Psychometric properties and local normative references of PSC-17, RCADS-25, CATS-2, SNAP-IV, MCHAT-R/F, and CAST: data from a nationwide sample in Greece

Psychometric properties and local normative references of PSC-17, RCADS-25, CATS-2, SNAP-IV, MCHAT-R/F, and CAST: data from a nationwide sample in Greece | medRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-P4HH5NV'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search Psychometric properties and local normative references of PSC-17, RCADS-25, CATS-2, SNAP-IV, MCHAT-R/F, and CAST: data from a nationwide sample in Greece View ORCID Profile André Simioni , View ORCID Profile Julia Luiza Schafer , View ORCID Profile Lauro Estivalete Marchionatti , View ORCID Profile Kenneth Schuster , View ORCID Profile Caio Borba Casella , View ORCID Profile Katerina Papanikolaou , View ORCID Profile Efstathia Kapsimalli , View ORCID Profile Panagiota Balikou , View ORCID Profile Giorgos Gerostergios , Kalliopi Triantafyllou , View ORCID Profile Maria Basta , Nikos Zilikis , Lilian Athanasopoulou , Vaios Dafoulis , View ORCID Profile Aspasia Serdari , View ORCID Profile Rafael V. S. Bastos , Peter Szatmari , View ORCID Profile Ioanna Giannopoulou , View ORCID Profile Anastasia Koumoula , View ORCID Profile Giovanni Abrahão Salum , View ORCID Profile Konstantinos Kotsis doi: https://doi.org/10.1101/2025.03.21.25324416 André Simioni 1 Child and Adolescent Mental Health Initiative (CAMHI), Stavros Niarchos Foundation (SNF) & Child Mind Institute (CMI) , Athens, Greece 2 Child Mind Institute (CMI) , New York, NY, USA MD PhD Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for André Simioni Julia Luiza Schafer 1 Child and Adolescent Mental Health Initiative (CAMHI), Stavros Niarchos Foundation (SNF) & Child Mind Institute (CMI) , Athens, Greece 2 Child Mind Institute (CMI) , New York, NY, USA PhD Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Julia Luiza Schafer Lauro Estivalete Marchionatti 1 Child and Adolescent Mental Health Initiative (CAMHI), Stavros Niarchos Foundation (SNF) & Child Mind Institute (CMI) , Athens, Greece 2 Child Mind Institute (CMI) , New York, NY, USA MD Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Lauro Estivalete Marchionatti Kenneth Schuster 1 Child and Adolescent Mental Health Initiative (CAMHI), Stavros Niarchos Foundation (SNF) & Child Mind Institute (CMI) , Athens, Greece 2 Child Mind Institute (CMI) , New York, NY, USA PsyD Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Kenneth Schuster Caio Borba Casella 1 Child and Adolescent Mental Health Initiative (CAMHI), Stavros Niarchos Foundation (SNF) & Child Mind Institute (CMI) , Athens, Greece 2 Child Mind Institute (CMI) , New York, NY, USA MD PhD Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Caio Borba Casella Katerina Papanikolaou 1 Child and Adolescent Mental Health Initiative (CAMHI), Stavros Niarchos Foundation (SNF) & Child Mind Institute (CMI) , Athens, Greece 3 Department of Child Psychiatry, Agia Sophia Children’s Hospital, National and Kapodistrian University of Athens , Athens, Greece MD PhD Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Katerina Papanikolaou Efstathia Kapsimalli 1 Child and Adolescent Mental Health Initiative (CAMHI), Stavros Niarchos Foundation (SNF) & Child Mind Institute (CMI) , Athens, Greece MD Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Efstathia Kapsimalli Panagiota Balikou 1 Child and Adolescent Mental Health Initiative (CAMHI), Stavros Niarchos Foundation (SNF) & Child Mind Institute (CMI) , Athens, Greece MSc PhD Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Panagiota Balikou Giorgos Gerostergios 1 Child and Adolescent Mental Health Initiative (CAMHI), Stavros Niarchos Foundation (SNF) & Child Mind Institute (CMI) , Athens, Greece Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Giorgos Gerostergios Kalliopi Triantafyllou 1 Child and Adolescent Mental Health Initiative (CAMHI), Stavros Niarchos Foundation (SNF) & Child Mind Institute (CMI) , Athens, Greece 4 National and Kapodistrian University of Athens , Athens, Greece 5 Neapolis University Pafos , Pafos, Cyprus PhD Find this author on Google Scholar Find this author on PubMed Search for this author on this site Maria Basta 1 Child and Adolescent Mental Health Initiative (CAMHI), Stavros Niarchos Foundation (SNF) & Child Mind Institute (CMI) , Athens, Greece 6 Department of Psychiatry, University Hospital of Heraklion , Crete, Greece MD PhD Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Maria Basta Nikos Zilikis 1 Child and Adolescent Mental Health Initiative (CAMHI), Stavros Niarchos Foundation (SNF) & Child Mind Institute (CMI) , Athens, Greece Find this author on Google Scholar Find this author on PubMed Search for this author on this site Lilian Athanasopoulou 1 Child and Adolescent Mental Health Initiative (CAMHI), Stavros Niarchos Foundation (SNF) & Child Mind Institute (CMI) , Athens, Greece Find this author on Google Scholar Find this author on PubMed Search for this author on this site Vaios Dafoulis 1 Child and Adolescent Mental Health Initiative (CAMHI), Stavros Niarchos Foundation (SNF) & Child Mind Institute (CMI) , Athens, Greece Find this author on Google Scholar Find this author on PubMed Search for this author on this site Aspasia Serdari 1 Child and Adolescent Mental Health Initiative (CAMHI), Stavros Niarchos Foundation (SNF) & Child Mind Institute (CMI) , Athens, Greece 7 Department of Child and Adolescent Psychiatry, Medical School, Democritus University of Thrace , Alexandroupolis, Greece MD PhD Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Aspasia Serdari Rafael V. S. Bastos 1 Child and Adolescent Mental Health Initiative (CAMHI), Stavros Niarchos Foundation (SNF) & Child Mind Institute (CMI) , Athens, Greece 8 Department of Psychology, São Francisco University , Campinas, SP, Brazil 11 Department of Psychiatry, University of Ioannina , Ioannina, Greece MSc Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Rafael V. S. Bastos Peter Szatmari 8 Department of Psychology, São Francisco University , Campinas, SP, Brazil MD PhD Find this author on Google Scholar Find this author on PubMed Search for this author on this site Ioanna Giannopoulou 10 2nd Department of Psychiatry, Attikon University Hospital, National and Kapodistrian University , Athens, Greece MD PhD Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Ioanna Giannopoulou Anastasia Koumoula 1 Child and Adolescent Mental Health Initiative (CAMHI), Stavros Niarchos Foundation (SNF) & Child Mind Institute (CMI) , Athens, Greece MD PhD Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Anastasia Koumoula Giovanni Abrahão Salum 1 Child and Adolescent Mental Health Initiative (CAMHI), Stavros Niarchos Foundation (SNF) & Child Mind Institute (CMI) , Athens, Greece 2 Child Mind Institute (CMI) , New York, NY, USA MD PhD Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Giovanni Abrahão Salum Konstantinos Kotsis 1 Child and Adolescent Mental Health Initiative (CAMHI), Stavros Niarchos Foundation (SNF) & Child Mind Institute (CMI) , Athens, Greece 11 Department of Psychiatry, University of Ioannina , Ioannina, Greece MD PhD Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Konstantinos Kotsis For correspondence: konkotsis{at}uoi.gr Abstract Full Text Info/History Metrics Supplementary material Preview PDF Abstract Health professionals in Greece face barriers in assessing child and adolescent mental health conditions due to the lack of instruments with evidence of validity in local samples. This study addresses this gap by evaluating the psychometric properties and establishing common norms for six globally recognized mental health tools in Greece: the Child and Adolescent Trauma Screen-2 (CATS-2), Pediatric Symptoms Checklist-17 (PSC-17), Revised Children’s Anxiety and Depression Scale-25 (RCADS-25), Swanson, Nolan, and Pelham Scale (SNAP-IV), Modified Checklist for Autism in Toddlers-Revised (MCHAT-R/F), and Child Autism Spectrum Test (CAST). We drew on a nationwide Greek survey comprising 1,756 caregivers and 1,201 children and adolescents (age groups: 1 to 18 years). Using Item Response Theory, we assessed internal consistency and factor models according to Consensus-based Standards for the Selection of Health Measurement Instruments (COSMIN) criteria for unidimensionality, local independence, monotonicity, and global model fit. Normative references were calculated using standardized metrics recommended by the Patient-Reported Outcomes Measurement Information System (PROMIS). Final sample sizes ranged from 1,356 (PSC-17, caregiver version) to 198 (CATS-2, caregiver version). Internal consistency was rated as good to excellent across all scales. Factor analyses supported all scales except the MCHAT-R/F (failing monotonicity) and CAST (failing monotonicity and unidimensionality). Local normative references were usually consistent with international samples. This toolkit provides essential evidence-based resources for child and adolescent mental health in Greece, offering a scalable model for other underserved settings. Further research with national probabilistic samples is recommended to enhance risk stratification accuracy. Introduction In Greece, significant hurdles for the provision of child and adolescent mental health care still persist. In the aftermath of an economic crisis, there is a shortage and unequal distribution of specialists working in the public sector as well as regional gaps in provision of care [ 1 ]. Adding on to that, referral systems and gatekeeping mechanisms are yet to be established, resulting in long waiting times in many child and adolescent mental health services. Within this context of constrained resources, it is of paramount importance to equip health professionals with tools to screen for and stratify the risk of mental health conditions in primary and pediatric care settings. Therefore, interventions and referrals could be oriented by evidence-based assessment of symptom severity [ 2 ]. Integrating psychosocial screening tools into pediatric care improves the identification and management of behavioral and emotional conditions, with several guidelines recommending the adoption of standardized core outcome measures [ 3 – 5 ]. In Greece, a recent systematic review highlighted that many widely-used instruments assessing child and adolescent mental health outcomes were either unavailable or lacked validation with local samples, including the Pediatric Symptom Checklist (PSC) and the Swanson, Noland, and Pelham (SNAP-IV) [ 6 ]. There was also a shortage of instruments for assessing child abuse and autism spectrum disorders, with key tools such as the Child and Adolescent Trauma Screen-2 (CATS-2), the Child Autism Spectrum Test (CAST), and the Modified Checklist for Autism in Toddlers - Revised (MCHAT-R/F) notably absent [ 7 – 10 ]. The absence of such tools significantly hinders best practices and research in Greece. In the case of autism spectrum disorders, it has prevented the implementation of systematic screening within the healthcare system and restricted prevalence estimates to administrative diagnostic data [ 11 – 13 ] The aim of this paper is to contribute to the efforts of the Child and Adolescent Mental Health Initiative (CAMHI) in delivering evidence-based resources to enhance child and adolescent mental health care capacity in Greece. As part of this effort, we previously conducted a nationwide survey covering several patient-relevant outcomes, which employed a set of assessment instruments selected for their brevity, availability, and reliability [ 14 ]. In the present study, we report the psychometric validation and local normative references of the following instruments: the Child and Adolescent Trauma Screen-2 (CATS-2), Child Autism Spectrum Test (CAST), Modified Checklist for Autism in Toddlers-Revised (MCHAT-R/F), Pediatric Symptoms Checklist-17 (PSC-17), Revised Children’s Anxiety and Depression Scale-25 (RCADS-25), and Swanson, Nolan, and Pelham Scale (SNAP-IV). Methods This study assesses the psychometric validity and local normative references of six screening instruments for child and adolescent mental health into a Greek sample (see Table 1 ). For each tool, symptom severity bands are presented with a dimensional approach (minimal, mild, moderate, and severe), ensuring user-friendly and comparable metrics aligned with standards defined by the Patient-Reported Outcomes Measurement Information System (PROMIS) group [ 15 , 16 ]. View this table: View inline View popup Table 1. Instruments’ description, factor models, and proposed cutoffs. We followed the STrengthening the Reporting of OBservational studies in Epidemiology (STROBE) guidelines (see Supplementary Table 1 ) [ 17 ]. The statistical codes, outcomes, and survey dataset are openly available on our Open Science Framework page at https://osf.io/crz6h/ [ 18 ]. Participants We drew on data from a 2022–2023 nationwide cross-sectional survey, which included a sample of 1,201 children and adolescents (aged 8 to 17 years) and 1,756 caregivers (children aged 1 to 18 years) (detailed in Koumoula et. al (2024) [ 14 ]). Instruments were administered to subsamples according to age, group of interest, and random allocation (see Figure 1 ). Caregivers were recruited via a proprietary online respondent panel based on a census frame; invitation was delivered following an algorithm considering residency region, offspring gender, and age quotas. A first group of 400 children/adolescents consisted of the offspring of the surveyed caregivers, who were invited to an online questionnaire with self-report versions of instruments also rated by their parents. Additionally, 801 children/adolescents were recruited via random phone calls following census quotas on region and gender, providing measures of general screening and sensitive topics (namely, substance use and self-harm). Download figure Open in new tab Figure 1. Sampling procedure. Abbreviations: CAST (Child Autism Spectrum Test), CATS-2 (Child and Adolescent Trauma Screen-2), MCHAT-R/F (Modified Checklist for Autism in Toddlers - Revised), PSC-17 (Pediatric Symptoms Checklist - 17 items), RCADS-25 (Revised Children’s Anxiety and Depression Scale - 25 items), SNAP-IV (Swanson, Nolan and Pelham Scale). Data collection was managed with the KoboToolbox [ 19 ]. Informed consent and assent were respectively obtained from caregivers and youth participants. Data was collected and preserved according to the General Data Protection Regulation (GDPR) National Policy [ 20 ]. The Research Ethics Committee of the Democritus University of Thrace approved the survey [approval number: ΔΠΘ/ΕΗΔΕ/42772/307]. Selection of instruments Table 1 outlines the instruments used in the nationwide survey [ 14 ]. First, we consulted the International Consortium for Health Outcomes Measurement (ICHOM) on patient-relevant outcomes for child and adolescent mental health [ 21 ]. We then reviewed the literature on instruments assessing general and specific symptoms of prevalent mental health conditions. We selected tools based on their brevity, availability, and reliability, as recommended by the Consensus-based Standards for the Selection of Health Measurement Instruments (COSMIN) [ 22 ]. Three of the selected instruments (PSC-17, SNAP-IV, and CATS-2) had either not been previously translated into Greek or were not freely available in Greek language. In such cases, we performed a structured procedure for cross-cultural adaptation comprising back-and-forth translation by independent translators, synthesis of versions, expert committee appraisal, and pilot testing with the targeted population [ 23 ]; each step has been thoughtfully documented in a previous publication [ 24 ]. We employed the brief versions of the Pediatric Symptom Checklist (PSC-17) and the Revised Children’s Anxiety and Depression Scale (RCADS-25) [ 25 – 27 ]. Although the nationwide survey initially used the full-length versions, only the items pertaining to the shortened versions were included in the analysis [ 14 ]. For the CATS-2, we validated only the 20-item scale for symptom assessment, which is applied after screening with any positive answer on a 15-item checklist of traumatic events [ 9 ]. Statistical analysis An Item Response Theory (IRT) approach was conducted to test factor models, internal reliability, and to generate common metrics for each subscale or unidimensional instrument. For normative reference per age group and gender, we converted scores into percentiles, Z-scores, and T-scores, establishing a color-coded classification of symptom severity (minimal, mild, moderate, and severe) [ 15 , 16 ]. Analysis was performed using the software R version 4.4.3 and the packages lavaan , semTools , ltm , psych , and mirt [ 28 – 33 ]. Selection of factor models Table 1 shows the factor models tested through Confirmatory Factor Analysis (CFA). Factorial structures were consulted at developers’ distribution pages and supporting literature. For CAST, CATS-2, and SNAP-IV, more than one structure was compared to identify the best fit for our data. As no developer-recommended structure was available for CAST, we compared models proposed in samples from Spain, Brazil, and China [ 34 – 36 ]. The Chinese two-factor model (“Sociability/Communication” and “Inflexible/Repetitive behaviors”) was selected for its superior fit to our data and alignment to DSM-5 criteria [ 34 ]. There are several structures for CATS-2 based on different diagnostic criteria [ 9 ]. While a hierarchical model demonstrated the best performance, there are factors with one or few items that may lead to model over rejection, and its clinical utility is limited due to complex scoring. We have chosen an unidimensional model following DSM-5 structure for its practical utility and superior fit to our data. While the original SNAP-IV suggests a three-factor model, our data demonstrated a significantly better fit when the ‘hyperactivity/impulsivity’ factor was split into two distinct factors [ 37 ]. This four-factor structure (inattention, hyperactivity, impulsivity, and opposition) has been supported in the literature and was selected for this analysis [ 38 ]. Psychometric analysis We conducted a factor analysis for each subscale or unidimensional tool, evaluating both item-level and model-level fit [ 32 , 39 , 40 ]. Model fit was assessed using the M2 command from the Mirt package, with estimations of the Root Mean Square Error of Approximation (RMSEA), the Standardized Root Mean-square Residual (SRMR), the Comparative Fit Index (CFI), and the Tucker-Lewis Index (TLI) [ 32 , 40 – 42 ]. Item performance was analyzed through factor loadings, residual correlations, item scalability, monotonicity violations, fit indices, and discriminative power. Reliability was estimated using Cronbach’s alpha (α) and McDonald’s omega (ω□) [ 43 – 45 ]. Evaluation Criteria for Measurement Properties Criteria were primarily based on the COSMIN manuals and supplemented with additional guidelines as recommended [ 22 , 46 , 47 ]. IRT literature prioritizes a combination of parameters to assess goodness-of-fit at item and test levels as opposed to isolated measures [ 40 , 42 , 48 , 49 ]. Internal consistency was considered positive if Cronbach’s alpha (α) or McDonald’s omega (ω□) exceeded 0.7 [ 22 , 43 , 50 , 51 ]. Values above 0.8 and 0.9 respectively indicated good and excellent reliability. Factor analysis was deemed positive if the following criteria were met: 1) unidimensionality (at least two of the following: RMSEA ≤ 0.06, SRMR ≤ 0.08, and TLI/CFI ≥ 0.95; RMSEA ≤ 0.08 is also considered acceptable [ 47 ]); 2) local independence (residual correlations among items < 0.2 OR the third quartile of correlations 0.3 OR adequate looking graphs); and 4) global model fit (unidimensionality criteria attended AND item infit mean squares ≥ 0.5 and ≤ 1.5). Additionally, factor loadings above 0.3 were considered positive, with values higher than 0.5 classified as very positive [ 52 , 53 ]. For monotonicity, we also evaluated the number of violations per item. The absence of violations indicated adequate monotonicity, and violations with critical values between 40 and 90 were also considered acceptable [ 39 , 54 ]. Local normative references Graded Response Models (GRMs) and Graded Rating Scale Models (GRSMs) were employed for parameterization, assigning an IRT score to each participant [ 41 , 55 , 56 ]. Scores were categorized by age group and gender, with T-scores calculated from factor scores (a T-score of 50 represents the reference population mean, and a 10-point difference corresponds to one standard deviation). Symptom level bands followed PROMIS recommendations for standardized metrics, consisting of four ranges: minimal symptoms (T-score < 55), mild symptoms (T-score 55–59), moderate symptoms (T-score 60–69), and severe symptoms (T-score ≥ 70) [ 16 , 57 , 58 ]. Scores were then rescaled according to the range of each T-score-based severity category, with values truncated within each band. Finally, crude scores were linked to IRT-based scores by grouping factor, T-scores, Z-scores, and percentiles for each summed score value. Results Table 2 presents the sociodemographic characteristics of caregivers and children/adolescents who completed each instrument. The PSC-17 (proxy-report, school-age children) had the largest sample size, including all 1,356 caregivers of 6- to 18-year-olds participating in the survey. Some instruments were administered to subsamples, with participant numbers ranging from 452 (RCADS-25, caregiver-rated; SNAP-IV, caregiver-rated) to 137 (CATS-2, self-report). View this table: View inline View popup Table 2. Sociodemographic characteristics of participants. Table 3 summarizes the psychometric properties of each tool. Table 4 provides normative references for PSC-17 (self-report). Standardized scores and classification bands for the remaining instruments are detailed in Supplementary Table 2 through Supplementary Table 10 . Test information curves, expected total score curves, item probability functions, and item and person infit and outfit statistics for each instrument’s subscale can be consulted in Supplementary Figure 1.1.1 to Supplementary Figure 10.4.4 . Comprehensive documentation of codes and measurement properties is also made accessible through our Open Science Framework repository ( https://osf.io/crz6h/ ) [ 18 ]. View this table: View inline View popup Table 3. Psychometric properties of the instruments. View this table: View inline View popup Table 4. Normative references in Greece: Pediatric Symptom Checklist Short Version (PSC-17), Self-report. Internal consistency was rated as good to excellent across all subscales, with Cronbach’s alpha (α) values ranging from 0.84 to 0.97 and Omega Total (ω□) values from 0.85 to 0.97. Factor analysis confirmed that all scales met criteria for unidimensionality, monotonicity, local independence, and global model fit, with the exception of MCHAT-R/F (failing monotonicity), CAST - inflexible/repetitive behavior (failing monotonicity), and CAST - social contact issues (failing unidimensionality, monotonicity and model fit). Factor loadings consistently exceeded the 0.3 cutoff across tools, with a single item in CAST - social contact issues - rating 0.18. Except CAST and MCHAT-R/F, all instruments demonstrated adequate item discriminative performance and test scores. In the CAST, both subscales failed to meet monotonicity (see Supplementary Figure 1.1.5 and Supplementary Figure 1.2.5 for item response functions). In the inflexible/repetitive behavior subscale, three of 15 items exhibited low scalability (<0.3), with items 7 and 36 demonstrating weaker discrimination (see item characteristic curves in Supplementary Figure 1.1.2). In the sociability subscale, 14 of 16 items had inadequate scalability, with item characteristic curves indicating particularly low discrimination for items 23 and 35 (Supplementary Figure 1.2.2). Additionally, the sociability subscale failed to meet unidimensionality, as only RMSEA (0.06) fell within an acceptable range, while TLI (0.90), CFI (0.90), and SRMR (0.09) indicated inadequate global model fit. MCHAT-R/F failed monotonicity as eight out of 20 items presented scalability values below the 0.3 threshold (the scale’s item response functions are detailed in Supplementary Figure 4.5 ). Item characteristic curves indicate that some questions are unable to discriminate between respondents at both the lower and upper ends of the score spectrum (see Supplementary Figure 4.2 ). For example, item 2 is overly easy to endorse, while items 5 and 12 are excessively difficult to endorse. Test information and expected score plots further indicate that the MCHAT effectively captures individuals with very low ability but fails to adequately assess those with high ability (see Supplementary Figure 4.1 ). Discussion This study validates and establishes local normative references for the Greek versions of six instruments: PSC-17 (caregiver- and self-report), RCADS-25 (caregiver- and self-report), CATS-2 (caregiver- and self-report), SNAP-IV (caregiver-report), MCHAT-R/F (caregiver-report), and CAST (caregiver-report). These scales demonstrated reliable and valid properties in a nationwide community sample of children, adolescents, and caregivers, with the exception of CAST and MCHAT-R/F which did not meet all criteria in factor analysis. To the best of our knowledge, this is the first validation of these tools in Greece apart from the prior national validation of the full-length RCADS-47 [ 59 , 60 ]. Scores were categorized into symptom severity bands using PROMIS ranges for standardized metrics, with norms generally aligning with cutoffs from other European and North American countries [ 15 , 16 ]. For example, a crude score of 5 on the PSC-17 internalizing subscales corresponded to a moderate symptom classification (T-score 60–69), consistent with risk cutoffs reported for samples from Spain and the United States [ 25 , 61 , 62 ]. On the RCADS-25 (self-report), anxiety subscale scores of 30 corresponded to a T-score of 70 (severe symptoms). This is consistent with crude-to-T-score conversion tables for boys in 3rd–4th grades and girls in 5th–6th grades from U.S. samples, yet this pattern did not hold for participants beyond the 5th grade [ 27 , 63 , 64 ]. These findings suggest that the scales could benefit clinical practice in Greece by helping professionals distinguish between higher- and lower-symptom patients. As the Greek public mental health system lacks defined patient pathways, these symptom classifications can guide referrals and treatment decisions, supporting a scaled approach to interventions tailored to individual needs [ 1 , 2 ]. Both scales assessing autism spectrum symptoms (CAST and MCHAT-R/F) did not fully meet performance criteria. This is likely due to their limited sample of 200 community-based caregivers, which is underpowered to represent individuals with more expressive clinical symptoms. Worth noting, the MCHAT-R/F is initially intended for screening children presenting developmental concerns [ 8 ]. While there is evidence of validity population-level screening, properties may differ when administered to asymptomatic samples [ 7 ]. Items were not dismissed in the scale, yet further validation in clinical samples is crucial to establish the psychometric properties and normative references of such tools. We analyzed data from a large nationwide sample, achieving consistent psychometric properties through modern IRT approaches and generating accessible metrics that further allows for cross-instrument comparisons. However, there are also some limitations. All 1,756 caregivers were recruited from a proprietary panel of individuals willing to participate in surveys, further leading to an inclusion of 400 children and adolescents cared for by these participants. Although recruitment followed census quotas for sociodemographic variables, this is not a strictly probabilistic approach. Another group of 801 children/adolescents was recruited through random phone calls, a method known for low response rates and potential bias. Some tools (MCHAT-R/F, CAST, CATS-2) relied on small sample sizes (137 to 200 participants), potentially underrepresenting the full spectrum of symptoms and requiring cautious interpretation of psychometric parameters [ 47 ]. While valuable for screening symptoms and orienting referral priorities, our classification bands cannot establish sound risk stratification cutoffs, as we did not include clinical samples and comparisons with gold-standard tools [ 65 , 66 ]. This toolkit addresses critical gaps in evidence-based resources in Greece by validating a set of widely-used tools, providing a scalable approach that can be applied to other underserved settings. Health professionals and researchers in Greece are now better equipped to reliably screen and assess symptoms across the severity of symptoms in various conditions, including anxiety, ADHD, autism spectrum disorders, depression, and trauma. Future research with clinical samples and instrument comparisons are warranted to confirm normative references and establish construct and criterion validity of these tools in the country. Statements and Declarations Funding This work is part of The Child and Adolescent Mental Health Initiative (CAMHI) aimed to enhance mental health care capacity in Greece. The CAMHI is funded by the Stavros-Niarchos Foundation (SNF) and led by the Child Mind Institute (CMI) in partnership with multiple institutions and actors in Greece. Conflicts of interest All authors declare no conflicts of interest. Data availability statement Data is openly available in Open Science Framework at http://doi.org/10.17605/OSF.IO/CRZ6H , including the database and the statistical codes. Acknowledgements The authors would like to thank the Stavros Niarchos Foundation (SNF) for funding the SNF-CMI Child and Adolescent Mental Health Initiative and SNF’s Co-President Andreas C. Dracopoulos for his leadership in creating, launching, and supporting the project. We would also like to thank Ms. Elianna Konialis, Ms. Dimitra Moustaka and Mr. Panos Papoulias for their critical role in multiple steps of the conceptualization and implementation of the SNF-CMI Child and Adolescent Mental Health Initiative. We also thank Samanta Duarte for designing the graphical representations included in this paper. References 1. ↵ Marchionatti LE , Schafer JL , Karagiorga VE , et al. ( 2024 ) The mental health care system for children and adolescents in Greece: a review and structure assessment . Front Health Serv 4 . : doi: 10.3389/frhs.2024.1470053 OpenUrl CrossRef 2. ↵ Patel V , Saxena S , Lund C , et al. ( 2018 ) The Lancet Commission on global mental health and sustainable development . Lancet 392 : 1553 – 1598 . doi: 10.1016/S0140-6736(18)31612-X OpenUrl CrossRef PubMed 3. ↵ US Preventive Services Task Force , Mangione CM , Barry MJ , et al. ( 2022 ) Screening for Anxiety in Children and Adolescents: US Preventive Services Task Force Recommendation Statement . JAMA 328 : 1438 – 1444 . doi: 10.1001/jama.2022.16936 OpenUrl CrossRef PubMed 4. Trafalis S , Giannini C , Joves J , et al. ( 2021 ) A pediatrician-friendly review of three common behavioral health screeners in pediatric practice: Findings and recommendations . Pediatr Investig 5 : 58 – 64 . doi: 10.1002/ped4.12246 OpenUrl CrossRef PubMed 5. ↵ Mulraney M , de Silva U , Joseph A , et al. ( 2024 ) International Consensus on Standard Outcome Measures for Neurodevelopmental Disorders: A Consensus Statement . JAMA Netw Open 7 : e2416760 . doi: 10.1001/jamanetworkopen.2024.16760 OpenUrl CrossRef 6. ↵ Koumoula A , Marchionatti LE , Caye A , et al. ( 2023 ) The science of child and adolescent mental health in Greece: a nationwide systematic review . Eur Child Adolesc Psychiatry . doi: 10.1007/s00787-023-02213-9 OpenUrl CrossRef 7. ↵ Chlebowski C , Robins DL , Barton ML , Fein D ( 2013 ) Large-scale use of the modified checklist for autism in low-risk toddlers . Pediatrics 131 : e1121 – 7 . doi: 10.1542/peds.2012-1525 OpenUrl CrossRef PubMed Web of Science 8. ↵ Robins DL , Casagrande K , Barton M , et al. ( 2014 ) Validation of the modified checklist for Autism in toddlers, revised with follow-up (M-CHAT-R/F) . Pediatrics 133 : 37 – 45 . doi: 10.1542/peds.2013-1813 OpenUrl CrossRef PubMed Web of Science 9. ↵ Sachser C , Berliner L , Risch E , et al. ( 2022 ) The child and Adolescent Trauma Screen 2 (CATS-2) - validation of an instrument to measure DSM-5 and ICD-11 PTSD and complex PTSD in children and adolescents . Eur J Psychotraumatol 13 : 2105580 . doi: 10.1080/20008066.2022.2105580 OpenUrl CrossRef PubMed 10. ↵ Scott FJ , Baron-Cohen S , Bolton P , Brayne C ( 2002 ) The CAST (Childhood Asperger Syndrome Test): preliminary development of a UK screen for mainstream primary-school-age children . Autism 6 : 9 – 31 . doi: 10.1177/1362361302006001003 OpenUrl CrossRef PubMed Web of Science 11. ↵ Thomaidis L , Mavroeidi N , Richardson C , et al. ( 2020 ) Autism Spectrum Disorders in Greece: Nationwide Prevalence in 10–11 Year-Old Children and Regional Disparities . J Clin Med Res 9 : 2163 . doi: 10.3390/jcm9072163 OpenUrl CrossRef 12. Kouznetsov R , Angelopoulos P , Moulinos S , et al. ( 2023 ) Epidemiological study of autism spectrum disorders in Greece for 2021: Nationwide prevalence in 2-17-year-old children and regional disparities . J Clin Med 12 : 2510 . doi: 10.3390/jcm12072510 OpenUrl CrossRef PubMed 13. ↵ Petinou K , Vogindroukas I , Christopoulou M ( 2024 ) Autism prevalence information and diagnosis processes in Cyprus, Greece and Malta . Neuropsychiatr Dis Treat 20 : 2499 – 2505 . doi: 10.2147/NDT.S468557 OpenUrl CrossRef PubMed 14. ↵ Koumoula A , Marchionatti LE , Karagiorga VE , et al. ( 2024 ) Understanding priorities and needs for child and adolescent mental health in Greece from multiple informants: an open resource dataset . Eur Child Adolesc Psychiatry . doi: 10.1007/s00787-024-02400-2 OpenUrl CrossRef 15. ↵ Alonso J , Bartlett SJ , Rose M , et al. ( 2013 ) The case for an international patient-reported outcomes measurement information system (PROMIS®) initiative . Health Qual Life Outcomes 11 : 210 . doi: 10.1186/1477-7525-11-210 OpenUrl CrossRef PubMed 16. ↵ Choi SW , Schalet B , Cook KF , Cella D ( 2014 ) Establishing a common metric for depressive symptoms: linking the BDI-II, CES-D, and PHQ-9 to PROMIS depression . Psychol Assess 26 : 513 – 527 . doi: 10.1037/a0035768 OpenUrl CrossRef PubMed 17. ↵ von Elm E , Altman DG , Egger M , et al. ( 2014 ) The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement: Guidelines for reporting observational studies . Int J Surg 12 : 1495 – 1499 . doi: 10.1016/j.ijsu.2014.07.013 OpenUrl CrossRef PubMed 18. ↵ Schäfer JL , Simioni AR , Marchionatti LE , et al. ( 2023 ) Child and Adolescent Mental Health Initiative (CAMHI) 19. ↵ Pundhir A , Mehto AK , Jaiswal A Das AS ( 2024 ) KoboToolbox . In: Pundhir A , Mehto AK , Jaiswal A (eds) Open Electronic Data Capture Tools for Medical and Biomedical Research and Medical Allied Professionals . Academic Press , pp 241 – 329 20. ↵ European Parliament , The Council of April, 27th 2016 ( 2016 ) Regulation (EU) 2016/679 on the protection of natural persons with regard to the processing of personal data and on the free movement of such data and repealing Directive 95/46/EC ( General Data Protection Regulation ). 679 : 21. ↵ International Consortium for Health Outcomes Measurement (ICHOM ) ( 2018 ) International Consortium for Health Outcomes Measurement (ICHOM) . In : ICHOM - Value Based Healthcare, Improving Patient Outcomes . https://www.ichom.org/ . Accessed 2 Jun 2023 22. ↵ Prinsen CAC , Mokkink LB , Bouter LM , et al. ( 2018 ) COSMIN guideline for systematic reviews of patient-reported outcome measures . Qual Life Res 27 : 1147 – 1157 . doi: 10.1007/s11136-018-1798-3 OpenUrl CrossRef PubMed 23. ↵ Beaton DE , Bombardier C , Guillemin F , Ferraz MB ( 2000 ) Guidelines for the process of cross-cultural adaptation of self-report measures . Spine 25 : 3186 – 3191 . doi: 10.1097/00007632-200012150-00014 OpenUrl CrossRef PubMed Web of Science 24. ↵ Karagiorga VE , Schafer JL , Marchionatti LE , et al. ( 2024 ) Translation and cross-cultural adaptation of seventeen widely-used assessment instruments for child and adolescent mental health in Greece . J Patient Rep Outcomes 8 : 18 . doi: 10.1186/s41687-024-00693-0 OpenUrl CrossRef 25. ↵ Gardner W , Murphy M , Childs G , et al. ( 1999 ) The PSC-17: A brief pediatric symptom checklist with psychosocial problem subscales . A report from PROS and ASPN. Ambulatory Child Health 5 : 225 – 236 OpenUrl 26. Murphy JM , Bergmann P , Chiang C , et al. ( 2016 ) The PSC-17: Subscale scores, reliability, and factor structure in a new national sample . Pediatrics 138 . : doi: 10.1542/peds.2016-0038 OpenUrl CrossRef PubMed 27. ↵ Ebesutani C , Reise SP , Chorpita BF , et al. ( 2012 ) The Revised Child Anxiety and Depression Scale-Short Version: scale reduction via exploratory bifactor modeling of the broad anxiety factor . Psychol Assess 24 : 833 – 845 . doi: 10.1037/a0027283 OpenUrl CrossRef PubMed 28. ↵ R Core Team ( 2024 ) R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria . http://www R-project.org/ 29. Rosseel Y ( 2012 ) lavaan: An R Package for Structural Equation Modeling . J Stat Softw 48 : 1 – 36 . doi: 10.18637/jss.v048.i02 OpenUrl CrossRef 30. Jorgensen TD , Pornprasertmanit S , Schoemann AM , et al. ( 2016 ) Package “semtools.” Website: https://cranr-projectorg/web/packages/semTools/semToolspdf 31. Rizopoulos D ( 2007 ) ltm: An R Package for Latent Variable Modeling and Item Response Analysis . J Stat Softw 17 : 1 – 25 . doi: 10.18637/jss.v017.i05 OpenUrl CrossRef 32. ↵ Chalmers RP ( 2012 ) Mirt: A multidimensional item response theory package for theREnvironment . J Stat Softw 48 : 1 – 29 . doi: 10.18637/jss.v048.i06 OpenUrl CrossRef 33. ↵ Van der A , Andriès L ( 2007 ) Mokken Scale Analysis in R . Journal of Statistical Software 20 : 1 – 19 . doi: 10.18637/JSS.V020.I11 OpenUrl CrossRef 34. ↵ Sun X , Allison C , Auyeung B , et al. ( 2014 ) Psychometric properties of the Mandarin version of the Childhood Autism Spectrum Test (CAST): an exploratory study . J Autism Dev Disord 44 : 1565 – 1576 . doi: 10.1007/s10803-013-2024-3 OpenUrl CrossRef PubMed 35. Ribeiro TC , Farhat LC , Casella EB , et al. ( 2022 ) Brazilian Portuguese Childhood Autism Spectrum Test: an investigation of the factor structure of autistic traits in school-aged children from Brazil . Rev Bras Psiquiatr 44 : 650 – 654 . doi: 10.47626/1516-4446-2022-2688 OpenUrl CrossRef PubMed 36. ↵ Morales-Hidalgo P , Roigé-Castellví J , Vigil-Colet A , Canals Sans J ( 2017 ) The Childhood Autism Spectrum Test (CAST): Spanish adaptation and validation . Autism Res 10 : 1491 – 1498 . doi: 10.1002/aur.1793 OpenUrl CrossRef PubMed 37. ↵ Bussing R , Fernandez M , Harwood M , et al. ( 2008 ) Parent and teacher SNAP-IV ratings of attention deficit hyperactivity disorder symptoms: psychometric properties and normative ratings from a school district sample . Assessment 15 : 317 – 328 . doi: 10.1177/1073191107313888 OpenUrl CrossRef PubMed Web of Science 38. ↵ Gau SS-F , Lin C-H , Hu F-C , et al. ( 2009 ) Psychometric properties of the Chinese version of the Swanson, Nolan, and Pelham, Version IV Scale-Teacher Form . J Pediatr Psychol 34 : 850 – 861 . doi: 10.1093/jpepsy/jsn133 OpenUrl CrossRef PubMed Web of Science 39. ↵ Sijtsma K , Molenaar IW ( 2002 ) Introduction to Nonparametric Item Response Theory . SAGE Publications . 40. ↵ Maydeu-Olivares A ( 2013 ) Goodness-of-fit assessment of item response theory models . Measurement (Mahwah NJ ) 11 : 71 – 101 . doi: 10.1080/15366367.2013.831680 OpenUrl CrossRef 41. ↵ R Documentation ( 2021 ) mirt: Full-Information Item Factor Analysis (Multidimensional Item Response Theory). {DataCamp, Inc} 42. ↵ Maydeu-Olivares A , Joe H ( 2014 ) Assessing approximate fit in categorical data analysis . Multivariate Behav Res 49 : 305 – 328 . doi: 10.1080/00273171.2014.911075 OpenUrl CrossRef PubMed 43. ↵ Hayes AF , Coutts JJ ( 2020 ) Use omega rather than cronbach’s alpha for estimating reliability. But… . Commun Methods Meas 14 : 1 – 24 . doi: 10.1080/19312458.2020.1718629 OpenUrl CrossRef 44. Goodboy AK , Martin MM ( 2020 ) Omega over alpha for reliability estimation of unidimensional communication measures . Ann Int Commun Assoc 44 : 422 – 439 . doi: 10.1080/23808985.2020.1846135 OpenUrl CrossRef 45. ↵ Dunn TJ , Baguley T , Brunsden V ( 2014 ) From alpha to omega: a practical solution to the pervasive problem of internal consistency estimation . Br J Psychol 105 : 399 – 412 . doi: 10.1111/bjop.12046 OpenUrl CrossRef 46. ↵ Prinsen CAC , Vohra S , Rose MR , et al. ( 2016 ) How to select outcome measurement instruments for outcomes included in a “Core Outcome Set” - a practical guideline . Trials 17 : 449 . doi: 10.1186/s13063-016-1555-2 OpenUrl CrossRef PubMed 47. ↵ Hu L , Bentler PM ( 1999 ) Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives . Struct Equ Modeling 6 : 1 – 55 . doi: 10.1080/10705519909540118 OpenUrl CrossRef Web of Science 48. ↵ Cai L , Monroe S ( 2014 ) A new statistic for evaluating item response theory models for ordinal data . CRESST report 839 . National Center for Research on Evaluation, Standards, and Student Testing (CRESST) 49. ↵ Swaminathan H , Hambleton RK , Rogers HJ ( 2006 ) 21 assessing the fit of item response theory models . Handbook Of Statist . 50. ↵ Kalkbrenner MT ( 2023 ) Alpha, omega, and H internal consistency reliability estimates: Reviewing these options and when to use them . Couns Outcome Res Eval 14 : 77 – 88 . doi: 10.1080/21501378.2021.1940118 OpenUrl CrossRef 51. ↵ Taber KS ( 2018 ) The use of cronbach’s alpha when developing and reporting research instruments in science education . Res Sci Educ 48 : 1273 – 1296 . doi: 10.1007/s11165-016-9602-2 OpenUrl CrossRef 52. ↵ Cabrera-Nguyen P ( 2010 ) Author guidelines for reporting scale development and validation results in the journal of the society for social work and research . J Soc Social Work Res 1 : 99 – 103 . doi: 10.5243/jsswr.2010.8 OpenUrl CrossRef 53. ↵ Bean GJ , Bowen NK ( 2021 ) Item Response Theory and Confirmatory Factor Analysis: Complementary Approaches for Scale Development . J Evid Based Soc Work . doi: 10.1080/26408066.2021.1906813 OpenUrl CrossRef 54. ↵ Kartal S , Dirlik EM ( 2021 ) Examining the dimensionality and monotonicity of an attitude dataset based on the item response theory models . International Journal of Assessment Tools in Education 8 : 296 – 309 OpenUrl 55. ↵ Samejima F ( 2016 ) Graded response models. In: Handbook of item response theory . Chapman and Hall/CRC , pp 95 – 107 56. ↵ Muraki E ( 1992 ) A generalized partial credit model: Application of an EM algorithm . Appl Psychol Meas 16 : 159 – 176 . doi: 10.1177/014662169201600206 OpenUrl CrossRef Web of Science 57. ↵ Terwee CB ( 2023 ) Common measures or common metrics? the value of IRT-based common metrics . J Patient Rep Outcomes 7 : 117 . doi: 10.1186/s41687-023-00657-w OpenUrl CrossRef PubMed 58. ↵ van Muilekom MM , Luijten MAJ , van Litsenburg RRL , et al. ( 2021 ) Psychometric properties of the Patient-Reported Outcomes Measurement Information System (PROMIS®) Pediatric Anger Scale in the Dutch general population . Psychol Assess 33 : 1261 – 1266 . doi: 10.1037/pas0001051 OpenUrl CrossRef PubMed 59. ↵ Giannopoulou I , Pasalari E , Bali P , et al. ( 2022 ) Psychometric properties of the Revised Child Anxiety and Depression Scale in Greek Adolescents . Clin Child Psychol Psychiatry 27 : 424 – 438 . doi: 10.1177/13591045211056502 OpenUrl CrossRef PubMed 60. ↵ Baschnagel J , Giannopoulou I , Argalia E , et al. ( 2024 ) RCADS 25 - Greek Version . In : Revised Child Anxiety and Depression Scale . https://rcads.ucla.edu/versions . Accessed 26 Sep 2024 61. ↵ Bergmann P , Lucke C , Nguyen T , et al. ( 2020 ) Identification and utility of a short form of the Pediatric Symptom Checklist-youth self-report (PSC-17-Y) . Eur J Psychol Assess 36 : 56 – 64 . doi: 10.1027/1015-5759/a000486 OpenUrl CrossRef 62. ↵ Gardner W , Lucas A , Kolko DJ , Campo JV ( 2007 ) Comparison of the PSC-17 and alternative mental health screens in an at-risk primary care sample . J Am Acad Child Adolesc Psychiatry 46 : 611 – 618 . doi: 10.1097/chi.0b013e318032384b OpenUrl CrossRef PubMed Web of Science 63. ↵ Klaufus L , Verlinden E , van der Wal M , et al. ( 2020 ) Psychometric evaluation of two short versions of the Revised Child Anxiety and Depression Scale . BMC Psychiatry 20 : 47 . doi: 10.1186/s12888-020-2444-5 OpenUrl CrossRef PubMed 64. ↵ University of California, Los Angeles Revised Children’s Anxiety and Depression Scale. In: RCADS . https://rcads.ucla.edu/ . Accessed 25 Jan 2025 65. ↵ Blackwell CK , Wakschlag L , Krogh-Jespersen S , et al. ( 2020 ) Pragmatic health assessment in early childhood: The PROMIS® of developmentally based measurement for pediatric psychology . J Pediatr Psychol 45 : 311 – 318 . doi: 10.1093/jpepsy/jsz094 OpenUrl CrossRef PubMed 66. ↵ Irwin DE , Gross HE , Stucky BD , et al. ( 2012 ) Development of six PROMIS pediatrics proxy-report item banks . Health Qual Life Outcomes 10 : 22 . doi: 10.1186/1477-7525-10-22 OpenUrl CrossRef PubMed 67. Piqueras JA , Martín-Vivar M , Sandin B , et al. ( 2017 ) The Revised Child Anxiety and Depression Scale: A systematic review and reliability generalization meta-analysis . J Affect Disord 218 : 153 – 169 . doi: 10.1016/j.jad.2017.04.022 OpenUrl CrossRef PubMed 68. Massachusetts General Hospital Pediatric Symptom Checklist. In: Massachusetts General Hospital . https://www.massgeneral.org/psychiatry/treatments-and-services/pediatric-symptom-checklist . Accessed 25 Jan 2025 69. Ebesutani C , Korathu-Larson P , Nakamura BJ , et al. ( 2017 ) The Revised Child Anxiety and Depression Scale 25-parent version: Scale development and validation in a school-based and clinical sample . Assessment 24 : 712 – 728 . doi: 10.1177/1073191115627012 OpenUrl CrossRef PubMed 70. Robins D ( 2015 ) MCHAT-R/F Translations. In: M-CHAT TM . https://mchatscreen.com/mchat-rf/translations/ . Accessed 26 Sep 2024 71. Robins DL ( 2015 ) M-CHAT TM - MCHAT R/F Translations. In: M-CHAT TM . https://www.mchatscreen.com/mchat-rf/translations/ . Accessed 25 Jan 2025 72. Williams J , Scott F , Stott C , et al. ( 2005 ) The CAST (Childhood Asperger Syndrome Test): test accuracy . Autism 9 : 45 – 68 . doi: 10.1177/1362361305049029 OpenUrl CrossRef PubMed Web of Science 73. Vogindroukas Y ( 2019 ) Childhood Autism Spectrum Test (CAST) - Greek version. In: Autism Research Centre . https://www.autismresearchcentre.com/tests/childhood-autism-spectrum-test-cast . Accessed 26 Sep 2024 View the discussion thread. Back to top Previous Next Posted March 23, 2025. Download PDF Supplementary Material Email Thank you for your interest in spreading the word about medRxiv. 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Share Psychometric properties and local normative references of PSC-17, RCADS-25, CATS-2, SNAP-IV, MCHAT-R/F, and CAST: data from a nationwide sample in Greece André Simioni , Julia Luiza Schafer , Lauro Estivalete Marchionatti , Kenneth Schuster , Caio Borba Casella , Katerina Papanikolaou , Efstathia Kapsimalli , Panagiota Balikou , Giorgos Gerostergios , Kalliopi Triantafyllou , Maria Basta , Nikos Zilikis , Lilian Athanasopoulou , Vaios Dafoulis , Aspasia Serdari , Rafael V. S. Bastos , Peter Szatmari , Ioanna Giannopoulou , Anastasia Koumoula , Giovanni Abrahão Salum , Konstantinos Kotsis medRxiv 2025.03.21.25324416; doi: https://doi.org/10.1101/2025.03.21.25324416 Share This Article: Copy Citation Tools Psychometric properties and local normative references of PSC-17, RCADS-25, CATS-2, SNAP-IV, MCHAT-R/F, and CAST: data from a nationwide sample in Greece André Simioni , Julia Luiza Schafer , Lauro Estivalete Marchionatti , Kenneth Schuster , Caio Borba Casella , Katerina Papanikolaou , Efstathia Kapsimalli , Panagiota Balikou , Giorgos Gerostergios , Kalliopi Triantafyllou , Maria Basta , Nikos Zilikis , Lilian Athanasopoulou , Vaios Dafoulis , Aspasia Serdari , Rafael V. S. Bastos , Peter Szatmari , Ioanna Giannopoulou , Anastasia Koumoula , Giovanni Abrahão Salum , Konstantinos Kotsis medRxiv 2025.03.21.25324416; doi: https://doi.org/10.1101/2025.03.21.25324416 Citation Manager Formats BibTeX Bookends EasyBib EndNote (tagged) EndNote 8 (xml) Medlars Mendeley Papers RefWorks Tagged Ref Manager RIS Zotero Tweet Widget Facebook Like Google Plus One Subject Area Psychiatry and Clinical Psychology Subject Areas All Articles Addiction Medicine (567) Allergy and Immunology (863) Anesthesia (296) Cardiovascular Medicine (4409) Dentistry and Oral Medicine (443) Dermatology (380) Emergency Medicine (606) Endocrinology (including Diabetes Mellitus and Metabolic Disease) (1505) Epidemiology (15203) Forensic Medicine (30) Gastroenterology (1119) Genetic and Genomic Medicine (6570) Geriatric Medicine (666) Health Economics (994) Health Informatics (4510) Health Policy (1365) Health Systems and Quality Improvement (1608) Hematology (537) HIV/AIDS (1263) Infectious Diseases (except HIV/AIDS) (15902) Intensive Care and Critical Care Medicine (1103) Medical Education (620) Medical Ethics (144) Nephrology (665) Neurology (6572) Nursing (345) Nutrition (998) Obstetrics and Gynecology (1139) Occupational and Environmental Health (954) Oncology (3319) Ophthalmology (967) Orthopedics (369) Otolaryngology (420) Pain Medicine (435) Palliative Medicine (129) Pathology (662) Pediatrics (1689) Pharmacology and Therapeutics (691) Primary Care Research (710) Psychiatry and Clinical Psychology (5421) Public and Global Health (9205) Radiology and Imaging (2190) Rehabilitation Medicine and Physical Therapy (1367) Respiratory Medicine (1191) Rheumatology (593) Sexual and Reproductive Health (709) Sports Medicine (529) Surgery (709) Toxicology (99) Transplantation (288) Urology (265) (function(){function c(){var b=a.contentDocument||a.contentWindow.document;if(b){var d=b.createElement('script');d.innerHTML="window.__CF$cv$params={r:'9fe72825fb5958d3',t:'MTc3OTIzNjIzMA=='};var a=document.createElement('script');a.src='/cdn-cgi/challenge-platform/scripts/jsd/main.js';document.getElementsByTagName('head')[0].appendChild(a);";b.getElementsByTagName('head')[0].appendChild(d)}}if(document.body){var a=document.createElement('iframe');a.height=1;a.width=1;a.style.position='absolute';a.style.top=0;a.style.left=0;a.style.border='none';a.style.visibility='hidden';document.body.appendChild(a);if('loading'!==document.readyState)c();else if(window.addEventListener)document.addEventListener('DOMContentLoaded',c);else{var e=document.onreadystatechange||function(){};document.onreadystatechange=function(b){e(b);'loading'!==document.readyState&&(document.onreadystatechange=e,c())}}}})();