Trajectories of adaptive functioning from early childhood to adolescence in autism: Identifying turning points and key correlates of chronogeneity.

Yun-Ju Chen, Eric Duku, Peter Szatmari, Mackenzie Salt, Isabel Smith, Annie Richard, Lonnie Zwaigenbaum, Tracy Vaillancourt, Anat Zaidman-Zait, Terry Bennett, Mayada Elsabbagh, Connor Kerns, Stelios Georgiades
Author Information
  1. Yun-Ju Chen: McMaster University Hamilton ON Canada. ORCID
  2. Eric Duku: McMaster University Hamilton ON Canada.
  3. Peter Szatmari: Centre for Addiction and Mental Health The Hospital for Sick Children University of Toronto Toronto ON Canada.
  4. Mackenzie Salt: McMaster University Hamilton ON Canada.
  5. Isabel Smith: Dalhousie University Halifax NS Canada.
  6. Annie Richard: Autism Research Centre IWK Health Centre Halifax NS Canada.
  7. Lonnie Zwaigenbaum: University of Alberta Edmonton AB Canada. ORCID
  8. Tracy Vaillancourt: University of Ottawa Ottawa ON Canada.
  9. Anat Zaidman-Zait: Tel Aviv University Tel Aviv Israel. ORCID
  10. Terry Bennett: McMaster University Hamilton ON Canada.
  11. Mayada Elsabbagh: McGill University Montreal QC Canada. ORCID
  12. Connor Kerns: University of British Columbia Vancouver BC Canada. ORCID
  13. Stelios Georgiades: McMaster University Hamilton ON Canada.

Abstract

Background: Previous research has demonstrated heterogeneous adaptive outcomes across the autism spectrum; however, the current literature remains limited in elucidating turning points and associated factors for longitudinal variability (chronogeneity). To address these empirical gaps, we aimed to provide a finer-grained characterization of trajectories of adaptive functioning from early childhood to adolescence in autism.
Methods: Our sample ( = 406) was drawn from an inception cohort of children diagnosed Autistic at ages 2-5. Adaptive functioning was assessed with Vineland Adaptive Behavior Scales (VABS, 2 Edition) across 6 visits from the time of diagnosis by age 18. Parallel-process latent growth curve modeling were used to estimate domain-level VABS trajectories, followed by latent class growth analysis to identify trajectory subgroups. Child characteristics at diagnosis, family demographics, and participation outcomes at adolescence were compared across subgroups.
Results: Piecewise latent growth models best described VABS trajectories with two turning points identified at around ages 5-6 and 9-10, respectively reflecting transitions into school age and early adolescence. We parsed four VABS trajectory subgroups that vary by level of functioning and change rate for certain domains and periods. Around 16% of the sample exhibited overall adequate functioning (standard score >85) with notable early growth and social adaptation during adolescence. About 21% showed low adaptive functioning (standard score ≤70), with decreasing slopes by age 6 followed by improvements in communication and daily-living skills by age 10. The other two subgroups (63% in total) were characterized by adaptive functioning between low and adequate levels, with relatively stable trajectories entering school age. These subgroups differed most in their cognitive ability at diagnosis, household income, and social participation in adolescence.
Conclusions: We identified key individual and family characteristics and time windows associated with distinct adaptive functioning trajectories, which have important implications for providing timely and tailored supports to Autistic people across developmental stages.

Keywords

References

  1. OTJR (Thorofare N J). 2021 Oct;41(4):243-250 [PMID: 33955293]
  2. Pediatr Med. 2019 Jun;2: [PMID: 31583390]
  3. Autism Res. 2021 Jul;14(7):1444-1455 [PMID: 33749170]
  4. Autism. 2015 Oct;19(7):774-84 [PMID: 25922445]
  5. J Neurodev Disord. 2023 Jan 17;15(1):4 [PMID: 36650450]
  6. Mol Autism. 2019 Mar 15;10:13 [PMID: 30923608]
  7. J Child Psychol Psychiatry. 2019 Jun;60(6):697-706 [PMID: 30295313]
  8. Dev Med Child Neurol. 2011 Nov;53(11):1030-7 [PMID: 22014322]
  9. J Autism Dev Disord. 2018 Aug;48(8):2870-2878 [PMID: 29551006]
  10. J Am Acad Child Adolesc Psychiatry. 2012 May;51(5):467-476.e6 [PMID: 22525953]
  11. J Autism Dev Disord. 2000 Jun;30(3):205-23 [PMID: 11055457]
  12. Phys Occup Ther Pediatr. 2012 Feb;32(1):34-47 [PMID: 21846290]
  13. Autism. 2024 Mar;28(3):540-564 [PMID: 37194194]
  14. Autism. 2012 Mar;16(2):201-13 [PMID: 21810908]
  15. J Autism Dev Disord. 2015 Dec;45(12):4074-83 [PMID: 26174048]
  16. BMJ. 2020 Jan 28;368:l6880 [PMID: 31992555]
  17. Clin Psychol Rev. 2023 Feb;99:102230 [PMID: 36469976]
  18. Autism. 2021 Feb;25(2):389-404 [PMID: 33023296]
  19. Autism. 2019 Nov;23(8):1882-1896 [PMID: 30915852]
  20. Autism Res. 2021 Feb;14(2):324-332 [PMID: 32902130]
  21. JAMA Pediatr. 2018 Aug 1;172(8):716-717 [PMID: 29946699]
  22. J Autism Dev Disord. 2022 Jan;52(1):392-401 [PMID: 33704613]
  23. Lancet. 2022 Jan 15;399(10321):271-334 [PMID: 34883054]
  24. J Child Psychol Psychiatry. 2013 Feb;54(2):195-205 [PMID: 23320807]
  25. Lancet Neurol. 2020 May;19(5):434-451 [PMID: 32142628]
  26. J Child Psychol Psychiatry. 2023 Feb;64(2):332-334 [PMID: 35772988]
  27. J Autism Dev Disord. 2021 Dec;51(12):4560-4574 [PMID: 33532881]
  28. Nat Rev Dis Primers. 2020 Jan 16;6(1):5 [PMID: 31949163]
  29. Autism. 2016 Jan;20(1):5-13 [PMID: 25576142]
  30. Am J Med Genet C Semin Med Genet. 2015 Jun;169(2):198-208 [PMID: 25959391]
  31. Autism Res. 2018 Nov;11(11):1455-1467 [PMID: 30270526]
  32. Autism. 2019 Apr;23(3):539-541 [PMID: 30971108]
  33. Autism. 2015 Jan;19(1):64-72 [PMID: 24275020]
  34. Autism. 2019 Aug;23(6):1485-1496 [PMID: 30525959]
  35. J Autism Dev Disord. 2019 Nov;49(11):4390-4399 [PMID: 31372802]
  36. Am J Public Health. 2017 Nov;107(11):1818-1826 [PMID: 28933930]
  37. Autism. 2016 Jan;20(1):106-15 [PMID: 25948601]
  38. Autism. 2021 Aug;25(6):1592-1600 [PMID: 33726526]
  39. Autism Res. 2019 Apr;12(4):645-657 [PMID: 30741482]
  40. Res Dev Disabil. 2023 Jan;132:104392 [PMID: 36493738]
  41. J Child Psychol Psychiatry. 2023 Jun;64(6):868-875 [PMID: 36562498]
  42. Autism. 2014 Jul;18(5):583-97 [PMID: 23787411]
  43. J Child Psychol Psychiatry. 2022 Nov;63(11):1243-1251 [PMID: 35098539]
  44. J Autism Dev Disord. 2015 Aug;45(8):2373-81 [PMID: 25725812]
  45. Int J Dev Disabil. 2019 Apr 5;66(3):235-244 [PMID: 34141386]
  46. J Autism Dev Disord. 2014 Feb;44(2):256-63 [PMID: 21598046]
  47. Assessment. 2020 Dec;27(8):1796-1809 [PMID: 30569744]
  48. Autism. 2019 Feb;23(2):306-325 [PMID: 29458258]
  49. Autism Res. 2020 Sep;13(9):1548-1560 [PMID: 32851813]
  50. Autism. 2020 Jan;24(1):221-232 [PMID: 31215791]
  51. Autism. 2018 Jul;22(5):560-570 [PMID: 28429605]
  52. J Child Psychol Psychiatry. 2017 May;58(5):634-636 [PMID: 28414862]
  53. J Dev Behav Pediatr. 2021 Oct-Nov 01;42(8):682-689 [PMID: 34510108]
  54. J Child Psychol Psychiatry. 2015 Jan;56(1):4-17 [PMID: 25130046]
  55. JAMA Psychiatry. 2015 Mar;72(3):276-83 [PMID: 25629657]
  56. Autism. 2021 Jan;25(1):79-89 [PMID: 32757622]
  57. JAMA Netw Open. 2021 Mar 1;4(3):e212530 [PMID: 33779740]
  58. J Child Psychol Psychiatry. 2014 May;55(5):485-94 [PMID: 24313878]
  59. J Autism Dev Disord. 2011 Aug;41(8):1007-18 [PMID: 21042872]
  60. J Dev Behav Pediatr. 2022 Apr 1;43(3):149-158 [PMID: 34510107]
  61. J Neurodev Disord. 2018 Jan 05;10(1):1 [PMID: 29329511]
  62. J Consult Clin Psychol. 2002 Feb;70(1):6-20 [PMID: 11860057]
  63. Autism. 2023 Feb 28;:13623613231154729 [PMID: 36855223]
  64. Pediatrics. 2020 Apr;145(Suppl 1):S35-S46 [PMID: 32238530]
  65. Int J Ment Health Addict. 2017;15(2):239-259 [PMID: 28424567]
  66. Pediatrics. 2023 Feb 1;151(2): [PMID: 36700335]
  67. J Autism Dev Disord. 2020 Jun;50(6):1866-1881 [PMID: 30806855]

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