Routine screening for obsessive-compulsive disorder in child and youth mental health services using the Obsessive-compulsive Inventory-Child Version-5 (OCI-CV-5)

Routine screening for obsessive-compulsive disorder in child and youth mental health services using the Obsessive-compulsive Inventory-Child Version-5 (OCI-CV-5) | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (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],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Routine screening for obsessive-compulsive disorder in child and youth mental health services using the Obsessive-compulsive Inventory-Child Version-5 (OCI-CV-5) Katelyn Dyason, Patrick Pham, Seona Wilson, Jessica Grisham, Lara Farrell, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7901842/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Obsessive Compulsive Disorder (OCD) is a debilitating disorder affecting 2–3% of children and adolescents. Despite availability of effective treatments, diagnosis is often delayed. We investigated the implementation of routine OCD screening in public mental health services for children and young people. Methods Six public health service teams and their clients were invited to participate. Three services consecutively implemented the Obsessive-compulsive Inventory-Child Version-5 (OCI-CV-5) screener. Clients with positive OCI-CV-5 scores were offered referral to a specialised OCD team for assessing diagnostic caseness using the Anxiety Disorders Interview Schedule-5 (ADIS-5) including clinical severity scores. Receiver Operating Characteristic (ROC) analysis on the confirmed OCD diagnosis group to re-examine the sensitivity and specificity of the OCDI-CV-5. Results Despite variable implementation across services, the OCI-CV-5 showed moderate, positive correlation with ADIS-5 clinician severity ratings r = 0.46, p = 0.007. Significant differences among the diagnostic groups were found on OCI-CV-5 score, H(2) = 7.08, p = 0.029, with the diagnosis group ranking highest (20.91), the subclinical group (16.00) and no diagnosis group (9.50). An ROC analysis demonstrated raising the OCI-CV-5 cut-off from 3 to 7 would improve sensitivity (0.56) and specificity (0.12). Conclusions Paediatric OCD detection in public health services remains an important challenge. Future research should evaluate screening measures, including the OCI-CV-5, across settings. Obsessive-compulsive disorder routine screening mental health public mental health services child and adolescent mental health services psychometrics Figures Figure 1 Figure 2 Introduction Obsessive-compulsive disorder (OCD) affects 2-3% of children and adolescents [1], with peaks of onset at 10-12 years and 20-24 years [2]. Approximately two-thirds of people who develop OCD will do so before 25 years old [2, 3]. OCD is often debilitating, with functional impairment across home, social, and academic activities [4]. Children and adolescents in Australia experience, on average, 14 days absent from school per year due to OCD [5]. For severe OCD, hospital inpatient data show that children and adolescents with primary OCD have a comparable length of stay to those with psychosis [6]. Fortunately, numerous effective treatment options exist, including cognitive-behavioural therapy focusing on exposure with response prevention (ERP), and medications such as selective serotonin reuptake inhibitors [7]. Despite treatment availability, young people typically experience over 2 years delay from symptom onset to diagnosis and treatment commencement [1, 8]. For children with OCD, this delay represents a substantial developmental period impacted by untreated illness [8]. For children and adolescents, untreated OCD is also associated with decreased developmental milestone achievement [8]. Moreover, duration of untreated OCD in childhood predicts symptom persistence in adulthood [9]. In adulthood, OCD has the second longest duration of untreated illness of all psychiatric conditions [10]. Early intervention is imperative for OCD: longer duration of untreated illness is associated with poorer response to treatment [11]. Major reasons for duration of untreated illness include misunderstanding of OCD and shame in patients, their families, and clinical services [12-14]. People tend not to report OCD symptoms unless asked [15, 16] and in the absence of routine screening, OCD is often not detected [15, 17-19]. Delayed diagnosis prolongs the duration of untreated illness [20]. To improve OCD detection at initial presentation to health services, public information dissemination, clinician training and routine screening are recommended [15, 19]. The current study focuses on accurate detection of OCD through the implementation of routine screening and accompanying clinician training in child and youth mental health services as part of a pilot trial of a comprehensive Model of Care for paediatric OCD in these services. There is currently a paucity of evidence on the validity of available screening tools for paediatric OCD [21]. Although the 21-item Obsessive-compulsive Inventory-Child Version (OCI-CV; [22]) is commonly used, no studies to date have administered the recently developed 5-item Obsessive-compulsive Inventory-Child Version-5 (OCI-CV-5; [23]) as a screening tool. In the current study we examined OCD detection through the implementation of routine screening, using the OCI-CV-5, in child and youth mental health services. Method Setting This study was part of a feasibility and effectiveness trial of a broader Model of Care (MOC) for paediatric OCD [24]; ethics approval 2022/ETH01213]). Routine screening for OCD was implemented in four public health child and adolescent mental health services (CAMHS) and two affiliated services (Headspace and an early intervention psychosis team) in Sydney, Australia. Headspace is a primary care provider of community services for subclinical or mild mental health conditions for people aged 12-25. CAMHS are tertiary care providers offering community outpatient services for children and adolescents up to 18 years old with moderate-severe mental health conditions Similarly, the early psychosis intervention team is a secondary care provider offering community services for young people (12-25) at risk of psychosis or other severe mental health conditions. All services are publicly funded, delivered at no-cost to the public, and are staffed by a variety of mental health professionals, including psychiatrists, psychologists, social workers, occupational therapists, and mental health nurses. Participants Three of the six services, Headspace and two CAMHS teams, routinely implemented the OCI-CV-5. Under a waiver of consent, clinical records were accessed for 186 clients aged 12-18 years receiving standard clinical care across these services. Due to severity and service differences between Headspace and CAMHS settings, data were analysed separately for the two service settings. Additionally, the records for 46 clients referred to the OCD speciality service for diagnostic assessment were analysed for validity purposes. Measures Anxiety Disorders Interview Schedule-5 (ADIS-5). The ADIS-5 [25] is widely used semi-structured diagnostic interview schedule for disorders in the Diagnostic and Statistical Manual-5 (DSM-5; [26]) for children and adolescents aged 7-17 years. The ADIS-5 is newly published, but the ADIS-IV was widely used, with excellent interrater and retest reliability for diagnostic ratings and clinician severity ratings [27-29]. In the current study, only the OCD Module was administered to parents, with the clinician severity rating used to determine OCD severity on an 8-point scale (0-8, with scores ³ 4 considered within the “clinical” range of severity). Obsessive-compulsive Inventory-Child Version-5. The OCI-CV-5 [23] is a self-report 5-item screening measure derived from the 21-item OCI-CV [22]. The OCI-CV-5’s highest loading items were based on a conceptual 5-factor model: checking/doubting, ordering, neutralising, washing and obsessing. Items (e.g., “I need to count while I do things” ) are rated ( 0=never ; 1= somewhat ; 2=always ) for occurrence in the past month. In the initial development study ( n =1,047; [23]), the entire OCI-CV was administered. Using a clinical cut-off of 3 across the 5 items of the OCI-CV-5 provided optimal balance of sensitivity (0.73) and specificity (0.72) when comparing OCD samples and clinical controls (with diagnoses other than OCD), correctly classifying 72% of the sample. The initial validation study demonstrated the 5-item measure had adequate internal reliability, ω=0.70. The OCI-CV-5 had good concurrent validity, discriminating between youth with OCD, clinical controls and non-clinical controls, and adequate convergent validity correlating r =0.28 with another measure of OCD, the CY-BOCS, but more strongly correlating with measures of anxiety and depression ( r s=0.54, 0.36 respectively). Sample Characteristics. Age, self-identified gender and diagnoses (by clinical interview) were collected from the client’s medical record. Procedure The OCD team provided training for services in the broader MOC, OCI-CV-5 screening, and OCD treatment before and throughout the pilot implementation of the MOC. Through a two-day workshop, key clinicians from each service were trained in OCD assessment and treatment, including group-based ERP. This workshop served to ensure an even level of clinical knowledge and understanding in OCD assessments and treatment. All clinicians (including clinicians who did not complete the two-day workshop) from the services were offered training in screening (including background on OCD, rationale for screening plus administering and scoring the OCI-CV-5) through several one-hour in-person presentations; training attendance was moderate to high across services. Scoring sheets, FAQs and example scripts for administering the screener were also provided during this training. Monthly working group meetings were held with at least one representative from each service to refine the model and discuss implementation and barriers. The OCD team was available for implementation support, administration queries and referrals through weekly “drop-in” sessions and via email. Headspace incorporated the OCI-CV-5 into their pre-existing online screening and assessment packet which all clients complete prior to their first appointment. All other services administered the OCI-CV-5 by paper either at the client’s first session or at a session deemed clinically appropriate if clinicians were screening their existing caseload. Clients with a positive screen were referred to a specialised OCD team at the local children’s hospital for an OCD diagnostic assessment and treatment recommendations, if the family consented to the referral and the client’s treating clinician deemed the referral to be appropriate based on clinical risk, treatment priorities and treatment stage. The OCD team completed diagnostic interviews via phone with parents and/or young people, as requested by services. Following the diagnostic interview, results were fed back to both the clients/family and the client’s treating team The young person and their family were also provided with basic psychoeducation on OCD, and treatment options were discussed. Statistical Analysis Due to unequal sample size and non-normal distribution, a Mann-Whitney U test was used to analyse the total CAMHS sample. This analysis allowed the comparison of OCI-CV-5 scores in clients who were diagnosed with OCD following a clinical interview against clients who were not diagnosed with OCD. Additionally, a comparison of the three OCD diagnostic sample groups, based on clinician severity ratings, was completed using a Kurskal-Wallis test as the assumptions for between groups ANOVA were violated. A further independent samples t -test was used to compare those who were diagnosed and those who were not. A Receiver Operating Characteristic (ROC) analysis on the confirmed OCD diagnosis group to re-examine the sensitivity and specificity of the OCDI-CV-5. Results OCI-CV-5 screener implementation was variable. Services used the screener frequently, but non-consecutively, as part of standard intake procedures. Two services administered the screener only if OCD was suspected and one service did not administer the screener. Headspace, who digitised the screener and integrated it into existing intake procedures, had the most consistent implementation and referral rates: 63.1% of new clients were screened over a 9-month period and 27.9% of positive screens were referred to the OCD team for diagnostic assessment. Two CAMHS services implemented paper-based screening of consecutive new referrals, one of these services also screened their existing client base. One CAMHS team reported they screened approximately 40% of both new referrals and existing caseload across 5 months and referred 57.7% of positive screens to the team OCD team. The second CAMHS team screened 81.3% of new referrals over 4 months but referred 0% of positive screens to the OCD team. Table 1 presents the descriptive demographic data for three samples. CAMHS Data ( n =45) Descriptive Data. OCI-CV-5 total scores ranged from 1-10, with 86.7% ( n =39) screening positively (≥3). The mean total score was 5.62 ( SD =2.72; Q1=3, Q2=5, Q3=8), and the modal total score was 8. Total scores were distributed with two modes at 3 and 8. Item-level scores were unavailable for 14 clients. In relation to item-level analyses (n=31), the most endorsed item (score of 1, 2) was question 2 (“I need things to be a certain way”), with only 1 client (3.2%) endorsing “never”. The highest scoring item was question 5 (“I get upset by bad thoughts that pop into my head when I don’t want them to”) with a mean score of 1.48 ( SD =0.68) and a modal score of 2. The least endorsed item and the lowest scoring item ( M =0.61, SD =0.76, Mode =0) was question 4 (“I wash my hands more than other kids”) with 54.8% ( n =17) endorsing “never”. No items had a normal distribution: questions 1 and 5 were heavily negatively skewed, questions 3 and 4 were positively skewed and question 2 had a flat distribution with the same number of clients endorsing 1 and 2, and only 1 client endorsing 0. Diagnostic Data. In the total CAMHS sample, n =5 (11.1%) cases were diagnosed with OCD based on clinical interview. The descriptive statistics for those with and without an OCD diagnosis are shown in Table 2. OCI-CV-5 scores had a bimodal distribution in those without a diagnosis of OCD, with peaks at 3 and 8. The OCD diagnosed group had higher scores on the OCI-CV-5 than the non-diagnosed group, U=158.50, p =.031. The area under the curve (AUC) was 0.79, which indicates the OCI-CV-5 had acceptable/moderate discrimination and predictive power in this sample (Figure 1). The produced ROC curve had ties, meaning cases in both groups had the same value and the corresponding lie was drawn diagonally rather than horizontally then vertically, or vice versa. There is therefore a risk of bias in the ROC curve and the AUC may be under-estimated. Based on distance to corner, 7.5 on the OCI-CV-5 would be the optimal cut-off to maximise sensitivity (0.60) and specificity (0.33). The classification rates using a cut-off of 7 are shown in Table 3. Headspace Data ( n =141) Descriptive Data. Total scores on the OCI-CV-5 were normally distributed and ranged from 0-10, with 78.7% ( n =111) screening positively (≥3). The mean total score was 4.52 ( SD =2.36; Q1=3, Q2=4, Q3=6), and the modal total score was 4. In relation to item-level analyses, the most endorsed (score of 1, 2) and highest- scoring item ( M =1.15, SD =0.70, Mode =1) was question 5 (“I get upset by bad thoughts that pop into my head when I don’t want them to”), with only 17.7% ( n =25) clients endorsing “never”. The least endorsed and lowest scoring item ( M =0.61, SD =0.76, Mode =0) was question 4 (“I wash my hands more than other kids”) with 56% ( n =79) endorsing “never”. Question 3 (“I need to count while I do things”) was also less endorsed with 50.4% ( n =71) endorsing “never”. Accordingly, questions 1 and 2 were normally distributed, questions 3 and 4 were heavily positively skewed and question 5 was somewhat negatively skewed (with “somewhat” still being the modal answer). Diagnostic Data. Diagnostic data was not available for the headspace sample as the headspace service model of care does not include diagnostic assessment. Clients with Positive OCI-CV-5 Screener Scores ( n =41) Descriptive Data. Of 64 referrals to the OCD team, n =41 completed the OCI-CV-5. Total scores on OCI-CV-5 ranged from 3-10, with a bimodal distribution featuring peaks at 5 and 7 with 7 being the largest peak. The mean total score was 6.68 ( SD =1.96; Q1=5, Q2=7, Q3=8), and the modal total score was 7. Diagnostic Data. Of the n =41 clients referred to the OCD speciality team who completed the OCI-CV-5, n =33 clients also completed an OCD diagnostic assessment using the ADIS-5 OCD module. There was a moderate, positive correlation between OCI-CV-5 total score and clinician severity rating (CSR; 0-8) on the ADIS, r =0.46, p = 0.007. Table 4 shows descriptive data for clients who received a diagnosis , a sub-clinical diagnosis and no diagnosis. Comparing between the three diagnostic groups using the Kruskal-Wallis test, there was a significant difference between the groups on OCI-CV-5 score, H(2)=7.08, p =0.029, with the diagnosis group ranking highest (20.91), followed by the subclinical group (16.00) and no diagnosis (9.50). Using an independent samples t -test to compare those who were diagnosed and those who were not (including sub-clinical; M =5.82, SD =1.85), there was a significant large difference on OCI-CV-5 scores, t (31)=-2.41, p =0.022, d =0.19. For the purpose of the ROC analysis, an additional n = 2 clients were included in the sub-sample who had scores recorded on the OCI-CV-5 and who had a diagnosis of OCD confirmed through clinical interview outside of the OCD team, leading to a sub-sample of n =35. The ROC curve is shown in Figure 2. The area under the curve (AUC) was 0.74, which indicates the OCI-CV-5 had moderate discrimination and predictive power with a cut-off of 3. Based on distance to corner, 7.5 on the OCI-CV-5 would again be the optimal cut-off to maximise sensitivity (0.56) and specificity (0.12). The classification rates using a cut-off of 7 are shown in Table 5. Discussion OCD is often under-diagnosed or mis-diagnosed, with a substantial duration of untreated illness of over 2 years for children and adolescents [ 1 , 8 ]. To reduce the duration of untreated illness, routine screening and clinician training have been recommended [ 15 , 19 ]. As part of a broader implementation pilot of a Model of Care for paediatric OCD, the OCI-CV-5 was implemented as a routine screening measure, accompanied by clinician training, in six child and youth mental health services in one local health district in Sydney, Australia, to improve detection rates of OCD. Implementing the OCI-CV-5 as a screening tool was often challenging—screening completion rates varied from 40% to 80% across the three services reporting “consistent” implementation. Two out of six services completed the screener only when they wanted to refer onwards to the OCD team and one service did not implement the screener. Primary reasons for not screening were that clients declined to complete measures, client had an existing diagnosis of OCD, or the clinician did not feel it was appropriate to administer based on client risk/severity or presenting problem, especially when clinicians held concerns over the high false positive rate and low face validity of the measure. Further discussion of the challenges in implementing screening will be discussed in Dyason et al [in prep]. The OCI-CV-5 demonstrated convergent validity with a moderate positive correlation between OCI-CV-5 scores and symptoms confirmed by structured clinical interview. Clients with a diagnosis of OCD scored higher on the OCI-CV-5 than those with subclinical symptoms, who in turn scored higher than those without a diagnosis. As expected, mean scores on the OCI-CV-5 were lowest for the primary care sample (headspace), higher for the CAMHS sample (tertiary care), and highest for the OCD team sample (quaternary care). However, the OCI-CV-5’s construct validity was low-moderate as two items (questions 2 and 5) of the five in the OCI-CV-5 were endorsed by the majority of participants (diagnosed with OCD and not diagnosed). This suggest these items were not detecting OCD but perhaps overall distress or presence of any mental health condition, aligning with previous findings of higher correlation in anxiety and depression measures comparative to OCD measure [ 23 ]. As such, clinicians frequently raised concerns over the face validity of these items [Dyason et al., in prep]. Item 4 (“I wash my hands more than other kids”) was the least commonly endorsed item in both samples, despite having high face validity for OCD (washing/cleaning compulsion). This item may be the most discriminatory question within the OCI-CV-5. With only moderate construct and face validity, the discriminant validity of the measure overall was relatively poor. In the original OCI-CV-5 development study [ 23 ], the full 21-item OCI-CV was administered, and thus this is the first study to investigate the administration of only the 5-item measure. With the additional 16 items in the full measure, the OCI-CV has good face validity measuring many symptoms of OCD; however, without the additional items, some of the context of the measure is lost—wording of the items was more ambiguous and could be interpreted as relating to symptoms of other disorders (e.g., intrusive thoughts in PTSD) [Dyason et al., in prep]. However, the OCI-CV-5’s sensitivity was high, detecting the majority of clients with OCD based on clinician diagnostic interview reports. However, 87% of clients screened in CAMHS and 79% of clients screened in Headspace screened positively and required further diagnostic assessments. This indicated the specificity and utility of the measure was low and suggests the OCI-CV-5’s current form, with a clinical cut-off of 3/10, is not suitable for use in public mental health services. The ROC analyses suggested a cut-off of 7/10 would maximise sensitivity and specificity across the CAMHS and OCD team samples. However, this may miss instances of sub-clinical or mild OCD. We could find no published data on OCD prevalence in CAMHS outpatient settings. Tentative extrapolation from the current study could inform future prospective research. Of CAMHS clients screened, 40–80% screened positive. Of people referred for full diagnostic assessment, 11% were diagnosed with OCD, yielding an estimated prevalence of 4–9% in this cohort. Despite multiple assumptions, this estimate is plausible. OCD prevalence in primary and state-based mental health service settings can reasonably be expected to be greater that in the general population, i.e., 2–3% [ 1 ]. In two CAMHS inpatient units, the prevalence of OCD was 9% [ 6 ], and so likely the true prevalence in a CAMHS mental health outpatient setting lies between the community prevalence and the inpatient prevalence. Limitations Although the current study is high in ecological validity, demonstrating the real-world use of a measure in routine clinical settings, there were limited psychometric analyses possible with non-consecutive administration of the measure, inconsistent referrals for diagnostic assessments, only one convergent validity measure available, and no reliability analyses possible. While the OCI-CV-5 was developed for use in 7–17 year old cohorts, it is worth noting that no children under 12 years old were represented in the data provided despite three of the six CAMHS offering services to this population. As such there was no validity data possible in the current sample for children aged 7–11. Finally, referrals to the OCD team were inconsistent, yet this is not a reflection of the screener, but about integration of clinical services and perceived usefulness to clinicians and families of referrals from one service to another. Conclusions and Future Directions With one of the longest durations of untreated illness of any psychiatric condition [ 10 ], there is a desperate need to increase detection of OCD [ 15 ]. Routine screening of OCD in healthcare settings is recommended [ 15 ], yet often not actioned. We trialled implementation of the OCI-CV-5 in six child and adolescent mental health service teams in real-world clinical settings where resources are limited and clinical complexity is high. Varying consistent implementation rates of OCD screeners indicate there are significant barriers in implementing routine OCD screening within health care settings, despite the need and recommendation for accurate OCD detection through routine screening. Our pending paper will further explore these barriers. Alarmingly despite the inconsistent implementation of OCD screening, our findings suggest the prevalence of OCD amongst public health child and adolescent health services may be higher than the general public but lower than inpatient units. This highlights not only the need for improvements on routine OCD screening but also the need for future studies to investigate and establish more accurate rates of OCD within public health child and adolescent health services. The OCI-CV-5’s poor face validity and specificity brings into question if the OCI-CV-5 in its current form with a clinical cut off of 3 is suitable as a screener in a public health setting in context where the clinical population often presents with complex presentations, comorbid conditions, and a high degree of risk. Future research should look to re-evaluate which items are included on the OCI-CV-5, swapping other items from the well-validated and commonly used longer format OCI-CV [ 22 ] to increase face validity and discriminant validity. Alternatively, other pre-existing OCD screening measures could be trialled, such as the Short Obsessive Compulsive Screener (SOCS;[ 30 ]) which was developed de novo for screening purposes, rather than being adapted from a longer measure. To effectively validate a screening measure in a routine clinical setting, it is recommended only the screening questions be administered so their stand-alone performance can be evaluated in the context for which it is designed to ensure fit-for-purpose. It is possible also that there are as-yet-unidentified alternatives, such as artificial intelligence analysis of written text provided by individuals and/or the use of algorithms to identify those at greatest risk for OCD. As the field continues to grow and our understanding of OCD increases, there is great potential to improve detection rates of OCD in routine clinical care, factoring in both clinical judgement and flexibility whilst also incorporating evidence-based recommendations to best meet clients’ needs. Declarations Conflict of Interest: Neither the scholarship nor funding providers were involved in the: collection, analyses, and interpretation of data; writing; or submission process. L. J. Farrell is the author of the OCD Busters program and receives consultancy fees for the delivery of training and supervision in relation to these materials. She receives royalties from Cambridge University Press, Elsevier, and Springer for published works and ongoing editorial work. The authors declare they have no other conflicts of interest. Competing Interests Neither the scholarship nor funding providers were involved in the: collection, analyses, and interpretation of data; writing; or submission process. L. J. Farrell is the author of the OCD Busters program and receives consultancy fees for the delivery of training and supervision in relation to these materials. She receives royalties from Cambridge University Press, Elsevier, and Springer for published works and ongoing editorial work. The authors declare they have no other conflicts of interest. Author Contribution KD was responsible for conceptualisation, methodology, formal analysis, investigation, data curation, writing (original draft), writing (review and editing), visualisation, and project administration.S.W was responsible for investigation and writing (review and editing).P.P was responsible for investigation and writing - (review and editing).J.G was responsible for conceptualisation, methodology, writing - (review and editing), supervision, and fund acquisition.L.F was responsible for conceptualisation, methodology, resources, writing - (review and editing), supervision, and fund acquisition.T.B, B.T, T.D, and R.L were responsible for investigation, resources, and writing (reviewing).C.G and K.K were responsible for conceptualisation, resources, supervision, fund acquisition.I.P was responsible for conceptualisation, methodology, investigations, writing - (review and editing), visualisation, supervision, and fund acquisition. Acknowledgement We would like to thank the clinicians and other members of the working group and steering committee for contributing their time and experiences, particularly, Caitlin Dixon, Antonia Ottavio, and Belinda Middleton. This work was supported the Sydney Children’s Hospitals Foundation and Mindgardens Neuroscience Network (funded by the Australian Government Department of Health and Aged Care). References Geller DA (2006) Obsessive-compulsive and spectrum disorders in children and adolescents. Psychiatr Clin North Am 29:353–370. https://doi.org/10.1016/j.psc.2006.02.012 Geller DA, Homayoun S, Johnson G (2021) Developmental Considerations in Obsessive Compulsive Disorder: Comparing Pediatric and Adult-Onset Cases. 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J Anxiety Disord 14:535–548. https://doi.org/10.1016/S0887-6185(00)00048-7 Glazier K, Calixte RM, Rothschild R, Pinto A (2013) High rates of OCD symptom misidentification by mental health professionals. Ann Clin Psychiatry 25(3):201–209 Glazier K, Swing M, McGinn LK (2015a) Half of obsessive-compulsive disorder cases misdiagnosed: vignette-based survey of primary care physicians. J Clin Psychiatry 76(6):e761–e767. https://doi.org/10.4088/JCP.14m09110 Senter MS, Patel SR, Dixon LB, Myers RW, Simpson HB (2021) Defining and Addressing Gaps in Care for Obsessive-Compulsive Disorder in the United States. Psychiatric Serv (Washington D C) 72(7):784–793. https://doi.org/10.1176/appi.ps.202000296 McKay D, Abramowitz JS, Storch EA (2021) Mechanisms of harmful treatments for obsessive–compulsive disorder. Clin Psychol Sci Pract 28(1):52 Adam, G. P., Caputo, E. L., Kanaan, G., Freeman, J. B., Brannan, E. H., Balk, E. M.,… Steele, D. W. (2025). Brief Assessment Tools for Obsessive-Compulsive Disorders in Children: A Systematic Review. Pediatrics, 155(3) Foa EB, Coles M, Huppert JD, Pasupuleti RV, Franklin ME, March J (2010) Development and validation of a child version of the obsessive compulsive inventory. Behav Ther 41(1):121–132. https://doi.org/10.1016/j.beth.2009.02.001 Abramovitch A, Abramowitz JS, McKay D, Cham H, Anderson KS, Farrell LJ, Geller DA, Hanna GL, Mathieu S, McGuire JF, Rosenberg DR, Stewart SE, Storch EA, Wilhelm S (2022) An ultra-brief screening scale for pediatric obsessive-compulsive disorder: The OCI-CV-5. J Affect Disord 312:208–216. https://doi.org/10.1016/j.jad.2022.06.009 Perkes I, Grisham J, Farrell L, Dyason KM, Racz J (2022) OCD BOUNCE: A Model of Care for Paediatric OCD. https://doi.org/10.17605/OSF.IO/HVTR2 Kerns CM, Silverman WK (2024) and Anne Marie Albano, 'Anxiety and Related Disorders Interview Schedule for DSM-5, Child and Parent Version: Autism Spectrum Addendum (ADIS/ASA)', Anxiety and Related Disorders Interview Schedule for DSM-5, Child and Parent Version: Clinician Manual (New York, ; online edn, Oxford Academic, 1 Mar. 2024). https://doi.org/10.1093/med-psych/9780199348343.003.0002 American Psychiatric Association (2013) Diagnostic and statistical manual of mental disorders, 5th edn. American Psychiatric Association. https://doi.org/10.1176/appi.books.9780890425596 Lyneham HJ, Abbott MJ, Rapee RM (2007) Interrater reliability of the anxiety disorders interview schedule for DSM-IV: Child and parent version. J Am Acad Child Adolesc Psychiatry 46(6):731–736 Silverman WK, Saavedra LM, Pina AA (2001) Test-retest reliability of anxiety symptoms and diagnoses with the Anxiety Disorders Interview Schedule for DSM-IV: child and parent versions. J Am Acad Child Adolesc Psychiatry 40(8):937–944 Greenberg EL, Geller DA (2019) Phenomenology and standard care of OCD in children and adolescents. In: Farrell LJ, Ollendick TH, Muris P (eds) Innovations in CBT for childhood anxiety, OCD and PTSD. Cambridge University Press, pp 289–312 Uher R, Heyman I, Mortimore C, Frampton I, Goodman R (2007) Screening young people for obsessive compulsive disorder. Br J Psychiatry 191:353–354. https://doi.org/10.1192/bjp.bp.106.034967 Tables Table 1 to 5 are available in the Supplementary Files section. Additional Declarations Competing interest reported. Neither the scholarship nor funding providers were involved in the: collection, analyses, and interpretation of data; writing; or submission process. L. J. Farrell is the author of the OCD Busters program and receives consultancy fees for the delivery of training and supervision in relation to these materials. She receives royalties from Cambridge University Press, Elsevier, and Springer for published works and ongoing editorial work. The authors declare they have no other conflicts of interest. Supplementary Files Tables.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7901842","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":533413601,"identity":"984e34ff-e14e-4102-89be-4ea1e9e5dae5","order_by":0,"name":"Katelyn 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1","display":"","copyAsset":false,"role":"figure","size":22462,"visible":true,"origin":"","legend":"\u003cp\u003eROC Curve Showing Sensitivity and Specificity for the OCI-CV-5 in the CAMHS Sample (n = 45)\u003c/p\u003e","description":"","filename":"Fig1ROCCurveShowingSensitivityandSpecificityfortheOCICV5intheCAMHSSamplen45.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7901842/v1/4620f5b9467eafb2270208d2.jpg"},{"id":95799111,"identity":"4a8a2e41-de41-46e0-8fa8-0390920f390f","added_by":"auto","created_at":"2025-11-13 08:18:49","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":36919,"visible":true,"origin":"","legend":"\u003cp\u003eROC Curve Showing Sensitivity and Specificity for the OCI-CV-5 in the OCD Specialty Team Sample (n = 35)\u003c/p\u003e","description":"","filename":"Fig2ROCCurveShowingSensitivityandSpecificityfortheOCICV5intheOCDSpecialtyTeamSamplen35.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7901842/v1/349e452dd16b812bb1ea8b1b.jpg"},{"id":101053746,"identity":"a054080f-d0e8-4f49-ac78-677db0346164","added_by":"auto","created_at":"2026-01-24 17:54:45","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":714746,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7901842/v1/2eb9a539-80b6-49d8-a2c7-74d855780b96.pdf"},{"id":95670771,"identity":"bd90956b-8907-4871-a477-e6ee065957d7","added_by":"auto","created_at":"2025-11-11 17:22:28","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":28366,"visible":true,"origin":"","legend":"","description":"","filename":"Tables.docx","url":"https://assets-eu.researchsquare.com/files/rs-7901842/v1/8acff378bc89e300d0f9dc84.docx"}],"financialInterests":"Competing interest reported. Neither the scholarship nor funding providers were involved in the: collection, analyses, and interpretation of data; writing; or submission process. L. J. Farrell is the author of the OCD Busters program and receives consultancy fees for the delivery of training and supervision in relation to these materials. She receives royalties from Cambridge University Press, Elsevier, and Springer for published works and ongoing editorial work. The authors declare they have no other conflicts of interest.","formattedTitle":"Routine screening for obsessive-compulsive disorder in child and youth mental health services using the Obsessive-compulsive Inventory-Child Version-5 (OCI-CV-5)","fulltext":[{"header":"Introduction","content":"\u003cp\u003eObsessive-compulsive disorder (OCD) affects 2-3% of children and adolescents [1], with peaks of onset at 10-12 years and 20-24 years [2]. Approximately two-thirds of people who develop OCD will do so before 25 years old [2, 3]. OCD is often debilitating, with functional impairment across home, social, and academic activities [4]. Children and adolescents in Australia experience, on average, 14 days absent from school per year due to OCD [5]. For severe OCD, hospital inpatient data show that children and adolescents with primary OCD have a comparable length of stay to those with psychosis [6].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFortunately, numerous effective treatment options exist, including cognitive-behavioural therapy focusing on exposure with response prevention (ERP), and medications such as selective serotonin reuptake inhibitors [7]. Despite treatment availability, young people typically experience over 2 years delay from symptom onset to diagnosis and treatment commencement [1, 8]. For children with OCD, this delay represents a substantial developmental period impacted by untreated illness [8]. For children and adolescents, untreated OCD is also associated with decreased developmental milestone achievement [8]. Moreover, duration of untreated OCD in childhood predicts symptom persistence in adulthood [9]. In adulthood, OCD has the second longest duration of untreated illness of all psychiatric conditions [10]. Early intervention is imperative for OCD: longer duration of untreated illness is associated with poorer response to treatment [11].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMajor reasons for duration of untreated illness include misunderstanding of OCD and shame in patients, their families, and clinical services [12-14]. People tend not to report OCD symptoms unless asked [15, 16] and in the absence of routine screening, OCD is often not detected [15, 17-19]. Delayed diagnosis prolongs the duration of untreated illness [20].\u003c/p\u003e\n\u003cp\u003eTo improve OCD detection at initial presentation to health services, public information dissemination, clinician training and routine screening are recommended [15, 19]. The current study focuses on accurate detection of OCD through the implementation of routine screening and accompanying clinician training in child and youth mental health services as part of a pilot trial of a comprehensive Model of Care for paediatric OCD in these services. \u0026nbsp;There is currently a paucity of evidence on the validity of available screening tools for paediatric OCD [21]. Although the 21-item Obsessive-compulsive Inventory-Child Version (OCI-CV; [22]) is commonly used, no studies to date have administered the recently developed 5-item Obsessive-compulsive Inventory-Child Version-5 (OCI-CV-5; [23]) as a screening tool.\u003c/p\u003e\n\u003cp\u003eIn the current study we examined OCD detection through the implementation of routine screening, using the OCI-CV-5, in child and youth mental health services.\u003c/p\u003e"},{"header":"Method","content":"\u003cp\u003e\u003cstrong\u003eSetting\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was part of a feasibility and effectiveness trial of a broader Model of Care (MOC) for paediatric OCD [24]; ethics approval 2022/ETH01213]). Routine screening for OCD was implemented in four public health child and adolescent mental health services (CAMHS) and two affiliated services (Headspace and an early intervention psychosis team) in Sydney, Australia. Headspace is a primary care provider of community services for subclinical or mild mental health conditions for people aged 12-25. CAMHS are tertiary care providers offering community outpatient services for children and adolescents up to 18 years old with moderate-severe mental health conditions Similarly, the early psychosis intervention team is a secondary care provider offering community services for young people (12-25) at risk of psychosis or other severe mental health conditions. All services are publicly funded, delivered at no-cost to the public, and are staffed by a variety of mental health professionals, including psychiatrists, psychologists, social workers, occupational therapists, and mental health nurses.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eParticipants\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThree of the six services, Headspace and two CAMHS teams, routinely implemented the OCI-CV-5. Under a waiver of consent, clinical records were accessed for 186 clients aged 12-18 years receiving standard clinical care across these services. Due to severity and service differences between Headspace and CAMHS settings, data were analysed separately for the two service settings. Additionally, the records for 46 clients referred to the OCD speciality service for diagnostic assessment were analysed for validity purposes.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMeasures\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAnxiety Disorders Interview Schedule-5 (ADIS-5).\u0026nbsp;\u003c/strong\u003eThe ADIS-5 [25] is widely used semi-structured diagnostic interview schedule for disorders in the Diagnostic and Statistical Manual-5 (DSM-5; [26]) for children and adolescents aged 7-17 years. The ADIS-5 is newly published, but the ADIS-IV was widely used, with excellent interrater and retest reliability for diagnostic ratings and clinician severity ratings [27-29]. In the current study, only the OCD Module was administered to parents, with the clinician severity rating used\u0026nbsp;to determine OCD severity on an 8-point scale (0-8, with scores\u0026nbsp;\u0026sup3;\u0026nbsp;4 considered within the \u0026ldquo;clinical\u0026rdquo; range of severity).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eObsessive-compulsive Inventory-Child Version-5.\u003c/strong\u003e The OCI-CV-5 [23] is a self-report 5-item screening measure derived from the 21-item OCI-CV [22]. The OCI-CV-5\u0026rsquo;s highest loading items were based on a conceptual 5-factor model: checking/doubting, ordering, neutralising, washing and obsessing. Items (e.g., \u003cem\u003e\u0026ldquo;I need to count while I do things\u0026rdquo;\u003c/em\u003e) are rated (\u003cem\u003e0=never\u003c/em\u003e; 1=\u003cem\u003esomewhat\u003c/em\u003e; \u003cem\u003e2=always\u003c/em\u003e) for occurrence in the past month. In the initial development study (\u003cem\u003en\u003c/em\u003e=1,047; [23]), the entire OCI-CV was administered. Using a clinical cut-off of 3 across the 5 items of the OCI-CV-5 provided optimal balance of sensitivity (0.73) and specificity (0.72) when comparing OCD samples and clinical controls (with diagnoses other than OCD), correctly classifying 72% of the sample. The initial validation study demonstrated the 5-item measure had adequate internal reliability, \u0026omega;=0.70. The OCI-CV-5 had good concurrent validity, discriminating between youth with OCD, clinical controls and non-clinical controls, and adequate convergent validity correlating \u003cem\u003er\u003c/em\u003e=0.28 with another measure of OCD, the CY-BOCS, but more strongly correlating with measures of anxiety and depression (\u003cem\u003er\u003c/em\u003es=0.54, 0.36 respectively).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSample Characteristics.\u0026nbsp;\u003c/strong\u003eAge, self-identified gender and diagnoses (by clinical interview) were collected from the client\u0026rsquo;s medical record.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eProcedure\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe OCD team provided training for services in the broader MOC, OCI-CV-5 screening, and OCD treatment before and throughout the pilot implementation of the MOC. Through a two-day workshop, key clinicians from each service were trained in OCD assessment and treatment, including group-based ERP. This workshop served to ensure an even level of clinical knowledge and understanding in OCD assessments and treatment. \u0026nbsp;All clinicians (including clinicians who did not complete the two-day workshop) from the services were offered training in screening (including background on OCD, rationale for screening plus administering and scoring the OCI-CV-5) through several one-hour in-person presentations; training attendance was moderate to high across services. Scoring sheets, FAQs and example scripts for administering the screener were also provided during this training. Monthly working group meetings were held with at least one representative from each service to refine the model and discuss implementation and barriers. The OCD team was available for implementation support, administration queries and referrals through weekly \u0026ldquo;drop-in\u0026rdquo; sessions and via email.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHeadspace incorporated the OCI-CV-5 into their pre-existing online screening and assessment packet which all clients complete prior to their first appointment. All other services administered the OCI-CV-5 by paper either at the client\u0026rsquo;s first session or at a session deemed clinically appropriate if clinicians were screening their existing caseload. Clients with a positive screen were referred to a specialised OCD team at the local children\u0026rsquo;s hospital for an OCD diagnostic assessment and treatment recommendations, if the family consented to the referral and the client\u0026rsquo;s treating clinician deemed the referral to be appropriate based on clinical risk, treatment priorities and treatment stage.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe OCD team completed diagnostic interviews via phone with parents and/or young people, as requested by services. Following the diagnostic interview, results were fed back to both the clients/family and the client\u0026rsquo;s treating team The young person and their family were also provided with basic psychoeducation on OCD, and treatment options were discussed. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDue to unequal sample size and non-normal distribution, a Mann-Whitney U test was used to analyse the total CAMHS sample. This analysis allowed the comparison of OCI-CV-5 scores in clients who were diagnosed with OCD following a clinical interview against clients who were not diagnosed with OCD. Additionally, a comparison of the three OCD diagnostic sample groups, based on clinician severity ratings, was completed using a Kurskal-Wallis test as the assumptions for between groups ANOVA were violated. A further independent samples \u003cem\u003et\u003c/em\u003e-test was used to compare those who were diagnosed and those who were not. A Receiver Operating Characteristic (ROC) analysis on the confirmed OCD diagnosis group to re-examine the sensitivity and specificity of the OCDI-CV-5.\u0026nbsp;\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eOCI-CV-5 screener implementation was variable. Services used the screener frequently, but non-consecutively, as part of standard intake procedures. Two services administered the screener only if OCD was suspected and one service did not administer the screener. Headspace, who digitised the screener and integrated it into existing intake procedures, had the most consistent implementation and referral rates: 63.1% of new clients were screened over a 9-month period and 27.9% of positive screens were referred to the OCD team for diagnostic assessment. Two CAMHS services implemented paper-based screening of consecutive new referrals, one of these services also screened their existing client base. One CAMHS team reported they screened approximately 40% of both new referrals and existing caseload across 5 months and referred 57.7% of positive screens to the team OCD team. The second CAMHS team screened 81.3% of new referrals over 4 months but referred 0% of positive screens to the OCD team. Table 1 presents the descriptive demographic data for three samples.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCAMHS Data (\u003cem\u003en\u003c/em\u003e=45)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDescriptive Data.\u0026nbsp;\u003c/strong\u003eOCI-CV-5 total scores ranged from 1-10, with 86.7% (\u003cem\u003en\u003c/em\u003e=39) screening positively (\u0026ge;3). The mean total score was 5.62 (\u003cem\u003eSD\u003c/em\u003e=2.72; Q1=3, Q2=5, Q3=8), and the modal total score was 8. Total scores were distributed with two modes at 3 and 8. Item-level scores were unavailable for 14 clients. In relation to item-level analyses (n=31), the most endorsed item (score of 1, 2) was question 2 (\u0026ldquo;I need things to be a certain way\u0026rdquo;), with only 1 client (3.2%) endorsing \u0026ldquo;never\u0026rdquo;. The highest scoring item was question 5 (\u0026ldquo;I get upset by bad thoughts that pop into my head when I don\u0026rsquo;t want them to\u0026rdquo;) with a mean score of 1.48 (\u003cem\u003eSD\u003c/em\u003e=0.68) and a modal score of 2. The least endorsed item and the lowest scoring item (\u003cem\u003eM\u003c/em\u003e=0.61, \u003cem\u003eSD\u003c/em\u003e=0.76, \u003cem\u003eMode\u003c/em\u003e=0) was question 4 (\u0026ldquo;I wash my hands more than other kids\u0026rdquo;) with 54.8% (\u003cem\u003en\u003c/em\u003e=17) endorsing \u0026ldquo;never\u0026rdquo;. No items had a normal distribution: questions 1 and 5 were heavily negatively skewed, questions 3 and 4 were positively skewed and question 2 had a flat distribution with the same number of clients endorsing 1 and 2, and only 1 client endorsing 0.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDiagnostic Data.\u0026nbsp;\u003c/strong\u003eIn the total CAMHS sample, \u003cem\u003en\u003c/em\u003e=5 (11.1%) cases were diagnosed with OCD based on clinical interview. The descriptive statistics for those with and without an OCD diagnosis are shown in Table 2. OCI-CV-5 scores had a bimodal distribution in those without a diagnosis of OCD, with peaks at 3 and 8. The OCD diagnosed group had higher scores on the OCI-CV-5 than the non-diagnosed group, U=158.50, \u003cem\u003ep\u003c/em\u003e=.031.\u003c/p\u003e\n\u003cp\u003eThe area under the curve (AUC) was 0.79, which indicates the OCI-CV-5 had acceptable/moderate discrimination and predictive power in this sample (Figure 1). The produced ROC curve had ties, meaning cases in both groups had the same value and the corresponding lie was drawn diagonally rather than horizontally then vertically, or vice versa. There is therefore a risk of bias in the ROC curve and the AUC may be under-estimated. Based on distance to corner, 7.5 on the OCI-CV-5 would be the optimal cut-off to maximise sensitivity (0.60) and specificity (0.33). The classification rates using a cut-off of 7 are shown in Table 3.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHeadspace Data (\u003cem\u003en\u003c/em\u003e=141)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDescriptive Data.\u0026nbsp;\u003c/strong\u003eTotal scores on the OCI-CV-5 were normally distributed and ranged from 0-10, with 78.7% (\u003cem\u003en\u003c/em\u003e=111) screening positively (\u0026ge;3). The mean total score was 4.52 (\u003cem\u003eSD\u003c/em\u003e=2.36; Q1=3, Q2=4, Q3=6), and the modal total score was 4. In relation to item-level analyses, the most endorsed (score of 1, 2) and highest- scoring item (\u003cem\u003eM\u003c/em\u003e=1.15, \u003cem\u003eSD\u003c/em\u003e=0.70, \u003cem\u003eMode\u003c/em\u003e=1) was question 5 (\u0026ldquo;I get upset by bad thoughts that pop into my head when I don\u0026rsquo;t want them to\u0026rdquo;), with only 17.7% (\u003cem\u003en\u003c/em\u003e=25) clients endorsing \u0026ldquo;never\u0026rdquo;. \u0026nbsp;The least endorsed and lowest scoring item (\u003cem\u003eM\u003c/em\u003e=0.61, \u003cem\u003eSD\u003c/em\u003e=0.76, \u003cem\u003eMode\u003c/em\u003e=0) was question 4 (\u0026ldquo;I wash my hands more than other kids\u0026rdquo;) with 56% (\u003cem\u003en\u003c/em\u003e=79) endorsing \u0026ldquo;never\u0026rdquo;. Question 3 (\u0026ldquo;I need to count while I do things\u0026rdquo;) was also less endorsed with 50.4% (\u003cem\u003en\u003c/em\u003e=71) endorsing \u0026ldquo;never\u0026rdquo;. Accordingly, questions 1 and 2 were normally distributed, questions 3 and 4 were heavily positively skewed and question 5 was somewhat negatively skewed (with \u0026ldquo;somewhat\u0026rdquo; still being the modal answer).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDiagnostic Data.\u003c/strong\u003e Diagnostic data was not available for the headspace sample as the headspace service model of care does not include diagnostic assessment.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClients with Positive OCI-CV-5 Screener Scores (\u003cem\u003en\u003c/em\u003e=41)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDescriptive Data.\u0026nbsp;\u003c/strong\u003eOf 64 referrals to the OCD team, \u003cem\u003en\u003c/em\u003e=41 completed the OCI-CV-5. Total scores on OCI-CV-5 ranged from 3-10, with a bimodal distribution featuring peaks at 5 and 7 with 7 being the largest peak. The mean total score was 6.68 (\u003cem\u003eSD\u003c/em\u003e=1.96; Q1=5, Q2=7, Q3=8), and the modal total score was 7.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDiagnostic Data.\u0026nbsp;\u003c/strong\u003eOf the \u003cem\u003en\u003c/em\u003e=41 clients referred to the OCD speciality team who completed the OCI-CV-5, \u003cem\u003en\u003c/em\u003e=33 clients also completed an OCD diagnostic assessment using the ADIS-5 OCD module. There was a moderate, positive correlation between OCI-CV-5 total score and clinician severity rating (CSR; 0-8) on the ADIS,\u003cem\u003e\u0026nbsp;r\u003c/em\u003e=0.46,\u003cem\u003e\u0026nbsp;p\u003c/em\u003e = 0.007.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 4 shows descriptive data for clients who received a diagnosis , a sub-clinical diagnosis and no diagnosis. Comparing between the three diagnostic groups using the Kruskal-Wallis test, there was a significant difference between the groups on OCI-CV-5 score, H(2)=7.08, \u003cem\u003ep\u003c/em\u003e=0.029, with the diagnosis group ranking highest (20.91), followed by the subclinical group (16.00) and no diagnosis (9.50). Using an independent samples \u003cem\u003et\u003c/em\u003e-test to compare those who were diagnosed and those who were not (including sub-clinical; \u003cem\u003eM\u003c/em\u003e =5.82, \u003cem\u003eSD\u003c/em\u003e=1.85), there was a significant large difference on OCI-CV-5 scores,\u003cem\u003e\u0026nbsp;t\u003c/em\u003e(31)=-2.41, \u003cem\u003ep\u003c/em\u003e=0.022, \u003cem\u003ed\u003c/em\u003e=0.19.\u003c/p\u003e\n\u003cp\u003eFor the purpose of the ROC analysis, an additional \u003cem\u003en\u0026nbsp;\u003c/em\u003e= 2 clients were included in the sub-sample who had scores recorded on the OCI-CV-5 and who had a diagnosis of OCD confirmed through clinical interview outside of the OCD team, leading to a sub-sample of \u003cem\u003en\u003c/em\u003e=35. The ROC curve is shown in Figure 2. The area under the curve (AUC) was 0.74, which indicates the OCI-CV-5 had moderate discrimination and predictive power with a cut-off of 3. Based on distance to corner, 7.5 on the OCI-CV-5 would again be the optimal cut-off to maximise sensitivity (0.56) and specificity (0.12). The classification rates using a cut-off of 7 are shown in Table 5.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eOCD is often under-diagnosed or mis-diagnosed, with a substantial duration of untreated illness of over 2 years for children and adolescents [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. To reduce the duration of untreated illness, routine screening and clinician training have been recommended [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. As part of a broader implementation pilot of a Model of Care for paediatric OCD, the OCI-CV-5 was implemented as a routine screening measure, accompanied by clinician training, in six child and youth mental health services in one local health district in Sydney, Australia, to improve detection rates of OCD.\u003c/p\u003e\u003cp\u003eImplementing the OCI-CV-5 as a screening tool was often challenging\u0026mdash;screening completion rates varied from 40% to 80% across the three services reporting \u0026ldquo;consistent\u0026rdquo; implementation. Two out of six services completed the screener only when they wanted to refer onwards to the OCD team and one service did not implement the screener. Primary reasons for not screening were that clients declined to complete measures, client had an existing diagnosis of OCD, or the clinician did not feel it was appropriate to administer based on client risk/severity or presenting problem, especially when clinicians held concerns over the high false positive rate and low face validity of the measure. Further discussion of the challenges in implementing screening will be discussed in Dyason et al [in prep].\u003c/p\u003e\u003cp\u003eThe OCI-CV-5 demonstrated convergent validity with a moderate positive correlation between OCI-CV-5 scores and symptoms confirmed by structured clinical interview. Clients with a diagnosis of OCD scored higher on the OCI-CV-5 than those with subclinical symptoms, who in turn scored higher than those without a diagnosis. As expected, mean scores on the OCI-CV-5 were lowest for the primary care sample (headspace), higher for the CAMHS sample (tertiary care), and highest for the OCD team sample (quaternary care).\u003c/p\u003e\u003cp\u003eHowever, the OCI-CV-5\u0026rsquo;s construct validity was low-moderate as two items (questions 2 and 5) of the five in the OCI-CV-5 were endorsed by the majority of participants (diagnosed with OCD and not diagnosed). This suggest these items were not detecting OCD but perhaps overall distress or presence of any mental health condition, aligning with previous findings of higher correlation in anxiety and depression measures comparative to OCD measure [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. As such, clinicians frequently raised concerns over the face validity of these items [Dyason et al., in prep]. Item 4 (\u0026ldquo;I wash my hands more than other kids\u0026rdquo;) was the least commonly endorsed item in both samples, despite having high face validity for OCD (washing/cleaning compulsion). This item may be the most discriminatory question within the OCI-CV-5. With only moderate construct and face validity, the discriminant validity of the measure overall was relatively poor.\u003c/p\u003e\u003cp\u003eIn the original OCI-CV-5 development study [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e], the full 21-item OCI-CV was administered, and thus this is the first study to investigate the administration of only the 5-item measure. With the additional 16 items in the full measure, the OCI-CV has good face validity measuring many symptoms of OCD; however, without the additional items, some of the context of the measure is lost\u0026mdash;wording of the items was more ambiguous and could be interpreted as relating to symptoms of other disorders (e.g., intrusive thoughts in PTSD) [Dyason et al., in prep].\u003c/p\u003e\u003cp\u003eHowever, the OCI-CV-5\u0026rsquo;s sensitivity was high, detecting the majority of clients with OCD based on clinician diagnostic interview reports. However, 87% of clients screened in CAMHS and 79% of clients screened in Headspace screened positively and required further diagnostic assessments. This indicated the specificity and utility of the measure was low and suggests the OCI-CV-5\u0026rsquo;s current form, with a clinical cut-off of 3/10, is not suitable for use in public mental health services. The ROC analyses suggested a cut-off of 7/10 would maximise sensitivity and specificity across the CAMHS and OCD team samples. However, this may miss instances of sub-clinical or mild OCD.\u003c/p\u003e\u003cp\u003eWe could find no published data on OCD prevalence in CAMHS outpatient settings. Tentative extrapolation from the current study could inform future prospective research. Of CAMHS clients screened, 40\u0026ndash;80% screened positive. Of people referred for full diagnostic assessment, 11% were diagnosed with OCD, yielding an estimated prevalence of 4\u0026ndash;9% in this cohort. Despite multiple assumptions, this estimate is plausible. OCD prevalence in primary and state-based mental health service settings can reasonably be expected to be greater that in the general population, i.e., 2\u0026ndash;3% [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. In two CAMHS inpatient units, the prevalence of OCD was 9% [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], and so likely the true prevalence in a CAMHS mental health outpatient setting lies between the community prevalence and the inpatient prevalence.\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eLimitations\u003c/h2\u003e\u003cp\u003eAlthough the current study is high in ecological validity, demonstrating the real-world use of a measure in routine clinical settings, there were limited psychometric analyses possible with non-consecutive administration of the measure, inconsistent referrals for diagnostic assessments, only one convergent validity measure available, and no reliability analyses possible. While the OCI-CV-5 was developed for use in 7\u0026ndash;17 year old cohorts, it is worth noting that no children under 12 years old were represented in the data provided despite three of the six CAMHS offering services to this population. As such there was no validity data possible in the current sample for children aged 7\u0026ndash;11. Finally, referrals to the OCD team were inconsistent, yet this is not a reflection of the screener, but about integration of clinical services and perceived usefulness to clinicians and families of referrals from one service to another.\u003c/p\u003e\u003c/div\u003e"},{"header":"Conclusions and Future Directions","content":"\u003cp\u003eWith one of the longest durations of untreated illness of any psychiatric condition [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], there is a desperate need to increase detection of OCD [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Routine screening of OCD in healthcare settings is recommended [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], yet often not actioned. We trialled implementation of the OCI-CV-5 in six child and adolescent mental health service teams in real-world clinical settings where resources are limited and clinical complexity is high.\u003c/p\u003e\u003cp\u003eVarying consistent implementation rates of OCD screeners indicate there are significant barriers in implementing routine OCD screening within health care settings, despite the need and recommendation for accurate OCD detection through routine screening. Our pending paper will further explore these barriers.\u003c/p\u003e\u003cp\u003eAlarmingly despite the inconsistent implementation of OCD screening, our findings suggest the prevalence of OCD amongst public health child and adolescent health services may be higher than the general public but lower than inpatient units. This highlights not only the need for improvements on routine OCD screening but also the need for future studies to investigate and establish more accurate rates of OCD within public health child and adolescent health services.\u003c/p\u003e\u003cp\u003eThe OCI-CV-5\u0026rsquo;s poor face validity and specificity brings into question if the OCI-CV-5 in its current form with a clinical cut off of 3 is suitable as a screener in a public health setting in context where the clinical population often presents with complex presentations, comorbid conditions, and a high degree of risk. Future research should look to re-evaluate which items are included on the OCI-CV-5, swapping other items from the well-validated and commonly used longer format OCI-CV [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] to increase face validity and discriminant validity. Alternatively, other pre-existing OCD screening measures could be trialled, such as the Short Obsessive Compulsive Screener (SOCS;[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]) which was developed de novo for screening purposes, rather than being adapted from a longer measure. To effectively validate a screening measure in a routine clinical setting, it is recommended only the screening questions be administered so their stand-alone performance can be evaluated in the context for which it is designed to ensure fit-for-purpose.\u003c/p\u003e\u003cp\u003eIt is possible also that there are as-yet-unidentified alternatives, such as artificial intelligence analysis of written text provided by individuals and/or the use of algorithms to identify those at greatest risk for OCD. As the field continues to grow and our understanding of OCD increases, there is great potential to improve detection rates of OCD in routine clinical care, factoring in both clinical judgement and flexibility whilst also incorporating evidence-based recommendations to best meet clients\u0026rsquo; needs.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003ch2\u003eConflict of Interest:\u003c/h2\u003e\u003cp\u003eNeither the scholarship nor funding providers were involved in the: collection, analyses, and interpretation of data; writing; or submission process. L. J. Farrell is the author of the OCD Busters program and receives consultancy fees for the delivery of training and supervision in relation to these materials. She receives royalties from Cambridge University Press, Elsevier, and Springer for published works and ongoing editorial work. The authors declare they have no other conflicts of interest.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003cp\u003eNeither the scholarship nor funding providers were involved in the: collection, analyses, and interpretation of data; writing; or submission process. L. J. Farrell is the author of the OCD Busters program and receives consultancy fees for the delivery of training and supervision in relation to these materials. She receives royalties from Cambridge University Press, Elsevier, and Springer for published works and ongoing editorial work. The authors declare they have no other conflicts of interest.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eKD was responsible for conceptualisation, methodology, formal analysis, investigation, data curation, writing (original draft), writing (review and editing), visualisation, and project administration.S.W was responsible for investigation and writing (review and editing).P.P was responsible for investigation and writing - (review and editing).J.G was responsible for conceptualisation, methodology, writing - (review and editing), supervision, and fund acquisition.L.F was responsible for conceptualisation, methodology, resources, writing - (review and editing), supervision, and fund acquisition.T.B, B.T, T.D, and R.L were responsible for investigation, resources, and writing (reviewing).C.G and K.K were responsible for conceptualisation, resources, supervision, fund acquisition.I.P was responsible for conceptualisation, methodology, investigations, writing - (review and editing), visualisation, supervision, and fund acquisition.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eWe would like to thank the clinicians and other members of the working group and steering committee for contributing their time and experiences, particularly, Caitlin Dixon, Antonia Ottavio, and Belinda Middleton. This work was supported the Sydney Children\u0026rsquo;s Hospitals Foundation and Mindgardens Neuroscience Network (funded by the Australian Government Department of Health and Aged Care).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eGeller DA (2006) Obsessive-compulsive and spectrum disorders in children and adolescents. Psychiatr Clin North Am 29:353\u0026ndash;370. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.psc.2006.02.012\u003c/span\u003e\u003cspan address=\"10.1016/j.psc.2006.02.012\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGeller DA, Homayoun S, Johnson G (2021) Developmental Considerations in Obsessive Compulsive Disorder: Comparing Pediatric and Adult-Onset Cases. 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Psychiatric Serv (Washington D C) 72(7):784\u0026ndash;793. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1176/appi.ps.202000296\u003c/span\u003e\u003cspan address=\"10.1176/appi.ps.202000296\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMcKay D, Abramowitz JS, Storch EA (2021) Mechanisms of harmful treatments for obsessive\u0026ndash;compulsive disorder. Clin Psychol Sci Pract 28(1):52\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAdam, G. P., Caputo, E. L., Kanaan, G., Freeman, J. B., Brannan, E. H., Balk, E. M.,\u0026hellip; Steele, D. W. (2025). Brief Assessment Tools for Obsessive-Compulsive Disorders in Children: A Systematic Review. Pediatrics, 155(3)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFoa EB, Coles M, Huppert JD, Pasupuleti RV, Franklin ME, March J (2010) Development and validation of a child version of the obsessive compulsive inventory. Behav Ther 41(1):121\u0026ndash;132. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.beth.2009.02.001\u003c/span\u003e\u003cspan address=\"10.1016/j.beth.2009.02.001\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAbramovitch A, Abramowitz JS, McKay D, Cham H, Anderson KS, Farrell LJ, Geller DA, Hanna GL, Mathieu S, McGuire JF, Rosenberg DR, Stewart SE, Storch EA, Wilhelm S (2022) An ultra-brief screening scale for pediatric obsessive-compulsive disorder: The OCI-CV-5. J Affect Disord 312:208\u0026ndash;216. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.jad.2022.06.009\u003c/span\u003e\u003cspan address=\"10.1016/j.jad.2022.06.009\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePerkes I, Grisham J, Farrell L, Dyason KM, Racz J (2022) OCD BOUNCE: A Model of Care for Paediatric OCD. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.17605/OSF.IO/HVTR2\u003c/span\u003e\u003cspan address=\"10.17605/OSF.IO/HVTR2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKerns CM, Silverman WK (2024) and Anne Marie Albano, 'Anxiety and Related Disorders Interview Schedule for DSM-5, Child and Parent Version: Autism Spectrum Addendum (ADIS/ASA)', \u003cem\u003eAnxiety and Related Disorders Interview Schedule for DSM-5, Child and Parent Version: Clinician Manual\u003c/em\u003e (New York, ; online edn, Oxford Academic, 1 Mar. 2024). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/med-psych/9780199348343.003.0002\u003c/span\u003e\u003cspan address=\"10.1093/med-psych/9780199348343.003.0002\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAmerican Psychiatric Association (2013) Diagnostic and statistical manual of mental disorders, 5th edn. American Psychiatric Association. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1176/appi.books.9780890425596\u003c/span\u003e\u003cspan address=\"10.1176/appi.books.9780890425596\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLyneham HJ, Abbott MJ, Rapee RM (2007) Interrater reliability of the anxiety disorders interview schedule for DSM-IV: Child and parent version. J Am Acad Child Adolesc Psychiatry 46(6):731\u0026ndash;736\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSilverman WK, Saavedra LM, Pina AA (2001) Test-retest reliability of anxiety symptoms and diagnoses with the Anxiety Disorders Interview Schedule for DSM-IV: child and parent versions. J Am Acad Child Adolesc Psychiatry 40(8):937\u0026ndash;944\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGreenberg EL, Geller DA (2019) Phenomenology and standard care of OCD in children and adolescents. In: Farrell LJ, Ollendick TH, Muris P (eds) Innovations in CBT for childhood anxiety, OCD and PTSD. Cambridge University Press, pp 289\u0026ndash;312\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eUher R, Heyman I, Mortimore C, Frampton I, Goodman R (2007) Screening young people for obsessive compulsive disorder. Br J Psychiatry 191:353\u0026ndash;354. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1192/bjp.bp.106.034967\u003c/span\u003e\u003cspan address=\"10.1192/bjp.bp.106.034967\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1 to 5 are available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Obsessive-compulsive disorder, routine screening, mental health, public mental health services, child and adolescent mental health services, psychometrics","lastPublishedDoi":"10.21203/rs.3.rs-7901842/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7901842/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eObsessive Compulsive Disorder (OCD) is a debilitating disorder affecting 2\u0026ndash;3% of children and adolescents. Despite availability of effective treatments, diagnosis is often delayed. We investigated the implementation of routine OCD screening in public mental health services for children and young people.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eSix public health service teams and their clients were invited to participate. Three services consecutively implemented the Obsessive-compulsive Inventory-Child Version-5 (OCI-CV-5) screener. Clients with positive OCI-CV-5 scores were offered referral to a specialised OCD team for assessing diagnostic caseness using the Anxiety Disorders Interview Schedule-5 (ADIS-5) including clinical severity scores. Receiver Operating Characteristic (ROC) analysis on the confirmed OCD diagnosis group to re-examine the sensitivity and specificity of the OCDI-CV-5.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eDespite variable implementation across services, the OCI-CV-5 showed moderate, positive correlation with ADIS-5 clinician severity ratings \u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.46, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.007. Significant differences among the diagnostic groups were found on OCI-CV-5 score, H(2)\u0026thinsp;=\u0026thinsp;7.08, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.029, with the diagnosis group ranking highest (20.91), the subclinical group (16.00) and no diagnosis group (9.50). An ROC analysis demonstrated raising the OCI-CV-5 cut-off from 3 to 7 would improve sensitivity (0.56) and specificity (0.12).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003ePaediatric OCD detection in public health services remains an important challenge. Future research should evaluate screening measures, including the OCI-CV-5, across settings.\u003c/p\u003e","manuscriptTitle":"Routine screening for obsessive-compulsive disorder in child and youth mental health services using the Obsessive-compulsive Inventory-Child Version-5 (OCI-CV-5)","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-11 17:22:24","doi":"10.21203/rs.3.rs-7901842/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f65ebc8c-746b-4e79-b74b-5c147a048f98","owner":[],"postedDate":"November 11th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-01-24T17:54:32+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-11 17:22:24","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7901842","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7901842","identity":"rs-7901842","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}