .16NBI Intensity 2.54 (.11) 2.43 (.15) 2.63 (.15) 0.74 1, 184 .39NBI Frequency 3.34 (.14) 3.20 (.19) 3.41 (.18) 0.16 1, 184 .69NBI Distress 53.8 (2.4) 47.2 (3.29) 59.1 (3.24) 5.85 1, 184 .02PA Intensity 3.25 (.10) 3.07 (.14) 3.33 (.14) 1.48 1, 184 .23PA Frequency 3.30 (.11) 3.16 (.16) 3.37 (.16) 0.18 1, 184 .67PA Distress 50.9 (2.33) 44.9 (3.11) 56.0 (3.06) 5.04 1, 184 .03

DIS Intensity 1.70 (.10) 1.74 (.13) 1.65 (.13) 0.39 1, 184 .54DIS Frequency 2.83 (1.93) 2.66 (.21) 2.94 (.21) 0.42 1, 184 .52DIS Distress 24.3 (1.93) 21.7 (2.61) 25.9 (2.58) 1.02 1, 184 .31Legend: SOFAS = Social and Occupational Functioning Assessment Scale; BDI = Beck Depression Inventory; SIAS = Social Interactions Anxiety Scale; PBIQ = Personal Beliefs About Illness Questionnaire; MANSA = Manchester Short Assessment of Quality of Life; CDS = Calgary Depression Scale; UTC = unusual thought content; NBI = non-bizarre ideas; PA = perceptual abnormalities; DIS = disorganized speech.

Discussion

The present paper describes the baseline characteristics of participants in the Dutch Early Detection and Intervention Evaluation (EDIE-NL) study and explored symptom profiles of patients at ultra high risk of developing psychosis. Our sample was help-seeking for several Axis-I disorders, with mood disorders and anxiety disorders as most prevalent diagnoses. However, 82% of the patients scored high on symptoms of depression and 28.1 % of the patients scored high on anxiety, independent of their previously assigned diagnosis. No distinct psychopathological pathways were found for patients experiencing unusual thought content, non-bizarre ideas, perceptual abnormalities or disorganized speech. Both sexes showed comparable scores for cognitive impairment (verbal fluency) and on intensity and frequency of the positive as well as negative symptoms. Women scored significantly higher on symptoms of depression, anxiety, and distress caused by non-bizarre ideas and perceptual abnormalities.

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The results show an overlap in perceptual abnormalities/hallucinations, unusual thought content and non-bizarre ideas. In this cross-sectional study, it is impossible to determine how unusual thought content, non-bizarre ideas and perceptual abnormalities are related. One recent study of college students (77% female) found that perceptually aberrant experiences may play a part in the emergence of self-reported subclinical paranoid patterns of thinking (Tone, Goulding & Compton, 2011).In line with the hypothesis that development of psychosis is mediated by emotional arousal, the results of this study demonstrate that the at risk mental state is associated with general psychopathology. This result corresponds to the results of previous studies which suggested depression to be associated with the late prodromal stage of psychosis (Corcoran et al., 2011; Häfner et al., 2003; Häfner et al., 2005b; Van Rossum, Dominguez, Lieb, Wittchen & Van Os, 2011). As mentioned earlier, more than fifty percent of a cohort of first episode patients sought treatment in secondary mental health care settings in the Netherlands for non-psychotic mental problems before the onset of psychosis (Rietdijk et al., 2011a).Although the results of the current study demonstrate that mood and anxiety disorders were the most prevalent disorders, it also shows that patients with an at risk mental state may experience several other Axis 1 and 2 disorders. Also, the symptoms reported on the Beck Depression Inventory (Van der Does, 2002) and Calgary Depression Scale (Addington et al., 1994) were comparable for all patients, independent of diagnosis, number of experienced positive symptoms and type of positive symptoms experienced. Patients diagnosed with personality disorders scored significantly higher on depression than patients diagnosed with other disorders (including mood disorders). This suggests that at risk mental states for psychosis are associated with help-seeking for all mental disorders and with distressed feelings. We did not find an increase in depression or anxiety when patients experienced more than one positive symptom. We did find however that the number of sub-clinical positive psychotic symptoms was associated with stronger negative beliefs about the illness: the more sub-clinical symptoms that are experienced, the more negative the personal beliefs about illnesses.As hypothesized, women in our study showed more symptoms of depression, anxiety and distress compared to men. This is in line with previous research showing that affective symptoms, social conflict and help-seeking behavior characterize the development of psychosis in females (Van Os et al., 2010). The same authors also suggested that psychotic onsets in men are more often associated with negative

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symptoms and cognitive impairments. However, the results of the present study show no differences in negative symptoms or cognitive impairments on the verbal fluency test for both sexes. Negative symptoms and cognitive impairments are present in all ARMS-patients. Population characteristicsOur study population differs slightly from other populations in terms of gender distribution. About fifty percent of the included subjects were female, whereas other trials included more male subjects (McGlashan et al., 2006; Morrison et al., 2011). However, our gender distribution is comparable to the gender distribution of the populations included in a study of the PACE clinic in Australia (Phillips et al., 2009). Based on the results of previous studies, it is suggested that the onset of schizophrenia and related psychotic disorders is gender and age related; as a result referral to early detection settings might be biased towards young men. However, in the present study the positive symptoms were comparable in both men and women. Moreover, the positive symptoms in both sexes were comparable to symptoms in other at-risk mental state for psychosis populations, which included a higher percentage of men (Morrison et al., 2011). The present results are supported by previous epidemiological studies, which found that the core symptoms of schizophrenia were comparable for both sexes, although the mean age of onset for psychosis was three to four years higher in females (Häfner et al., 1993). Other studies however did find differences in symptoms and functioning across the sexes (Lewine, 1981). However, it is not clear whether these differences were actually the result of age at onset rather than gender. Schizophrenia may show the same phenotype in both sexes, but the clinical presentation might seem to be different as a result of the later onset in women. The differences in the gender profile of the current population compared to other populations might also be the result of the unique recruitment strategies used in the current study. This study was the first to include both the consecutive cases in a general help-seeking population entering the secondary mental health care settings and referrals to a specialized academic diagnostic center (Rietdijk et al., 2011b). Other studies are completely dependent on referral to their research programs (Morrison et al., 2011; Yung et al., 2011). We concluded in a previous paper that the screening procedure detected a group of patients who were at risk for a first psychotic episode, but who did not all match the traditional profile of a schizophrenia development (e.g. male, young age, negative symptoms and marked decline in social functioning) (Rietdijk et al., 2011a). The community health

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caretakers do not routinely assess subclinical psychotic symptoms. In addition, the screening method detected not only those patients at ultra high risk of developing a psychosis in the schizophrenia spectrum, but also in the affective spectrum (i.e. bipolar disorders and mood disorders with psychotic features). This suggests that many of the patients with an ultra high risk for developing any first episode psychosis, especially women, are overlooked in the traditional referral process to specialized or research settings. Previous research has indicated that patients who are in care for other psychological problems and become psychotic during treatment, have a longer duration of untreated psychosis (Boonstra, Wunderink, Sytema & Wiersma, 2008; Brunet, Birchwood, Lester & Thornhill, 2007). Boonstra et al. (2008) found that only 33% of patients presenting with a psychotic symptom in the secondary mental health care services of Friesland in the Netherlands was assigned to a diagnosis of psychosis. In addition, of all the patients who were referred to the Academic Diagnostic Center because of suspicion of an at risk mental state for psychosis, 36% were actually found to be already full-blown psychotic (Nieman et al., 2009).The patients included in our study are somewhat older (mean age 22.7 years) than the populations in other prevention trials (means 18-19 years). This is largely the result of the selected age-range of the recruitment populations. Recruitment in most prevention trials is conducted in populations with an age range of 14-30 years (Morrison et al., 2011), whereas our study was conducted in a population of 14-35 years. In The Hague, the site with most inclusions (n= 93), the minimum age of inclusion was even higher (18 years) as ‘PsyQ Haaglanden’ only provides adult care. Other studies show that mean ages for having an at risk mental state and the mean age for psychosis onset vary when studied in different populations. Clinical trials conducted in adolescent age groups recruited ARMS-populations with a mean age of 18-19 (Morrison et al., 2011; Phillips et al., 2009), whereas recruitment in adult cohorts had mean ages of 25 (Koutsouleris, 2011) and 26 years (Allen et al., 2011). Häfner et al. (1993) found a mean onset age of 29 in a first episode cohort. This supports our hypothesis that research on high-risk patients and first episode patients may be biased toward younger age groups.

Strengths and limitationsThe results in this paper must be interpreted in the light of the limitations of this study. The first limitation concerns the recruitment of the included patients using two different inclusion methods. The use of the two different methods may have resulted in the inclusion of two different populations. As reported in a previous

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publication, the screening method detected a threefold higher incidence of at risk mental states and transition to psychosis than the referral strategy (Rietdijk et al., 2011b). Both populations differed on demographic characteristics and psychopathology, with the screening method yielding a larger percentage of included females and an older mean age. Analyses of the subgroups did find that age significantly influenced the transition rate: older people converted into psychosis more often. No effect was found for gender on symptoms (Rietdijk et al., 2011b). A second limitation is that the study used self-report questionnaires for assessing mood, anxiety, quality of life and personal beliefs about illness. This could result in biases, e.g. over-reporting of symptoms. On the other hand, previous studies showed that self-reporting is reliable in help-seeking and general populations, (Eaton, Romanoski, Anthony & Nestadt, 1991; Hanssen, Bak, Bijl, Vollenberg & Van Os, 2005) and the used questionnaires reported good reliability and validity. A third limitation is that the first contact diagnoses were assigned by caregivers. We may question the reliability of these initial diagnoses, since psychiatrists and psychologists generally do not use diagnostic instruments during intake to establish the presence of symptoms. It is however the current practice.The strong internal and external validity is a strength of this study. The contributing services all implemented the early detection procedure in routine care, which has an immediate and positive effect on clinical practice. All raters who interviewed the patients with the CAARMS received intensive two-day training by Alison Yung, who was the principal investigator and developer of this instrument. Fidelity checks were conducted every three months.

Conclusions and clinical implicationsThe emphasis on adolescence and young adulthood as the characteristic period of onset of schizophrenia and related disorders has probably led to an overrepresentation of young men in clinical research settings. In addition, the high-risk symptoms are non-specific and not easily detected by health professionals who are the most important referrers to specialized clinical and research settings. As a consequence, referral to specialized research programs may be biased towards an overrepresentation of young men. The symptoms reported in the male and female subpopulations are comparable to those reported in the other studies. Furthermore, at-risk mental states were associated with high scores of depression in 82% of the population. These high scores were uniformly present in a variety of disorders, not only in patients diagnosed with mood disorders. This implies that

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having an at-risk mental state is generally accompanied by low mood. Pending the outcome of future studies, for instance in general help-seeking populations, we hope that the inclusion procedure based on systematic screening of help-seeking patients at the entry of mental health care services will be useful in detecting those patients who are overlooked by referral strategies.

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