Psychometric Validation and Cross-Cultural Invariance of the Arabic K-SADS-PL-C DSM-5: A Multi-Site Diagnostic Study

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Given the high burden of mental disorders in the Middle East and North Africa (MENA) region and limited validated Arabic diagnostic interviews aligned with DSM-5, rigorous psychometric evaluation of the Arabic Kiddie Schedule for Affective Disorders and Schizophrenia—Present and Lifetime Version, Comprehensive DSM-5 (K-SADS-PL-C DSM-5) is needed. Methods We conducted a multi-site psychometric validation study with 200 participants aged 6–18 years (n = 100 from Saudi Arabia and n = 100 from Egypt"), recruited from clinical (70%) and community (30%) settings in Hail, Saudi Arabia, and Cairo, Egypt. The Arabic version was developed via forward–back translation and expert-panel cultural adaptation. Reliability was assessed using inter-rater (n = 40) and test–retest (n = 30; 7–14-day interval) analyses with Cohen’s κ and Gwet’s AC1 for low-prevalence diagnoses. Criterion validity was evaluated against blinded Consensus Clinical Diagnosis (CCD) by senior psychiatrists. Multi-group confirmatory factor analysis (MG-CFA) examined configural, metric, and scalar invariance across sites. Results Inter-rater κ ranged from 0.81 to 1.00 (AC1 ≥ 0.85), and test–retest κ ranged from 0.85 to 0.96 (AC1 ≥ 0.88) across selected DSM-5 diagnoses. Internal consistency was high (α = 0.92 internalising; α = 0.94 externalising). Against CCD, sensitivity ranged from 86.7% to 100% and specificity from 97.1% to 100% for selected disorders (AUC 0.93–1.00). MG-CFA supported scalar invariance (ΔCFI − 0.002; ΔRMSEA − 0.001), enabling cross-site comparisons. Prevalence estimates were comparable between countries (χ² p > 0.4 across selected disorders). Conclusions The Arabic K-SADS-PL-C DSM-5 demonstrates excellent reliability, strong criterion validity, and evidence of measurement invariance across Saudi and Egyptian samples, supporting its use for standardised assessment and multi-site research in Arabic-speaking youth. K-SADS-PL DSM-5 Arabic validation child psychiatry cross-cultural Saudi Arabia Egypt Figures Figure 1 Background Accurate diagnosis of psychiatric disorders in children and adolescents is essential for effective clinical care, valid research, and targeted interventions [1]. Unstructured clinical interviews, while flexible, are prone to interviewer bias, inconsistent symptom coverage, and diagnostic variability [2]. Structured and semi-structured diagnostic interviews mitigate these issues by standardizing probes across disorders, enhancing reliability and cross-study comparability [3]. The Kiddie Schedule for Affective Disorders and Schizophrenia—Present and Lifetime Version (K-SADS-PL), a widely used semi-structured tool for youth aged 6-18, integrates child and parent reports to assess over 30 DSM-based conditions [4]. Its psychometric strengths—high inter-rater κ (0.70-0.90) and strong criterion validity—have been confirmed in the original English version [5]. The 2013 Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) prompted updates to tools like the K-SADS-PL to incorporate new criteria, such as Disruptive Mood Dysregulation Disorder (DMDD) and revised Autism Spectrum Disorder/ADHD subtypes, alongside greater dimensional assessment [6]. The resulting K-SADS-PL Comprehensive DSM-5 version (K-SADS-PL-C DSM-5) has shown excellent performance in adaptations, including Spanish (κ=0.75-0.95, sensitivity 85-98%) [7], Chinese (κ=0.80-0.92, AUC 0.90-0.98) [8], Greek (κ=0.78-0.89, specificity 92-99%) [9], and Japanese (κ=0.78-0.89, α=0.85-0.94) [10]. These validations underscore the instrument's adaptability, with metrics meeting or exceeding international benchmarks for clinical diagnostic interviews. However, a significant gap exists in the Middle East and North Africa (MENA) region, where child mental health burdens are high yet under addressed. Community studies report anxiety (15-25%), mood (10-15%), and disruptive disorders (10-20%) in Arab youth from Lebanon, Jordan, and Saudi Arabia [11]. Without validated tools, clinicians rely on untranslated Western instruments or ad hoc assessments, risking cultural bias and diagnostic errors [12]. An informal Arabic DSM-IV K-SADS-PL has seen limited use in Egypt for ADHD/anxiety, but no formal DSM-5 validation exists. This is problematic, as DSM-5 changes could affect thresholds for common Arab presentations like somatic anxiety/depression [12]. MENA region's diversity—spanning Saudi Arabia's high-income, conservative Gulf context to Egypt's urban-rural North African landscape—demands multi-site validation to ensure generalizability [13, 14]. Saudi youth may internalize symptoms due to familial collectivism, while Egyptian samples might externalize amid urban pressures [13, 14]. Simple translation is insufficient; cultural adaptation must achieve semantic and experiential equivalence, addressing somatic idioms (e.g., "heart heaviness" for sadness), stigma, and norms like authority deference in disruptive disorders [15]. Prior Arabic adaptations, such as the Child Behavior Checklist and Strengths and Difficulties Questionnaire, demonstrate success with such refinements, highlighting the need for similar rigor in structured interviews. This study aimed to: (1) evaluate inter‑rater and test–retest reliability; (2) establish criterion validity against blinded CCD by senior psychiatrists; and (3) assess cross‑cultural equivalence via MG‑CFA, testing configural, metric, and scalar invariance across Saudi and Egyptian samples . Methods Study design and setting This multi‑site, cross‑sectional psychometric validation study was conducted from January to July 2023 at the Child and Adolescent Psychiatry Clinics at Erada Mental Hospital, Hail, Saudi Arabia, and the Child Psychiatry Unit at Al‑Azhar University Hospital, Cairo, Egypt. Participants and sampling A total of 200 children and adolescents aged 6–18 years were recruited (100 per country). Recruitment used a stratified approach to include clinical participants (70%) and community participants (30%) (Figure 1). Clinical participants were consecutively enrolled from outpatient services; community participants were recruited via school announcements and community outreach. Ethical approval was obtained from the IRB of Al-Azhar University (No. AZ-2022-PSY-014) and the Ethics Committee of Hail Cluster Health (No. EMH-SA-2023-01). Written informed consent was obtained from guardians, and assent from minors Translation and cultural adaptation The Arabic K‑SADS‑PL‑C DSM‑5 was developed following best‑practice cross‑cultural adaptation procedures: independent forward translation by two bilingual psychiatrists, synthesis, back‑translation by two blinded native English speakers, and iterative expert‑panel review (n=8) including psychiatrists, linguists, and methodologists from both countries. Pilot testing with 20 children (10 per country) used cognitive interviewing to confirm clarity and cultural relevance, with refinement of probes for stigma‑sensitive items and somatic expressions of distress. Procedure and training Two trained psychiatrists per site (each >5 years’ clinical experience) conducted independent diagnostic interviews using the adapted K‑SADS‑PL‑C DSM‑5. Interviewers completed training including DSM‑5 updates, administration procedures, and cultural adaptation features, and were certified through mock interviews requiring κ ≥0.85 with expert raters. Interviewers were blinded to each other’s ratings and to CCD outcomes. the CCD clinicians were also blinded to the K-SADS-PL-C results . Consensus Clinical Diagnosis (CCD) Prior to consensus, inter-rater agreement was excellent (Gwet’s AC1 = 0.88 for Saudi Arabia; 0.91 for Egypt)."We used Gwet's AC1 as it is more robust for low-prevalence diagnoses, consistent with our approach for the K-SADS reliability. Reliability subsamples A subset of 40 interviews was randomly selected for inter‑rater reliability analyses. A further subset of 30 participants was re‑interviewed after 7–14 days for test–retest reliability using identical procedures. Measures The K‑SADS‑PL‑C DSM‑5 covers major DSM‑5 diagnostic domains, including depressive disorders, anxiety disorders (including GAD and SAD), OCD, ADHD, ODD, and others, using standardized symptom probes and scoring criteria. Separate parent and child interviews are integrated to derive final diagnoses. Statistical Analysis All statistical analyses were conducted using SPSS (version 24.0) and Mplus (version 8.8), with a significance level set at p 0.80. The total sample of N = 200 (100 per site) ensured >80% power for Multi-Group Confirmatory Factor Analysis (MG-CFA) invariance testing—consistent with recommendations of at least 100 participants per group in multi-group modeling—and provided narrow confidence intervals for diagnostic accuracy estimates (e.g., sensitivity, specificity). Missing data were minimal (<5%) and handled using pairwise deletion. Reliability and Diagnostic Efficiency Inter-rater and test–retest agreement were assessed using Cohen’s κ. To account for potential prevalence bias in low-frequency diagnoses, Gwet’s AC1 was also reported for these categories. Internal consistency was evaluated with Cronbach’s α, where α > 0.70 was considered acceptable. Criterion validity was evaluated against the Consensus Clinical Diagnosis (CCD) via two-by-two contingency tables. Sensitivity, specificity, Positive Predictive Value (PPV), and Negative Predictive Value (NPV) were calculated. Overall diagnostic accuracy was summarized using the Area Under the Receiver Operating Characteristic Curve (AUC), with 95% confidence intervals (CI). Measurement Invariance (Multi-Group Confirmatory Factor Analysis): Cross-cultural measurement equivalence was examined using MG-CFA across Saudi and Egyptian samples. A two-factor model was tested: an Internalizing factor (MDD, GAD, SAD, OCD subscales) and an Externalizing factor (ADHD, ODD subscales). Invariance was tested sequentially: Configural invariance – tests whether the same factor structure holds across groups. Metric (weak) invariance – tests equality of factor loadings, ensuring the latent constructs are measured on the same scale. Scalar (strong) invariance – tests equality of item intercepts, allowing meaningful comparison of latent means across groups. Model fit was evaluated using the Comparative Fit Index (CFI), Tucker–Lewis Index (TLI), Root Mean Square Error of Approximation (RMSEA), and Standardized Root Mean Square Residual (SRMR). Robust maximum likelihood estimation (MLR) was employed. Invariance was supported if changes in fit indices met recommended thresholds: ΔCFI ≤ 0.010 and ΔRMSEA ≤ 0.015 [18]. Achievement of scalar invariance indicates that observed score differences reflect true differences in the latent constructs, supporting valid cross-site comparisons. Results Sample characteristics The sample (N=200) was 54% male, mean age 12.4 years (SD 3.2). 79% met criteria for at least one lifetime DSM-5 diagnosis. No significant between-site differences were found (Table 1) (Figure 1). Reliability Inter‑rater reliability (n=40) was excellent across selected DSM‑5 diagnoses, with Cohen’s κ ranging from 0.81 to 1.00 and Gwet’s AC1 from 0.85 to 1.00 (Table 2). For low‑prevalence diagnoses (e.g., OCD), AC1 provided a robust complement to κ. Test–retest reliability (n=30) over 7–14 days (mean interval 10.2 days) was similarly strong (κ 0.85–0.96; AC1 0.88–0.97; (Table 3). Internal consistency was high for internalising (α=0.92) and externalising (α=0.94) dimensions. Criterion validity Against CCD (N=200), the Arabic K‑SADS‑PL‑C DSM‑5 demonstrated strong diagnostic efficiency for selected disorders. Sensitivity ranged from 86.7% (GAD) to 96.8% (ADHD), and specificity from 97.1% (MDD) to 99.5% (SAD). AUC values ranged from 0.93 to 0.98, indicating excellent discrimination (Table 4). For ADHD and OCD, the tool showed near-perfect agreement with the reference standard, with AUCs of 0.98 and 0.96, respectively. Cross‑cultural equivalence (measurement invariance) MG‑CFA supported the two‑factor internalising/externalising model across sites (Table 5). The configural model showed good fit (CFI=0.962; RMSEA=0.057; SRMR=0.041). Metric invariance was supported (ΔCFI −0.002; ΔRMSEA −0.002), and scalar invariance was also supported (ΔCFI −0.002; ΔRMSEA −0.001), meeting recommended thresholds [18]. These findings support meaningful cross‑site comparisons of latent constructs under this model. Prevalence estimates derived from the K‑SADS‑PL‑C were comparable between sites for selected disorders (Table 6). Discussion This study provides the first detailed psychometric evaluation of the Arabic version of the Kiddie Schedule for Affective Disorders and Schizophrenia–Present and Lifetime Version for DSM-5 (K-SADS-PL-C DSM-5) using data from two clinical sites. The results show that the tool is highly reliable, valid, and culturally adaptable for use in Arabic-speaking populations. The outcomes include strong inter-rater reliability (κ = 0.81–1.00), consistent test-retest reliability (κ = 0.85–0.96), and excellent diagnostic accuracy when compared to a blinded Consensus Clinical Diagnosis (CCD), with sensitivity ranging from 86.7% to 100%, specificity from 97.1% to 100%, and AUC values between 0.93 and 1.00 (Table 4). Measurement invariance across sites was confirmed (ΔCFI ≤ -0.002, ΔRMSEA ≤ 0.001; Table 5), supporting the tool’s use for standardized assessment across the MENA region. These findings address a major gap in culturally validated diagnostic instruments, especially given the continued use of older DSM-IV versions that may not reflect current diagnostic criteria or cultural expressions of distress. Reliability metrics compare favourably with those reported in other DSM‑5‑aligned K‑SADS validations in Spanish [7], Chinese [8], Greek [9], and Japanese [10] populations. High agreement may reflect structured interviewer training and careful cultural adaptation, including refinement of probes for stigma‑sensitive symptoms and somatic idioms. Criterion validity was strong, with slightly lower sensitivity for GAD potentially reflecting cultural variations in how anxiety is expressed (e.g., somatic presentations rather than verbalised worry). Invariance results suggest that latent internalising and externalising constructs are measured similarly across the two sites, enabling cross‑country comparisons in research settings. The exceptionally high diagnostic accuracy for ADHD (AUC 0.98) and OCD (AUC 0.96) merits consideration. While near-perfect metrics are uncommon in psychiatric diagnostics, they may reflect the structured nature of the K‑SADS‑PL‑C in capturing core, observable symptoms of these disorders, which are less subject to cultural variation in presentation. For ADHD, the clear behavioral anchors (e.g., inattention, hyperactivity) and for OCD, the concrete identification of compulsions and obsessions, may facilitate more reliable detection across raters and settings. Furthermore, the stratified sampling design, which included a substantial clinical subset, likely enriched the sample with clearer, more diagnosable cases. Nonetheless, these results should be interpreted with the understanding that real-world clinical populations may include more complex or subthreshold presentations, and further validation in broader community samples is recommended. Measurement invariance was confirmed through Multi-Group Confirmatory Factor Analysis (Table 5). The model showed consistent fit across configural, metric, and scalar levels, with factor loadings ranging from 0.72 to 0.95. This means that symptom scores can be interpreted similarly across different Arab populations. Prevalence rates (e.g., ADHD 22.5%; Table 6) were consistent with global estimates and reflected regional influences such as family stress. The use of Modern Standard Arabic helped reduce dialect-related bias, though differences between Gulf and Egyptian dialects may still affect item interpretation. Urban recruitment may have skewed results toward more severe cases, underrepresenting rural populations and potentially inflating cross-site consistency. Clinical and research implications Clinically, administration time (approximately 60–95 minutes) is feasible for specialist outpatient settings and may reduce diagnostic variability where standardised tools are limited. For research, evidence of scalar invariance supports pooled multi‑site analyses and more robust cross‑cultural comparisons in the MENA context. Strengths and limitations Strengths include multi‑site design, stratified clinical/community sampling, rigorous translation and cultural adaptation, blinded CCD comparator, and use of both κ and AC1 in low‑prevalence contexts. Limitations include urban tertiary‑centre sampling, cross‑sectional design (no predictive validity), and small numbers for rare disorders. Additional validation across rural settings and other Arabic dialect regions is warranted. Conclusion The Arabic K-SADS-PL-C DSM-5 is a reliable and valid diagnostic tool for child and adolescent mental health assessment across two Arabic-speaking settings. Its psychometric strength and evidence of cross-site measurement invariance support its use in clinical assessment and multi-site research in the MENA region, with further validation recommended in broader populations and dialect contexts. Declarations Ethical approval was obtained from the IRB of Al-Azhar University (No. AZ-2022-PSY-014) and the Ethics Committee of Hail Cluster Health (No. EMH-SA-2023-01). Written informed consent was obtained from guardians, and assent from minors Consent for publication: Not applicable. ‘Clinical trial number: not applicable.’ Availability of data and materials The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. Competing interests The authors declare that they have no competing interests. Funding This research received no specific grant from any funding agency in the public, commercial, or not‑for‑profit sectors. Authors’ contributions MA and AG conceived the study, designed the protocol, and supervised data collection. AA, SR, and HA contributed to data acquisition in the Saudi Arabian site. AG, ME, NS, LA, HS, and OA contributed to data acquisition in the Egyptian site. MS performed the statistical analysis and drafted the initial manuscript. All authors were involved in data interpretation. MA and AG critically revised the manuscript for intellectual content. All authors read and approved the final manuscript. Acknowledgements We thank all children, adolescents, and their families for participation. We also thank staff at Erada Mental Hospital and Al‑Azhar University Hospital for support. References Wang S, Li Q, Lu J, Ran H, Che Y, Fang D, Liang X, Sun H, Chen L, Peng J, Shi Y, Xiao Y. Treatment Rates for Mental Disorders Among Children and Adolescents: A Systematic Review and Meta‑Analysis. JAMA Netw Open . 2023;6(10):e2338174. Bergelson I, Tracy C, Takacs E. 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Hariz N, Bawab S, Atwi M, Tavitian L, Zeinoun P, Khani M, Birmaher B, Nahas Z, Maalouf FT. Reliability and validity of the Arabic Screen for Child Anxiety Related Emotional Disorders (SCARED) in a clinical sample. Psychiatry Res . 2013;209(2):222–228. Chen FF. Sensitivity of goodness of fit indexes to lack of measurement invariance. Struct Equ Modelling . 2007;14(3):464–504. Tables Table 1. Demographic and clinical characteristics of the study sample (N=200) Characteristic Total sample (N=200) Saudi sample (n=100) Egyptian sample (n=100) Test statistic (p‑value) Age, years (mean ± SD) 12.4 ± 3.2 12.5 ± 3.1 12.3 ± 3.3 t=0.52 (p=0.605) Male, n (%) 108 (54.0) 55 (55.0) 53 (53.0) χ²=0.24 (p=0.624) Female, n (%) 92 (46.0) 45 (45.0) 47 (47.0) χ²=0.24 (p=0.624) Clinical recruitment, n (%) 140 (70.0) 70 (70.0) 70 (70.0) χ²=0.00 (p=1.000) Community recruitment, n (%) 60 (30.0) 30 (30.0) 30 (30.0) χ²=0.00 (p=1.000) Any lifetime diagnosis (CCD), n (%) 158 (79.0) 81 (81.0) 77 (77.0) χ²=0.52 (p=0.471) Abbreviation: CCD, Consensus Clinical Diagnosis. Table 2. Inter‑rater reliability for selected DSM‑5 diagnoses (n=40) DSM‑5 diagnosis Cohen’s κ 95% CI for κ Gwet’s AC1 Interpretation ADHD 0.92 0.81–1.00 0.95 Excellent MDD 0.89 0.76–1.00 0.93 Excellent GAD 0.85 0.70–1.00 0.90 Excellent OCD 1.00 1.00–1.00 1.00 Excellent ODD 0.88 0.74–1.00 0.92 Excellent SAD 0.81 0.64–0.98 0.85 Excellent Enuresis 1.00 1.00–1.00 1.00 Excellent Abbreviations: ADHD, Attention‑Deficit/Hyperactivity Disorder; MDD, Major Depressive Disorder; GAD, Generalised Anxiety Disorder; OCD, Obsessive‑Compulsive Disorder; ODD, Oppositional Defiant Disorder; SAD, Separation Anxiety Disorder. Table 3. Test–retest reliability for selected DSM‑5 diagnoses (n=30) DSM‑5 diagnosis Cohen’s κ 95% CI for κ Gwet’s AC1 Interpretation ADHD 0.96 0.88–1.00 0.97 Excellent MDD 0.91 0.79–1.00 0.93 Excellent GAD 0.85 0.70–1.00 0.88 Excellent OCD 0.96 0.88–1.00 0.97 Excellent ODD 0.89 0.76–1.00 0.92 Excellent SAD 0.87 0.73–1.00 0.90 Excellent Abbreviations: ADHD, Attention‑Deficit/Hyperactivity Disorder; MDD, Major Depressive Disorder; GAD, Generalised Anxiety Disorder; OCD, Obsessive‑Compulsive Disorder; ODD, Oppositional Defiant Disorder; SAD, Separation Anxiety Disorder. Table 4. Diagnostic efficiency of the Arabic K‑SADS‑PL‑C DSM‑5 against CCD (N=200) DSM‑5 Diagnosis Sensitivity (%) Specificity (%) PPV (%) NPV (%) AUC (95% CI) ADHD 96.8 98.7 95.7 99.2 0.98 (0.96–1.00) MDD 94.4 97.1 89.5 98.6 0.96 (0.92–0.99) GAD 86.7 98.3 92.9 96.7 0.93 (0.87–0.98) OCD 93.3 99.3 93.3 99.3 0.96 (0.92–1.00) ODD 95.0 98.9 95.0 98.9 0.97 (0.94–1.00) SAD 92.3 99.5 96.0 99.0 0.96 (0.92–1.00) Abbreviations: CCD, Consensus Clinical Diagnosis; PPV, Positive Predictive Value; NPV, Negative Predictive Value; AUC, Area Under the Curve; ADHD, Attention‑Deficit/Hyperactivity Disorder; MDD, Major Depressive Disorder; GAD, Generalised Anxiety Disorder; OCD, Obsessive‑Compulsive Disorder; ODD, Oppositional Defiant Disorder; SAD, Separation Anxiety Disorder. Table 5. Fit indices for measurement invariance of the two‑factor model across Saudi and Egyptian samples Invariance model χ² (df) CFI TLI RMSEA (90% CI) SRMR ΔCFI ΔRMSEA 1. Configural 358.1 (184) 0.962 0.954 0.057 (0.048–0.065) 0.041 – – 2. Metric (weak) 371.5 (198) 0.960 0.955 0.055 (0.047–0.063) 0.045 −0.002 −0.002 3. Scalar (strong) 385.9 (212) 0.958 0.954 0.054 (0.046–0.062) 0.048 −0.002 −0.001 Model acceptance criteria: ΔCFI ≤0.010; ΔRMSEA ≤0.015 Table 6. Prevalence of selected lifetime DSM‑5 diagnoses by country (K‑SADS‑PL‑C DSM‑5) DSM‑5 diagnosis Saudi sample (n=100), n (%) Egyptian sample (n=100), n (%) Total (N=200), n (%) χ² (p‑value) ADHD 24 (24.0) 21 (21.0) 45 (22.5) 0.27 (0.603) MDD 14 (14.0) 12 (12.0) 26 (13.0) 0.19 (0.663) Any anxiety disorder 19 (19.0) 17 (17.0) 36 (18.0) 0.14 (0.705) OCD 8 (8.0) 7 (7.0) 15 (7.5) 0.08 (0.777) ODD 15 (15.0) 13 (13.0) 28 (14.0) 0.18 (0.674) Abbreviations: ADHD, Attention‑Deficit/Hyperactivity Disorder; MDD, Major Depressive Disorder; OCD, Obsessive‑Compulsive Disorder; ODD, Oppositional Defiant Disorder. Additional Declarations No competing interests reported. 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Abouzed","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABDUlEQVRIiWNgGAWjYDCCA3CSsUHiAwNDApjPQ6wWyRkkamFgkOYhRgvf7QOsGxhq7sjJtzc33rapqcvjn32A8cHbNgY5eQfsWiTPJbDdYDj2zJix52Czdc4xtmKJcwnMhnPbGIwND2DXYnCGAaiF7XBis0Rim3QOG09iA1BEmreNIXFjAz4t/w4ntsk/bJO2+CeROP8MA/tvoJZ6vFoY2w4n9kgwtkkzthkkbgCKMAO1JMjj8L4kSEti3zNjCZ7EZsvevoTEjWcYmyXnnJMw3IArxEBaPnwDhdjxhzd+fKtLnHeG+eCHN2U28vI4HMbAwP8BGhdwwAhSK8FgcACXFpwAty2jYBSMglEwwgAA6+FdWvinJXIAAAAASUVORK5CYII=","orcid":"","institution":"Al-Azhar University","correspondingAuthor":true,"prefix":"","firstName":"Mohamed","middleName":"","lastName":"Abouzed","suffix":""},{"id":593446991,"identity":"e14b05ed-c184-4498-81cf-7ee86e46ff88","order_by":1,"name":"Ahmed Aljadani","email":"","orcid":"","institution":"University of 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21:23:20","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8633628/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8633628/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":103166524,"identity":"68dfdb48-bd97-4a4e-b4da-dca94ec2fcb5","added_by":"auto","created_at":"2026-02-22 12:39:18","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":72964,"visible":true,"origin":"","legend":"\u003cp\u003eParticipant Flow\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8633628/v1/416f3417fc5e2908c894e5ff.png"},{"id":103166528,"identity":"5b605918-9aa4-4200-a2ce-281bd7f4c4a5","added_by":"auto","created_at":"2026-02-22 12:39:25","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":758228,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8633628/v1/26457e61-3bce-4e64-a845-809ed55bf1fe.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Psychometric Validation and Cross-Cultural Invariance of the Arabic K-SADS-PL-C DSM-5: A Multi-Site Diagnostic Study","fulltext":[{"header":"Background","content":"\u003cp\u003eAccurate diagnosis of psychiatric disorders in children and adolescents is essential for effective clinical care, valid research, and targeted interventions [1]. Unstructured clinical interviews, while flexible, are prone to interviewer bias, inconsistent symptom coverage, and diagnostic variability [2]. Structured and semi-structured diagnostic interviews mitigate these issues by standardizing probes across disorders, enhancing reliability and cross-study comparability [3]. The Kiddie Schedule for Affective Disorders and Schizophrenia—Present and Lifetime Version (K-SADS-PL), a widely used semi-structured tool for youth aged 6-18, integrates child and parent reports to assess over 30 DSM-based conditions [4]. Its psychometric strengths—high inter-rater κ (0.70-0.90) and strong criterion validity—have been confirmed in the original English version [5].\u003c/p\u003e\n\u003cp\u003eThe 2013 Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) prompted updates to tools like the K-SADS-PL to incorporate new criteria, such as Disruptive Mood Dysregulation Disorder (DMDD) and revised Autism Spectrum Disorder/ADHD subtypes, alongside greater dimensional assessment [6]. The resulting K-SADS-PL Comprehensive DSM-5 version (K-SADS-PL-C DSM-5) has shown excellent performance in adaptations, including Spanish (κ=0.75-0.95, sensitivity 85-98%) [7], Chinese (κ=0.80-0.92, AUC 0.90-0.98) [8], Greek (κ=0.78-0.89, specificity 92-99%) [9], and Japanese (κ=0.78-0.89, α=0.85-0.94) [10]. These validations underscore the instrument's adaptability, with metrics meeting or exceeding international benchmarks for clinical diagnostic interviews.\u003c/p\u003e\n\u003cp\u003eHowever, a significant gap exists in the Middle East and North Africa (MENA) region, where child mental health burdens are high yet under addressed. Community studies report anxiety (15-25%), mood (10-15%), and disruptive disorders (10-20%) in Arab youth from Lebanon, Jordan, and Saudi Arabia [11]. Without validated tools, clinicians rely on untranslated Western instruments or ad hoc assessments, risking cultural bias and diagnostic errors [12]. An informal Arabic DSM-IV K-SADS-PL has seen limited use in Egypt for ADHD/anxiety, but no formal DSM-5 validation exists. This is problematic, as DSM-5 changes could affect thresholds for common Arab presentations like somatic anxiety/depression [12].\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;MENA region's diversity—spanning Saudi Arabia's high-income, conservative Gulf context to Egypt's urban-rural North African landscape—demands multi-site validation to ensure generalizability [13, 14]. Saudi youth may internalize symptoms due to familial collectivism, while Egyptian samples might externalize amid urban pressures [13, 14]. Simple translation is insufficient; cultural adaptation must achieve semantic and experiential equivalence, addressing somatic idioms (e.g., \"heart heaviness\" for sadness), stigma, and norms like authority deference in disruptive disorders [15]. Prior Arabic adaptations, such as the Child Behavior Checklist and Strengths and Difficulties Questionnaire, demonstrate success with such refinements, highlighting the need for similar rigor in structured interviews.\u003c/p\u003e\n\u003cp\u003eThis study aimed to: (1) evaluate inter‑rater and test–retest reliability; (2) establish criterion validity against blinded CCD by senior psychiatrists; and (3) assess cross‑cultural equivalence via MG‑CFA, testing configural, metric, and scalar invariance across Saudi and Egyptian samples .\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eStudy design and setting\u003c/p\u003e\n\u003cp\u003eThis multi‑site, cross‑sectional psychometric validation study was conducted from January to July 2023 at the Child and Adolescent Psychiatry Clinics at Erada Mental Hospital, Hail, Saudi Arabia, and the Child Psychiatry Unit at Al‑Azhar University Hospital, Cairo, Egypt.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eParticipants and sampling\u003c/p\u003e\n\u003cp\u003eA total of 200 children and adolescents aged 6–18 years were recruited (100 per country). Recruitment used a stratified approach to include clinical participants (70%) and community participants (30%) (Figure 1). Clinical participants were consecutively enrolled from outpatient services; community participants were recruited via school announcements and community outreach. \u0026nbsp;Ethical approval was obtained from the IRB of Al-Azhar University (No. AZ-2022-PSY-014) and the Ethics Committee of Hail Cluster Health (No. EMH-SA-2023-01). Written informed consent was obtained from guardians, and assent from minors\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTranslation and cultural adaptation\u003c/p\u003e\n\u003cp\u003eThe Arabic K‑SADS‑PL‑C DSM‑5 was developed following best‑practice cross‑cultural adaptation procedures: independent forward translation by two bilingual psychiatrists, synthesis, back‑translation by two blinded native English speakers, and iterative expert‑panel review (n=8) including psychiatrists, linguists, and methodologists from both countries. Pilot testing with 20 children (10 per country) used cognitive interviewing to confirm clarity and cultural relevance, with refinement of probes for stigma‑sensitive items and somatic expressions of distress.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eProcedure and training\u003c/p\u003e\n\u003cp\u003eTwo trained psychiatrists per site (each \u0026gt;5 years’ clinical experience) conducted independent diagnostic interviews using the adapted K‑SADS‑PL‑C DSM‑5. Interviewers completed training including DSM‑5 updates, administration procedures, and cultural adaptation features, and were certified through mock interviews requiring κ ≥0.85 with expert raters. Interviewers were blinded to each other’s ratings and to CCD outcomes. the CCD clinicians were also blinded to the K-SADS-PL-C results .\u003c/p\u003e\n\u003cp\u003eConsensus Clinical Diagnosis (CCD)\u003c/p\u003e\n\u003cp\u003ePrior to consensus, inter-rater agreement was excellent (Gwet’s AC1 = 0.88 for Saudi Arabia; 0.91 for Egypt).\"We used Gwet's AC1 as it is more robust for low-prevalence diagnoses, consistent with our approach for the K-SADS reliability.\u003c/p\u003e\n\u003cp\u003eReliability subsamples\u003c/p\u003e\n\u003cp\u003eA subset of 40 interviews was randomly selected for inter‑rater reliability analyses. A further subset of 30 participants was re‑interviewed after 7–14 days for test–retest reliability using identical procedures.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMeasures\u003c/p\u003e\n\u003cp\u003eThe K‑SADS‑PL‑C DSM‑5 covers major DSM‑5 diagnostic domains, including depressive disorders, anxiety disorders (including GAD and SAD), OCD, ADHD, ODD, and others, using standardized symptom probes and scoring criteria. Separate parent and child interviews are integrated to derive final diagnoses.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll statistical analyses were conducted using SPSS (version 24.0) and Mplus (version 8.8), with a significance level set at\u0026nbsp;p\u0026nbsp;\u0026lt; 0.05.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSample Size and Power\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA priori power analyses were performed using PASS 2022. For reliability analyses, a sample of 30–40 participants was estimated to provide 80% power to detect Cohen’s κ \u0026gt; 0.80. The total sample of \u003cem\u003eN\u003c/em\u003e = 200 (100 per site) ensured \u0026gt;80% power for Multi-Group Confirmatory Factor Analysis (MG-CFA) invariance testing—consistent with recommendations of at least 100 participants per group in multi-group modeling—and provided narrow confidence intervals for diagnostic accuracy estimates (e.g., sensitivity, specificity). Missing data were minimal (\u0026lt;5%) and handled using pairwise deletion.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eReliability and Diagnostic Efficiency\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInter-rater and test–retest agreement were assessed using Cohen’s κ. To account for potential prevalence bias in low-frequency diagnoses, Gwet’s AC1 was also reported for these categories. Internal consistency was evaluated with Cronbach’s α, where α \u0026gt; 0.70 was considered acceptable.\u003cbr\u003e\u0026nbsp;Criterion validity was evaluated against the Consensus Clinical Diagnosis (CCD) via two-by-two contingency tables. Sensitivity, specificity, Positive Predictive Value (PPV), and Negative Predictive Value (NPV) were calculated. Overall diagnostic accuracy was summarized using the Area Under the Receiver Operating Characteristic Curve (AUC), with 95% confidence intervals (CI).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMeasurement Invariance (Multi-Group Confirmatory Factor Analysis):\u0026nbsp;\u003c/strong\u003e\u003cbr\u003eCross-cultural measurement equivalence was examined using MG-CFA across Saudi and Egyptian samples. A two-factor model was tested: an \u003cstrong\u003eInternalizing factor\u003c/strong\u003e (MDD, GAD, SAD, OCD subscales) and an \u003cstrong\u003eExternalizing factor\u003c/strong\u003e (ADHD, ODD subscales).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eInvariance was tested sequentially:\u003c/p\u003e\n\u003col\u003e\n \u003cli\u003e\u003cstrong\u003eConfigural invariance\u003c/strong\u003e – tests whether the same factor structure holds across groups.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eMetric (weak) invariance\u003c/strong\u003e – tests equality of factor loadings, ensuring the latent constructs are measured on the same scale.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eScalar (strong) invariance\u003c/strong\u003e – tests equality of item intercepts, allowing meaningful comparison of latent means across groups.\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eModel fit was evaluated using the Comparative Fit Index (CFI), Tucker–Lewis Index (TLI), Root Mean Square Error of Approximation (RMSEA), and Standardized Root Mean Square Residual (SRMR). Robust maximum likelihood estimation (MLR) was employed. Invariance was supported if changes in fit indices met recommended thresholds: ΔCFI ≤ 0.010 and ΔRMSEA ≤ 0.015 [18]. Achievement of scalar invariance indicates that observed score differences reflect true differences in the latent constructs, supporting valid cross-site comparisons.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eSample characteristics\u003c/p\u003e\n\u003cp\u003eThe sample (N=200) was 54% male, mean age 12.4 years (SD 3.2). 79% met criteria for at least one lifetime DSM-5 diagnosis. No significant between-site differences were found (Table 1) (Figure 1).\u003c/p\u003e\n\u003cp\u003eReliability\u003c/p\u003e\n\u003cp\u003eInter‑rater reliability (n=40) was excellent across selected DSM‑5 diagnoses, with Cohen’s κ ranging from 0.81 to 1.00 and Gwet’s AC1 from 0.85 to 1.00 (Table 2). For low‑prevalence diagnoses (e.g., OCD), AC1 provided a robust complement to κ. Test–retest reliability (n=30) over 7–14 days (mean interval 10.2 days) was similarly strong (κ 0.85–0.96; AC1 0.88–0.97; (Table 3). Internal consistency was high for internalising (α=0.92) and externalising (α=0.94) dimensions.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCriterion validity\u003c/p\u003e\n\u003cp\u003eAgainst CCD (N=200), the Arabic K‑SADS‑PL‑C DSM‑5 demonstrated strong diagnostic efficiency for selected disorders. Sensitivity ranged from 86.7% (GAD) to 96.8% (ADHD), and specificity from 97.1% (MDD) to 99.5% (SAD). AUC values ranged from 0.93 to 0.98, indicating excellent discrimination (Table 4). For ADHD and OCD, the tool showed near-perfect agreement with the reference standard, with AUCs of 0.98 and 0.96, respectively.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCross‑cultural equivalence (measurement invariance)\u003c/p\u003e\n\u003cp\u003eMG‑CFA supported the two‑factor internalising/externalising model across sites (Table 5). The configural model showed good fit (CFI=0.962; RMSEA=0.057; SRMR=0.041). Metric invariance was supported (ΔCFI −0.002; ΔRMSEA −0.002), and scalar invariance was also supported (ΔCFI −0.002; ΔRMSEA −0.001), meeting recommended thresholds [18]. These findings support meaningful cross‑site comparisons of latent constructs under this model.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePrevalence estimates derived from the K‑SADS‑PL‑C were comparable between sites for selected disorders (Table 6).\u0026nbsp;\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study provides the first detailed psychometric evaluation of the Arabic version of the Kiddie Schedule for Affective Disorders and Schizophrenia–Present and Lifetime Version for DSM-5 (K-SADS-PL-C DSM-5) using data from two clinical sites. The results show that the tool is highly reliable, valid, and culturally adaptable for use in Arabic-speaking populations.\u003c/p\u003e\n\u003cp\u003eThe outcomes include strong inter-rater reliability (κ = 0.81–1.00), consistent test-retest reliability (κ = 0.85–0.96), and excellent diagnostic accuracy when compared to a blinded Consensus Clinical Diagnosis (CCD), with sensitivity ranging from 86.7% to 100%, specificity from 97.1% to 100%, and AUC values between 0.93 and 1.00 (Table 4). Measurement invariance across sites was confirmed (ΔCFI ≤ -0.002, ΔRMSEA ≤ 0.001; Table 5), supporting the tool’s use for standardized assessment across the MENA region. These findings address a major gap in culturally validated diagnostic instruments, especially given the continued use of older DSM-IV versions that may not reflect current diagnostic criteria or cultural expressions of distress.\u003c/p\u003e\n\u003cp\u003eReliability metrics compare favourably with those reported in other DSM‑5‑aligned K‑SADS validations in Spanish [7], Chinese [8], Greek [9], and Japanese [10] populations. High agreement may reflect structured interviewer training and careful cultural adaptation, including refinement of probes for stigma‑sensitive symptoms and somatic idioms.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCriterion validity was strong, with slightly lower sensitivity for GAD potentially reflecting cultural variations in how anxiety is expressed (e.g., somatic presentations rather than verbalised worry). Invariance results suggest that latent internalising and externalising constructs are measured similarly across the two sites, enabling cross‑country comparisons in research settings.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe exceptionally high diagnostic accuracy for ADHD (AUC 0.98) and OCD (AUC 0.96) merits consideration. While near-perfect metrics are uncommon in psychiatric diagnostics, they may reflect the structured nature of the K‑SADS‑PL‑C in capturing core, observable symptoms of these disorders, which are less subject to cultural variation in presentation. For ADHD, the clear behavioral anchors (e.g., inattention, hyperactivity) and for OCD, the concrete identification of compulsions and obsessions, may facilitate more reliable detection across raters and settings. Furthermore, the stratified sampling design, which included a substantial clinical subset, likely enriched the sample with clearer, more diagnosable cases. Nonetheless, these results should be interpreted with the understanding that real-world clinical populations may include more complex or subthreshold presentations, and further validation in broader community samples is recommended.\u003c/p\u003e\n\u003cp\u003eMeasurement invariance was confirmed through Multi-Group Confirmatory Factor Analysis (Table 5). The model showed consistent fit across configural, metric, and scalar levels, with factor loadings ranging from 0.72 to 0.95. This means that symptom scores can be interpreted similarly across different Arab populations. Prevalence rates (e.g., ADHD 22.5%; Table 6) were consistent with global estimates and reflected regional influences such as family stress. The use of Modern Standard Arabic helped reduce dialect-related bias, though differences between Gulf and Egyptian dialects may still affect item interpretation. Urban recruitment may have skewed results toward more severe cases, underrepresenting rural populations and potentially inflating cross-site consistency.\u003c/p\u003e\u003cp\u003eClinical and research implications\u003c/p\u003e\n\u003cp\u003eClinically, administration time (approximately 60\u0026ndash;95 minutes) is feasible for specialist outpatient settings and may reduce diagnostic variability where standardised tools are limited. For research, evidence of scalar invariance supports pooled multi‑site analyses and more robust cross‑cultural comparisons in the MENA context.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eStrengths and limitations\u003c/p\u003e\n\u003cp\u003eStrengths include multi‑site design, stratified clinical/community sampling, rigorous translation and cultural adaptation, blinded CCD comparator, and use of both \u0026kappa; and AC1 in low‑prevalence contexts. Limitations include urban tertiary‑centre sampling, cross‑sectional design (no predictive validity), and small numbers for rare disorders. Additional validation across rural settings and other Arabic dialect regions is warranted.\u0026nbsp;\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe Arabic K-SADS-PL-C DSM-5 is a reliable and valid diagnostic tool for child and adolescent mental health assessment across two Arabic-speaking settings. Its psychometric strength and evidence of cross-site measurement invariance support its use in clinical assessment and multi-site research in the MENA region, with further validation recommended in broader populations and dialect contexts.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eEthical approval was obtained from the IRB of Al-Azhar University (No. AZ-2022-PSY-014) and the Ethics Committee of Hail Cluster Health (No. EMH-SA-2023-01). Written informed consent was obtained from guardians, and assent from minors\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lsquo;Clinical trial number:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003enot applicable.\u0026rsquo;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research received no specific grant from any funding agency in the public, commercial, or not‑for‑profit sectors.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMA and AG conceived the study, designed the protocol, and supervised data collection. AA, SR, and HA contributed to data acquisition in the Saudi Arabian site. AG, ME, NS, LA, HS, and OA contributed to data acquisition in the Egyptian site. MS performed the statistical analysis and drafted the initial manuscript. All authors were involved in data interpretation. MA and AG critically revised the manuscript for intellectual content. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank all children, adolescents, and their families for participation. We also thank staff at Erada Mental Hospital and Al‑Azhar University Hospital for support.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWang S, Li Q, Lu J, Ran H, Che Y, Fang D, Liang X, Sun H, Chen L, Peng J, Shi Y, Xiao Y. Treatment Rates for Mental Disorders Among Children and Adolescents: A Systematic Review and Meta‑Analysis. \u003cem\u003eJAMA Netw Open\u003c/em\u003e. 2023;6(10):e2338174. \u003c/li\u003e\n\u003cli\u003eBergelson I, Tracy C, Takacs E. Best Practices for Reducing Bias in the Interview Process. \u003cem\u003eCurr Urol Rep\u003c/em\u003e. 2022;23(11):319\u0026ndash;325. \u003c/li\u003e\n\u003cli\u003eKvig EI, Nilssen S. Does method matter? Assessing the validity and clinical utility of structured diagnostic interviews among a clinical sample of first‑admitted patients with psychosis: a replication study. \u003cem\u003eFront Psychiatry\u003c/em\u003e. 2023;14. \u003c/li\u003e\n\u003cli\u003eKaufman J, Birmaher B, Axelson D, Perepletchikova F, Brent D, Ryan N. \u003cem\u003eK‑SADS‑PL DSM‑5\u003c/em\u003e. Pittsburgh: Western Psychiatric Institute and Clinic; 2016. \u003c/li\u003e\n\u003cli\u003eKaufman J, Birmaher B, Brent D, Rao U, Flynn C, Moreci P, Williamson D, Ryan N. 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Depression, anxiety and stress among Saudi adolescent school boys. \u003cem\u003ePerspect Public Health\u003c/em\u003e. 2007;127:33\u0026ndash;37. \u003c/li\u003e\n\u003cli\u003eHariz N, Bawab S, Atwi M, Tavitian L, Zeinoun P, Khani M, Birmaher B, Nahas Z, Maalouf FT. Reliability and validity of the Arabic Screen for Child Anxiety Related Emotional Disorders (SCARED) in a clinical sample. \u003cem\u003ePsychiatry Res\u003c/em\u003e. 2013;209(2):222\u0026ndash;228. \u003c/li\u003e\n\u003cli\u003eChen FF. Sensitivity of goodness of fit indexes to lack of measurement invariance. \u003cem\u003eStruct Equ Modelling\u003c/em\u003e. 2007;14(3):464\u0026ndash;504. \u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1. Demographic and clinical characteristics of the study sample (N=200)\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"3\" cellpadding=\"0\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eCharacteristic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eTotal sample (N=200)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eSaudi sample (n=100)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eEgyptian sample (n=100)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eTest statistic (p‑value)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAge, years (mean \u0026plusmn; SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e12.4 \u0026plusmn; 3.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e12.5 \u0026plusmn; 3.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e12.3 \u0026plusmn; 3.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003et=0.52 (p=0.605)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMale, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e108 (54.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e55 (55.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e53 (53.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026chi;\u0026sup2;=0.24 (p=0.624)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eFemale, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e92 (46.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e45 (45.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e47 (47.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026chi;\u0026sup2;=0.24 (p=0.624)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eClinical recruitment, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e140 (70.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e70 (70.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e70 (70.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026chi;\u0026sup2;=0.00 (p=1.000)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eCommunity recruitment, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e60 (30.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e30 (30.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e30 (30.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026chi;\u0026sup2;=0.00 (p=1.000)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAny lifetime diagnosis (CCD), n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e158 (79.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e81 (81.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e77 (77.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026chi;\u0026sup2;=0.52 (p=0.471)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAbbreviation: CCD, Consensus Clinical Diagnosis.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 2. Inter‑rater reliability for selected DSM‑5 diagnoses (n=40)\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"3\" cellpadding=\"0\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eDSM‑5 diagnosis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eCohen\u0026rsquo;s \u0026kappa;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e95% CI for \u0026kappa;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eGwet\u0026rsquo;s AC1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eInterpretation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eADHD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.81\u0026ndash;1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eExcellent\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMDD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.76\u0026ndash;1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eExcellent\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eGAD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.70\u0026ndash;1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eExcellent\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eOCD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.00\u0026ndash;1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eExcellent\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eODD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.74\u0026ndash;1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eExcellent\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSAD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.64\u0026ndash;0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eExcellent\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eEnuresis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.00\u0026ndash;1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eExcellent\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAbbreviations: ADHD, Attention‑Deficit/Hyperactivity Disorder; MDD, Major Depressive Disorder; GAD, Generalised Anxiety Disorder; OCD, Obsessive‑Compulsive Disorder; ODD, Oppositional Defiant Disorder; SAD, Separation Anxiety Disorder.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 3. Test\u0026ndash;retest reliability for selected DSM‑5 diagnoses (n=30)\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"3\" cellpadding=\"0\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eDSM‑5 diagnosis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eCohen\u0026rsquo;s \u0026kappa;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e95% CI for \u0026kappa;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eGwet\u0026rsquo;s AC1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eInterpretation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eADHD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.88\u0026ndash;1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eExcellent\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMDD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.79\u0026ndash;1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eExcellent\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eGAD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.70\u0026ndash;1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eExcellent\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eOCD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.88\u0026ndash;1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eExcellent\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eODD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.76\u0026ndash;1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eExcellent\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSAD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.73\u0026ndash;1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eExcellent\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAbbreviations: ADHD, Attention‑Deficit/Hyperactivity Disorder; MDD, Major Depressive Disorder; GAD, Generalised Anxiety Disorder; OCD, Obsessive‑Compulsive Disorder; ODD, Oppositional Defiant Disorder; SAD, Separation Anxiety Disorder.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 4. Diagnostic efficiency of the Arabic K‑SADS‑PL‑C DSM‑5 against CCD (N=200)\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eDSM‑5 Diagnosis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003eSensitivity (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003eSpecificity (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003ePPV (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eNPV (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003eAUC (95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eADHD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e96.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e98.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e95.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e99.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.98 (0.96\u0026ndash;1.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eMDD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e94.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e97.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e89.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e98.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.96 (0.92\u0026ndash;0.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eGAD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e86.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e98.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e92.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e96.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.93 (0.87\u0026ndash;0.98)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eOCD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e93.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e99.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e93.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e99.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.96 (0.92\u0026ndash;1.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eODD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e95.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e98.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e95.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e98.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.97 (0.94\u0026ndash;1.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eSAD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e92.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e99.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e96.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e99.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.96 (0.92\u0026ndash;1.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAbbreviations: CCD, Consensus Clinical Diagnosis; PPV, Positive Predictive Value; NPV, Negative Predictive Value; AUC, Area Under the Curve; ADHD, Attention‑Deficit/Hyperactivity Disorder; MDD, Major Depressive Disorder; GAD, Generalised Anxiety Disorder; OCD, Obsessive‑Compulsive Disorder; ODD, Oppositional Defiant Disorder; SAD, Separation Anxiety Disorder.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 5. Fit indices for measurement invariance of the two‑factor model across Saudi and Egyptian samples\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"3\" cellpadding=\"0\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eInvariance model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026chi;\u0026sup2; (df)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eCFI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eTLI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eRMSEA (90% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eSRMR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026Delta;CFI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026Delta;RMSEA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e1. Configural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e358.1 (184)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.962\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.954\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.057 (0.048\u0026ndash;0.065)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.041\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e2. Metric (weak)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e371.5 (198)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.960\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.955\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.055 (0.047\u0026ndash;0.063)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.045\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e3. Scalar (strong)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e385.9 (212)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.958\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.954\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.054 (0.046\u0026ndash;0.062)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.048\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eModel acceptance criteria: \u0026Delta;CFI \u0026le;0.010; \u0026Delta;RMSEA \u0026le;0.015\u003c/p\u003e\n\u003cp\u003eTable 6. Prevalence of selected lifetime DSM‑5 diagnoses by country (K‑SADS‑PL‑C DSM‑5)\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"3\" cellpadding=\"0\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eDSM‑5 diagnosis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eSaudi sample (n=100), n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eEgyptian sample (n=100), n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eTotal (N=200), n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026chi;\u0026sup2; (p‑value)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eADHD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e24 (24.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e21 (21.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e45 (22.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.27 (0.603)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMDD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e14 (14.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e12 (12.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e26 (13.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.19 (0.663)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAny anxiety disorder\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e19 (19.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e17 (17.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e36 (18.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.14 (0.705)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eOCD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e8 (8.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7 (7.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e15 (7.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.08 (0.777)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eODD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e15 (15.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e13 (13.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e28 (14.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.18 (0.674)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAbbreviations: ADHD, Attention‑Deficit/Hyperactivity Disorder; MDD, Major Depressive Disorder; OCD, Obsessive‑Compulsive Disorder; ODD, Oppositional Defiant Disorder.\u0026nbsp;\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"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":"bmc-psychiatry","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bpsy","sideBox":"Learn more about [BMC Psychiatry](http://bmcpsychiatry.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bpsy/default.aspx","title":"BMC Psychiatry","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"K-SADS-PL, DSM-5, Arabic, validation, child psychiatry, cross-cultural, Saudi Arabia, Egypt","lastPublishedDoi":"10.21203/rs.3.rs-8633628/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8633628/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eAccurate diagnosis of psychiatric disorders in children and adolescents is essential for effective clinical care, valid research, and targeted interventions. Given the high burden of mental disorders in the Middle East and North Africa (MENA) region and limited validated Arabic diagnostic interviews aligned with DSM-5, rigorous psychometric evaluation of the Arabic Kiddie Schedule for Affective Disorders and Schizophrenia\u0026mdash;Present and Lifetime Version, Comprehensive DSM-5 (K-SADS-PL-C DSM-5) is needed.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe conducted a multi-site psychometric validation study with 200 participants aged 6\u0026ndash;18 years (n\u0026thinsp;=\u0026thinsp;100 from Saudi Arabia and n\u0026thinsp;=\u0026thinsp;100 from Egypt\"), recruited from clinical (70%) and community (30%) settings in Hail, Saudi Arabia, and Cairo, Egypt. The Arabic version was developed via forward\u0026ndash;back translation and expert-panel cultural adaptation. Reliability was assessed using inter-rater (n\u0026thinsp;=\u0026thinsp;40) and test\u0026ndash;retest (n\u0026thinsp;=\u0026thinsp;30; 7\u0026ndash;14-day interval) analyses with Cohen\u0026rsquo;s κ and Gwet\u0026rsquo;s AC1 for low-prevalence diagnoses. Criterion validity was evaluated against blinded Consensus Clinical Diagnosis (CCD) by senior psychiatrists. Multi-group confirmatory factor analysis (MG-CFA) examined configural, metric, and scalar invariance across sites.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eInter-rater κ ranged from 0.81 to 1.00 (AC1\u0026thinsp;\u0026ge;\u0026thinsp;0.85), and test\u0026ndash;retest κ ranged from 0.85 to 0.96 (AC1\u0026thinsp;\u0026ge;\u0026thinsp;0.88) across selected DSM-5 diagnoses. Internal consistency was high (α\u0026thinsp;=\u0026thinsp;0.92 internalising; α\u0026thinsp;=\u0026thinsp;0.94 externalising). Against CCD, sensitivity ranged from 86.7% to 100% and specificity from 97.1% to 100% for selected disorders (AUC 0.93\u0026ndash;1.00). MG-CFA supported scalar invariance (ΔCFI \u0026minus;\u0026thinsp;0.002; ΔRMSEA \u0026minus;\u0026thinsp;0.001), enabling cross-site comparisons. Prevalence estimates were comparable between countries (χ\u0026sup2; p\u0026thinsp;\u0026gt;\u0026thinsp;0.4 across selected disorders).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eThe Arabic K-SADS-PL-C DSM-5 demonstrates excellent reliability, strong criterion validity, and evidence of measurement invariance across Saudi and Egyptian samples, supporting its use for standardised assessment and multi-site research in Arabic-speaking youth.\u003c/p\u003e","manuscriptTitle":"Psychometric Validation and Cross-Cultural Invariance of the Arabic K-SADS-PL-C DSM-5: A Multi-Site Diagnostic Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-22 12:38:16","doi":"10.21203/rs.3.rs-8633628/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-02-24T11:01:09+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"193389054135816364345878863603998064055","date":"2026-02-24T10:54:46+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-02-16T13:38:00+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-01-23T11:10:53+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-01-21T10:44:23+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-01-21T10:44:00+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Psychiatry","date":"2026-01-18T21:06:42+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-psychiatry","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bpsy","sideBox":"Learn more about [BMC Psychiatry](http://bmcpsychiatry.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bpsy/default.aspx","title":"BMC Psychiatry","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"bf5ad9af-c517-4762-87c1-984f130b1b9f","owner":[],"postedDate":"February 22nd, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-02-22T12:38:16+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-22 12:38:16","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8633628","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8633628","identity":"rs-8633628","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}