Évaluation des professeurs de langue dans les classes d'enseignement général et spécialisé au service des élèves autistes du primaire

Aperçu: G.M.

Cette étude a examiné comment les enseignants et les paraprofessionnels de 126 classes d'enseignement général et spécialisé de la maternelle à la deuxième année ont parlé avec leurs 194 élèves autistes, et en outre, comment les caractéristiques individuelles des élèves en termes de langage, de symptômes de l'autisme et de capacités sociales ont influencé cette conversation. 

À l'aide de méthodes d'observation systématiques et d'analyses factorielles, nous avons identifié un modèle unidimensionnel de langage des enseignants pour les classes d'enseignement général et spécialisé, tout en observant des différences entre les paramètres, avec plus de langage observé dans les classes d'enseignement spécialisé, dont une grande partie comprenait des directives et des questions fermées. 

Le vocabulaire réceptif des élèves expliquait une quantité significative de variance dans le langage des enseignants au-delà de sa covariance partagée avec les troubles sociaux et les problèmes de comportement dans les classes d'enseignement général, mais n'était pas significatif dans les classes d'enseignement spécialisé. Les implications pour la recherche sont discutées.

. 2021 Jun 9.   doi: 10.1007/s10803-021-05115-4. 

Evaluating Teacher Language Within General and Special Education Classrooms Serving Elementary Students with Autism

Nicole Sparapani  ^{1   2} , Vanessa P Reinhardt  ^{3   4} , Jessica L Hooker  ⁴ , Lindee Morgan  ^{4   5} , Christopher Schatschneider  ⁶ , Amy M Wetherby  ⁴

Affiliations

• PMID: 34106392
• DOI: 10.1007/s10803-021-05115-4

Abstract

This study examined how teachers and paraprofessionals in 126 kindergarten-second grade general and special education classrooms talked with their 194 students with autism, and further, how individual student characteristics in language, autism symptoms, and social abilities influenced this talk. Using systematic observational methods and factor analysis, we identified a unidimensional model of teacher language for general and special education classrooms yet observed differences between the settings, with more language observed in special education classrooms-much of which included directives and close-ended questions. Students' receptive vocabulary explained a significant amount of variance in teacher language beyond its shared covariance with social impairment and problem behavior in general education classrooms but was non-significant within special education classrooms. Research implications are discussed.

Keywords: Autism; Autism spectrum disorder; Measurement invariance; Student characteristics; Teacher language.

References

1. 1. American Psychiatric Association. (2000). Diagnostic and statistical manual of mental disorders; Volume IV-TR. American Psychiatric Association.
2. 1. Bronfenbrenner, U., & Morris, P. A. (2006). The bioecological model of human development. In R. M. Lerner, & W. Damon (Eds.), Handbook of child psychology: Theoretical models of human development (6th ed., Vol. 1, pp. 793–828). Wiley.
3. 1. Brownell, R. (2000). Expressive One-Word Picture Vocabulary Test-third edition (EOWPVT). Academic Therapy Publications.
4. 1. Burchinal, M. R., Howes, C., Pianta, R., Bryant, D., Early, D., Clifford, R., et al. (2008). Predicting child outcomes at the end of kindergarten from the quality of pre-kindergarten teacher–child interactions and instruction. Applied Development Science, 12, 140–153. - DOI
5. 1. Connor, C. M. (2016). A lattice model of the development of reading comprehension. Child Development Perspectives, 10(4), 269–274. - DOI
6. 1. Connor, C. M., Kelcey, B., Sparapani, N., Petscher, P., Siegal, S., Adams, A., Hwang, J., & Carlisle, J. (2020). Predicting second and third graders’ reading comprehension gains: Observing students’ and classmates talk during literacy instruction using COLT. Scientific Studies of Reading. https://doi.org/10.1080/10888438.2019.1698583 - DOI - PubMed
7. 1. Curby, T. W., Rimm-Kaufman, S. E., & Ponitz, C. C. (2009). Teacher–child interactions and children’s achievement trajectories across kindergarten and first grade. Journal of Educational Psychology, 101(4), 912–925. - DOI
8. 1. de Kruif, R. E., McWilliam, R. A., Ridley, S. M., & Wakely, M. B. (2000). Classification of teachers’ interaction behaviors in early childhood classrooms. Early Childhood Research Quarterly, 15(2), 247–268. - DOI
9. 1. DeWitt, J., & Hohenstein, J. (2010). School trips and classroom lessons: An investigation into teacher–student talk in two settings. Journal of Research in Science Teaching: The Official Journal of the National Association for Research in Science Teaching, 47(4), 454–473. - DOI
10. 1. Dobbs, J., & Arnold, D. H. (2009). Relationship between preschool teachers’ reports of children’s behavior and their behavior toward those children. School Psychology Quarterly, 24(2), 95. - DOI
11. 1. Downer, J. T., Sabol, T., & Hamre, B. K. (2010). Teacher-child interactions in the classroom: Toward a theory of within- and cross-domain links to children’s developmental outcomes. Early Education and Development, 21, 699–723. - DOI
12. 1. Duke, N. K., Pearson, P. D., Strachan, S. L., & Billman, A. K. (2011). Essential elements of fostering and teaching reading comprehension. In S. J. Samuels, & A. E. Farstrup (Eds.), What research has to say about reading instruction (4th ed.). International Reading Association.
13. 1. Dunn, L. M., & Dunn, D. M. (2007). PPVT-4: Peabody Picture Vocabulary Test. Pearson Assessments.
14. 1. Dykstra, J. R., Sabatos-DeVito, M. G., Irvin, D. W., Boyd, B. A., Hume, K. A., & Odom, S. L. (2013). Using the Language Environment Analysis (LENA) system in preschool classrooms with children with autism spectrum disorders. Autism, 17(5), 582–594. - DOI
15. 1. Fleury, V. P., Hedges, S., Hume, K., Browder, D. M., Thompson, J. L., Fallin, K., El Zein, F., Reutebuch, C. K., & Vaughn, S. (2014). Addressing the academic needs of adolescents with autism spectrum disorder in secondary education. Remedial and Special Education, 35(2), 68–79. https://doi.org/10.1177/0741932513518823 - DOI
16. 1. Gast, S. D., Holland-Coviello, R., Welsh, J., Eicher-Catt, D. L., & Gill, S. (2010). Development subcontexts in head start classrooms: Distinctive patterns of teacher talk during free play, mealtime, and book reading. Early Education and Development, 72, 37–41.
17. 1. Girolametto, L., & Weitzman, E. (2002). Responsiveness of child care providers in interactions with toddlers and preschoolers. Language, Speech, and Hearing Services in Schools, 33, 268–281. https://doi.org/10.1044/0161-1461(2002/022) - DOI - PubMed
18. 1. Gotham, K., Pickles, A., & Lord, C. (2009). Standardizing ADOS scores for a measure of severity in autism spectrum disorders. Journal of Autism and Developmental Disorders, 39(5), 693–705. - DOI
19. 1. Hamre, B., Hatfield, B., Pianta, R., & Jamil, F. (2014). Evidence for general and domain-specific elements of teacher–child interactions: Associations with preschool children’s development. Child Development, 85(3), 1257–1274. - DOI
20. 1. Hamre, B. K., & Pianta, R. C. (2005). Can instructional and emotional support in the first-grade classroom make a difference for children at risk of school failure. Child Development, 76, 949–967. - DOI
21. 1. Hamre, B. K., & Pianta, R. C. (2007). Learning opportunities in preschool and early elementary classrooms. In R. C. Pianta, M. J. Cox, & K. L. Snow (Eds.), School readiness and the transition to kindergarten in the era of accountability (p. 49–83). Paul H Brookes Publishing.
22. 1. Hamre, B. K., Pianta, R. C., Downer, J. T., DeCoster, J., Mashburn, A. J., Jones, S. M., Brown, J. L., Cappella, E., Atkins, M., Rivers, S. E., Brackett, M. A., & Hamagami, A. (2013). Teaching through interactions: Testing a developmental framework of teacher effectiveness in over 4,000 classrooms. The Elementary School Journal, 113(4), 461–487. - DOI
23. 1. Hestenes, L. L., Cassidy, D. J., & Niemeyer, J. (2004). A microanalysis of teachers’ verbalizations in inclusive classrooms. Early Education and Development, 15(1), 23–38. - DOI
24. 1. Howes, C., Burchinal, M., Pianta, R., Bryant, D., Early, D., Clifford, R., & Oscar, B. (2008). Ready to learn? Children’s pre-academic achievement in pre-kindergarten programs. Early Childhood Research Quarterly, 23(1), 27–50. - DOI
25. 1. Hus, V., Gotham, K., & Lord, C. (2014). Standardizing ADOS domain scores: Separating severity of social affectand restricted and repetitive behaviors. Journal of Autism and Developmental Disorders, 44(10), 2400–2412. https://doi.org/10.1007/s10803-012-1719-1 - DOI
26. 1. Irvin, D. W., Boyd, B. A., & Odom, S. L. (2015). Child and setting characteristics affecting the adult talk directed at preschoolers with autism spectrum disorder in the inclusive classroom. Autism, 19(2), 223–234. https://doi.org/10.1177/1362361313517398 - DOI - PubMed
27. 1. Irvin, D. W., Hume, K., Boyd, B. A., McBee, M. T., & Odom, S. L. (2013). Child and classroom characteristics associated with the adult language provided to preschoolers with autism spectrum disorder. Research in Autism Spectrum Disorders, 7(8), 947–955. - DOI
28. 1. Jadallah, M., Anderson, R. C., Nguyen-Jahiel, K., Miller, B. W., Kim, I. H., Kuo, L. J., Dong, T., & Wu, X. (2011). Influence of a teacher’s scaffolding moves during child-led small-group discussions. American Educational Research Journal, 48(1), 194–230. - DOI
29. 1. Jones, N. (2015). "Teachers' perceptions of autism spectrum disorder: An analysis of the relationship among teachers' knowledge, exposure, and attitudes". PCOM Psychology Dissertations. 350. http://digitalcommons.pcom.edu/psychology_dissertations/350
30. 1. Keen, D., Sigafoos, J., & Woodyatt, G. (2005). Teacher responses to the communicative attempts of children with autism. Journal of Developmental and Physical Disabilities, 17(1), 19–33. - DOI
31. 1. Kline, R. B. (2016). Principles and practice of structural equation modeling (3rd ed.). A Division of Guilford Publications Inc.
32. 1. Koenen, A. K., Vervoort, E., Kelchtermans, G., Verschueren, K., & Spilt, J. L. (2019). Teacher sensitivity in interaction with individual students: The role of teachers’ daily negative emotions. European Journal of Special Needs Education, 34(4), 514–529. - DOI
33. 1. Lindsay, S., Proulx, M., Thomson, N., & Scott, H. (2013). Educators’ challenges of including children with autism spectrum disorder in mainstream classrooms. International Journal of Disability, Development and Education, 60(4), 347–362. https://doi.org/10.1080/1034912X.2013.846470 - DOI
34. 1. Liu, Y. (2008). Teacher–student talk in Singapore Chinese language classrooms: A case study of initiation/response/follow-up (IRF). Asia Pacific Journal of Education, 28(1), 87–102. - DOI
35. 1. Maenner, M., Shaw, K., Baio, J., et al. (2020). Prevalence of autism spectrum disorder among children aged 8 years—ADDM Network, 11 sites, United States, 2016. Morbidity and Mortality Weekly Report (MMWR), 63(2), 1–21.
36. 1. Mashburn, A. J., Pianta, R. C., Hamre, B. K., Downer, J. T., Barbarin, O., Bryant, D., Burchinal, M., Early, D. M., & Howes, C. (2008). Measures of classroom quality in prekindergarten and children’s development of academic, language, and social skills. Child Development, 79, 732–749. https://doi.org/10.1111/j.1467-8624.2008.01154.x - DOI - PubMed
37. 1. McWilliam, R. A., de Kruif, R. E., & Zulli, R. A. (2002). The observed construction of teaching: Four contexts. Journal of Research in Childhood Education, 16(2), 148–161. - DOI
38. 1. Mercer, N. (1996). The quality of talk in children’s collaborative activity in the classroom. Learning and Instruction, 6(4), 359–377. - DOI
39. 1. Milburn, T. F., Girolametto, L., Weitzman, E., & Greenberg, J. (2014). Enhancing preschool educators’ ability to facilitate conversations during shared book reading. Journal of Early Childhood Literacy, 14(1), 105–140. - DOI
40. 1. Mirenda, P. L., & Donnellan, A. M. (1986). Effects of adult interaction style on conversational behavior in students with severe communication problems. Language, Speech, and Hearing Services in Schools, 17(2), 126–141. - DOI
41. 1. Morgan, L., Hooker, J. L., Sparapani, N., Rinehardt, V., Schatschneider, C., & Wetherby, A. (2018). Cluster randomized trial of the classroom SCERTS intervention for students with autism spectrum disorder. Journal of Consulting and Clinical Psychology, 86(7), 631–644. - DOI
42. 1. Muthén, L. K., & Muthén, B. O. (1998–2017). Mplus user’s guide (8th ed.). Muthén & Muthén.
43. 1. O’Connor, E. (2010). Instructor-child relationships as dynamic systems. Journal of School Psychology, 48, 187–218. https://doi.org/10.1016/j.jsp.2010.01.001 - DOI - PubMed
44. 1. Partee, A. M., Hamre, B. K., & Williford, A. P. (2020). Examining the role of preschool classrooms’ behavioral composition as a predictor of the quality of teacher–child interactions. Early Education and Development, 31(6), 873–891. - DOI
45. 1. Pianta, R. C. (2016). Teacher-student interactions. Policy Insights from the Behavioral and Brain Sciences, 3(1), 98–105. https://doi.org/10.1177/2372732215622457 - DOI
46. 1. Pianta, R. C., La Paro, K. M., & Hamre, B. K. (2008). Classroom Assessment Scoring System (CLASS). Brookes.
47. 1. Qian, X. (2018). Differences in teachers verbal responsiveness to groups of children with ASD who vary in cognitive and language abilities. Journal of Intellectual Disability Research, 62(6), 557–568. - DOI
48. 1. Reznitskaya, A., Kuo, L.-J., Clark, A.-M., Miller, B., Jadallah, M., Anderson, R. C., & Nguyen-Jahiel, K. (2009). Collaborative reasoning: A dialogic approach to group discussions. Cambridge Journal of Education, 39(1), 29–48. - DOI
49. 1. Roid, G. H. (2003). Stanford–Binet Intelligence Scale, Fifth Edition. Riverside Publishing.
50. 1. Sadler, J., & Mogford-Bevan, K. (1997). “Teacher talk” with children with language disorders: Four case studies. Child Language Teaching and Therapy, 13(1), 15–35. https://doi.org/10.1177/026565909701300103 - DOI
51. 1. Sameroff, A. (2009). The transactional model. American Psychological Association. - DOI
52. 1. Sparapani, N., Solari, E., Towers, L., McIntyre, N., Henry, A., & Zajic, M. (2020). Secondary analysis of reading-based activities utilizing a scripted language approach: Evaluating interactions between students with autism and their interventionists. Journal of Speech, Language, and Hearing Research, 63(9), 3130–3154. - DOI
53. 1. Sparrow, S. S., Cichetti, D.V. & Balla, D.A. (2005). Vineland Adaptive Behavior Scales–Second Edition (Vineland–II). Pearson Assessment
54. 1. Turnbull, K. P., Anthony, A. B., Justice, L., & Bowles, R. (2013). Preschoolers’ exposure to language stimulation in classrooms serving at-risk children: The contribution of group size and activity context. Early Education & Development, 20(1), 53–79. https://doi.org/10.1080/10409280802206601 - DOI
55. 1. Walsh, B., & Rose, K. (2013). Impact of adult vocabulary noneliciting and eliciting questions on the novel vocabulary acquisition of preschoolers enrolled in Head Start. Journal of Research in Childhood Education. https://doi.org/10.1080/02568543.2012.712085 - DOI
56. 1. Walsh, S. (2002). Construction or obstruction: Teacher talk and learner involvement in the EFL classroom. Language Teaching Research, 6, 3–23. https://doi.org/10.1191/1362168802lr095oa - DOI
57. 1. Westgate, D., & Hughes, M. (1997). Identifying’quality’in classroom talk: An enduring research task. Language and Education, 11(2), 125–139. - DOI
58. 1. Williford, A. P., LoCasale-Crouch, J., Whittaker, J. V., DeCoster, J., Hartz, K. A., Carter, L. M., Wolcott, C. S., & Hatfield, B. E. (2017). Changing teacher–child dyadic interactions to improve preschool children’s externalizing behaviors. Child Development, 88(5), 1544–1553. - DOI
59. 1. Wilson, H. K., Pianta, R. C., & Stuhlman, M. (2007). Typical classroom experiences in first grade: The role of classroom climate and functional risk in the development of social competencies. The Elementary School Journal, 108(2), 81–96. - DOI
60. 1. Yoshikawa, H., & Hsueh, J. (2001). Child development and public policy: Toward a dynamic systems perspective. Child Development, 72(6), 1887–1903. - DOI

La régression linguistique est associée à un développement moteur précoce plus rapide chez les enfants avec un diagnostic de "trouble du spectre de l'autisme"

Aperçu: G.M.

La régression linguistique (RL) est un phénomène constant et reproductible signalé par environ 25% des parents d'enfants ayant un diagnostic de "trouble du spectre de l'autisme" (dTSA). Cependant, il existe une controverse concernant la signification étiologique et clinique de ce phénomène. 

Ici, nous avons examiné les données d'une cohorte de 218 enfants avec un dTSA du Negev Autism Centre en Israël. Nous avons identifié 36 enfants avec un dTSA chez qui, à trois reprises, leurs parents avaient clairement signalé leur RL  et les avons comparés à 104 enfants dont les parents n’ont signalé aucun problème de régression (NR). 

Nous avons comparé diverses caractéristiques de développement clés parmi ces deux groupes. Nous avons constaté que l'âge auquel les enfants avec un dTSA du groupe LR atteignaient des étapes clés du développement, à savoir ramper, marcher et utiliser les premiers mots, est nettement plus jeune que l'âge des enfants du groupe NR et comparable à l'âge des enfants en développement typique . En revanche, aucune différence n'a été observée dans les caractéristiques de croissance physique telles que le tour de tête, le poids ou la taille entre les groupes. En outre, presque tous les enfants atteints de RL sont nés près de la fin de leur vie (> 35 semaines) et aucun d'entre eux n'avait d'antécédents d'hypotonie. En particulier, malgré leur développement précoce apparemment typique, on a diagnostiqué chez les enfants RL des symptômes de TSA plus graves que chez les enfants NR. 

Ces résultats renforcent la motivation à poursuivre et à étudier le RL chez les enfants avec un dTSA et suggèrent que la stratification des enfants dans les groupes de RL et de NR pourrait tirer profit des études de dépistage précoce et d'intervention.

Autism Res. 2019 Aug 30. doi: 10.1002/aur.2197.

Language regression is associated with faster early motor development in children with autism spectrum disorder

Manelis L^1,2, Meiri G³, Ilan M^1,3, Flusser H⁴, Michaelovski A⁴, Faroy M³, Kerub O⁵, Dinstein I^1,2,6, Menashe I^2,7.

Author information

1

Psychology Department, Ben Gurion University, Beer Sheva, Israel.

2

Zlotowski Center for Neuroscience, Ben Gurion University, Beer Sheva, Israel.

3

Pre-School Psychiatry Unit, Soroka University Medical Center, Beer Sheva, Israel.

4

Zusman Child Development Center, Soroka University Medical Center, Beer Sheva, Israel.

5

Ministry of Health, Jerusalem, Israel.

6

Cognitive and Brain Sciences Department, Ben Gurion University, Beer Sheva, Israel.

7

Public Health Department, Ben Gurion University, Beer Sheva, Israel.

Abstract

Language regression (LR) is a consistent and reproducible phenomenon that is reported by ~25% of parents who have children with autism spectrum disorder (ASD). However, there is controversy regarding the etiological and clinical significance of this phenomenon. Here, we examined data from a cohort of 218 children with ASD from the Negev Autism Center in Israel. We identified 36 children with ASD who were reported to exhibit clear LR by their parent on three independent occasions and compared them to 104 children whose parents did not report any concern of regression (NR). We compared a variety of key developmental characteristics across these two groups. We found that the age at which children with ASD in the LR group achieve key developmental milestones of crawling, walking, and use of first words is significantly younger than the age of children in the NR group, and comparable to the age of typically developing children. In contrast, no differences were observed in physical growth characteristics such as head circumference, weight, or height between the groups. Furthermore, almost all children with LR were born close to full term (>35 weeks) and none had a history of hypotonia. Notably, despite their apparently typical early development, children with LR were diagnosed with more severe symptoms of ASD than children with NR. These results strengthen the motivation to continue and study LR among children with ASD and suggest that early detection and intervention studies of ASD may benefit from stratifying children into LR and NR groups. Autism Res 2019, 1-12. © 2019 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: The presence of language regression (LR) among children with autism is still a matter of scientific debate. Here, we show that children with autism and reported LR start to crawl, talk, and walk at the same age as other typically developing children and significantly earlier than other children with autism. These findings, along with other medical differences between these groups, suggest that children who experienced LR comprise a distinct subgroup within the autism spectrum.

© 2019 International Society for Autism Research, Wiley Periodicals, Inc.

PMID:31468744

DOI:10.1002/aur.2197

Utilisation du dépistage de l'autisme LENA avec des enfants sourds ou malentendants

Aperçu: G.M.

Contexte et objectifs: 

Cette revue systématique rapporte les preuves de la littérature concernant le potentiel d’utilisation d’une analyse vocale automatisée, l’analyse de l’environnement des langues (LENA, Fondation de recherche LENA, Boulder, CO, États-Unis) dans le processus de dépistage des enfants présentant un risque de trouble du spectre de l'autisme  (TSA) et sourd ou malentendant (D / HH). La comorbidité du TSA et de D/HH ont augmenté, mais les outils actuels de diagnostic comportemental et de dépistage ont des limites. Le dépistage linguistique de l'autisme LENA (LENA) peut offrir un outil supplémentaire pour lever l’ambiguïté des TSA dans le D/HH chez les jeunes enfants. 

Matériels et méthodes: 

Nous examinons les rapports empiriques qui utilisent des méthodes d'analyse vocale automatique pour différencier les enfants atteints de troubles de développement de ceux présentant un développement typique. 

Résultats: 

Un consensus parmi la littérature scientifique échantillonnée montre que l'utilisation de méthodes automatiques de dépistage et de désambiguïsation des enfants avec un TSA et D / HH est favorable. 

Il existe certaines preuves de différenciation vocale entre TSA, D/HH et les enfants au développement typique justifiant l’utilisation de LENA , mais des preuves empiriques supplémentaires sont nécessaires pour mieux comprendre les forces et les faiblesses de l’outil. 

Conclusions: 

Les résultats présentés ici justifient des recherches plus approfondies, méthodologiquement valables, pleinement capables de montrer une différence fiable. Les résultats peuvent être utiles aux cliniciens et aux chercheurs pour mieux identifier et comprendre les troubles de la communication.

Medicina (Kaunas). 2019 Aug 16;55(8). pii: E495. doi: 10.3390/medicina55080495.

Use of the LENA Autism Screen with Children who are Deaf or Hard of Hearing

VanDam M^1,2, Yoshinaga-Itano C³.

Author information

1

Department of Speech & Hearing Sciences, Elson S. Floyd College of Medicine, Washington State University, Spokane, WA 99202, USA. mark.vandam@wsu.edu.

2

Hearing Oral Program of Excellence (HOPE), Spokane, WA 99202, USA. mark.vandam@wsu.edu.

3

Institute of Cognitive Science, University of Colorado, Boulder, CO 80309, USA.

Abstract

Background and Objectives: This systematic review reports the evidence from the literature concerning the potential for using an automated vocal analysis, the Language ENvironment Analysis (LENA, LENA Research Foundation, Boulder, CO, USA) in the screening process for children at risk for autism spectrum disorder (ASD) and deaf or hard of hearing (D/HH). ASD and D/HH have increased comorbidity, but current behavioral diagnostic and screening tools have limitations. The LENA Language Autism Screen (LLAS) may offer an additional tool to disambiguate ASD from D/HH in young children. Materials and Methods: We examine empirical reports that use automatic vocal analysis methods to differentiate disordered from typically developing children. Results: Consensus across the sampled scientific literature shows support for use of automatic methods for screening and disambiguation of children with ASD and D/HH. There is some evidence of vocal differentiation between ASD, D/HH, and typically-developing children warranting use of the LLAS, but additional empirical evidence is needed to better understand the strengths and weaknesses of the tool. Conclusions: The findings reported here warrant further, more substantive, methodologically-sound research that is fully powered to show a reliable difference. Findings may be useful for both clinicians and researchers in better identification and understanding of communication disorders.

PMID:31426435

DOI:10.3390/medicina55080495

Prédicteurs du développement à long terme du langage expressif dans deux cohortes longitudinales indépendantes d'enfants d'âge préscolaire avec un retard de langage et un diagnostic de "trouble du spectre de l'autisme"

Aperçu: G.M.

CONTEXTE:

Des études estiment que 30% des personnes autistes sont très peu verbales. Il est essentiel de comprendre quels facteurs prédisent le développement expressif à long terme chez les enfants présentant des retards de langage afin d’éclairer l’identification et le traitement des personnes à risque de troubles persistants du langage. La présente étude a examiné les facteurs prédictifs du développement du langage expressif chez les enfants d'âge préscolaire avec un retard de langage, suivis jusqu'à l'âge scolaire et le début de l'âge adulte.

METHODES:

Les enfants qui utilisaient des mots simples ou moins inscrits dans l'Autism Diagnostic Observation Schedule  (ADOS) à l'âge de 3 ans environ ont été sélectionnés dans une cohorte  longitudinale parmi l'Early Diagnosis (EDX) and Pathways in ASD. Les prédicteurs du niveau de langue ADOS de l'âge 3 à l'âge 19 ont été identifiés à l'aide d'arbres de classification et de régression (CART) dans l'échantillon EDX. Les modèles mixtes linéaires ont examiné les effets des prédicteurs identifiés par CART sur les trajectoires de communication expressive (VExp) du Vineland de 3 ans à 19 ans. Les mêmes modèles mixtes linéaires ont été examinés dans l'échantillon Pathways, identifiant les prédicteurs de la VExp âgés de 3 à 10,5 ans.

RÉSULTATS:

La motricité fine considérablement retardée (score T <20) était le plus puissant prédicteur CART de la langue à 19 ans. Dans les modèles mixtes linéaires, le temps, la motricité fine à 3 ans et le début de l'attention conjointe (IJA) prédisaient les trajectoires de VExp dans l'échantillon EDX, même en contrôlant les capacités de réceptivité visuelle de 3 ans. Dans l'échantillon Pathways, les habiletés motrices fines du moment et à l'âge 3 étaient des prédicteurs significatifs des trajectoires de VExp; L'IJA et les compétences cognitives n'étaient pas des prédicteurs significatifs.

CONCLUSIONS:

Les déficits marqués de la motricité fine peuvent constituer un indicateur de substitution déterminant pour l'identification des enfants atteints de TSA retardés du langage et présentant un risque de troubles persistants du langage. Cette découverte s'ajoute à la littérature démontrant une relation entre le développement moteur et le développement du langage chez les TSA. Enquêter sur des domaines de compétences individuels (par exemple, compétences motrices fines et compétences non verbales en résolution de problèmes), plutôt que des indices plus généraux du niveau de développement (par exemple, le QI non verbal) peut fournir des indications importantes pour comprendre les résultats linguistiques à long terme pouvant être ciblés lors d'une intervention précoce.

J Child Psychol Psychiatry. 2019 Aug 19. doi: 10.1111/jcpp.13117.

Predictors of longer-term development of expressive language in two independent longitudinal cohorts of language-delayed preschoolers with Autism Spectrum Disorder

Bal VH¹, Fok M¹, Lord C², Smith IM³, Mirenda P⁴, Szatmari P⁵, Vaillancourt T⁶, Volden J⁷, Waddell C⁸, Zwaigenbaum L⁷, Bennett T⁹, Duku E⁹, Elsabbagh M¹⁰, Georgiades S¹⁰, Ungar WJ¹¹, Zaidman-Zait A¹².

Author information

1

Rutgers University-New Brunswick, Piscataway, NJ, USA.

2

Semel Institute of Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA.

3

Dalhousie University and IWK Health Centre, Halifax, NS, Canada.

4

University of British Columbia, Vancouver, BC, Canada.

5

The Hospital for Sick Children, Centre for Addiction and Mental Health, University of Toronto, Toronto, ON, Canada.

6

University of Ottawa, Ottawa, ON, Canada.

7

Glenrose Rehabilitation Hospital, University of Alberta, Edmonton, AB, Canada.

8

Simon Fraser University, Vancouver, BC, Canada.

9

McMaster University, Hamilton, ON, Canada.

10

McGill University, Montreal, QC, Canada.

11

The Hospital for Sick Children Research Institute, University of Toronto, Toronto, ON, Canada.

12

Tel Aviv University, Tel Aviv, Israel.

Abstract

BACKGROUND:

Studies estimate that 30% of individuals with autism are minimally verbal. Understanding what factors predict longer-term expressive development in children with language delays is critical to inform identification and treatment of those at-risk for persistent language impairments. The present study examined predictors of expressive language development in language-delayed preschoolers followed through later school-age and young adulthood.

METHODS:

Children using single words or less on the Autism Diagnostic Observation Schedule (ADOS) at approximately 3 years old were drawn from the Early Diagnosis (EDX) and Pathways in ASD longitudinal cohorts. Age-3 predictors of Age-19 ADOS language level were identified using Classification and Regression Trees (CART) in the EDX sample. Linear mixed models examined the effects of CART-identified predictors on Vineland expressive communication (VExp) trajectories from Age-3 to Age-19. The same linear mixed models were examined in the Pathways sample, identifying predictors of VExp from ages 3 to 10.5 years.

RESULTS:

Significantly delayed fine motor skills (T-score < 20) was the strongest CART predictor of Age-19 language. In the linear mixed models, time, Age-3 fine motor skills and initiation of joint attention (IJA) predicted VExp trajectories in the EDX sample, even when controlling for Age-3 visual receptive abilities. In the Pathways sample, time and Age-3 fine motor skills were significant predictors of VExp trajectories; IJA and cognitive skills were not significant predictors.

CONCLUSIONS:

Marked deficits in fine motor skills may be a salient proxy marker for identifying language-delayed children with ASD who are at risk for persistent language impairments. This finding adds to the literature demonstrating a relation between motor and language development in ASD. Investigating individual skill areas (e.g., fine motor and nonverbal problem-solving skills), rather than broader indices of developmental level (e.g., nonverbal IQ) may provide important cues to understanding longer-term language outcomes that can be targeted in early intervention.

© 2019 Association for Child and Adolescent Mental Health.

PMID:31429087

DOI:10.1111/jcpp.13117

Différences sociales entre les enfants monolingues anglais et bilingues anglais-espagnol avec un diagnostic de "trouble du spectre de l'autisme"

Aperçu: G.M.

OBJECTIF:
Le bilinguisme est de plus en plus répandu; Cependant, les recherches sur les enfants autistes bilingues sont rares. Le but de cette étude était de comparer les habiletés sociales et les caractéristiques de l'autisme chez les enfants monolingues anglais et bilingues anglais-espagnol avec un diagnostic de "trouble du spectre de l'autisme".
METHODES:
Nous avons procédé à un examen des évaluations multidisciplinaires effectuées chez tous les enfants âgés de un à six ans diagnostiqués avec un trouble du spectre de l'autisme dans un centre-ville situé dans une clinique affiliée à une université entre 2003 et 2013. Les informations collectées comprenaient la démographie, les tests de développement et les caractéristiques de l'autisme.
RÉSULTATS:
Nous avons identifié 462 enfants; 165 étaient bilingues anglais-espagnol et 297 étaient anglais monolingue. Les parents d'enfants bilingues ont signalé une utilisation stéréotypée ou répétitive du langage plus souvent (66% vs 48% p = 0,002) que les monolingues. Aucune différence significative n'a été trouvée dans les interactions sociales, l'utilisation de comportements non verbaux, les relations avec les pairs, le partage ou la réciprocité sociale ou émotionnelle, les manies ou la sévérité de l'autisme.
CONCLUSIONS:
Le bilinguisme ne semble pas conférer une vulnérabilité supplémentaire aux enfants avec un diagnostic de "trouble du spectre de l'autisme", cependant, des différences d'utilisation qualitative du langage ont été observées.

Pediatr Neurol. 2019 Jul 11. pii: S0887-8994(19)30330-3. doi: 10.1016/j.pediatrneurol.2019.07.001.

Social Differences Between Monolingual English and Bilingual English-Spanish Children With Autism Spectrum Disorders

Valicenti-McDermott M¹, Seijo R², Shulman L².

Author information

1

Children's Evaluation and Rehabilitation Center, R. F. Kennedy Center of Excellence in Developmental Disabilities, and Children's Hospital at Montefiore, Albert Einstein College of Medicine, Bronx, New York. Electronic address: rvalicenti@hotmail.com.

2

Children's Evaluation and Rehabilitation Center, R. F. Kennedy Center of Excellence in Developmental Disabilities, and Children's Hospital at Montefiore, Albert Einstein College of Medicine, Bronx, New York.

Abstract

OBJECTIVE:

Bilingualism is increasingly prevalent; however, research in bilingual children with autism is sparse. The purpose of this study was to compare social skills and autistic features in monolingual English and bilingual English-Spanish children with autism spectrum disorder.

METHODS:

We conducted a review of the multidisciplinary evaluations done in all children aged one to six years diagnosed with autism spectrum disorder in an inner city, university-affiliated clinic from 2003 to 2013. Collected information included demographics, developmental testing, and autistic characteristics.

RESULTS:

We identified 462 children; 165 were bilingual English-Spanish and 297 were monolingual English. Parents of bilingual children reported stereotyped or repetitive use of language more often (66% vs 48% P = 0.002) than monolinguals. Significant differences were not found in social interaction, use of nonverbal behaviors, peer relationships, sharing or social or emotional reciprocity, mannerisms, or autism severity.

CONCLUSIONS:

Bilingualism does not seem to confer an extra vulnerability on children with autism spectrum disorder; however, differences in qualitative use of language were observed.

Copyright © 2019 Elsevier Inc. All rights reserved.

PMID:31416724

DOI:10.1016/j.pediatrneurol.2019.07.001

Prédire le taux de développement du langage à partir des habiletés motrices précoces chez les nourrissons à risque qui développent un "trouble du spectre de l'autisme"

Aperçu: G.M.

Le présent document avait pour objectif d'utiliser les données d'une étude prospective pour évaluer l'impact des habiletés motrices précoces sur le taux de développement du langage chez les nourrissons d'un frère ou d'une soeur âgé ayant un diagnostic de "trouble du spectre de l'autisme" (TSA), qui courent un risque accru de développer un TSA. 

Les nourrissons ont été testés de manière prospective à quatre moments (7, 14, 24 et 36 mois) et ont été évalués pour un TSA lors de la dernière visite. L'analyse de la courbe de croissance latente a été utilisée pour modéliser le taux de développement du langage à l'aide des échelles de comportement adaptatif de Vineland entre 7 et 36 mois chez les nourrissons présentant un risque familial élevé ou faible de TSA. 

Les scores moteurs des échelles de Mullen de l'apprentissage précoce à 7 mois ont été utilisés comme prédicteurs de la croissance du langage. 

Les scores moteurs bruts ont prédit le taux ultérieur de développement du langage expressif, mais non réceptif, chez les frères et sœurs à risque chez qui un diagnostic de TSA a ensuite été diagnostiqué. 

Bien que la tendance soit similaire pour la motricité fine, la relation n’atteignait pas la signification. Il semble que le retard moteur précoce influe sur le taux de développement du langage expressif, ce qui peut revêtir une importance particulière pour les nourrissons exposés à un risque accru de développer un TSA.

Res Autism Spectr Disord. 2015 May;13-14:15-24. doi: 10.1016/j.rasd.2014.12.012. Epub 2015 Mar 12.

Predicting the rate of language development from early motor skills in at-risk infants who develop autism spectrum disorder

Leonard HC¹, Bedford R², Pickles A², Hill EL¹; BASIS team.

Author information

1

Department of Psychology, Goldsmiths College, University of London, London, UK.

2

Biostatistics Department, Institute of Psychiatry, King's College London, London, UK.

Abstract

The aim of the current paper was to use data from a prospective study to assess the impact of early motor skills on the rate of language development in infants with an older sibling with Autism Spectrum Disorder (ASD), who are at increased risk of developing ASD themselves. Infants were tested prospectively at four points (7, 14, 24 and 36 months), and were assessed for ASD at the last visit. Latent growth curve analysis was used to model rate of language development using the Vineland Adaptive Behavior Scales between 7-36 months in infants at high and low familial risk for ASD. Motor scores from the Mullen Scales of Early Learning at 7 months were used as predictors of language growth. Gross motor scores predicted the subsequent rate of expressive, but not receptive, language development in at-risk siblings who were later diagnosed with ASD. Although the pattern was similar for fine motor skills, the relationship did not reach significance. It seems that early motor delay impacts the rate of development of expressive language, and this may be of particular importance to infants at increased risk of developing ASD.

PMID:31410102

PMCID:PMC6692163

DOI:10.1016/j.rasd.2014.12.012