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Gentles SJ, Ng-Cordell EC, Hunsche MC, McVey AJ, Bednar ED, DeGroote MG, Chen YJ, Duku E, Kerns CM, Banfield L, Szatmari P, Georgiades S. Trajectory research in children with an autism diagnosis: A scoping review. AUTISM : THE INTERNATIONAL JOURNAL OF RESEARCH AND PRACTICE 2024; 28:540-564. [PMID: 37194194 PMCID: PMC10913344 DOI: 10.1177/13623613231170280] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/18/2023]
Abstract
LAY ABSTRACT The types of outcomes studied in children on the autism spectrum include clinical characteristics, such as social functioning, communication, language, or autism symptoms. Research that measures these outcomes at multiple timepoints is useful to improve our understanding of what to expect as children develop. In trajectory studies, researchers assess outcomes at three or more timepoints. This method has advantages over two-timepoint studies because it allows researchers to describe changes in the speed of development, such as accelerations, plateaus, or slowdowns. We identified and reviewed 103 published trajectory studies in children (to age 18 years) with an autism diagnosis. Importantly, we did not include studies of treatments or their effects, nor did we summarize the results of studies. Instead, this review summarizes the characteristics of the available published research, including the methods used, the many different outcomes that have been studied over time and the ages over which they have been studied. This summary may be of interest to autistic people and caregivers (parents) who want to know about the existence of research that provides answers about what to expect during an autistic child's development. We have recommended that future trajectory research efforts try to make up for the lack of studies from low- and middle-income countries; that more attention is given to the following outcomes that are meaningful to caregivers and autistic people; and to try to fill in the age gaps where more outcome-specific data are needed.
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Nishimura T, Kato T, Okumura A, Harada T, Iwabuchi T, Rahman MS, Hirota T, Takahashi M, Adachi M, Kuwabara H, Takagai S, Nomura Y, Takahashi N, Senju A, Tsuchiya KJ. Trajectories of Adaptive Behaviors During Childhood in Females and Males in the General Population. Front Psychiatry 2022; 13:817383. [PMID: 35401255 PMCID: PMC8983934 DOI: 10.3389/fpsyt.2022.817383] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Accepted: 02/28/2022] [Indexed: 11/13/2022] Open
Abstract
Little is known about the trajectory patterns and sex differences in adaptive behaviors in the general population. We examined the trajectory classes of adaptive behaviors using a representative sample and examined whether the class structure and trajectory patterns differed between females and males. We further explored sex differences in neurodevelopmental traits in each latent class. Participants (n = 994) were children in the Hamamatsu Birth Cohort for Mothers and Children (HBC Study)-a prospective birth cohort study. Adaptive behaviors in each domain of communication, daily living skills, and socialization were evaluated at five time points when participants were 2.7, 3.5, 4.5, 6, and 9 years old using the Vineland Adaptive Behavior Scales-Second Edition. Parallel process multigroup latent class growth analysis extracted sex-specific trajectory classes. Neurodevelopmental traits of children at age 9, autistic traits, attention deficit hyperactivity disorder (ADHD) traits, and cognitive ability were examined for females and males in each identified class. A 4-class model demonstrated the best fit. Moreover, a 4-class model that allowed for differences in class probabilities and means of growth parameters between females and males provided a better fit than a model assuming no sex differences. In the communication domain, females scored higher than their male counterparts in all four classes. In the daily living skills and socialization domains, the two higher adaptive classes (Class 1: females, 18.6%; males, 17.8%; Class 2: females, 48.8%; males, 49.8%) had similar trajectories for males and females, whereas in the two lower adaptive behavior classes (Class 3: females, 27.5%; males, 29.4%; Class 4: females, 5.1%; males, 3.0%), females had higher adaptive scores than their male counterparts. In Class 4, females were more likely to have autistic and ADHD traits exceeding the cutoffs, while males were more likely to have below-average IQ. Different trajectories in females and males suggest that adaptive skills may require adjustment based on the sex of the child, when standardizing scores, in order to achieve better early detection of skill impairment.
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Affiliation(s)
- Tomoko Nishimura
- Research Center for Child Mental Development, Hamamatsu University School of Medicine, Hamamatsu, Japan.,United Graduate School of Child Development, Hamamatsu University School of Medicine, Hamamatsu, Japan
| | - Takeo Kato
- Research Center for Child Mental Development, Hamamatsu University School of Medicine, Hamamatsu, Japan.,United Graduate School of Child Development, Hamamatsu University School of Medicine, Hamamatsu, Japan
| | - Akemi Okumura
- Research Center for Child Mental Development, Hamamatsu University School of Medicine, Hamamatsu, Japan.,United Graduate School of Child Development, Hamamatsu University School of Medicine, Hamamatsu, Japan
| | - Taeko Harada
- Research Center for Child Mental Development, Hamamatsu University School of Medicine, Hamamatsu, Japan.,United Graduate School of Child Development, Hamamatsu University School of Medicine, Hamamatsu, Japan
| | - Toshiki Iwabuchi
- Research Center for Child Mental Development, Hamamatsu University School of Medicine, Hamamatsu, Japan.,United Graduate School of Child Development, Hamamatsu University School of Medicine, Hamamatsu, Japan
| | - Md Shafiur Rahman
- Research Center for Child Mental Development, Hamamatsu University School of Medicine, Hamamatsu, Japan.,United Graduate School of Child Development, Hamamatsu University School of Medicine, Hamamatsu, Japan
| | - Tomoya Hirota
- Department of Psychiatry and Behavioral Sciences, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, United States.,Department of Clinical Psychological Science, Graduate School of Health Sciences, Hirosaki University, Hirosaki, Japan
| | - Michio Takahashi
- Department of Clinical Psychological Science, Graduate School of Health Sciences, Hirosaki University, Hirosaki, Japan
| | - Masaki Adachi
- Department of Clinical Psychological Science, Graduate School of Health Sciences, Hirosaki University, Hirosaki, Japan
| | - Hitoshi Kuwabara
- Research Center for Child Mental Development, Hamamatsu University School of Medicine, Hamamatsu, Japan.,Faculty of Medicine, Saitama Medical University, Saitama, Japan
| | - Shu Takagai
- Department of Child and Adolescent Psychiatry, Hamamatsu University School of Medicine, Hamamatsu, Japan
| | - Yoko Nomura
- Research Center for Child Mental Development, Hamamatsu University School of Medicine, Hamamatsu, Japan.,Queens College and Graduate Center, City University of New York, New York, NY, United States
| | - Nagahide Takahashi
- Research Center for Child Mental Development, Hamamatsu University School of Medicine, Hamamatsu, Japan.,Department of Child and Adolescent Psychiatry, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Atsushi Senju
- Research Center for Child Mental Development, Hamamatsu University School of Medicine, Hamamatsu, Japan.,United Graduate School of Child Development, Hamamatsu University School of Medicine, Hamamatsu, Japan
| | - Kenji J Tsuchiya
- Research Center for Child Mental Development, Hamamatsu University School of Medicine, Hamamatsu, Japan.,United Graduate School of Child Development, Hamamatsu University School of Medicine, Hamamatsu, Japan
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Riglin L, Wootton RE, Thapar AK, Livingston LA, Langley K, Collishaw S, Tagg J, Smith GD, Stergiakouli E, Tilling K, Thapar A. Variable Emergence of Autism Spectrum Disorder Symptoms From Childhood to Early Adulthood. Am J Psychiatry 2021; 178:752-760. [PMID: 33900814 PMCID: PMC7611492 DOI: 10.1176/appi.ajp.2020.20071119] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
OBJECTIVE Autism spectrum disorder (ASD) is currently considered an early-onset neurodevelopmental condition. Follow-up studies of clinic-ascertained autism suggest that autistic symptoms typically decline with age, although symptom improvement is limited for some. To date there have been no population-based prospective studies investigating the natural history of autistic symptoms from childhood to adulthood. The aim of this study was to characterize the development and heterogeneity of autistic symptoms in a population-based cohort from childhood to age 25. METHODS Data were analyzed in a prospective U.K. population-based cohort (ALSPAC). Trajectories were derived using five assessments of the parent-rated Social and Communication Disorders Checklist (SCDC) spanning ages 7-25. Additional measures were used to validate symptom trajectories. RESULTS Three distinct SCDC symptom trajectory classes were identified: low (88.5%), declining (5.0%), and late-emerging (6.5%). Both the declining and late-emerging trajectory classes were associated with child and adult ASD measures, low IQ, communication problems, peer problems, and worse adult functioning compared with the low trajectory class. Male sex was associated with a higher likelihood of being in the declining trajectory class (odds ratio=2.84, 95% CI=2.19, 3.69). This sex difference was not observed in the late-emerging class (odds ratio=1.00, 95% CI=0.80, 1.24) compared with the low trajectory class. CONCLUSIONS ASD symptom levels that emerged early tended to decline across development, although impairment was still present in adulthood for some. For others, autistic symptoms emerged across adolescence and adulthood. This challenges our current understanding that ASD symptoms inevitably first manifest early in development.
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Affiliation(s)
- Lucy Riglin
- Division of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, UK
| | - Robyn E Wootton
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Ajay K Thapar
- Division of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, UK
| | | | - Kate Langley
- Division of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, UK,School of Psychology, Cardiff University, UK
| | - Stephan Collishaw
- Division of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, UK
| | - Jack Tagg
- Division of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, UK
| | | | - Evie Stergiakouli
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Kate Tilling
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Anita Thapar
- Division of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, UK,Corresponding author. Division of Psychological Medicine and Clinical Neurosciences, Cardiff University School of Medicine, Hadyn Ellis Building, Maindy Road, Cathays, Cardiff, CF24 4HQ. Tel: +442920688478.
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Agelink van Rentergem JA, Deserno MK, Geurts HM. Validation strategies for subtypes in psychiatry: A systematic review of research on autism spectrum disorder. Clin Psychol Rev 2021; 87:102033. [PMID: 33962352 DOI: 10.1016/j.cpr.2021.102033] [Citation(s) in RCA: 36] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2020] [Revised: 02/14/2021] [Accepted: 04/14/2021] [Indexed: 12/11/2022]
Abstract
Heterogeneity within autism spectrum disorder (ASD) is recognized as a challenge to both biological and psychological research, as well as clinical practice. To reduce unexplained heterogeneity, subtyping techniques are often used to establish more homogeneous subtypes based on metrics of similarity and dissimilarity between people. We review the ASD literature to create a systematic overview of the subtyping procedures and subtype validation techniques that are used in this field. We conducted a systematic review of 156 articles (2001-June 2020) that subtyped participants (range N of studies = 17-20,658), of which some or all had an ASD diagnosis. We found a large diversity in (parametric and non-parametric) methods and (biological, psychological, demographic) variables used to establish subtypes. The majority of studies validated their subtype results using variables that were measured concurrently, but were not included in the subtyping procedure. Other investigations into subtypes' validity were rarer. In order to advance clinical research and the theoretical and clinical usefulness of identified subtypes, we propose a structured approach and present the SUbtyping VAlidation Checklist (SUVAC), a checklist for validating subtyping results.
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Affiliation(s)
- Joost A Agelink van Rentergem
- Department of Psychology, University of Amsterdam, Amsterdam, the Netherlands; Dutch Autism & ADHD Research Center, the Netherlands.
| | - Marie K Deserno
- Department of Psychology, University of Amsterdam, Amsterdam, the Netherlands; Dutch Autism & ADHD Research Center, the Netherlands
| | - Hilde M Geurts
- Department of Psychology, University of Amsterdam, Amsterdam, the Netherlands; Dutch Autism & ADHD Research Center, the Netherlands; Dr. Leo Kannerhuis, the Netherlands
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McIntyre NS, Tomaszewski B, Hume KA, Odom SL. Stability of Literacy Profiles of Adolescents With Autism Spectrum Disorder and Associations With Stakeholder Perceptions of Appropriate High School Support Needs. Lang Speech Hear Serv Sch 2021; 52:209-224. [PMID: 33464986 DOI: 10.1044/2020_lshss-20-00016] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
Abstract
Purpose For many individuals with autism spectrum disorder (ASD), postsecondary outcomes are poor. This may be due to insufficient academic supports, particularly with regard to literacy skills, during high school. More information is needed about skill profiles so that we can better differentiate support for students with varying social, communication, cognitive, and academic proficiency levels. This study was designed to (a) identify unique literacy profiles of high school students with ASD, (b) assess profile stability over time, (c) identify predictors of profile membership, and (d) analyze stakeholder reports of required school support intensity. Method Participants were a diverse sample of high school students with ASD, 14-21 years old (N = 544), their parents, and their teachers who participated in a randomized controlled trial of a comprehensive treatment model for high school students with ASD. Standardized measures were administered to assess nonverbal IQ, autism symptomatology, language/adaptive communication, reading comprehension, academic knowledge, and parent/teacher report of school support needs intensity. Latent transition analysis was conducted to examine sample heterogeneity and to explore the stability of the profiles. Associations between profiles and reports of support intensity were examined. Results Four literacy profiles were identified that were stable over 2 years: Emergent Literacy/Comprehensive Support, Low Literacy/Intensive Support, Average Literacy/Moderate Support, and Average Literacy/Limited Support. Parent and teacher reports of school support intensity generally aligned with the profiles. Conclusions These analyses provide insight into the diverse literacy and support needs in ASD. Implications for practice and the role of speech-language pathologists in assessment and intervention are discussed. Supplemental Material https://doi.org/10.23641/asha.13495119.
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