Utility of the 3Di short version in the identification and diagnosis of autism in children at the Kenyan coast
IntroductionThe precise epidemiological burden of autism is unknown because of the limited capacity to identify and diagnose the disorder in resource-constrained settings, related in part to a lack of appropriate standardised assessment tools and health care experts. We assessed the reliability, val...
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Frontiers Media S.A.
2024-02-01
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| Series: | Frontiers in Psychiatry |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fpsyt.2024.1234929/full |
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| author | Patricia Kipkemoi Patricia Kipkemoi Symon M. Kariuki Symon M. Kariuki Symon M. Kariuki Joseph Gona Felicita Wangeci Mwangi Martha Kombe Collins Kipkoech Paul Murimi William Mandy Richard Warrington David Skuse Charles R.J.C. Newton Charles R.J.C. Newton Charles R.J.C. Newton Charles R.J.C. Newton Amina Abubakar Amina Abubakar Amina Abubakar |
| author_facet | Patricia Kipkemoi Patricia Kipkemoi Symon M. Kariuki Symon M. Kariuki Symon M. Kariuki Joseph Gona Felicita Wangeci Mwangi Martha Kombe Collins Kipkoech Paul Murimi William Mandy Richard Warrington David Skuse Charles R.J.C. Newton Charles R.J.C. Newton Charles R.J.C. Newton Charles R.J.C. Newton Amina Abubakar Amina Abubakar Amina Abubakar |
| author_sort | Patricia Kipkemoi |
| collection | DOAJ |
| description | IntroductionThe precise epidemiological burden of autism is unknown because of the limited capacity to identify and diagnose the disorder in resource-constrained settings, related in part to a lack of appropriate standardised assessment tools and health care experts. We assessed the reliability, validity, and diagnostic accuracy of the Developmental Diagnostic Dimensional Interview (3Di) in a rural setting on the Kenyan coast.MethodsUsing a large community survey of neurodevelopmental disorders (NDDs), we administered the 3Di to 2,110 children aged between 6 years and 9 years who screened positive or negative for any NDD and selected 242 who had specific symptoms suggestive of autism based on parental report and the screening tools for review by a child and adolescent psychiatrist. On the basis of recorded video, a multi-disciplinary team applied the Autism Diagnostic Observation Schedule to establish an autism diagnosis. Internal consistency was used to examine the reliability of the Swahili version of the 3Di, tetrachoric correlations to determine criterion validity, structural equation modelling to evaluate factorial structure and receiver operating characteristic analysis to calculate diagnostic accuracy against Diagnostic Statistical Manual of Mental Disorders (DSM) diagnosis.ResultsThe reliability coefficients for 3Di were excellent for the entire scale {McDonald’s omega (ω) = 0.83 [95% confidence interval (CI) 0.79–0.91]}. A higher-order three-factor DSM-IV-TR model showed an adequate fit with the model, improving greatly after retaining high-loading items and correlated items. A higher-order two-factor DSM-5 model also showed an adequate fit. There were weak to satisfactory criterion validity scores [tetrachoric rho = 0.38 (p = 0.049) and 0.59 (p = 0.014)] and good diagnostic accuracy metrics [area under the curve = 0.75 (95% CI: 0.54–0.96) and 0.61 (95% CI: 0.49–0.73] for 3Di against the DSM criteria. The 3Di had a moderate sensitivity [66.7% (95% CI: 0.22–0.96)] and a good specificity [82.5% (95% CI: 0.74–0.89)], when compared with the DSM-5. However, we observed poor sensitivity [38.9% (95% CI: 0.17–0.64)] and good specificity [83.5% (95% CI: 0.74–0.91)] against DSM-IV-TR.ConclusionThe Swahili version of the 3Di provides information on autism traits, which may be helpful for descriptive research of endophenotypes, for instance. However, for accuracy in newly diagnosed autism, it should be complemented by other tools, e.g., observational clinical judgment using the DSM criteria or assessments such as the Autism Diagnostic Observation Schedule. The construct validity of the Swahili 3Di for some domains, e.g., communication, should be explored in future studies. |
| first_indexed | 2024-03-07T19:43:44Z |
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| id | doaj.art-b98577960a064c308d8a9f843f639d2a |
| institution | Directory Open Access Journal |
| issn | 1664-0640 |
| language | English |
| last_indexed | 2024-03-07T19:43:44Z |
| publishDate | 2024-02-01 |
| publisher | Frontiers Media S.A. |
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| series | Frontiers in Psychiatry |
| spelling | doaj.art-b98577960a064c308d8a9f843f639d2a2024-02-29T05:12:45ZengFrontiers Media S.A.Frontiers in Psychiatry1664-06402024-02-011510.3389/fpsyt.2024.12349291234929Utility of the 3Di short version in the identification and diagnosis of autism in children at the Kenyan coastPatricia Kipkemoi0Patricia Kipkemoi1Symon M. Kariuki2Symon M. Kariuki3Symon M. Kariuki4Joseph Gona5Felicita Wangeci Mwangi6Martha Kombe7Collins Kipkoech8Paul Murimi9William Mandy10Richard Warrington11David Skuse12Charles R.J.C. Newton13Charles R.J.C. Newton14Charles R.J.C. Newton15Charles R.J.C. Newton16Amina Abubakar17Amina Abubakar18Amina Abubakar19Neuroscience Unit, Kenya Medical Research Institute (KEMRI)-Wellcome Trust Research Programme, Kilifi, KenyaComplex Trait Genetics Department, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, Amsterdam, NetherlandsNeuroscience Unit, Kenya Medical Research Institute (KEMRI)-Wellcome Trust Research Programme, Kilifi, KenyaDepartment of Psychiatry, University of Oxford, Warneford Hospital, Oxford, United KingdomDepartment of Public Health, Pwani University, Kilifi, KenyaNeuroscience Unit, Kenya Medical Research Institute (KEMRI)-Wellcome Trust Research Programme, Kilifi, KenyaDepartment of Psychiatry, Moi Teaching and Referral Hospital, Eldoret, KenyaNeuroscience Unit, Kenya Medical Research Institute (KEMRI)-Wellcome Trust Research Programme, Kilifi, KenyaNeuroscience Unit, Kenya Medical Research Institute (KEMRI)-Wellcome Trust Research Programme, Kilifi, KenyaInstitute for Human Development, Aga Khan University, Nairobi, KenyaDivision of Psychology and Language Sciences, University College London (UCL) Research Department of Clinical, Educational and Health Psychology, London, United KingdomInstitute of Child Health, University College London (UCL), London, United KingdomInstitute of Child Health, University College London (UCL), London, United KingdomNeuroscience Unit, Kenya Medical Research Institute (KEMRI)-Wellcome Trust Research Programme, Kilifi, KenyaDepartment of Psychiatry, University of Oxford, Warneford Hospital, Oxford, United KingdomDepartment of Public Health, Pwani University, Kilifi, KenyaInstitute for Human Development, Aga Khan University, Nairobi, KenyaNeuroscience Unit, Kenya Medical Research Institute (KEMRI)-Wellcome Trust Research Programme, Kilifi, KenyaDepartment of Psychiatry, University of Oxford, Warneford Hospital, Oxford, United KingdomInstitute for Human Development, Aga Khan University, Nairobi, KenyaIntroductionThe precise epidemiological burden of autism is unknown because of the limited capacity to identify and diagnose the disorder in resource-constrained settings, related in part to a lack of appropriate standardised assessment tools and health care experts. We assessed the reliability, validity, and diagnostic accuracy of the Developmental Diagnostic Dimensional Interview (3Di) in a rural setting on the Kenyan coast.MethodsUsing a large community survey of neurodevelopmental disorders (NDDs), we administered the 3Di to 2,110 children aged between 6 years and 9 years who screened positive or negative for any NDD and selected 242 who had specific symptoms suggestive of autism based on parental report and the screening tools for review by a child and adolescent psychiatrist. On the basis of recorded video, a multi-disciplinary team applied the Autism Diagnostic Observation Schedule to establish an autism diagnosis. Internal consistency was used to examine the reliability of the Swahili version of the 3Di, tetrachoric correlations to determine criterion validity, structural equation modelling to evaluate factorial structure and receiver operating characteristic analysis to calculate diagnostic accuracy against Diagnostic Statistical Manual of Mental Disorders (DSM) diagnosis.ResultsThe reliability coefficients for 3Di were excellent for the entire scale {McDonald’s omega (ω) = 0.83 [95% confidence interval (CI) 0.79–0.91]}. A higher-order three-factor DSM-IV-TR model showed an adequate fit with the model, improving greatly after retaining high-loading items and correlated items. A higher-order two-factor DSM-5 model also showed an adequate fit. There were weak to satisfactory criterion validity scores [tetrachoric rho = 0.38 (p = 0.049) and 0.59 (p = 0.014)] and good diagnostic accuracy metrics [area under the curve = 0.75 (95% CI: 0.54–0.96) and 0.61 (95% CI: 0.49–0.73] for 3Di against the DSM criteria. The 3Di had a moderate sensitivity [66.7% (95% CI: 0.22–0.96)] and a good specificity [82.5% (95% CI: 0.74–0.89)], when compared with the DSM-5. However, we observed poor sensitivity [38.9% (95% CI: 0.17–0.64)] and good specificity [83.5% (95% CI: 0.74–0.91)] against DSM-IV-TR.ConclusionThe Swahili version of the 3Di provides information on autism traits, which may be helpful for descriptive research of endophenotypes, for instance. However, for accuracy in newly diagnosed autism, it should be complemented by other tools, e.g., observational clinical judgment using the DSM criteria or assessments such as the Autism Diagnostic Observation Schedule. The construct validity of the Swahili 3Di for some domains, e.g., communication, should be explored in future studies.https://www.frontiersin.org/articles/10.3389/fpsyt.2024.1234929/fullautismdiagnosisAfrica3Dipsychometricsreliability |
| spellingShingle | Patricia Kipkemoi Patricia Kipkemoi Symon M. Kariuki Symon M. Kariuki Symon M. Kariuki Joseph Gona Felicita Wangeci Mwangi Martha Kombe Collins Kipkoech Paul Murimi William Mandy Richard Warrington David Skuse Charles R.J.C. Newton Charles R.J.C. Newton Charles R.J.C. Newton Charles R.J.C. Newton Amina Abubakar Amina Abubakar Amina Abubakar Utility of the 3Di short version in the identification and diagnosis of autism in children at the Kenyan coast Frontiers in Psychiatry autism diagnosis Africa 3Di psychometrics reliability |
| title | Utility of the 3Di short version in the identification and diagnosis of autism in children at the Kenyan coast |
| title_full | Utility of the 3Di short version in the identification and diagnosis of autism in children at the Kenyan coast |
| title_fullStr | Utility of the 3Di short version in the identification and diagnosis of autism in children at the Kenyan coast |
| title_full_unstemmed | Utility of the 3Di short version in the identification and diagnosis of autism in children at the Kenyan coast |
| title_short | Utility of the 3Di short version in the identification and diagnosis of autism in children at the Kenyan coast |
| title_sort | utility of the 3di short version in the identification and diagnosis of autism in children at the kenyan coast |
| topic | autism diagnosis Africa 3Di psychometrics reliability |
| url | https://www.frontiersin.org/articles/10.3389/fpsyt.2024.1234929/full |
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