Hostname: page-component-586b7cd67f-g8jcs Total loading time: 0 Render date: 2024-11-26T22:29:51.975Z Has data issue: false hasContentIssue false

23 Latent Profiles of Children Referred for Possible Autism

Published online by Cambridge University Press:  21 December 2023

Phebe Albert*
Affiliation:
Georgia State University, Atlanta, GA, USA
MaryAnn Romski
Affiliation:
Georgia State University, Atlanta, GA, USA
Gal Kaldes
Affiliation:
Georgia State University, Atlanta, GA, USA
*
Correspondence: Phebe Albert, Georgia State University, [email protected]
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.
Objective:

Autism is a neurodevelopmental disorder characterized by impairments in social communication and the presence of restricted and repetitive behaviors (RRBs). Clinical diagnosis of autism is often complicated by heterogeneity in core autism traits and other individual characteristics (e.g., cognition). Previous literature suggests that degree of autism characteristics, cognitive ability, and age contribute to identifying homogenous subgroups of autism, which facilitates prognosis and treatment planning. The present study extends these findings by examining profiles of cognition, age, and autism characteristics (measured by the Autism Diagnostic Observation Schedule, Second Edition [ADOS-2]) in a clinical sample of school-aged children presenting with concern for possible autism. Profiles are also described according to whether children received an autism diagnosis and clinician ratings of emotional/behavioral problems, which have been shown to influence diagnostic clarity when assessing for autism.

Participants and Methods:

We conducted a retrospective chart review of 188 children (68% male) ages 4-17 years (M=8.9) who were referred for an autism evaluation. Latent profile analysis was conducted using age, ADOS-2 Social Affect (SA) and RRB scores, and verbal and non-verbal intelligence quotients (VIQ/NVIQ). Model fit comparing 2, 3, 4, and 5-class models was assessed using log-likelihood, AIC, BIC, SABIC, entropy, and Lo, Mendell, and Rubin (LMR) and bootstrap likelihood ratio (BLRT) tests. The frequency of clinical autism diagnosis and ADOS-2 emotional/behavioral problems were calculated across profiles in the best-fitting model.

Results:

The 5-class model demonstrated the best fit. The following characteristics were observed across five profiles: 1) mean age = 9.5 years, Low Average VIQ/NVIQ, and low SA (M=5.2) and RRB (M=0.7) scores; 2) mean age = 7.3 years, Average VIQ/NVIQ, and low SA (M=3.1) and RRB (M=0.8) scores; 3) mean age = 10.1 years, Low Average VIQ/NVIQ, and high SA (M=11.3) and RRB (M=4.2) scores; 4) mean age = 8.8 years, Average VIQ/NVIQ, and moderately high SA (M=9.6) and RRB (M=3.4) scores; and 5) Exceptionally High VIQ, Above Average NVIQ, and comparatively mid-level SA (M=6.6) and RRB (M=3.6) scores. Autism diagnosis and emotional/behavioral problems varied across profiles. Profiles 1 and 2 contained lower diagnosis rates (33% and 10%, respectively). Profiles 3 and 4 contained the highest diagnosis rates (97% in both), followed by profile 5 (75%). In terms of emotional/behavioral problems, Profile 2 exhibited the highest overactivity (56%). Profile 3 demonstrated the highest rate of tantrums/disruptive behaviors (20%).

Conclusions:

Findings revealed distinct profiles of IQ and autism characteristics within a clinical sample of school-aged children referred for possible autism. Children with the highest scoring ADOS profile were older compared to other profiles. Higher and lower scoring ADOS profiles exhibited both lower and higher IQ scores. Descriptive analyses suggested that the frequency of autism diagnosis was notably higher in moderate and high-scoring ADOS profiles; however, emotional/behavioral problems were salient in only one low and one high-scoring ADOS profile. The findings suggest that higher-scoring ADOS profiles consistently demonstrated high autism diagnosis rates but varied across IQ and behavioral problems. These results have implications for interpreting these characteristics during clinical autism diagnosis.

Type
Poster Session 07: Developmental | Pediatrics
Copyright
Copyright © INS. Published by Cambridge University Press, 2023