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Self-reported attenuated psychotic-like experiences in help-seeking adolescents and their association with age, functioning and psychopathology
Schizophrenia Research 160 (2014) 110–117
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Self-reported attenuated psychotic-like experiences in help-seeking adolescents and their association with age, functioning and psychopathology Martina Brandizzi a,c,⁎,1, Frauke Schultze-Lutter b,1, Alice Masillo c, Andrea Lanna d, Martina Curto a, Juliana Fortes Lindau a, Andrea Solfanelli a, Giulia Listanti c, Martina Patanè c, Giorgio Kotzalidis a, Eva Gebhardt a, Nicholas Meyer f, Diana Di Pietro e, Donato Leccisi e, Paolo Girardi a, Paolo Fiori Nastro c a Neurosciences, Mental Health and Sensory Functions (NESMOS) Department, Sapienza University of Rome, Faculty of Medicine and Psychology, Sant'Andrea Hospital, Via di Grottarossa 1035, 00189 Rome, Italy b University Hospital for Child and Adolescent Psychiatry and Psychotherapy, University of Bern, Bolligenstr. 111, Haus A 3000 Bern 60, Bern, Switzerland c Department of Neurology and Psychiatry, Sapienza University of Rome, Faculty of Medicine and Odontology, Rome 00156, Italy d Department of Computer, Control, and Management Engineering “A. Ruberti”, Sapienza University of Rome, Rome 00185, Italy e Community Mental Health Service, ASL Rome H, 00041 Rome, Italy f Institute of Psychiatry, King's College, 16 De Crespigny Park, SE5 8AF London, United Kingdom
a r t i c l e
i n f o
Article history: Received 5 June 2014 Received in revised form 13 September 2014 Accepted 7 October 2014 Available online 29 October 2014 Keywords: Ultra-high risk Screening Attenuated psychotic-like experiences Perceptual abnormalities Children and adolescents
a b s t r a c t Objective: Self-rated attenuated psychotic-like experiences (APLEs) are increasingly used to screen for ultra-highrisk (UHR) across all ages. However, self-rated psychotic-like experiences (PLEs), in particular perception-related ones, were more frequent in children and adolescents, in which they possessed less clinical significance. We therefore explored the prevalence of different factors of APLEs in help-seeking adolescents, and their relationship with age, functioning and psychopathology. Method: As a part of the “Liberiamo il Futuro” project, help-seeking adolescents (N = 171; 11–18 years, 53% male) were screened with the 92-item Prodromal Questionnaire (PQ-92). A factor analysis was performed on the PQ-92 positive items (i.e., APLEs) to identify different APLE-factors. These were assessed for their association with age, functioning and psychopathology using regression analyses. Results: APLEs were very common in help-seeking adolescents, and formed four factors: “Conceptual Disorganization and Suspiciousness”, “Perceptual Abnormalities”, “Bizarre Experiences”, and “Magical Ideation”. Associations with age and functioning but not psychopathology were found for “Perceptual Abnormalities” that was significantly more severe in 11–12-year-olds, while “Conceptual Disorganization and Suspiciousness” was significantly related to psychopathology. Conclusion: In line with findings on PLEs, prevalence and clinical significance of APLEs, especially perceptionrelated ones, might depend on age and thus neurodevelopmental stage, and may fall within the normal spectrum of experience during childhood. This should be considered when screening for UHR status in younger age groups. © 2014 Elsevier B.V. All rights reserved.
1. Introduction Early detection of psychosis has become an important topic in psychiatry for which two main approaches have been developed: the ultra-high risk (UHR) approach and the basic symptom (BS) approach (Fusar-Poli et al., 2013; Schultze-Lutter et al., 2014a). However,
⁎ Corresponding author at: Department of Neurology and Psychiatry, UOD Psicoterapia, Sapienza University of Rome, Faculty of Medicine and Odontology, Via Casal Dè Pazzi 16, 00156 Rome, Italy. Tel.: +39 0 6 4080 0589; fax: +39 0 6 4070 447. E-mail address: [email protected] (M. Brandizzi). 1 Joint first authors.
http://dx.doi.org/10.1016/j.schres.2014.10.005 0920-9964/© 2014 Elsevier B.V. All rights reserved.
instruments assessing UHR criteria generally require additional training even of mental health specialists and several hours of clinicians' time. 1.1. Screening for ultra-high risk status using self-report questionnaires Therefore, self-report screening instruments were developed to preselect potential UHR patients for in-depth clinical assessment; one is the 92-item Prodromal Questionnaire (PQ-92) (Loewy et al., 2005; 2011) that is based on the Structured Interview for Psychosis-Risk Syndromes (SIPS; McGlashan et al., 2010; Miller et al., 2003). Concurrent validity of the PQ-92 was reported for different clinical samples: (1) patients from an early detection center (N = 113; 12–35 years) (Loewy et al., 2005); (2) patients from a secondary mental health service (N = 3,671;
M. Brandizzi et al. / Schizophrenia Research 160 (2014) 110–117
18–35 years) (Ising et al., 2012) with a cut-off “≥18 positive symptoms” predicting SIPS-UHR status with 90% sensitivity and 90% specificity; and (3) adolescent patients from a general mental health clinic (N = 80; 15–18 years) (Loewy et al., 2012) where both sensitivity (82%) and specificity (49%) were lower using the same cut-off, although psychosis-predictive validity of the PQ-assessed UHR status was comparable to that of the SIPS-assessed at one-year follow-up. 1.2. Age-related differences of self-reported (attenuated) psychotic symptoms Most research on the PQ-92 has been carried out in mixed adolescent–young adult samples with little consideration of age-related differences. In a community sample of children and adolescents, agerelated differences were reported for prevalence rates of self-rated psychotic-like experiences (PLEs). In particular, perception-related PLEs clearly decreased with age (from 21–23% of 11–13-year-olds to 7% of 13–16-year-olds), and increased in association with poorer socio-occupational functioning (Kelleher et al., 2012a; 2014) and with the presence of mental disorder (Kelleher et al., 2012a; Laurens et al., 2012). However, longitudinal studies of adolescents in the community (Dominguez et al., 2011; Smeets et al., 2012) suggest that persistence rather than prevalence of PLEs increases psychosis-risk. Yet, PLEs appeared to be poor estimates of clinician-assessed attenuated psychotic symptoms (APS), the main UHR criterion (Schultze-Lutter et al., 2011, 2014b). Thus, the content-valid assessment of APS might require specialized instruments such as the PQ-92. Furthermore, symptoms related to psychosis-risk were reported to cluster differently in children and adolescents compared to adults (Schultze-Lutter et al., 2012; Fux et al., 2013). From these findings, a need for research into the early detection of psychosis across the child and adolescent age-range was identified (Schimmelmann and Schultze-Lutter, 2012; Schimmelmann et al., 2013). 1.3. Aims and hypotheses In order to address the need for age-related research in the study of self-reported attenuated psychotic-like experiences (APLEs), we examined the structure and prevalence of APLEs assessed with the positive symptom PQ-92-subscale, as a self-report estimate not of psychotic symptoms but of APS in help-seeking adolescents. In addition to a perception-related factor, we expected a three-factor structure of delusion-like experiences similar to that reported for the Community Assessment of Psychic Experiences (CAPE) in 15–24-yearolds (N = 140) (Yung et al., 2006), despite the PQ-92 assessing a broader spectrum of APLEs. Consistent with other PLE studies, a high prevalence of APLEs was expected, being highest in younger age groups, in particular with respect to perception-related APLEs. Additionally, an association of the presence and number of APLEs with poor functioning and psychopathology was hypothesized that might differ in strength between APLE-factors. 2. Materials and methods 2.1. Setting Data were collected in six Child and Adolescent Neuropsychiatric Services (CANS) in the area of Roma H, Rome, Italy, between January 2012 and July 2013 as part of the early detection project “Liberiamo il Futuro” (LIF; Supplement material S1). 2.2. Sample Inclusion criteria were: age between 11 and 18 years, residency in the Roma H area, and help-seeking from services for any psychological or behavioral problem. Of 384 eligible adolescents, 171 (44%) individuals
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and their parents or guardians gave written informed consent to participate. Ethical approval was obtained from the local research ethics committee. Participants were significantly older than refusers (mean ± SD: 14.8 ± 1.9 vs. 14.3 ± 1.8; median: 15 vs. 14; U = 15186.0; p = 0.005), though the effect size was small (Rosenthal's r = −0.14) with no gender difference (male: 53% of participants vs. 56% of refusers; χ2 (1) = 0.164; p = 0.381). 2.3. Assessments APLEs and self-reported negative, disorganized and general symptoms were assessed with an Italian translation of the PQ-92 that takes approximately 20 min to complete (Loewy et al., 2005). The translation was conducted by a trainee in psychiatry and a PhD student both fluent in English, with back-translation by a bilingual trainee in psychiatry. PQ92 items were adapted from the SIPS and the Schizotypal Personality Questionnaire (Raine, 1991). Statements are rated true (1) or false (0); four subscales scores can be obtained by adding up affirmative responses: 1) 45 (attenuated) positive symptoms, i.e. APLEs (PQ-positive; Table 2), 2) 19 negative symptoms (PQ-negative; e.g., flat affect, social isolation), 3) 13 disorganization items (PQ-disorganization; e.g., odd behavior) and 4) 15 general symptoms (PQ-general; e.g., depression, functional deficits). For a global rating of psychological, social and occupational functioning, we used the Global Assessment of Functioning Scale (GAF) (Hall, 1995) that had been part of DSM-IV (APA 1994) but was not included in the DSM-5 (APA, 2013). A cut-off of ‘60’ was considered to distinguish between poor and good general functioning (Bachmann et al., 2008; Schennach-Wolff et al., 2009). As additional functional outcome measures, two scales developed for the National Institute of Mental Health-funded multi-site NAPLS project (Cornblatt et al., 2007) were used: the GF:Social scale assessing social functioning by taking into account quantity and quality of peer and family relationships/conflicts including age-appropriate intimate relationships (Auther et al., 2006), and the GF:Role scale measuring role functioning by taking into account quantity and quality of school, work or homemaker performance (Niendam et al., 2006; Cornblatt et al., 2007). Both scales are rated between ‘1’ (extreme dysfunction) and ‘10’ (superior functioning); a cut-off of ‘6’ distinguishes between poor and adequate functioning (Schlosser et al., 2012; Carrion et al., 2013). Past and present axis-I DSM-IV diagnoses were evaluated with the Kiddie-Schedule for Affective Disorders and Schizophrenia — Present and Lifetime (K-SADS-PL) version (Kaufman et al., 1997), a reliable semi-structured psychiatric interview. 2.4. Data analysis Analyses were conducted using SPSS 20.0. Where Kolmogorov– Smirnov (K–S) tests for normal distribution were significant, nonparametric analyses of continuous data were preferred. Number and type of APLE-factors were determined using principal component analysis (varimax and oblimin method). Initially, the requirement of sufficient frequency of correlations N 0.3 was assured by inspection of the correlation matrix (Tabachnick and Fidell, 2007). Optimum number of factors was established using the Kaiser's method (Field, 2005) and a screen plot (Cattell, 1966). Associations of the presence and number of APLEs with age, socio-demographic variables (i.e., gender, positive family history of any psychiatric disorder), functioning (i.e., binary: GF:Role, GF:Social and GAF) and symptomatology (i.e., any anxiety or depressive disorder, PQ-negative, PQ-disorganization, PQ-general) were independently explored by binary, multinominal and ordinal regression analyses with the presence/severity of APLE-factors as covariates. In ordinal regression analyses, the complementary log–log option was chosen assuming that higher categories are more probable.
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3. Results 3.1. Sample characteristics and their association with age About half of the sample was male with fewer girls among the 11– 12-year-olds (Table 1). All but 6 patients (3.5%) were in education and those aged 11–14 were more likely to attend primary school; 17–18year-olds were more likely to have sought help on their own initiative. The main reasons for referral were school or peer relationship problems (40.0%) and anxiousness or depressiveness (40.0%). School difficulties were most frequent in 11–12-year-olds and least frequent in 17–18year-olds who often reported ‘other’ reasons, mainly related to aggressiveness or subclinical psychotic experiences (Table 1). Independent of age, anxiety (27.0%) and mood disorders (21.4%) were frequent. Illicit drug use was most likely reported by 17–18-year-olds and least likely by 11–12-year-olds. Poor functioning was frequent with no indication of an age effect (Table 1).
3.2. Factors of APLEs A four-factor solution best fitted the 45 APLEs accounting for 34% of the explained variance, with only nine variables showing crossloadings ≥ 0.35 (Table 2). Three factors related to delusional APLEs and one to perception-related APLEs. Factor 1 was composed of 15 items that generally related to “Conceptual Disorganization and Suspiciousness” (CDS), among these, the eleven most frequently endorsed items ranged from ‘comprehension problems of others’ in 39.8% of patients to ‘déjà-vu’ in 67.8%. Factor 2 included 11 items describing “Perceptual Abnormalities” (PA). Factor 3 consisted of 13 items that
could generally be described as “Bizarre Experiences” (BE), mainly in terms of experiences resembling ideas of reference or so called IchStörungen. Factor 4 contained only six items relating to “Magical Ideation” (MI). 3.3. Prevalence and frequency of APLEs APLEs were commonly reported, with 167 patients (97.7%) disclosing at least one. CDS was the most prevalent factor, with 95% (n = 163) reporting at least one of its 15 items. A further 130 patients (76.0%) reported at least one BE-item, and 104 (60.8%) at least one MI-item. In all, any one delusional APLE was as frequent as any APLE. At least one PAitem was less frequently reported by only 126 patients (73.7%), always in conjunction with a delusion-like experience. The median number of APLEs was 13 (0–36 of 45). The median number of PA-items was two (0–11 of 11), that of CDS-items seven (0–15 of 15), that of BE-items two (0–12 of 13), and that of MI-items only one (0–5 of 6); the median number of delusional APLEs was ten (0–27 of 34). KS-tests indicated a non-normal distribution of most PQ-factors and subscales (Supplementary material 2, Table S2-1). 3.4. Association of age and other sociodemographic variables with APLEs Multinominal regression analysis with the four APLE-factors as covariates and 17–18-year-olds as the reference group indicated an association of higher PA scores with an age of 11–12 years (Exp(β) = 1.309; 95% CIs: 1.039/1.649) and an association of lower BE scores with an age of 15–16 years (Exp(β) = 0.805; 95% CIs: 0.656/0.989) (Table 3). The age effect of PA but not that of BE remained when GF:Social, GF:Role,
Table 1 Socio-demographic and clinical characteristics and correlation by age group (N = 171).
Age groupsa
Gender Educational levelb
Sources of referral
Reasons for referral
Main diagnosis (K-SADS-PL)
Previous contact with mental health services Family history of any mental disorder Present use/misuse/dependence of illicit drugs GF:Social GF:Role GAF PQ-threshold (≥18 PLEs) met
11–12 13–14 15–16 17–18 Male Primary school Lower secondary school Upper general secondary school Upper vocational secondary school Psychiatrist or other specialist School or family Patient's own initiative Anxious or depressive symptom School difficulties Peer relationship difficulties Other None Anxiety disorder Mood disorder Conduct or learning disorder, ADHD Other Yes Yes Yes Poor (≤6) Poor (≤6) Poor (≤60) Yes
N
%
30 52 49 40 90 64 98 5 4 28 115 22 66 42 24 33 22 43 34 23 37 59 47 34 54 73 50 43
17.5 30.4 28.7 23.4 52.6 37.4 57.3 2.9 2.3 17.0 69.7 13.3 40.0 25.5 14.5 20.0 13.8 27.0 21.4 14.5 23.3 35.3 27.6 21.1 34.2 46.2 35.0 25.1
Coefficient of contingency, C (p)
0.210 (0.048) c 0.562 (b0.001) d
0.286 (0.023) e
0.370 (0.002) f
0.281 (0.322)
0.141 (0.337) 0.082 (0.767) 0.330 (b0.001) g 0.147 (0.320) 0.200 (0.086) 0.063 (0.904) 0.103 (0.401)
K-SADS-PL: Kiddie-Schedule for Affective Disorders and Schizophrenia—Present and Lifetime Version; 12 patients refused the interview. GAF: Global assessment of functioning relying on both social and occupational functioning and psychopathology. a Mean age of total sample was 15 (SD = 2) years at a median age of 15; no significant distribution differences across the 4 age groups (1-dimensional χ2(3) = 6.895, p = 0.075). b Only 6 patients (3.5%) were not in school or occupational training. c Main effect for fewer girls among 11–12-year-olds (only 27% as compared to 48–59%; standardized residual, SR = −1.6). d Main effects for more primary school and less higher education levels among 11–12- as well as 13–14-year-olds (SR = 4.4 and 2.2). e Main effect for more help-seeking on patient's own initiative in 17–18-year-olds (SR = 2.9). f Main effects for more school difficulties in 11–12-year-olds (SR = 2.3) and fewer school difficulties, but more other reasons in 17–18-year-olds (SR = −2.9 and 1.8). g Main effects for fewer use in 11–12-year-olds (SR = −2.1) and more in 17–18-year-olds (SR = 2.7).
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Table 2 Factor loadings (N0.3) and item frequencies in % in descending order. #
Item description
8 3 38 77 25 2 49 27 57 55 90 60
I often seem to live through events exactly as they happened before (déjà vu). I have difficulty organizing my thoughts or finding the right words. I often feel that other people are watching me or talking about me. I am often concerned that my closest friends and co-workers are not really loyal or trustworthy. I often feel that others have it in for me. The passage of time feels faster or slower than usual. My thinking feels confused, muddled, or disturbed in some way. I have felt that I am not in control of my own ideas or thoughts. I have been confused at times whether something I experienced was real or imaginary. At times I worry that something may be wrong with my mind. People sometimes find it hard to understand what I am saying. I have experienced unusual bodily sensations such as tingling, pulling, pressure, aches, burning, cold, numbness, shooting pains, vibrations or electricity. Other people say that I wander off the topic or ramble on too much when I am speaking. Sometimes I feel suddenly distracted by distant sounds that I am not normally aware of. My thoughts are sometimes so strong that I can almost hear them. I often pick up hidden threats or put-downs from what people say or do. I sometimes smell or taste things that other people don't notice. I have had the sense that some person or force is around me, even though I could not see anyone. I feel that parts of my body have changed in some way, or that parts of my body are working differently. I sometimes use words in unusual ways. Familiar surroundings sometimes seem strange, confusing, threatening or unreal. I have many thoughts that fill my mind and compete for my attention. My sense of smell sometimes becomes unusually strong. I have heard my own thoughts as if they are outside of my head. I sometimes feel that things I see on the TV or read in the newspaper have a special meaning for me. Sometimes I am sure that other people can tell what I am thinking or feeling without me telling them. I believe in telepathy, psychic forces, or fortune-telling. I have heard things other people can't hear like voices of people whispering or talking. I am unusually sensitive to noise. I hold beliefs that other people would find unusual or bizarre. I believe that I am very important or have special gifts. I often hear unusual sounds like banging, clicking, hissing, clapping or ringing in my ears. I sometimes see special meanings in advertisements, shop windows, or in the way things are arranged around me. I am superstitious. When I look at a person, or look at myself in a mirror, I have seen the face change right before my eyes. I have felt that I don't exist, the world does not exist, or that I am dead. I sometimes get strange feelings on or just beneath my skin, like bugs crawling. Some people drop hints about me or say things with a double meaning. Things that I see appear different from the way they usually do (brighter or duller, larger or smaller, or changed in some other way). I have seen unusual things like flashes, flames, blinding light or geometric figures. Sometimes my thoughts seem to be broadcast out loud so that other people know what I am thinking. I have seen things that other people can't see or don't seem to. I often mistake shadows for people or noises for voices. At times I have felt that some person or force interferes with my thinking or puts thoughts into my head. I have had experiences with the supernatural, astrology, seeing the future or UFOs.
23 50 65 68 9 52 64 69 7 37 26 36 46 12 24 13 34 61 30 18 67 35 4 56 5 76 20 79 32 84 19 74 75
F1
F2
0.38 0.48 0.60 0.50 0.68 0.37 0.68 0.54 0.57 0.55 0.48
F3
F4
67.8 62.0 59.6 54.4 52.6 52.6 46.8 44.4 43.3 40.4 39.8 36.3
(0.35)
0.53
(−0.39)
0.43 0.58 0.56
(0.35)
0.58 0.59
−0.56 (−0.43) (0.38) 0.31 −0.64
0.32 0.44 0.33 (0.50)
(0.39) −0.50 −0.55 −0.58 0.64
0.62 0.54 0.71 (0.36) 0.76
−0.49 −0.59 0.51 −0.35 0.35 −0.42 −0.40 −0.35
(0.47)
0.60 −0.46 0.64 0.45 −0.33 (0.35)
%
0.35
35.1 35.1 33.3 31.6 30.4 29.2 28,7 28.7 26,9 26.9 26.9 25.1 25.1 25.1 23.4 22.8 22.2 21.6 20.5 20.5 20.5 19.9 19.9 19.3 18.7 16,4 16.4 15.8 15.8 15.2 15.2 14.0 8.8
#: PQ-item number; F1: Factor 1 ‘Conceptual Disorganization and Suspiciousness’ (CDS), 15 items; F2: Factor 2 ‘Perceptual Abnormalities’ (PA), 11 items; F3: Factor 3 ‘Bizarre Experience’ (BE), 13 items; F4: Factor 4 ‘Magical Ideation’ (MI), 6 items; model fit: Kaiser–Meyer–Olkin measure of sampling adequacy: 0.780; Bartlett's test of sphericity: 2 (990) = 2446.6; p b 0.000.
PQ-negative, PQ-disorganization and PQ-general were entered into the model (Table S2-2). Entering gender and family history into the regression analysis of age again did not alter the age effect of PA but rendered that of BE insignificant (see Supplementary Table S2-2). Furthermore, higher CDS scores were associated with significantly increased odds for female gender (Exp(β) = 1.240; 95% CIs: 1.107/1.388), and higher BE scores with increased odds for a positive family history (Exp (β) = 1.277; 95% CIs: 1.085/1.504); education was unrelated to APLEfactors (Table 3). With regard to the presence of APLE-factors (see Supplementary Table S2-3), the only significant association indicated the absence of CDS being predictive of primary school level (Exp(β) = 0.00062; 95% CIs: 0.00013/0.0029). At a trend level, an additional association of PA presence with being 11–12-years-old was found (p = 0.061; Exp(β) = 4.397; 95% CIs: 0.935/20.678).
functioning (Exp(β) = 1.265; 95% CIs: 1.083/1.477). Poor functioning according to GAF and the presence of an anxiety or a mood disorder diagnosis were unrelated to PQ-factors. Across all three ordinal regression analyses of PQ-subscales, CDS was a significant predictor of psychopathology (PQ-negative: 0.303 (95% CIs: 0.238/0.367); PQ-disorganization: 0.172 (95% CIs: 0.116/0.229); PQ-general: 0.223 (95% CIs: 0.164/0.283)), complemented only by PA in case of PQdisorganization (0.093; 95% CIs: 0.021/0.166) (Table 4). With regard to the presence of APLE-factors (see Supplementary Table S2-3), the only significant association indicated that the presence of BE was predictive of poor social functioning (Exp(β) = 2.639; 95% CIs: 1.016/6.851). Otherwise, trend-level associations of the presence of PA with poor role functioning (p = 0.053; Exp(β) = 2.326; 95% CIs: 0.991/5.462) and poor general functioning (p = 0.055; Exp (β) = 2.624; 95% CIs: 0.980/7.022) were found.
3.5. Association of disability and psychopathology with APLEs
4. Discussion
Higher PA scores were significantly associated with a higher likelihood of poor social (Exp(β) = 1.226; 95% CIs: 1.054/1.426) and role
Consistent with other PLE studies, our study found a high prevalence of APLEs, with perception-related APLEs highest in younger age groups
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M. Brandizzi et al. / Schizophrenia Research 160 (2014) 110–117
Table 3 Results of regression analyses of effect of age and sociodemographic variables on APLE factors. Dependent variable (reference category)
Covariates
Age group (17–18 years)
11–12 years CDS PA BE MI 13–14 years CDS PA BE MI 15–16 years CDS PA BE MI CDS PA BE MI CDS PA BE MI Primary CDS PA BE MI Lower secondary CDS PA BE MI Upper secondary general CDS PA BE MI
Gender (female)
Family history (present)
Education (upper secondary-vocational)
β
−0.177 −0.055 0.269 −0.189 0.018 0.048 0.028 0.150 −0.173 0.108 −0.085 −0.049 0.141 −0.217 0.022 0.215 −0.106 −0.066 0.021 −0.109 −0.043 0.245 −0.047 2.365 0.019 0.490 −0.188 −0.193 2.344 0.126 0.306 −0.065 −0.278 1.004 0.064 0.046 −0.435 −0.729
SE
0.484 0.084 0.118 0.120 0.210 0.438 0.073 0.103 0.101 0.180 0.459 0.076 0.111 0.105 0.191 0.058 0.083 0.077 0.135 0.060 0.083 0.083 0.150 0.982 0.186 0.352 0.276 0.433 0.977 0.184 0.349 0.271 0.429 1.214 0.246 0.533 0.503 0.748
Wald
0.134 0.431 5.223 2.472 0.008 0.012 0.153 2.118 2.947 0.358 0.034 3.413 0.196 4.276 0.013 13.836 2.126 0.747 0.024 3.321 0.272 8.633 0.096 5.800 0.010 1.941 0.465 0.200 5.755 0.469 0.767 0.058 0.420 0.684 0.068 0.008 0.747 0.949
p
0.714 0.511 0.022⁎ 0.116 0.930 0.912 0.696 0.146 0.086 0.550 0.853 0.065 0.658 0.039⁎ 0.908 0.000⁎⁎ 0.145 0.387 0.878 0.068 0.602 0.003⁎⁎ 0.757 0.016 0.919 0.164 0.495 0.655 0.016 0.493 0.381 0.810 0.517 0.408 0.931 0.794 0.388 0.330
Exp(β)
95%-CI of Exp(β) Lower
Upper
0.946 1.309 0.828 1.019
0.803 1.039 0.654 0.676
1.115 1.649 1.048 1.536
1.029 1.161 0.841 1.114
0.892 0.949 0.691 0.782
1.186 1.421 1.025 1.586
0.952 1.151 0.805 1.022
0.767 0.991 0.656 0.703
1.183 1.337 0.989 1.486
1.240 0.899 0.936 1.021 0.896 0.958 1.277 0.955 1.019 1.633 0.828 0.824
1.107 0.779 0.805 0.783 0.797 0.815 1.085 0.711 0.708 0.819 0.482 0.353
1.388 1.037 1.088 1.330 1.008 1.126 1.504 1.282 1.468 3.256 1.423 1.926
1.135 1.358 0.937 0.757
0.790 0.685 0.551 0.327
1.629 2.690 1.593 1.754
1.066 1.047 0.647 0.482
0.659 0.368 0.241 0.111
1.726 2.978 1.736 2.091
CDS: Conceptual Disorganization and Suspiciousness; PA: Perceptual Abnormalities; BE: Bizarre Experience; MI Magical Ideation. ⁎ p b 0.05. ⁎⁎ p b 0.005.
(11–12 years). Additionally, an association of PA with poor role and social functioning and of CDS with psychopathology emerged.
4.1. Prevalence and frequency of APLEs The prevalence of PLEs in the community exceeds that of psychosis by far, especially when assessed with self-report measures (Linscott and van Os, 2013), and PLEs are even more frequent in help-seeking samples (Yung et al., 2006; Schultze-Lutter et al., 2013). As in earlier studies of PLEs in clinical samples (Yung et al., 2006; Wigman et al., 2011; Koren et al., 2013; Ames et al., 2014; Schultze-Lutter et al., 2014b), APLEs were highly prevalent in our adolescent sample, and nearly all patients – irrespective of age – reported at least any one APLE at a median of 13 APLEs. Unexpectedly, delusional, particularly persecutory APLEs were more frequent than perception-related APLEs. This is in line with findings of persecutory ideas being most frequent in adolescents and young adults (Yung et al., 2006), and may reflect the small number of children (11–12-years-old) in our sample. It should be noted that in this study, younger adolescents had a higher refusal rate. Although reasons for refusal were not systematically assessed, refusal in this group seemed to be mainly resulting from fears of guardians that study participation might overstrain their young and already troubled child.
Furthermore, contrary to the report of auditory PLEs being most frequent in children and adolescents, particularly in younger age (Kelleher et al., 2012b), auditory APLEs were fewer than somatic, gustatory and olfactory APLEs. Yet, PLE assessments such as CAPE or the Adolescent Psychotic-like Symptoms Screener (Kelleher et al., 2011) commonly include only questions on auditory and/or visual hallucinations, and thus lack data on PLEs related to other sensory modalities. However, it was earlier reported that younger age was related to higher rates of hallucinations across all modalities (David et al., 2011); thus their assessment might be most important in younger age groups. In line with reports from community samples (Adachi et al., 2003; Brown, 2003) déjà-vu experiences were most frequently endorsed in 68% of participants; yet, déjà-vu is commonly rated below APSseverity threshold in the SIPS.
4.2. Factors of APLEs As expected, four factors were identified, three relating to delusional APLEs. These were indeed similar to those generated on CAPE-assessed PLEs (Yung et al., 2006): The CAPE factor “Persecutory Ideas” was best reflected by “Conceptual Disorganization and Suspiciousness” (CDS) in that questions of the SIPS P2-item “suspiciousness/persecutory ideas” joined with questions related to SIPS-P5 “disorganized communication”
M. Brandizzi et al. / Schizophrenia Research 160 (2014) 110–117
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Table 4 Results of regression analyses of effect of functioning and psychopathology on APLE factors. Dependent variable (reference category)
Covariates
βa
SE
Wald
p
Exp(β)
95%-CIb Lower
Upper
Poor social functioning (GF:S ≥ 6)
CDS PA BE MI CDS PA BE MI CDS PA BE MI CDS PA BE MI CDS PA BE MI CDS PA BE MI CDS PA BE MI
−0.021 0.204 0.005 −0.075 −0.081 0.235 −0.043 −0.246 0.047 0.109 0.144 −0.230 0.055 −0.750 0.098 0.105 0.303 0.0026 0.000 0.005 0.172 0.093 0.055 0.102 0.223 −0.007 0.012 0.023
0.058 0.077 0.081 0.142 0.056 0.079 0.080 0.141 0.061 0.078 0.085 0.152 0.079 0.110 0.124 0.206 0.033 0.036 0.037 0.066 0.029 0.037 0.038 0.067 0.030 0.036 0.037 0.066
0.138 6.959 0.005 0.278 2.113 8.801 0.291 3.039 0.602 1.973 2.879 2.285 0.470 0.470 0.622 0.259 84.490 0.527 0.000 0.007 35.829 6.400 2.117 2.358 54.912 0.034 0.110 0.118
0.711 0.008⁎ 0.946 0.598 0.146 0.003⁎⁎
0.979 1.226 1.005 0.928 0.922 1.265 0.958 0.782 1.048 1.116 1.155 0.794 1.056 0.927 1.103 1.111 –
0.874 1.054 0.858 0.703 0.827 1.083 0.818 0.593 0.931 0.958 0.978 0.589
1.096 1.426 1.178 1.225 1.477 1.029 1.121 1.031 1.181 1.299 1.364 1.071 1.233 1.150 1.407 1.664 0.367 0.097 0.073 0.135 0.227 0.166 0.129 0.233 0.283 0.063 0.085 0.151
Poor role functioning (GF:R ≥ 6)
Poor general functioning (GAF ≤ 60)
Any anxiety or mood dis. (present)
PQ-negative
PQ-disorganized
PQ-general psychopathology
0.590 0.081 0.438 0.160 0.090 0.131 0.490 0.493 0.430 0.611 0.000⁎⁎ 0.468 0.997 0.934 0.000⁎⁎ 0.011⁎ 0.146 0.125 0.000⁎⁎ 0.853 0.740 0.732
–
–
0.905 0.748 0.865 0.742 0.238 −0.045 −0.073 −0.124 0.116 0.021 −0.019 −0.028 0.164 −0.077 −0.061 −0.106
CDS: Conceptual Disorganization and Suspiciousness; PA: Perceptual Abnormalities; BE: Bizarre Experience; MI Magical Ideation. a Estimate as provided by ordinal regression analyses. b Exp(β) in binary logistic regression analyses and estimate in ordinal regression analyses. ⁎ p b 0.05. ⁎⁎ p b 0.005.
(not assessed in CAPE) and mainly below-APS-threshold phenomena of SIPS-P1 “unusual thought content” such as déjà-vu, derealization, and changes in time perception (not assessed in CAPE). Like its corresponding CAPE-factor, “Bizarre Experience” (BE) mainly included ideas of reference, audible thoughts and so called Ich-Störungen, in addition to grandiose ideas and below-APS-threshold “perceptual abnormalities” of SIPS-P4 (not assessed in CAPE). Other than the CAPE-factor “Magical Thinking”, the corresponding APLE-factor “Magical ideation” (MI) did not include grandiose ideas but unusual ideas and superstition as well as nihilistic ideas and somatopsychic depersonalization (both not assessed in CAPE). Almost identical to the numbers reported for the CAPE-factors (Yung et al., 2006), at least one CDS item was affirmed by almost all patients reporting APLEs, followed by BE (76%), and MI (61%). Any “Perceptual abnormality” (PA) was reported by 74%.
4.3. Association of age and sociodemographic variables with APLEs When controlling for sociodemographic characteristics, disability and other psychopathology, the only association with age was found for the PA-score. Being significantly higher in 11–12-year-olds, this association was in line with previous findings of a decline in the prevalence especially of hallucinatory PLEs from childhood into adolescence (Kelleher et al., 2012a; 2012b). Furthermore, an association between female gender and higher CDS-scores was consistent with the association found in community samples between female gender and higher scores on the CAPE “Persecutory Ideas” factor (Armando et al., 2010; Ziermans, 2013). Contrary to a recently reported lack of association between clinician-assessed psychotic experiences and genetic risk variants for schizophrenia in an adolescent community sample (Zammit et al., 2013), the association between BE-score and family history was significant in our sample. This might indicate that, irrespective of family
history or diagnosis of a particular disorder, more bizarre experiences might have a stronger genetic underpinning than other APLEs.
4.4. Association of disability and psychopathology with APLEs While PA-scores were related to deficits in social and role functioning and the disorganization PQ-subscale, CDS-scores were related to a more severe psychopathology in terms of higher scores on all nonpsychotic PQ-subscales. This was surprising, since earlier reports had pointed towards an association of persecutory ideas and bizarre experiences but not perceptual aberrations with functional deficits (Armando et al., 2010; 2012). No association was found for the GAF, or an anxiety or depression diagnosis; the latter possibly due to the high frequency of these mental disorders and, relatedly, lack of variance. As reported earlier (Yung et al., 2009; Armando et al., 2010; 2012; Collip et al., 2013), MI-scores were unrelated to psychopathology or functioning, supporting the view of magical thinking being a benign phenomenon in adolescence.
4.5. Strengths and limitations Our study advances most studies of subclinical psychotic experiences by the use of the PQ-92 that was specifically designed to assess subclinical psychotic experiences in terms of APS. Yet, the use of the PQ as a measure of APLEs in a clinical sample puts some restrictions to comparisons with other studies that predominately focused on PLEs in the community. In line with PLE self-ratings, however, our study probably shares the lack of content validity for clinician-assessed APS (Ochoa et al., 2008; Michel et al., 2014; Schultze-Lutter et al., 2014b) that has not studied for the PQ-92 so far.
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4.6. Conclusion APLEs are common in help-seeking children and adolescents and partially associated with functional deficits and higher symptom load. Thus for the clinical significance that seems to be inherent to APLEs in help-seeking samples, these should be routinely assessed and considered in treatment beyond their potential association with subsequent psychosis, which remains to be studied longitudinally. For the broad assessment of these phenomena in clinical practice however, valid and reliable, yet change-sensitive self-rating scales would be of great value (Michel et al., 2014). Thus further steps should be taken to ensure reliability and validity of the PQ. Thereby, special attention should be paid to the content validity of its single items with the gold standard of a clinical interview across different age groups and across groups of different educational background, since both developmental stage and intellectual abilities might influence the understanding of items and, consequently, reflect on both concurrent and prospective validity of the scale as well as on its reliability (Michel et al., 2014). Further, the higher prevalence of perception-related phenomena in children found in this study in line with earlier reports (Kelleher et al., 2012a; 2014) and their potentially lesser clinical significance should be the subject of further cross-sectional and longitudinal studies in both clinical and general population samples. Role of funding source Sapienza University of Rome provides a Ph.D. scholarship for two authors (AM and GDK) and allows other trainees in Psychiatry (MB, JFL, MC, AS) to spend part of their training working for the present study; Rome H Mental Health Department supports this study by organizing clinical supervision on the early detection work. Contributors Martina Brandizzi, Frauke Schultze-Lutter, Alice Masillo, and Juliana Fortes Lindau designed the study and wrote the protocol. Martina Curto and Andrea Solfanelli collected the data. Giulia Listanti, Martina Patanè, Eva Gebhardt, and Giorgio Kotzalidis managed the literature searches and analyses. Andrea Lanna, Martina Brandizzi, and Frauke SchultzeLutter performed the statistical analysis, and authors Martina Brandizzi and Frauke Schultze-Lutter wrote the first draft of the manuscript. Nicholas Meyer corrected the final version of the paper. Diana Di Pietro, Donato Leccisi, Paolo Girardi and Paolo Fiori Nastro supervised and managed the study. All authors contributed to and have approved the final manuscript. Conflict of interest All authors declare that they have no conflicts of interest. Acknowledgments Our special thanks go to all the staff and service users of ASL Rome H Community Mental Health Services and Child and Adolescents Mental Health Services.
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Self-reported attenuated psychotic-like experiences in help-seeking adolescents and their association with age, functioning and psychopathology Martina Brandizzi a,c,⁎,1, Frauke Schultze-Lutter b,1, Alice Masillo c, Andrea Lanna d, Martina Curto a, Juliana Fortes Lindau a, Andrea Solfanelli a, Giulia Listanti c, Martina Patanè c, Giorgio Kotzalidis a, Eva Gebhardt a, Nicholas Meyer f, Diana Di Pietro e, Donato Leccisi e, Paolo Girardi a, Paolo Fiori Nastro c a Neurosciences, Mental Health and Sensory Functions (NESMOS) Department, Sapienza University of Rome, Faculty of Medicine and Psychology, Sant'Andrea Hospital, Via di Grottarossa 1035, 00189 Rome, Italy b University Hospital for Child and Adolescent Psychiatry and Psychotherapy, University of Bern, Bolligenstr. 111, Haus A 3000 Bern 60, Bern, Switzerland c Department of Neurology and Psychiatry, Sapienza University of Rome, Faculty of Medicine and Odontology, Rome 00156, Italy d Department of Computer, Control, and Management Engineering “A. Ruberti”, Sapienza University of Rome, Rome 00185, Italy e Community Mental Health Service, ASL Rome H, 00041 Rome, Italy f Institute of Psychiatry, King's College, 16 De Crespigny Park, SE5 8AF London, United Kingdom
a r t i c l e
i n f o
Article history: Received 5 June 2014 Received in revised form 13 September 2014 Accepted 7 October 2014 Available online 29 October 2014 Keywords: Ultra-high risk Screening Attenuated psychotic-like experiences Perceptual abnormalities Children and adolescents
a b s t r a c t Objective: Self-rated attenuated psychotic-like experiences (APLEs) are increasingly used to screen for ultra-highrisk (UHR) across all ages. However, self-rated psychotic-like experiences (PLEs), in particular perception-related ones, were more frequent in children and adolescents, in which they possessed less clinical significance. We therefore explored the prevalence of different factors of APLEs in help-seeking adolescents, and their relationship with age, functioning and psychopathology. Method: As a part of the “Liberiamo il Futuro” project, help-seeking adolescents (N = 171; 11–18 years, 53% male) were screened with the 92-item Prodromal Questionnaire (PQ-92). A factor analysis was performed on the PQ-92 positive items (i.e., APLEs) to identify different APLE-factors. These were assessed for their association with age, functioning and psychopathology using regression analyses. Results: APLEs were very common in help-seeking adolescents, and formed four factors: “Conceptual Disorganization and Suspiciousness”, “Perceptual Abnormalities”, “Bizarre Experiences”, and “Magical Ideation”. Associations with age and functioning but not psychopathology were found for “Perceptual Abnormalities” that was significantly more severe in 11–12-year-olds, while “Conceptual Disorganization and Suspiciousness” was significantly related to psychopathology. Conclusion: In line with findings on PLEs, prevalence and clinical significance of APLEs, especially perceptionrelated ones, might depend on age and thus neurodevelopmental stage, and may fall within the normal spectrum of experience during childhood. This should be considered when screening for UHR status in younger age groups. © 2014 Elsevier B.V. All rights reserved.
1. Introduction Early detection of psychosis has become an important topic in psychiatry for which two main approaches have been developed: the ultra-high risk (UHR) approach and the basic symptom (BS) approach (Fusar-Poli et al., 2013; Schultze-Lutter et al., 2014a). However,
⁎ Corresponding author at: Department of Neurology and Psychiatry, UOD Psicoterapia, Sapienza University of Rome, Faculty of Medicine and Odontology, Via Casal Dè Pazzi 16, 00156 Rome, Italy. Tel.: +39 0 6 4080 0589; fax: +39 0 6 4070 447. E-mail address: [email protected] (M. Brandizzi). 1 Joint first authors.
http://dx.doi.org/10.1016/j.schres.2014.10.005 0920-9964/© 2014 Elsevier B.V. All rights reserved.
instruments assessing UHR criteria generally require additional training even of mental health specialists and several hours of clinicians' time. 1.1. Screening for ultra-high risk status using self-report questionnaires Therefore, self-report screening instruments were developed to preselect potential UHR patients for in-depth clinical assessment; one is the 92-item Prodromal Questionnaire (PQ-92) (Loewy et al., 2005; 2011) that is based on the Structured Interview for Psychosis-Risk Syndromes (SIPS; McGlashan et al., 2010; Miller et al., 2003). Concurrent validity of the PQ-92 was reported for different clinical samples: (1) patients from an early detection center (N = 113; 12–35 years) (Loewy et al., 2005); (2) patients from a secondary mental health service (N = 3,671;
M. Brandizzi et al. / Schizophrenia Research 160 (2014) 110–117
18–35 years) (Ising et al., 2012) with a cut-off “≥18 positive symptoms” predicting SIPS-UHR status with 90% sensitivity and 90% specificity; and (3) adolescent patients from a general mental health clinic (N = 80; 15–18 years) (Loewy et al., 2012) where both sensitivity (82%) and specificity (49%) were lower using the same cut-off, although psychosis-predictive validity of the PQ-assessed UHR status was comparable to that of the SIPS-assessed at one-year follow-up. 1.2. Age-related differences of self-reported (attenuated) psychotic symptoms Most research on the PQ-92 has been carried out in mixed adolescent–young adult samples with little consideration of age-related differences. In a community sample of children and adolescents, agerelated differences were reported for prevalence rates of self-rated psychotic-like experiences (PLEs). In particular, perception-related PLEs clearly decreased with age (from 21–23% of 11–13-year-olds to 7% of 13–16-year-olds), and increased in association with poorer socio-occupational functioning (Kelleher et al., 2012a; 2014) and with the presence of mental disorder (Kelleher et al., 2012a; Laurens et al., 2012). However, longitudinal studies of adolescents in the community (Dominguez et al., 2011; Smeets et al., 2012) suggest that persistence rather than prevalence of PLEs increases psychosis-risk. Yet, PLEs appeared to be poor estimates of clinician-assessed attenuated psychotic symptoms (APS), the main UHR criterion (Schultze-Lutter et al., 2011, 2014b). Thus, the content-valid assessment of APS might require specialized instruments such as the PQ-92. Furthermore, symptoms related to psychosis-risk were reported to cluster differently in children and adolescents compared to adults (Schultze-Lutter et al., 2012; Fux et al., 2013). From these findings, a need for research into the early detection of psychosis across the child and adolescent age-range was identified (Schimmelmann and Schultze-Lutter, 2012; Schimmelmann et al., 2013). 1.3. Aims and hypotheses In order to address the need for age-related research in the study of self-reported attenuated psychotic-like experiences (APLEs), we examined the structure and prevalence of APLEs assessed with the positive symptom PQ-92-subscale, as a self-report estimate not of psychotic symptoms but of APS in help-seeking adolescents. In addition to a perception-related factor, we expected a three-factor structure of delusion-like experiences similar to that reported for the Community Assessment of Psychic Experiences (CAPE) in 15–24-yearolds (N = 140) (Yung et al., 2006), despite the PQ-92 assessing a broader spectrum of APLEs. Consistent with other PLE studies, a high prevalence of APLEs was expected, being highest in younger age groups, in particular with respect to perception-related APLEs. Additionally, an association of the presence and number of APLEs with poor functioning and psychopathology was hypothesized that might differ in strength between APLE-factors. 2. Materials and methods 2.1. Setting Data were collected in six Child and Adolescent Neuropsychiatric Services (CANS) in the area of Roma H, Rome, Italy, between January 2012 and July 2013 as part of the early detection project “Liberiamo il Futuro” (LIF; Supplement material S1). 2.2. Sample Inclusion criteria were: age between 11 and 18 years, residency in the Roma H area, and help-seeking from services for any psychological or behavioral problem. Of 384 eligible adolescents, 171 (44%) individuals
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and their parents or guardians gave written informed consent to participate. Ethical approval was obtained from the local research ethics committee. Participants were significantly older than refusers (mean ± SD: 14.8 ± 1.9 vs. 14.3 ± 1.8; median: 15 vs. 14; U = 15186.0; p = 0.005), though the effect size was small (Rosenthal's r = −0.14) with no gender difference (male: 53% of participants vs. 56% of refusers; χ2 (1) = 0.164; p = 0.381). 2.3. Assessments APLEs and self-reported negative, disorganized and general symptoms were assessed with an Italian translation of the PQ-92 that takes approximately 20 min to complete (Loewy et al., 2005). The translation was conducted by a trainee in psychiatry and a PhD student both fluent in English, with back-translation by a bilingual trainee in psychiatry. PQ92 items were adapted from the SIPS and the Schizotypal Personality Questionnaire (Raine, 1991). Statements are rated true (1) or false (0); four subscales scores can be obtained by adding up affirmative responses: 1) 45 (attenuated) positive symptoms, i.e. APLEs (PQ-positive; Table 2), 2) 19 negative symptoms (PQ-negative; e.g., flat affect, social isolation), 3) 13 disorganization items (PQ-disorganization; e.g., odd behavior) and 4) 15 general symptoms (PQ-general; e.g., depression, functional deficits). For a global rating of psychological, social and occupational functioning, we used the Global Assessment of Functioning Scale (GAF) (Hall, 1995) that had been part of DSM-IV (APA 1994) but was not included in the DSM-5 (APA, 2013). A cut-off of ‘60’ was considered to distinguish between poor and good general functioning (Bachmann et al., 2008; Schennach-Wolff et al., 2009). As additional functional outcome measures, two scales developed for the National Institute of Mental Health-funded multi-site NAPLS project (Cornblatt et al., 2007) were used: the GF:Social scale assessing social functioning by taking into account quantity and quality of peer and family relationships/conflicts including age-appropriate intimate relationships (Auther et al., 2006), and the GF:Role scale measuring role functioning by taking into account quantity and quality of school, work or homemaker performance (Niendam et al., 2006; Cornblatt et al., 2007). Both scales are rated between ‘1’ (extreme dysfunction) and ‘10’ (superior functioning); a cut-off of ‘6’ distinguishes between poor and adequate functioning (Schlosser et al., 2012; Carrion et al., 2013). Past and present axis-I DSM-IV diagnoses were evaluated with the Kiddie-Schedule for Affective Disorders and Schizophrenia — Present and Lifetime (K-SADS-PL) version (Kaufman et al., 1997), a reliable semi-structured psychiatric interview. 2.4. Data analysis Analyses were conducted using SPSS 20.0. Where Kolmogorov– Smirnov (K–S) tests for normal distribution were significant, nonparametric analyses of continuous data were preferred. Number and type of APLE-factors were determined using principal component analysis (varimax and oblimin method). Initially, the requirement of sufficient frequency of correlations N 0.3 was assured by inspection of the correlation matrix (Tabachnick and Fidell, 2007). Optimum number of factors was established using the Kaiser's method (Field, 2005) and a screen plot (Cattell, 1966). Associations of the presence and number of APLEs with age, socio-demographic variables (i.e., gender, positive family history of any psychiatric disorder), functioning (i.e., binary: GF:Role, GF:Social and GAF) and symptomatology (i.e., any anxiety or depressive disorder, PQ-negative, PQ-disorganization, PQ-general) were independently explored by binary, multinominal and ordinal regression analyses with the presence/severity of APLE-factors as covariates. In ordinal regression analyses, the complementary log–log option was chosen assuming that higher categories are more probable.
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3. Results 3.1. Sample characteristics and their association with age About half of the sample was male with fewer girls among the 11– 12-year-olds (Table 1). All but 6 patients (3.5%) were in education and those aged 11–14 were more likely to attend primary school; 17–18year-olds were more likely to have sought help on their own initiative. The main reasons for referral were school or peer relationship problems (40.0%) and anxiousness or depressiveness (40.0%). School difficulties were most frequent in 11–12-year-olds and least frequent in 17–18year-olds who often reported ‘other’ reasons, mainly related to aggressiveness or subclinical psychotic experiences (Table 1). Independent of age, anxiety (27.0%) and mood disorders (21.4%) were frequent. Illicit drug use was most likely reported by 17–18-year-olds and least likely by 11–12-year-olds. Poor functioning was frequent with no indication of an age effect (Table 1).
3.2. Factors of APLEs A four-factor solution best fitted the 45 APLEs accounting for 34% of the explained variance, with only nine variables showing crossloadings ≥ 0.35 (Table 2). Three factors related to delusional APLEs and one to perception-related APLEs. Factor 1 was composed of 15 items that generally related to “Conceptual Disorganization and Suspiciousness” (CDS), among these, the eleven most frequently endorsed items ranged from ‘comprehension problems of others’ in 39.8% of patients to ‘déjà-vu’ in 67.8%. Factor 2 included 11 items describing “Perceptual Abnormalities” (PA). Factor 3 consisted of 13 items that
could generally be described as “Bizarre Experiences” (BE), mainly in terms of experiences resembling ideas of reference or so called IchStörungen. Factor 4 contained only six items relating to “Magical Ideation” (MI). 3.3. Prevalence and frequency of APLEs APLEs were commonly reported, with 167 patients (97.7%) disclosing at least one. CDS was the most prevalent factor, with 95% (n = 163) reporting at least one of its 15 items. A further 130 patients (76.0%) reported at least one BE-item, and 104 (60.8%) at least one MI-item. In all, any one delusional APLE was as frequent as any APLE. At least one PAitem was less frequently reported by only 126 patients (73.7%), always in conjunction with a delusion-like experience. The median number of APLEs was 13 (0–36 of 45). The median number of PA-items was two (0–11 of 11), that of CDS-items seven (0–15 of 15), that of BE-items two (0–12 of 13), and that of MI-items only one (0–5 of 6); the median number of delusional APLEs was ten (0–27 of 34). KS-tests indicated a non-normal distribution of most PQ-factors and subscales (Supplementary material 2, Table S2-1). 3.4. Association of age and other sociodemographic variables with APLEs Multinominal regression analysis with the four APLE-factors as covariates and 17–18-year-olds as the reference group indicated an association of higher PA scores with an age of 11–12 years (Exp(β) = 1.309; 95% CIs: 1.039/1.649) and an association of lower BE scores with an age of 15–16 years (Exp(β) = 0.805; 95% CIs: 0.656/0.989) (Table 3). The age effect of PA but not that of BE remained when GF:Social, GF:Role,
Table 1 Socio-demographic and clinical characteristics and correlation by age group (N = 171).
Age groupsa
Gender Educational levelb
Sources of referral
Reasons for referral
Main diagnosis (K-SADS-PL)
Previous contact with mental health services Family history of any mental disorder Present use/misuse/dependence of illicit drugs GF:Social GF:Role GAF PQ-threshold (≥18 PLEs) met
11–12 13–14 15–16 17–18 Male Primary school Lower secondary school Upper general secondary school Upper vocational secondary school Psychiatrist or other specialist School or family Patient's own initiative Anxious or depressive symptom School difficulties Peer relationship difficulties Other None Anxiety disorder Mood disorder Conduct or learning disorder, ADHD Other Yes Yes Yes Poor (≤6) Poor (≤6) Poor (≤60) Yes
N
%
30 52 49 40 90 64 98 5 4 28 115 22 66 42 24 33 22 43 34 23 37 59 47 34 54 73 50 43
17.5 30.4 28.7 23.4 52.6 37.4 57.3 2.9 2.3 17.0 69.7 13.3 40.0 25.5 14.5 20.0 13.8 27.0 21.4 14.5 23.3 35.3 27.6 21.1 34.2 46.2 35.0 25.1
Coefficient of contingency, C (p)
0.210 (0.048) c 0.562 (b0.001) d
0.286 (0.023) e
0.370 (0.002) f
0.281 (0.322)
0.141 (0.337) 0.082 (0.767) 0.330 (b0.001) g 0.147 (0.320) 0.200 (0.086) 0.063 (0.904) 0.103 (0.401)
K-SADS-PL: Kiddie-Schedule for Affective Disorders and Schizophrenia—Present and Lifetime Version; 12 patients refused the interview. GAF: Global assessment of functioning relying on both social and occupational functioning and psychopathology. a Mean age of total sample was 15 (SD = 2) years at a median age of 15; no significant distribution differences across the 4 age groups (1-dimensional χ2(3) = 6.895, p = 0.075). b Only 6 patients (3.5%) were not in school or occupational training. c Main effect for fewer girls among 11–12-year-olds (only 27% as compared to 48–59%; standardized residual, SR = −1.6). d Main effects for more primary school and less higher education levels among 11–12- as well as 13–14-year-olds (SR = 4.4 and 2.2). e Main effect for more help-seeking on patient's own initiative in 17–18-year-olds (SR = 2.9). f Main effects for more school difficulties in 11–12-year-olds (SR = 2.3) and fewer school difficulties, but more other reasons in 17–18-year-olds (SR = −2.9 and 1.8). g Main effects for fewer use in 11–12-year-olds (SR = −2.1) and more in 17–18-year-olds (SR = 2.7).
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Table 2 Factor loadings (N0.3) and item frequencies in % in descending order. #
Item description
8 3 38 77 25 2 49 27 57 55 90 60
I often seem to live through events exactly as they happened before (déjà vu). I have difficulty organizing my thoughts or finding the right words. I often feel that other people are watching me or talking about me. I am often concerned that my closest friends and co-workers are not really loyal or trustworthy. I often feel that others have it in for me. The passage of time feels faster or slower than usual. My thinking feels confused, muddled, or disturbed in some way. I have felt that I am not in control of my own ideas or thoughts. I have been confused at times whether something I experienced was real or imaginary. At times I worry that something may be wrong with my mind. People sometimes find it hard to understand what I am saying. I have experienced unusual bodily sensations such as tingling, pulling, pressure, aches, burning, cold, numbness, shooting pains, vibrations or electricity. Other people say that I wander off the topic or ramble on too much when I am speaking. Sometimes I feel suddenly distracted by distant sounds that I am not normally aware of. My thoughts are sometimes so strong that I can almost hear them. I often pick up hidden threats or put-downs from what people say or do. I sometimes smell or taste things that other people don't notice. I have had the sense that some person or force is around me, even though I could not see anyone. I feel that parts of my body have changed in some way, or that parts of my body are working differently. I sometimes use words in unusual ways. Familiar surroundings sometimes seem strange, confusing, threatening or unreal. I have many thoughts that fill my mind and compete for my attention. My sense of smell sometimes becomes unusually strong. I have heard my own thoughts as if they are outside of my head. I sometimes feel that things I see on the TV or read in the newspaper have a special meaning for me. Sometimes I am sure that other people can tell what I am thinking or feeling without me telling them. I believe in telepathy, psychic forces, or fortune-telling. I have heard things other people can't hear like voices of people whispering or talking. I am unusually sensitive to noise. I hold beliefs that other people would find unusual or bizarre. I believe that I am very important or have special gifts. I often hear unusual sounds like banging, clicking, hissing, clapping or ringing in my ears. I sometimes see special meanings in advertisements, shop windows, or in the way things are arranged around me. I am superstitious. When I look at a person, or look at myself in a mirror, I have seen the face change right before my eyes. I have felt that I don't exist, the world does not exist, or that I am dead. I sometimes get strange feelings on or just beneath my skin, like bugs crawling. Some people drop hints about me or say things with a double meaning. Things that I see appear different from the way they usually do (brighter or duller, larger or smaller, or changed in some other way). I have seen unusual things like flashes, flames, blinding light or geometric figures. Sometimes my thoughts seem to be broadcast out loud so that other people know what I am thinking. I have seen things that other people can't see or don't seem to. I often mistake shadows for people or noises for voices. At times I have felt that some person or force interferes with my thinking or puts thoughts into my head. I have had experiences with the supernatural, astrology, seeing the future or UFOs.
23 50 65 68 9 52 64 69 7 37 26 36 46 12 24 13 34 61 30 18 67 35 4 56 5 76 20 79 32 84 19 74 75
F1
F2
0.38 0.48 0.60 0.50 0.68 0.37 0.68 0.54 0.57 0.55 0.48
F3
F4
67.8 62.0 59.6 54.4 52.6 52.6 46.8 44.4 43.3 40.4 39.8 36.3
(0.35)
0.53
(−0.39)
0.43 0.58 0.56
(0.35)
0.58 0.59
−0.56 (−0.43) (0.38) 0.31 −0.64
0.32 0.44 0.33 (0.50)
(0.39) −0.50 −0.55 −0.58 0.64
0.62 0.54 0.71 (0.36) 0.76
−0.49 −0.59 0.51 −0.35 0.35 −0.42 −0.40 −0.35
(0.47)
0.60 −0.46 0.64 0.45 −0.33 (0.35)
%
0.35
35.1 35.1 33.3 31.6 30.4 29.2 28,7 28.7 26,9 26.9 26.9 25.1 25.1 25.1 23.4 22.8 22.2 21.6 20.5 20.5 20.5 19.9 19.9 19.3 18.7 16,4 16.4 15.8 15.8 15.2 15.2 14.0 8.8
#: PQ-item number; F1: Factor 1 ‘Conceptual Disorganization and Suspiciousness’ (CDS), 15 items; F2: Factor 2 ‘Perceptual Abnormalities’ (PA), 11 items; F3: Factor 3 ‘Bizarre Experience’ (BE), 13 items; F4: Factor 4 ‘Magical Ideation’ (MI), 6 items; model fit: Kaiser–Meyer–Olkin measure of sampling adequacy: 0.780; Bartlett's test of sphericity: 2 (990) = 2446.6; p b 0.000.
PQ-negative, PQ-disorganization and PQ-general were entered into the model (Table S2-2). Entering gender and family history into the regression analysis of age again did not alter the age effect of PA but rendered that of BE insignificant (see Supplementary Table S2-2). Furthermore, higher CDS scores were associated with significantly increased odds for female gender (Exp(β) = 1.240; 95% CIs: 1.107/1.388), and higher BE scores with increased odds for a positive family history (Exp (β) = 1.277; 95% CIs: 1.085/1.504); education was unrelated to APLEfactors (Table 3). With regard to the presence of APLE-factors (see Supplementary Table S2-3), the only significant association indicated the absence of CDS being predictive of primary school level (Exp(β) = 0.00062; 95% CIs: 0.00013/0.0029). At a trend level, an additional association of PA presence with being 11–12-years-old was found (p = 0.061; Exp(β) = 4.397; 95% CIs: 0.935/20.678).
functioning (Exp(β) = 1.265; 95% CIs: 1.083/1.477). Poor functioning according to GAF and the presence of an anxiety or a mood disorder diagnosis were unrelated to PQ-factors. Across all three ordinal regression analyses of PQ-subscales, CDS was a significant predictor of psychopathology (PQ-negative: 0.303 (95% CIs: 0.238/0.367); PQ-disorganization: 0.172 (95% CIs: 0.116/0.229); PQ-general: 0.223 (95% CIs: 0.164/0.283)), complemented only by PA in case of PQdisorganization (0.093; 95% CIs: 0.021/0.166) (Table 4). With regard to the presence of APLE-factors (see Supplementary Table S2-3), the only significant association indicated that the presence of BE was predictive of poor social functioning (Exp(β) = 2.639; 95% CIs: 1.016/6.851). Otherwise, trend-level associations of the presence of PA with poor role functioning (p = 0.053; Exp(β) = 2.326; 95% CIs: 0.991/5.462) and poor general functioning (p = 0.055; Exp (β) = 2.624; 95% CIs: 0.980/7.022) were found.
3.5. Association of disability and psychopathology with APLEs
4. Discussion
Higher PA scores were significantly associated with a higher likelihood of poor social (Exp(β) = 1.226; 95% CIs: 1.054/1.426) and role
Consistent with other PLE studies, our study found a high prevalence of APLEs, with perception-related APLEs highest in younger age groups
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Table 3 Results of regression analyses of effect of age and sociodemographic variables on APLE factors. Dependent variable (reference category)
Covariates
Age group (17–18 years)
11–12 years CDS PA BE MI 13–14 years CDS PA BE MI 15–16 years CDS PA BE MI CDS PA BE MI CDS PA BE MI Primary CDS PA BE MI Lower secondary CDS PA BE MI Upper secondary general CDS PA BE MI
Gender (female)
Family history (present)
Education (upper secondary-vocational)
β
−0.177 −0.055 0.269 −0.189 0.018 0.048 0.028 0.150 −0.173 0.108 −0.085 −0.049 0.141 −0.217 0.022 0.215 −0.106 −0.066 0.021 −0.109 −0.043 0.245 −0.047 2.365 0.019 0.490 −0.188 −0.193 2.344 0.126 0.306 −0.065 −0.278 1.004 0.064 0.046 −0.435 −0.729
SE
0.484 0.084 0.118 0.120 0.210 0.438 0.073 0.103 0.101 0.180 0.459 0.076 0.111 0.105 0.191 0.058 0.083 0.077 0.135 0.060 0.083 0.083 0.150 0.982 0.186 0.352 0.276 0.433 0.977 0.184 0.349 0.271 0.429 1.214 0.246 0.533 0.503 0.748
Wald
0.134 0.431 5.223 2.472 0.008 0.012 0.153 2.118 2.947 0.358 0.034 3.413 0.196 4.276 0.013 13.836 2.126 0.747 0.024 3.321 0.272 8.633 0.096 5.800 0.010 1.941 0.465 0.200 5.755 0.469 0.767 0.058 0.420 0.684 0.068 0.008 0.747 0.949
p
0.714 0.511 0.022⁎ 0.116 0.930 0.912 0.696 0.146 0.086 0.550 0.853 0.065 0.658 0.039⁎ 0.908 0.000⁎⁎ 0.145 0.387 0.878 0.068 0.602 0.003⁎⁎ 0.757 0.016 0.919 0.164 0.495 0.655 0.016 0.493 0.381 0.810 0.517 0.408 0.931 0.794 0.388 0.330
Exp(β)
95%-CI of Exp(β) Lower
Upper
0.946 1.309 0.828 1.019
0.803 1.039 0.654 0.676
1.115 1.649 1.048 1.536
1.029 1.161 0.841 1.114
0.892 0.949 0.691 0.782
1.186 1.421 1.025 1.586
0.952 1.151 0.805 1.022
0.767 0.991 0.656 0.703
1.183 1.337 0.989 1.486
1.240 0.899 0.936 1.021 0.896 0.958 1.277 0.955 1.019 1.633 0.828 0.824
1.107 0.779 0.805 0.783 0.797 0.815 1.085 0.711 0.708 0.819 0.482 0.353
1.388 1.037 1.088 1.330 1.008 1.126 1.504 1.282 1.468 3.256 1.423 1.926
1.135 1.358 0.937 0.757
0.790 0.685 0.551 0.327
1.629 2.690 1.593 1.754
1.066 1.047 0.647 0.482
0.659 0.368 0.241 0.111
1.726 2.978 1.736 2.091
CDS: Conceptual Disorganization and Suspiciousness; PA: Perceptual Abnormalities; BE: Bizarre Experience; MI Magical Ideation. ⁎ p b 0.05. ⁎⁎ p b 0.005.
(11–12 years). Additionally, an association of PA with poor role and social functioning and of CDS with psychopathology emerged.
4.1. Prevalence and frequency of APLEs The prevalence of PLEs in the community exceeds that of psychosis by far, especially when assessed with self-report measures (Linscott and van Os, 2013), and PLEs are even more frequent in help-seeking samples (Yung et al., 2006; Schultze-Lutter et al., 2013). As in earlier studies of PLEs in clinical samples (Yung et al., 2006; Wigman et al., 2011; Koren et al., 2013; Ames et al., 2014; Schultze-Lutter et al., 2014b), APLEs were highly prevalent in our adolescent sample, and nearly all patients – irrespective of age – reported at least any one APLE at a median of 13 APLEs. Unexpectedly, delusional, particularly persecutory APLEs were more frequent than perception-related APLEs. This is in line with findings of persecutory ideas being most frequent in adolescents and young adults (Yung et al., 2006), and may reflect the small number of children (11–12-years-old) in our sample. It should be noted that in this study, younger adolescents had a higher refusal rate. Although reasons for refusal were not systematically assessed, refusal in this group seemed to be mainly resulting from fears of guardians that study participation might overstrain their young and already troubled child.
Furthermore, contrary to the report of auditory PLEs being most frequent in children and adolescents, particularly in younger age (Kelleher et al., 2012b), auditory APLEs were fewer than somatic, gustatory and olfactory APLEs. Yet, PLE assessments such as CAPE or the Adolescent Psychotic-like Symptoms Screener (Kelleher et al., 2011) commonly include only questions on auditory and/or visual hallucinations, and thus lack data on PLEs related to other sensory modalities. However, it was earlier reported that younger age was related to higher rates of hallucinations across all modalities (David et al., 2011); thus their assessment might be most important in younger age groups. In line with reports from community samples (Adachi et al., 2003; Brown, 2003) déjà-vu experiences were most frequently endorsed in 68% of participants; yet, déjà-vu is commonly rated below APSseverity threshold in the SIPS.
4.2. Factors of APLEs As expected, four factors were identified, three relating to delusional APLEs. These were indeed similar to those generated on CAPE-assessed PLEs (Yung et al., 2006): The CAPE factor “Persecutory Ideas” was best reflected by “Conceptual Disorganization and Suspiciousness” (CDS) in that questions of the SIPS P2-item “suspiciousness/persecutory ideas” joined with questions related to SIPS-P5 “disorganized communication”
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Table 4 Results of regression analyses of effect of functioning and psychopathology on APLE factors. Dependent variable (reference category)
Covariates
βa
SE
Wald
p
Exp(β)
95%-CIb Lower
Upper
Poor social functioning (GF:S ≥ 6)
CDS PA BE MI CDS PA BE MI CDS PA BE MI CDS PA BE MI CDS PA BE MI CDS PA BE MI CDS PA BE MI
−0.021 0.204 0.005 −0.075 −0.081 0.235 −0.043 −0.246 0.047 0.109 0.144 −0.230 0.055 −0.750 0.098 0.105 0.303 0.0026 0.000 0.005 0.172 0.093 0.055 0.102 0.223 −0.007 0.012 0.023
0.058 0.077 0.081 0.142 0.056 0.079 0.080 0.141 0.061 0.078 0.085 0.152 0.079 0.110 0.124 0.206 0.033 0.036 0.037 0.066 0.029 0.037 0.038 0.067 0.030 0.036 0.037 0.066
0.138 6.959 0.005 0.278 2.113 8.801 0.291 3.039 0.602 1.973 2.879 2.285 0.470 0.470 0.622 0.259 84.490 0.527 0.000 0.007 35.829 6.400 2.117 2.358 54.912 0.034 0.110 0.118
0.711 0.008⁎ 0.946 0.598 0.146 0.003⁎⁎
0.979 1.226 1.005 0.928 0.922 1.265 0.958 0.782 1.048 1.116 1.155 0.794 1.056 0.927 1.103 1.111 –
0.874 1.054 0.858 0.703 0.827 1.083 0.818 0.593 0.931 0.958 0.978 0.589
1.096 1.426 1.178 1.225 1.477 1.029 1.121 1.031 1.181 1.299 1.364 1.071 1.233 1.150 1.407 1.664 0.367 0.097 0.073 0.135 0.227 0.166 0.129 0.233 0.283 0.063 0.085 0.151
Poor role functioning (GF:R ≥ 6)
Poor general functioning (GAF ≤ 60)
Any anxiety or mood dis. (present)
PQ-negative
PQ-disorganized
PQ-general psychopathology
0.590 0.081 0.438 0.160 0.090 0.131 0.490 0.493 0.430 0.611 0.000⁎⁎ 0.468 0.997 0.934 0.000⁎⁎ 0.011⁎ 0.146 0.125 0.000⁎⁎ 0.853 0.740 0.732
–
–
0.905 0.748 0.865 0.742 0.238 −0.045 −0.073 −0.124 0.116 0.021 −0.019 −0.028 0.164 −0.077 −0.061 −0.106
CDS: Conceptual Disorganization and Suspiciousness; PA: Perceptual Abnormalities; BE: Bizarre Experience; MI Magical Ideation. a Estimate as provided by ordinal regression analyses. b Exp(β) in binary logistic regression analyses and estimate in ordinal regression analyses. ⁎ p b 0.05. ⁎⁎ p b 0.005.
(not assessed in CAPE) and mainly below-APS-threshold phenomena of SIPS-P1 “unusual thought content” such as déjà-vu, derealization, and changes in time perception (not assessed in CAPE). Like its corresponding CAPE-factor, “Bizarre Experience” (BE) mainly included ideas of reference, audible thoughts and so called Ich-Störungen, in addition to grandiose ideas and below-APS-threshold “perceptual abnormalities” of SIPS-P4 (not assessed in CAPE). Other than the CAPE-factor “Magical Thinking”, the corresponding APLE-factor “Magical ideation” (MI) did not include grandiose ideas but unusual ideas and superstition as well as nihilistic ideas and somatopsychic depersonalization (both not assessed in CAPE). Almost identical to the numbers reported for the CAPE-factors (Yung et al., 2006), at least one CDS item was affirmed by almost all patients reporting APLEs, followed by BE (76%), and MI (61%). Any “Perceptual abnormality” (PA) was reported by 74%.
4.3. Association of age and sociodemographic variables with APLEs When controlling for sociodemographic characteristics, disability and other psychopathology, the only association with age was found for the PA-score. Being significantly higher in 11–12-year-olds, this association was in line with previous findings of a decline in the prevalence especially of hallucinatory PLEs from childhood into adolescence (Kelleher et al., 2012a; 2012b). Furthermore, an association between female gender and higher CDS-scores was consistent with the association found in community samples between female gender and higher scores on the CAPE “Persecutory Ideas” factor (Armando et al., 2010; Ziermans, 2013). Contrary to a recently reported lack of association between clinician-assessed psychotic experiences and genetic risk variants for schizophrenia in an adolescent community sample (Zammit et al., 2013), the association between BE-score and family history was significant in our sample. This might indicate that, irrespective of family
history or diagnosis of a particular disorder, more bizarre experiences might have a stronger genetic underpinning than other APLEs.
4.4. Association of disability and psychopathology with APLEs While PA-scores were related to deficits in social and role functioning and the disorganization PQ-subscale, CDS-scores were related to a more severe psychopathology in terms of higher scores on all nonpsychotic PQ-subscales. This was surprising, since earlier reports had pointed towards an association of persecutory ideas and bizarre experiences but not perceptual aberrations with functional deficits (Armando et al., 2010; 2012). No association was found for the GAF, or an anxiety or depression diagnosis; the latter possibly due to the high frequency of these mental disorders and, relatedly, lack of variance. As reported earlier (Yung et al., 2009; Armando et al., 2010; 2012; Collip et al., 2013), MI-scores were unrelated to psychopathology or functioning, supporting the view of magical thinking being a benign phenomenon in adolescence.
4.5. Strengths and limitations Our study advances most studies of subclinical psychotic experiences by the use of the PQ-92 that was specifically designed to assess subclinical psychotic experiences in terms of APS. Yet, the use of the PQ as a measure of APLEs in a clinical sample puts some restrictions to comparisons with other studies that predominately focused on PLEs in the community. In line with PLE self-ratings, however, our study probably shares the lack of content validity for clinician-assessed APS (Ochoa et al., 2008; Michel et al., 2014; Schultze-Lutter et al., 2014b) that has not studied for the PQ-92 so far.
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4.6. Conclusion APLEs are common in help-seeking children and adolescents and partially associated with functional deficits and higher symptom load. Thus for the clinical significance that seems to be inherent to APLEs in help-seeking samples, these should be routinely assessed and considered in treatment beyond their potential association with subsequent psychosis, which remains to be studied longitudinally. For the broad assessment of these phenomena in clinical practice however, valid and reliable, yet change-sensitive self-rating scales would be of great value (Michel et al., 2014). Thus further steps should be taken to ensure reliability and validity of the PQ. Thereby, special attention should be paid to the content validity of its single items with the gold standard of a clinical interview across different age groups and across groups of different educational background, since both developmental stage and intellectual abilities might influence the understanding of items and, consequently, reflect on both concurrent and prospective validity of the scale as well as on its reliability (Michel et al., 2014). Further, the higher prevalence of perception-related phenomena in children found in this study in line with earlier reports (Kelleher et al., 2012a; 2014) and their potentially lesser clinical significance should be the subject of further cross-sectional and longitudinal studies in both clinical and general population samples. Role of funding source Sapienza University of Rome provides a Ph.D. scholarship for two authors (AM and GDK) and allows other trainees in Psychiatry (MB, JFL, MC, AS) to spend part of their training working for the present study; Rome H Mental Health Department supports this study by organizing clinical supervision on the early detection work. Contributors Martina Brandizzi, Frauke Schultze-Lutter, Alice Masillo, and Juliana Fortes Lindau designed the study and wrote the protocol. Martina Curto and Andrea Solfanelli collected the data. Giulia Listanti, Martina Patanè, Eva Gebhardt, and Giorgio Kotzalidis managed the literature searches and analyses. Andrea Lanna, Martina Brandizzi, and Frauke SchultzeLutter performed the statistical analysis, and authors Martina Brandizzi and Frauke Schultze-Lutter wrote the first draft of the manuscript. Nicholas Meyer corrected the final version of the paper. Diana Di Pietro, Donato Leccisi, Paolo Girardi and Paolo Fiori Nastro supervised and managed the study. All authors contributed to and have approved the final manuscript. Conflict of interest All authors declare that they have no conflicts of interest. Acknowledgments Our special thanks go to all the staff and service users of ASL Rome H Community Mental Health Services and Child and Adolescents Mental Health Services.
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