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Gepubliceerd in: Journal of Autism and Developmental Disorders 5/2015

01-05-2015 | Original Paper

Comparing Diagnostic Outcomes of Autism Spectrum Disorder Using DSM-IV-TR and DSM-5 Criteria

Auteurs: Elizabeth B. Harstad, Jason Fogler, Georgios Sideridis, Sarah Weas, Carrie Mauras, William J. Barbaresi

Gepubliceerd in: Journal of Autism and Developmental Disorders | Uitgave 5/2015

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Abstract

Controversy exists regarding the DSM-5 criteria for ASD. This study tested the psychometric properties of the DSM-5 model and determined how well it performed across different gender, IQ, and DSM-IV-TR sub-type, using clinically collected data on 227 subjects (median age = 3.95 years, majority had IQ > 70). DSM-5 was psychometrically superior to the DSM-IV-TR model (Comparative Fit Index of 0.970 vs 0.879, respectively). Measurement invariance revealed good model fit across gender and IQ. Younger children tended to meet fewer diagnostic criteria. Those with autistic disorder were more likely to meet social communication and repetitive behaviors criteria (p < .001) than those with PDD-NOS. DSM-5 is a robust model but will identify a different, albeit overlapping population of individuals compared to DSM-IV-TR.
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Voetnoten
1
In essence favoring more complex models (Breivik and Olsson 2001).
 
2
The sample size adjusted BIC-SABIC was preferred to the corrected AIC (Hurvich and Tsai 1989) for the following reason: the AICc has proven useful for the time series autoregressive models for which it was originally developed. There is to date little evidence on its utility in other types of analyses (Brockwell and Davis 1991; McQuarrie and Tsai 1998). With small, less complex models and medium sample sizes, as was the present case, both AIC and AICc will generate similar estimates. Based on the early work of Rafterty (1995), Gignac and Watkins (2013) have recommended that effect sizes need to be suggested for AIC and BIC. They recommended that difference AIC/BIC values of 2, 6, 10 or >10 units reflect “weak”, “positive”, “strong”, and “very strong” effects in favor of the simpler model.
 
Literatuur
go back to reference Akaike, H. (1974). A new look at the statistical model identification. IEEE Transactions on Automatic Control, 19(6), 716–723. CrossRef Akaike, H. (1974). A new look at the statistical model identification. IEEE Transactions on Automatic Control, 19(6), 716–723. CrossRef
go back to reference Akaike, H. (1980). Likelihood and the Bayes procedure. In J. M. Bernardo (Ed.), Bayesian Statistics (Vol. 31, pp. 143–166). Valencia: University Press. Akaike, H. (1980). Likelihood and the Bayes procedure. In J. M. Bernardo (Ed.), Bayesian Statistics (Vol. 31, pp. 143–166). Valencia: University Press.
go back to reference American Psychiatric Association. (2000). Diagnostic and Statistical Manual of Mental Disorders-IV-Text Revision. Washington, DC: American Psychiatric Publishing. American Psychiatric Association. (2000). Diagnostic and Statistical Manual of Mental Disorders-IV-Text Revision. Washington, DC: American Psychiatric Publishing.
go back to reference American Psychiatric Association. (2013). Diagnostic and Statistical Manual of Mental Disorders-Fifth Edition. Arlington, VA: American Psychiatric Publishing. CrossRef American Psychiatric Association. (2013). Diagnostic and Statistical Manual of Mental Disorders-Fifth Edition. Arlington, VA: American Psychiatric Publishing. CrossRef
go back to reference Amir, R. E., Van den Veyver, I. B., Wan, M., Tran, C. Q., Francke, U., & Zoghbi, H. Y. (1999). Rett syndrome is caused by mutations in X-linked MECP2, encoding methyl-CpG-binding protein 2. Nature Genetics, 23(2), 185–188. doi: 10.​1038/​13810. CrossRefPubMed Amir, R. E., Van den Veyver, I. B., Wan, M., Tran, C. Q., Francke, U., & Zoghbi, H. Y. (1999). Rett syndrome is caused by mutations in X-linked MECP2, encoding methyl-CpG-binding protein 2. Nature Genetics, 23(2), 185–188. doi: 10.​1038/​13810. CrossRefPubMed
go back to reference Bayley, N. (2006). Manual for the Bayley Scales of Infant and Toddler Development (3rd ed.). San Antonio: The Psychological Corporation. Bayley, N. (2006). Manual for the Bayley Scales of Infant and Toddler Development (3rd ed.). San Antonio: The Psychological Corporation.
go back to reference Bentler, P. M. (1990). Comparative fit indexes in structural models. Psychological Bulletin, 107(2), 238–246. CrossRefPubMed Bentler, P. M. (1990). Comparative fit indexes in structural models. Psychological Bulletin, 107(2), 238–246. CrossRefPubMed
go back to reference Bentler, P. M., & Bonett, D. G. (1980). Significance tests and goodness of fit in the analysis of covariance structures. Psychological Bulletin, 88(3), 588–606. CrossRef Bentler, P. M., & Bonett, D. G. (1980). Significance tests and goodness of fit in the analysis of covariance structures. Psychological Bulletin, 88(3), 588–606. CrossRef
go back to reference Bollen, K. A. (1989). Structural equations with latent variables. New York, NY: Wiley. CrossRef Bollen, K. A. (1989). Structural equations with latent variables. New York, NY: Wiley. CrossRef
go back to reference Bond, T. G., & Fox, C. M. (2001). Applying the Rasch model (2nd ed.). Mahwah, NJ: Lawrence Erlbaum. Bond, T. G., & Fox, C. M. (2001). Applying the Rasch model (2nd ed.). Mahwah, NJ: Lawrence Erlbaum.
go back to reference Breivik, E., & Olsson, U. (2001). Adding variables to improve fit: the effect of model size on fit assessment in Lisrel. In R. Cudeck, S. du Toit, & D. Sorbom (Eds.), Structural equation modeling: Present and future (pp. 169–194). Lincolnwood, IL: Scientific Software International. Breivik, E., & Olsson, U. (2001). Adding variables to improve fit: the effect of model size on fit assessment in Lisrel. In R. Cudeck, S. du Toit, & D. Sorbom (Eds.), Structural equation modeling: Present and future (pp. 169–194). Lincolnwood, IL: Scientific Software International.
go back to reference Brockwell, P. J., & Davis, R. A. (1991). Time series: theory and methods (2nd ed.). New York: Springer. CrossRef Brockwell, P. J., & Davis, R. A. (1991). Time series: theory and methods (2nd ed.). New York: Springer. CrossRef
go back to reference Elliott, C. (2007). Differential ability scales (2nd ed.). San Antonio: Pearson. Elliott, C. (2007). Differential ability scales (2nd ed.). San Antonio: Pearson.
go back to reference Enders, C. K., & Tofighi, D. (2008). The impact of misspecifying class-specific residual variances in growth mixture models. Structural Equation Modeling: A Multidisciplinary Journal, 15, 75–95. CrossRef Enders, C. K., & Tofighi, D. (2008). The impact of misspecifying class-specific residual variances in growth mixture models. Structural Equation Modeling: A Multidisciplinary Journal, 15, 75–95. CrossRef
go back to reference Frazier, T. W., Youngstrom, E. A., Kubu, C. S., Sinclair, L., & Rezai, A. (2008). Exploratory and confirmatory factor analysis of the autism diagnostic interview-revised. Journal of Autism and Developmental Disorders, 38(3), 474–480. doi: 10.​1007/​s10803-007-0415-z. CrossRefPubMed Frazier, T. W., Youngstrom, E. A., Kubu, C. S., Sinclair, L., & Rezai, A. (2008). Exploratory and confirmatory factor analysis of the autism diagnostic interview-revised. Journal of Autism and Developmental Disorders, 38(3), 474–480. doi: 10.​1007/​s10803-007-0415-z. CrossRefPubMed
go back to reference Gibbs, V., Aldridge, F., Chandler, F., Witzlsperger, E., & Smith, K. (2012). Brief report: an exploratory study comparing diagnostic outcomes for autism spectrum disorders under DSM-IV-TR with the proposed DSM-5 revision. Journal of Autism and Developmental Disorders, 42(8), 1750–1756. doi: 10.​1007/​s10803-012-1560-6. CrossRefPubMed Gibbs, V., Aldridge, F., Chandler, F., Witzlsperger, E., & Smith, K. (2012). Brief report: an exploratory study comparing diagnostic outcomes for autism spectrum disorders under DSM-IV-TR with the proposed DSM-5 revision. Journal of Autism and Developmental Disorders, 42(8), 1750–1756. doi: 10.​1007/​s10803-012-1560-6. CrossRefPubMed
go back to reference Gignac, G. E., & Watkins, M. W. (2013). Bifactor modeling and the estimation of model-based reliability in the WAIS-IV. Multivariate Behavioral Research, 48, 639–662. CrossRef Gignac, G. E., & Watkins, M. W. (2013). Bifactor modeling and the estimation of model-based reliability in the WAIS-IV. Multivariate Behavioral Research, 48, 639–662. CrossRef
go back to reference Gotham, K., Risi, S., Pickles, A., & Lord, C. (2007). The Autism Diagnostic Observation Schedule: revised algorithms for improved diagnostic validity. Journal of Autism and Developmental Disorders, 37(4), 613–627. doi: 10.​1007/​s10803-006-0280-1. CrossRefPubMed Gotham, K., Risi, S., Pickles, A., & Lord, C. (2007). The Autism Diagnostic Observation Schedule: revised algorithms for improved diagnostic validity. Journal of Autism and Developmental Disorders, 37(4), 613–627. doi: 10.​1007/​s10803-006-0280-1. CrossRefPubMed
go back to reference Hambleton, R. K., & Swaminathan, H. (1985). Item response theory: Principles and applications. Boston: Kluwer. CrossRef Hambleton, R. K., & Swaminathan, H. (1985). Item response theory: Principles and applications. Boston: Kluwer. CrossRef
go back to reference Hu, L. T., & Bentler, P. M. (1995). Evaluating model fit. In R. H. Hoyle (Ed.), Structural equation modeling concepts, issues, and applications (pp. 76–99). London: Sage. Hu, L. T., & Bentler, P. M. (1995). Evaluating model fit. In R. H. Hoyle (Ed.), Structural equation modeling concepts, issues, and applications (pp. 76–99). London: Sage.
go back to reference Hu, L. T., & Bentler, P. M. (1998). Fit indices in covariance structure modeling: Sensitivity to underparameterized model misspecification. Psychological Methods, 3, 424–453. CrossRef Hu, L. T., & Bentler, P. M. (1998). Fit indices in covariance structure modeling: Sensitivity to underparameterized model misspecification. Psychological Methods, 3, 424–453. CrossRef
go back to reference Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6(1), 1–55. CrossRef Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6(1), 1–55. CrossRef
go back to reference Huerta, M., Bishop, S. L., Duncan, A., Hus, V., & Lord, C. (2012). Application of DSM-5 criteria for autism spectrum disorder to three samples of children with DSM-IV diagnoses of pervasive developmental disorders. The American Journal of Psychiatry, 169(10), 1056–1064. doi: 10.​1176/​appi.​ajp.​2012.​12020276. CrossRefPubMed Huerta, M., Bishop, S. L., Duncan, A., Hus, V., & Lord, C. (2012). Application of DSM-5 criteria for autism spectrum disorder to three samples of children with DSM-IV diagnoses of pervasive developmental disorders. The American Journal of Psychiatry, 169(10), 1056–1064. doi: 10.​1176/​appi.​ajp.​2012.​12020276. CrossRefPubMed
go back to reference Hurvich, C. M., & Tsai, C.-L. (1989). Regression and time series model selection in small samples. Biometrika, 76(2), 297–307. CrossRef Hurvich, C. M., & Tsai, C.-L. (1989). Regression and time series model selection in small samples. Biometrika, 76(2), 297–307. CrossRef
go back to reference Joreskog, K. (1973). A general method for estimating a linear structural equation system. In A. S. Goldberger & O. D. Duncan (Eds.), Structural equation models in the social sciences (pp. 85–112). New York: Seminar Press. Joreskog, K. (1973). A general method for estimating a linear structural equation system. In A. S. Goldberger & O. D. Duncan (Eds.), Structural equation models in the social sciences (pp. 85–112). New York: Seminar Press.
go back to reference Kim, Y. S., Fombonne, E., Koh, Y. J., Kim, S. J., Cheon, K. A., & Leventhal, B. L. (2014). A comparison of DSM-IV pervasive developmental disorder and DSM-5 autism spectrum disorder prevalence in an epidemiologic sample. Journal of the American Academy of Child and Adolescent Psychiatry, 53(5), 500–508. doi: 10.​1016/​j.​jaac.​2013.​12.​021. CrossRefPubMed Kim, Y. S., Fombonne, E., Koh, Y. J., Kim, S. J., Cheon, K. A., & Leventhal, B. L. (2014). A comparison of DSM-IV pervasive developmental disorder and DSM-5 autism spectrum disorder prevalence in an epidemiologic sample. Journal of the American Academy of Child and Adolescent Psychiatry, 53(5), 500–508. doi: 10.​1016/​j.​jaac.​2013.​12.​021. CrossRefPubMed
go back to reference Loehlin, J. C. (2004). Latent variable models: An introduction to factor, path, and structural equation analysis. Mahwah, NJ: Lawrence. Loehlin, J. C. (2004). Latent variable models: An introduction to factor, path, and structural equation analysis. Mahwah, NJ: Lawrence.
go back to reference Lord, C., Risi, S., Lambrecht, L., Cook, E. H., Leventhal, B. L., DiLavare, P. C., et al. (2000). The autism diagnostic observation schedule-generic: A standard measure of social and communication deficits associated with the spectrum of autism. Journal of Autism and Developmental Disorders, 30(3), 205–223. CrossRefPubMed Lord, C., Risi, S., Lambrecht, L., Cook, E. H., Leventhal, B. L., DiLavare, P. C., et al. (2000). The autism diagnostic observation schedule-generic: A standard measure of social and communication deficits associated with the spectrum of autism. Journal of Autism and Developmental Disorders, 30(3), 205–223. CrossRefPubMed
go back to reference MacCallum, R. C., Browne, M. W., & Sugawara, H. M. (1996). Power analysis and determination of sample size for covariance structure modeling. Psychological Methods, 1(2), 130–149. CrossRef MacCallum, R. C., Browne, M. W., & Sugawara, H. M. (1996). Power analysis and determination of sample size for covariance structure modeling. Psychological Methods, 1(2), 130–149. CrossRef
go back to reference Mahoney, W. J., Szatmari, P., Maclean, J. E., Bryson, S. E., Bartolucci, G., Walter, S. D., et al. (1998). Reliability and accuracy of differentiating pervasive developmental disorder subtypes. Journal of the American Academy of Child and Adolescent Psychiatry, 37(3), 278–285. doi: 10.​1097/​00004583-199803000-00012. CrossRefPubMed Mahoney, W. J., Szatmari, P., Maclean, J. E., Bryson, S. E., Bartolucci, G., Walter, S. D., et al. (1998). Reliability and accuracy of differentiating pervasive developmental disorder subtypes. Journal of the American Academy of Child and Adolescent Psychiatry, 37(3), 278–285. doi: 10.​1097/​00004583-199803000-00012. CrossRefPubMed
go back to reference Marsh, H. W., Hau, K.-T., & Grayson, D. (2005). Goodness of fit in structural equation models. In A. Maydeu-Olivares & J. J. McArdle (Eds.), Contemporary psychometrics. A Festschrift for Roderick P. McDonald. Mahwah, NJ: Lawrence Erlbaum. Marsh, H. W., Hau, K.-T., & Grayson, D. (2005). Goodness of fit in structural equation models. In A. Maydeu-Olivares & J. J. McArdle (Eds.), Contemporary psychometrics. A Festschrift for Roderick P. McDonald. Mahwah, NJ: Lawrence Erlbaum.
go back to reference McQuarrie, A. D. R., & Tsai, C.-L. (1998). Regression and time series model selection. Singapore: World Scientific. CrossRef McQuarrie, A. D. R., & Tsai, C.-L. (1998). Regression and time series model selection. Singapore: World Scientific. CrossRef
go back to reference Muthen, L. K., & Muthen, B. O. (2007). Mplus user’s guide 4. Los Angeles, CA: Muthen & Muthen. Muthen, L. K., & Muthen, B. O. (2007). Mplus user’s guide 4. Los Angeles, CA: Muthen & Muthen.
go back to reference Raftery, A. E. (1995). Bayesian model selection in social research. Sociological Methodology, 25, 111–163. CrossRef Raftery, A. E. (1995). Bayesian model selection in social research. Sociological Methodology, 25, 111–163. CrossRef
go back to reference Rasch, G. (1980). Probabilistic models for some intelligence and attainment tests. Chicago, IL: The University of Chicago Press. Rasch, G. (1980). Probabilistic models for some intelligence and attainment tests. Chicago, IL: The University of Chicago Press.
go back to reference Raykov, T. (2005). Studying group and time invariance in maximal reliability for multiple-component measuring instruments via covariance structure modelling. The British Journal of Mathematical and Statistical Psychology, 58(Pt 2), 301–317. doi: 10.​1348/​000711005X38591. CrossRefPubMed Raykov, T. (2005). Studying group and time invariance in maximal reliability for multiple-component measuring instruments via covariance structure modelling. The British Journal of Mathematical and Statistical Psychology, 58(Pt 2), 301–317. doi: 10.​1348/​000711005X38591. CrossRefPubMed
go back to reference Raykov, T., & Marcoulides, G. (2000). A first course in structural equation modeling. Mahwah, NJ: Lawrence. Raykov, T., & Marcoulides, G. (2000). A first course in structural equation modeling. Mahwah, NJ: Lawrence.
go back to reference Reise, S. (1990). A comparison of item and person fit methods of assessing model fit in IRT. Applied Psychological Measurement, 42, 127–137. CrossRef Reise, S. (1990). A comparison of item and person fit methods of assessing model fit in IRT. Applied Psychological Measurement, 42, 127–137. CrossRef
go back to reference Rieske, R. D., Matson, J. L., Beighley, J. S., Cervantes, P. E., Goldin, R. L., & Jang, J. (2013). Comorbid psychopathology rates in children diagnosed with autism spectrum disorders according to the DSM-IV-TR and the proposed DSM-5. Developmental Neurorehabilitation: Advance online publication. doi: 10.​3109/​17518423.​2013.​790519. Rieske, R. D., Matson, J. L., Beighley, J. S., Cervantes, P. E., Goldin, R. L., & Jang, J. (2013). Comorbid psychopathology rates in children diagnosed with autism spectrum disorders according to the DSM-IV-TR and the proposed DSM-5. Developmental Neurorehabilitation: Advance online publication. doi: 10.​3109/​17518423.​2013.​790519.
go back to reference Rigdon, E. E. (1996). CFI versus RMSEA: A comparison of two fit indexes for structural equation modeling. Structural Equation Modeling, 3(4), 369–379. CrossRef Rigdon, E. E. (1996). CFI versus RMSEA: A comparison of two fit indexes for structural equation modeling. Structural Equation Modeling, 3(4), 369–379. CrossRef
go back to reference Schwarz, G. E. (1978). Estimating the dimension of a model. The Annals of Statistics, 6(2), 461–464. CrossRef Schwarz, G. E. (1978). Estimating the dimension of a model. The Annals of Statistics, 6(2), 461–464. CrossRef
go back to reference Sideridis, G. D., Simos, P., Papanicolaou, A., & Fletcher, J. (2014). Using structural equation modeling to assess functional connectivity in the brain: Power and sample size considerations. Educational and Psychological Measurement, 74, 733–758. CrossRefPubMedCentralPubMed Sideridis, G. D., Simos, P., Papanicolaou, A., & Fletcher, J. (2014). Using structural equation modeling to assess functional connectivity in the brain: Power and sample size considerations. Educational and Psychological Measurement, 74, 733–758. CrossRefPubMedCentralPubMed
go back to reference Smith, E. V, Jr. (2002). Detecting and evaluating the impact of multidimensionality using item fit statistics and principal component analysis of residuals. Journal of Applied Measurement, 3, 205–231. PubMed Smith, E. V, Jr. (2002). Detecting and evaluating the impact of multidimensionality using item fit statistics and principal component analysis of residuals. Journal of Applied Measurement, 3, 205–231. PubMed
go back to reference Smith, R. M., Schumacker, R. E., & Bush, M. J. (1998). Using item mean squares to evaluate fit to the Rasch model. Journal of Outcome Measurement, 2, 66–78. PubMed Smith, R. M., Schumacker, R. E., & Bush, M. J. (1998). Using item mean squares to evaluate fit to the Rasch model. Journal of Outcome Measurement, 2, 66–78. PubMed
go back to reference Steiger, J. H. (1990). Structural model evaluation and modification: An interval estimation approach. Multivariate Behavioral Research, 25(2), 173–180. CrossRef Steiger, J. H. (1990). Structural model evaluation and modification: An interval estimation approach. Multivariate Behavioral Research, 25(2), 173–180. CrossRef
go back to reference Steiger, J. H. (2000). Point Estimation, hypothesis testing, and interval estimation using the RMSEA: Some comments and a reply to Hayduk and Glaser. Structural Equation Modeling, 7(2), 149–162. CrossRef Steiger, J. H. (2000). Point Estimation, hypothesis testing, and interval estimation using the RMSEA: Some comments and a reply to Hayduk and Glaser. Structural Equation Modeling, 7(2), 149–162. CrossRef
go back to reference Steiger, J. H. (2007). Understanding the limitations of global fit assessment in structural equation modeling. Personality and Individual Differences, 42, 893–898. CrossRef Steiger, J. H. (2007). Understanding the limitations of global fit assessment in structural equation modeling. Personality and Individual Differences, 42, 893–898. CrossRef
go back to reference Stuive, I., Kiers, H. A. L., Timmerman, M. E., & ten Berge, J. M. F. (2008). The empirical verification of an assignment of items to subtests: The oblique multiple group method versus the confirmatory common factor method. Educational and Psychological Measurement, 68(6), 923–939. CrossRef Stuive, I., Kiers, H. A. L., Timmerman, M. E., & ten Berge, J. M. F. (2008). The empirical verification of an assignment of items to subtests: The oblique multiple group method versus the confirmatory common factor method. Educational and Psychological Measurement, 68(6), 923–939. CrossRef
go back to reference Tofghi, D., & Enders, C. K. (2007). Identifying the correct number of classes in mixture models. In G. R. Hancock & K. M. Samulelsen (Eds.), Advances in latent variable mixture models (pp. 317–341). Greenwich, CT: Information Age. Tofghi, D., & Enders, C. K. (2007). Identifying the correct number of classes in mixture models. In G. R. Hancock & K. M. Samulelsen (Eds.), Advances in latent variable mixture models (pp. 317–341). Greenwich, CT: Information Age.
go back to reference Tucker, L. R., & Lewis, C. (1973). The reliability coefficient for maximum likelihood factor analysis. Psychometrica, 38, 1–10. CrossRef Tucker, L. R., & Lewis, C. (1973). The reliability coefficient for maximum likelihood factor analysis. Psychometrica, 38, 1–10. CrossRef
go back to reference Widaman, K. F., & Thompson, J. S. (2003). On specifying the null model for incremental fit indices in structural equation modeling. Psychological Methods, 8(1), 16–37. CrossRefPubMed Widaman, K. F., & Thompson, J. S. (2003). On specifying the null model for incremental fit indices in structural equation modeling. Psychological Methods, 8(1), 16–37. CrossRefPubMed
go back to reference Worley, J. A., & Matson, J. L. (2012). Comparing symptoms of autism spectrum disorders using the current DSM-IV-TR diagnostic criteria and the proposed DSM-V diagnostic criteria. Research in Autism Spectrum Disorders, 6, 965–970. CrossRef Worley, J. A., & Matson, J. L. (2012). Comparing symptoms of autism spectrum disorders using the current DSM-IV-TR diagnostic criteria and the proposed DSM-V diagnostic criteria. Research in Autism Spectrum Disorders, 6, 965–970. CrossRef
go back to reference Young, R. L., & Rodi, M. L. (2013). Redefining Autism Spectrum Disorder Using DSM-5: The Implications of the Proposed DSM-5 Criteria for Autism Spectrum Disorders. Journal of Autism and Developmental Disorders, 44(4), 758–765. doi: 10.​1007/​s10803-013-1927-3. CrossRef Young, R. L., & Rodi, M. L. (2013). Redefining Autism Spectrum Disorder Using DSM-5: The Implications of the Proposed DSM-5 Criteria for Autism Spectrum Disorders. Journal of Autism and Developmental Disorders, 44(4), 758–765. doi: 10.​1007/​s10803-013-1927-3. CrossRef
Metagegevens
Titel
Comparing Diagnostic Outcomes of Autism Spectrum Disorder Using DSM-IV-TR and DSM-5 Criteria
Auteurs
Elizabeth B. Harstad
Jason Fogler
Georgios Sideridis
Sarah Weas
Carrie Mauras
William J. Barbaresi
Publicatiedatum
01-05-2015
Uitgeverij
Springer US
Gepubliceerd in
Journal of Autism and Developmental Disorders / Uitgave 5/2015
Print ISSN: 0162-3257
Elektronisch ISSN: 1573-3432
DOI
https://doi.org/10.1007/s10803-014-2306-4

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