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Developmental Trajectories of Symptom Severity and Adaptive Functioning in an Inception Cohort of Preschool Children With Autism Spectrum Disorder
Abstract
IMPORTANCE: Symptom severity and adaptive functioning are fundamental domains of the autism spectrum disorder (ASD) phenotype. To date, the longitudinal association between these 2 domains has not been examined. OBJECTIVE: To describe the developmental trajectories of autistic symptom severity and adaptive functioning in a large inception cohort of preschool children with ASD. DESIGN, SETTING, AND PARTICIPANTS: The sample consisted of 421 newly diagnosed preschool children with ASD 2 to 4 years old (355 boys; mean age at study enrollment, 39.87 months) participating in a large Canadian multisite longitudinal study (Pathways in ASD Study). Prospective data collected at 4 points from time of diagnosis to age 6 years were used to track the developmental trajectories of children. MAIN OUTCOMES AND MEASURES: Autistic symptom severity was indexed using the Autism Diagnostic Observation Schedule. Adaptive functioning was indexed using the Vineland Adaptive Behavior Scales, Second Edition. RESULTS: Two distinct trajectory groups provided the best fit to the autistic symptom severity data. Group 1 (11.4% of the sample) had less severe symptoms and an improving trajectory (P < .05), whereas group 2 (88.6% of the sample) had more severe symptoms and a stable trajectory. Three distinct trajectory groups provided the best fit to the adaptive functioning data. Group 1 (29.2% of the sample) showed lower functioning and a worsening trajectory, group 2 (49.9% of the sample) had moderate functioning and a stable trajectory, and group 3 (20.9% of the sample) had higher functioning and an improving trajectory (P < .05). Cross-trajectory overlap between the autistic symptom severity and adaptive functioning groups was low (φ = 0.13, P < .05). Sex was a significant predictor of autistic symptom severity group membership and age at diagnosis, and language and cognitive scores at baseline predicted membership in adaptive functioning trajectories. Trajectories of both symptom severity and adaptive functioning predicted several different outcomes at age 6 years. CONCLUSIONS AND RELEVANCE: Findings confirm the heterogeneous nature of developmental trajectories in ASD. Change in adaptive functioning suggests that improvement is possible in roughly 20% of the sample. Autistic symptom severity appears to be more stable, with roughly 11% of the sample showing a marked decrease in symptom severity. During the preschool years, there appears to be only a small amount of "yoking" of developmental trajectories in autistic symptom severity and adaptive functioning. It is imperative that a flexible suite of interventions that target both autistic symptom severity and adaptive functioning should be implemented and tailored to each child's strengths and difficulties.
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In the citing paper
“ASD manifests with broad phenotypic variability and evolves along heterogeneous developmental trajectories (1).”
From Genetics and genomics of autism spectrum disorder: embracing complexity (2015) · cites this paper as [1]
In the citing paper
“These differences overlapped substantially with the differences observed between ASD and controls (Figure 5A), suggesting that normal variation in mechanisms that are also affected by ASD may cause variation in how ASD may manifest 1,91.”
From Subtyping cognitive profiles in Autism Spectrum Disorder using a Functional Random Forest algorithm (2018) · cites this paper as [91]
In the citing paper
“it is possible that variation within the ASD subgroups identified here may actually be “nested” within the normal variation found in brain networks across typical children 1,71,91”
From Subtyping cognitive profiles in Autism Spectrum Disorder using a Functional Random Forest algorithm (2018) · cites this paper as [91]
In the citing paper
“Because we are confident in the ASD diagnosis, we suspect that the variation between these three subgroups reflects typical variation in cognitive mechanisms, which may be independent of autism symptom severity but influence ASD presentation14,91.”
From Subtyping cognitive profiles in Autism Spectrum Disorder using a Functional Random Forest algorithm (2018) · cites this paper as [91]
Citations
Cites
Diagnostic and Statistical Manual of Mental Disorders
American Psychiatric Association (2013) · doi:10.1176/appi.books.9780890425596 · Cited by 116,369
Diagnostic and Statistical Manual of Mental Disorders
Williams, J. B. W., & First, M. B. (2013) · Oxford University Press eBooks · doi:10.1093/acrefore/9780199975839.013.104 · Cited by 109,845
Lord, C., Rutter, M., & Le Couteur, A. (1994) · Journal of Autism and Developmental Disorders · doi:10.1007/bf02172145 · Cited by 9,065
Lord, C., Risi, S., Lambrecht, L., Cook, E. H., Leventhal, B. L., DiLavore, P. C., Pickles, A., & Rutter, M. (2000) · Journal of Autism and Developmental Disorders · doi:10.1023/a:1005592401947 · Cited by 7,520
Group-Based Modeling of Development
NAGIN, D. (2005) · doi:10.4159/9780674041318 · Cited by 4,164
Standardizing ADOS Scores for a Measure of Severity in Autism Spectrum Disorders
Gotham, K., Pickles, A., & Lord, C. (2009) · Journal of Autism and Developmental Disorders · doi:10.1007/s10803-008-0674-3 · Cited by 1,605
Vineland Adaptive Behavior Scales, Second Edition
Sparrow, S. S., Cicchetti, D. V., & Balla, D. (2005) · PsycTESTS Dataset · doi:10.1037/t15164-000 · Cited by 983
Autism From 2 to 9 Years of Age
Lord, C., Risi, S., DiLavore, P. S., Shulman, C., Thurm, A., & Pickles, A. (2006) · Archives of General Psychiatry · doi:10.1001/archpsyc.63.6.694 · Cited by 973
Lyons, M. (2021) · Springer eBooks · doi:10.1007/978-3-319-91280-6_979 · Cited by 964
Young Adult Outcome of Autism Spectrum Disorders
Eaves, L. C., & Ho, H. H. (2008) · Journal of Autism and Developmental Disorders · doi:10.1007/s10803-007-0441-x · Cited by 683
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Masi, A., DeMayo, M. M., Glozier, N., & Guastella, A. J. (2017) · Neuroscience Bulletin · doi:10.1007/s12264-017-0100-y · Cited by 987
Big data approaches to decomposing heterogeneity across the autism spectrum
Lombardo, M. V., Lai, M.-C., & Baron-Cohen, S. (2019) · Molecular Psychiatry · doi:10.1038/s41380-018-0321-0 · Cited by 537
Autism spectrum heterogeneity: fact or artifact?
Mottron, L., & Bzdok, D. (2020) · Molecular Psychiatry · doi:10.1038/s41380-020-0748-y · Cited by 332
Alvares, G. A., Bebbington, K., Cleary, D., Evans, K., Glasson, E. J., Maybery, M. T., Pillar, S., Uljarević, M., Varcin, K., Wray, J., et al. (2020) · Autism · doi:10.1177/1362361319852831 · Cited by 331
Constantino, J. N., & Charman, T. (2016) · The Lancet Neurology · doi:10.1016/s1474-4422(15)00151-9 · Cited by 294
Autism spectrum disorder: advances in diagnosis and evaluation
Zwaigenbaum, L., & Penner, M. (2018) · BMJ · doi:10.1136/bmj.k1674 · Cited by 275
Self-citationSex and gender in neurodevelopmental conditions
Bölte, S., Neufeld, J., Marschik, P. B., Williams, Z. J., Gallagher, L., & Lai, M.-C. (2023) · Nature Reviews Neurology · doi:10.1038/s41582-023-00774-6 · Cited by 249
Sex and gender impacts on the behavioural presentation and recognition of autism
Lai, M.-C., & Szatmari, P. (2020) · Current Opinion in Psychiatry · doi:10.1097/yco.0000000000000575 · Cited by 237
Genetics and genomics of autism spectrum disorder: embracing complexity
De Rubeis, S., & Buxbaum, J. D. (2015) · Human Molecular Genetics · doi:10.1093/hmg/ddv273 · Cited by 208
Genetics of autism spectrum disorder
Ramaswami, G., & Geschwind, D. H. (2018) · Handbook of clinical neurology · doi:10.1016/b978-0-444-63233-3.00021-x · Cited by 233
The EU-AIMS Longitudinal European Autism Project (LEAP): clinical characterisation
Charman, T., Loth, E., Tillmann, J., Crawley, D., Wooldridge, C., Goyard, D., Ahmad, J., Auyeung, B., Ambrosino, S., Banaschewski, T., et al. (2017) · Molecular Autism · doi:10.1186/s13229-017-0145-9 · Cited by 183
Subtyping cognitive profiles in Autism Spectrum Disorder using a Functional Random Forest algorithm
Feczko, E., Balba, N. M., Miranda-Dominguez, O., Cordova, M., Karalunas, S. L., Irwin, L., Demeter, D. V., Hill, A. P., Langhorst, B. H., Grieser Painter, J., et al. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2017.12.044 · Cited by 173
Self-citationChallenges Surrounding the Diagnosis of Autism in Children
Hus, Y., & Segal, O. (2021) · Neuropsychiatric Disease and Treatment · doi:10.2147/ndt.s282569 · Cited by 225
Toward Neurosubtypes in Autism
Hong, S., Vogelstein, J. T., Gozzi, A., Bernhardt, B. C., Yeo, B. T. T., Milham, M. P., & Martino, A. D. (2020) · Biological Psychiatry · doi:10.1016/j.biopsych.2020.03.022 · Cited by 175
Adaptive behavior in autism: Minimal clinically important differences on the Vineland‐II
Chatham, C., Taylor, K. I., Charman, T., D’ardhuy, X. L., Eule, E., Fedele, A., Hardan, A. Y., Loth, E., Murtagh, L., Rubido, M. D. V., et al. (2017) · Autism Research · doi:10.1002/aur.1874 · Cited by 181
Ameis, S. H., Lerch, J. P., Taylor, M. J., Lee, W., Viviano, J. D., Pipitone, J., Nazeri, A., Croarkin, P. E., Voineskos, A. N., Lai, M.-C., et al. (2016) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2016.15111435 · Cited by 155
Tillmann, J., Cáceres, A. S. J., Chatham, C., Crawley, D., Holt, R., Oakley, B. F. M., Banaschewski, T., Baron‐Cohen, S., Bölte, S., Buitelaar, J. K., et al. (2019) · Autism Research · doi:10.1002/aur.2081 · Cited by 164
Gabbay-Dizdar, N., Ilan, M., Meiri, G., Faroy, M., Michaelovski, A., Flusser, H., Menashe, I., Koller, J., Zachor, D. A., & Dinstein, I. (2021) · Autism · doi:10.1177/13623613211049011 · Cited by 150
Kim, S. H., Macari, S., Koller, J., & Chawarska, K. (2016) · Journal of Child Psychology and Psychiatry · doi:10.1111/jcpp.12448 · Cited by 160
A Deep Learning Approach to Predict Autism Spectrum Disorder Using Multisite Resting-State fMRI
Subah, F. Z., Deb, K., Dhar, P. K., & Koshiba, T. (2021) · Applied Sciences · doi:10.3390/app11083636 · Cited by 147
Autism and the Social Brain: The First-Year Puzzle
Elsabbagh, M., & Johnson, M. H. (2016) · Biological Psychiatry · doi:10.1016/j.biopsych.2016.02.019 · Cited by 136
Self-citationRakić, M., Cabezas, M., Kushibar, K., Oliver, A., & Lladó, X. (2020) · NeuroImage Clinical · doi:10.1016/j.nicl.2020.102181 · Cited by 140
Environmental enrichment as a therapy for autism: A clinical trial replication and extension.
Woo, C. C., Donnelly, J. H., Steinberg-Epstein, R., & Leon, M. (2015) · Behavioral Neuroscience · doi:10.1037/bne0000068 · Cited by 132
Scahill, L., Bearss, K., Lecavalier, L., Smith, T., Swiezy, N., Aman, M. G., Sukhodolsky, D. G., McCracken, C., Minshawi, N., Turner, K., et al. (2016) · Journal of the American Academy of Child & Adolescent Psychiatry · doi:10.1016/j.jaac.2016.05.001 · Cited by 123
Tillmann, J., Ashwood, K., Absoud, M., Bölte, S., Bonnet-Brilhault, F., Buitelaar, J. K., Calderoni, S., Calvo, R., Canal-Bedia, R., Canitano, R., et al. (2018) · Journal of Autism and Developmental Disorders · doi:10.1007/s10803-018-3510-4 · Cited by 121
The development of autistic social traits across childhood and adolescence in males and females
Mandy, W., Pellicano, L., St Pourcain, B., Skuse, D., & Heron, J. (2018) · Journal of Child Psychology and Psychiatry · doi:10.1111/jcpp.12913 · Cited by 117
Plitt, M., Barnes, K. A., Wallace, G. L., Kenworthy, L., & Martin, A. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1510098112 · Cited by 114
Masi, A., Breen, E. J., Alvares, G. A., Glozier, N., Hickie, I. B., Hunt, A. M., Hui, J., Beilby, J. P., Ravine, D., Wray, J. A., et al. (2017) · Molecular Autism · doi:10.1186/s13229-017-0176-2 · Cited by 117
Informant discrepancy defines discrete, clinically useful autism spectrum disorder subgroups
Lerner, M. D., Reyes, A. D. L., Drabick, D. A. G., Gerber, A. S., & Gadow, K. D. (2017) · Journal of Child Psychology and Psychiatry · doi:10.1111/jcpp.12730 · Cited by 107
Editorial Perspective: Longitudinal research in autism – introducing the concept of ‘chronogeneity’
Georgiades, S., Bishop, S. L., & Frazier, T. (2017) · Journal of Child Psychology and Psychiatry · doi:10.1111/jcpp.12690 · Cited by 100
Self-citationNeurodevelopmental heterogeneity and computational approaches for understanding autism
Jacob, S., Wolff, J. J., Steinbach, M. S., Doyle, C. B., Kumar, V., & Elison, J. T. (2019) · Translational Psychiatry · doi:10.1038/s41398-019-0390-0 · Cited by 107
Autism severity and its relationship to disability
Waizbard‐Bartov, E., FEIN, D. A., Lord, C., & Amaral, D. G. (2023) · Autism Research · doi:10.1002/aur.2898 · Cited by 119
Chawner, S. J. R. A., Doherty, J. L., Anney, R. J. L., Antshel, K. M., Bearden, C. E., Bernier, R., Chung, W. K., Clements, C. C., Curran, S. R., Cuturilo, G., et al. (2021) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2020.20010015 · Cited by 95
Structure and function of neonatal social communication in a genetic mouse model of autism
Takahashi, T., Okabe, S., Broin, P. Ó., Nishi, A., Ye, K., Beckert, M., Izumi, T., Machida, A., Kang, G., Abe, S., et al. (2015) · Molecular Psychiatry · doi:10.1038/mp.2015.190 · Cited by 94
Moradi, E., Khundrakpam, B. S., Lewis, J. D., Evans, A. C., & Tohka, J. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.09.049 · Cited by 89
School participation of autistic youths: The influence of youth, family and school factors
Li, B., Heyne, D. A., Scheeren, A. M., Blijd-Hoogewys, E. M. A., & Rieffe, C. J. (2024) · Autism · doi:10.1177/13623613231225490 · Cited by 93
Concordance of the Vineland Adaptive Behavior Scales, second and third editions
Farmer, C., Adedipe, D., Bal, V. H., Chlebowski, C., & Thurm, A. E. (2019) · Journal of Intellectual Disability Research · doi:10.1111/jir.12691 · Cited by 91
Autism spectrum disorder ( ASD ) and its perioperative management
Taghizadeh, N., Davidson, A. J., Williams, K. J., & Story, D. (2015) · Pediatric Anesthesia · doi:10.1111/pan.12732 · Cited by 94
Unsupervised data-driven stratification of mentalizing heterogeneity in autism
Lombardo, M. V., Lai, M., Bonnie Auyeung, B., Holt, R., Allison, C. L., Smith, P. L., Chakrabarti, B., Ruigrok, A. N. V., Suckling, J., Bullmore, E. T., et al. (2016) · Scientific Reports · doi:10.1038/srep35333 · Cited by 94
Lai, M.-C., Lin, H.-Y., & Ameis, S. H. (2022) · Current Opinion in Psychiatry · doi:10.1097/yco.0000000000000770 · Cited by 86
Ameis, S. H., Blumberger, D. M., Croarkin, P. E., Mabbott, D., Lai, M., Desarkar, P., Szatmári, P., & Daskalakis, Z. J. (2020) · Brain stimulation · doi:10.1016/j.brs.2020.01.007 · Cited by 92
Allen, S., Smith, I. M., Duku, E., Vaillancourt, T., Szatmári, P., Bryson, S., Fombonne, E. J., Volden, J., Waddell, C., Zwaigenbaum, L., et al. (2015) · Journal of Pediatric Psychology · doi:10.1093/jpepsy/jsv006 · Cited by 87
Self-citationUsing the tools of genetic epidemiology to understand sex differences in neuropsychiatric disorders
Merikangas, A. K., & Almasy, L. (2020) · Genes, Brain and Behavior · doi:10.1111/gbb.12660 · Cited by 82
Trajectories of Autism Symptom Severity Change During Early Childhood
Waizbard‐Bartov, E., Ferrer, E. E., Young, G. S., Heath, B. E., Rogers, S. J., Nordahl, C. W., Solomon, M., & Amaral, D. G. (2020) · Journal of Autism and Developmental Disorders · doi:10.1007/s10803-020-04526-z · Cited by 86
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Bieleninik, Ł., Posserud, M.-B. R., Geretsegger, M., Thompson, G. A., Elefant, C., & Gold, C. (2017) · PLoS ONE · doi:10.1371/journal.pone.0183160 · Cited by 91
Rodgers, M., Marshall, D. C., Simmonds, M. C., Couteur, A. S. L., Biswas, M., Wright, K. E., Rai, D., Palmer, S., Stewart, L. A., & Hodgson, R. M. (2020) · Health Technology Assessment · doi:10.3310/hta24350 · Cited by 74
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Patel, S., Dale, R. C., Rose, D. R., Heath, B. E., Nordahl, C. W., Rogers, S. J., Guastella, A. J., & Ashwood, P. (2020) · Translational Psychiatry · doi:10.1038/s41398-020-00976-2 · Cited by 72
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Farmer, C., Swineford, L., Swedo, S. E., & Thurm, A. (2018) · Journal of Neurodevelopmental Disorders · doi:10.1186/s11689-017-9222-9 · Cited by 69
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Visser, J. C., Rommelse, N. N. J., Lappenschaar, M. G. A., Servatius-Oosterling, I. J., Greven, C. U., & Buitelaar, J. K. (2017) · Journal of the American Academy of Child & Adolescent Psychiatry · doi:10.1016/j.jaac.2017.05.022 · Cited by 64
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Jacobs, G. R., Voineskos, A. N., Hawco, C. S., Stefanik, L., Forde, N. J., Dickie, E. W., Lai, M., Szatmári, P., Schachar, R. J., Crosbie, J., et al. (2020) · Neuropsychopharmacology · doi:10.1038/s41386-020-00902-6 · Cited by 60
Conlon, O., Volden, J., Smith, I., Duku, E., Zwaigenbaum, L., Waddell, C., Szatmari, P., Mirenda, P., Vaillancourt, T., Bennett, T., et al. (2019) · Journal of Autism and Developmental Disorders · doi:10.1007/s10803-018-03873-2 · Cited by 54
Self-citationIdentifying autism symptom severity trajectories across childhood
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Baghdadli, A., Michelon, C., Pernon, É., Picot, M., Miot, S., Sonié, S., Rattaz, C., & Mottron, L. (2018) · Autism Research · doi:10.1002/aur.2022 · Cited by 62
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Díaz‐Caneja, C. M., State, M. W., Hagerman, R. J., Jacquemont, S., Marín, Ó., Bagni, C., Umbricht, D., Simonoff, E. A., Andres-Trelles, F., Kaale, A., et al. (2021) · European Neuropsychopharmacology · doi:10.1016/j.euroneuro.2021.02.020 · Cited by 56
Waizbard‐Bartov, E., & Miller, M. R. (2022) · Clinical Psychology Review · doi:10.1016/j.cpr.2022.102230 · Cited by 56
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Peverill, S., Smith, I. M., Duku, E., Szatmári, P., Mirenda, P., Vaillancourt, T., Volden, J., Zwaigenbaum, L., Bennett, T. A., Elsabbagh, M., et al. (2019) · Journal of Pediatric Psychology · doi:10.1093/jpepsy/jsz033 · Cited by 56
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Searles, V. B., Wang, B., & State, M. W. (2020) · Neuropsychopharmacology · doi:10.1038/s41386-020-0768-y · Cited by 53
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Vlassakova, B. G., & Emmanouil, D. E. (2016) · Current Opinion in Anaesthesiology · doi:10.1097/aco.0000000000000325 · Cited by 55
Mensi, M. M., Rogantini, C., Marchesi, M., Borgatti, R., & Chiappedi, M. A. (2021) · Nutrients · doi:10.3390/nu13062036 · Cited by 50
Zheng, S., Hume, K., Able, H., Bishop, S. L., & Boyd, B. A. (2020) · Autism Research · doi:10.1002/aur.2263 · Cited by 56
Georgiades, S., Tait, P. A., McNicholas, P. D., Duku, E., Zwaigenbaum, L., Smith, I. M., Bennett, T. A., Elsabbagh, M., Kerns, C. M., Mirenda, P., et al. (2021) · Journal of Autism and Developmental Disorders · doi:10.1007/s10803-021-04949-2 · Cited by 50
Self-citationShi, B., Wu, W., Dai, M., Zeng, J., Luo, J., Cai, L., Wan, B., & Jin, J. (2021) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2021.691148 · Cited by 54
Gao, Y., Linke, A. C., Keehn, R. J. J., Punyamurthula, S., Jahedi, A., Gates, K. M., Fishman, I., & Müller, R. (2019) · Autism Research · doi:10.1002/aur.2171 · Cited by 52
Tunç, B., Yankowitz, L., Parker, D., Alappatt, J. A., Pandey, J., Schultz, R., & Verma, R. (2019) · Molecular Autism · doi:10.1186/s13229-019-0301-5 · Cited by 47
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Self-citationDavico, C., Marcotulli, D., Cudia, V. F., Arletti, L., Ghiggia, A., Svevi, B., Faraoni, C., Amianto, F., Ricci, F., & Vitiello, B. (2022) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2022.846146 · Cited by 46
Flanagan, H. E., Smith, I. M., Vaillancourt, T., Duku, E., Szatmári, P., Bryson, S. E., Fombonne, E. J., Mirenda, P., Roberts, W., Volden, J., et al. (2015) · Journal of Autism and Developmental Disorders · doi:10.1007/s10803-015-2433-6 · Cited by 46
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Metadata
- Authors
- Szatmari, P., Georgiades, S., Duku, E., Bennett, T. A., Bryson, S., Fombonne, E., Mirenda, P., Roberts, W., Smith, I. M., Vaillancourt, T., Volden, J., Waddell, C., Zwaigenbaum, L., Elsabbagh, M., & Thompson, A.
- Affiliations
- Centre for Addiction and Mental Health, The Hospital for Sick Children, University of Toronto, Toronto, Ontario, Canada
- McMaster University (CA)
- Dalhousie University (CA)
- Oregon Health & Science University (US)
- University of British Columbia (CA)
- University of Toronto (CA)
- University of Ottawa (CA)
- University of Alberta (CA)
- Simon Fraser University (CA)
- McGill University (CA)
- ORCID
- Venue
- JAMA Psychiatry
- Publisher
- American Medical Association (AMA)
- Published
- 2015-03-01
- Volume
- 72
- Issue
- 3
- Pages
- 276
- ISSN
- 2168-622X (ISSN-L)
- OpenAlex
- W2120646369
- Cited by
- 322
- References
- 39
- Citations by year
- 2026: 26 · 2025: 23 · 2024: 26 · 2023: 33 · 2022: 29 · 2021: 36 · 2020: 38 · 2019: 36 · 2018: 26 · 2017: 27 · 2016: 11 · 2015: 10
- FWCI
- 14.82
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- JAMA Psychiatry (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Autism Speaks
- Sinneave Family Foundation
- Alberta Innovates
- Canadian Institutes of Health Research
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Autism Spectrum Disorder Research
- Health Sciences › Medicine › Psychiatry and Mental health › Child Nutrition and Feeding Issues
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetics and Neurodevelopmental Disorders
- Keywords
- autism spectrum disorder, preschool children, symptom severity, adaptive behavior, developmental trajectories, trajectory heterogeneity, autism phenotype, sex differences, developmental outcomes
- MeSH terms
- Adaptation, Psychological, Canada, Child, Child Development, Child Development Disorders, Pervasive, Child, Preschool, Female, Humans, Longitudinal Studies, Male, Severity of Illness Index
About these checks
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