Profiling Language Skills in Minimally Verbal Autism: Findings From Greek-Speaking Preschoolers.

Background and aims: Minimally verbal (MV) autistic children constitute a considerable portion of the autism spectrum, representing approximately one-third of the autistic individuals. Despite the urgency of understanding this population, relatively few studies have focused specifically on the language abilities of MV autistic children. This study aims to examine the language abilities of Greek-speaking preschool-aged MV children with autism prior to intervention. Specifically, we sought to identify the children's strengths and weaknesses across various language systems (receptive, expressive, and organizational) and modalities (phonological, semantic, and morphosyntactic), and also assess the influence of nonverbal intelligence (performance intelligence quotient [PIQ]) and age on their language performance.

Methods: Twenty-six MV autistic preschoolers (mean age = 5;3) from Greece participated in the study. They were assessed using Level I of the LaTo tool, a standardized battery for evaluating language in young Greek-speaking children. The tool comprises 10 subtests covering expressive, receptive, and organizational language within the phonological, semantic, and morphosyntactic modality. Standard scores were compared across language systems (receptive, expressive, and organizational) and modalities (phonological, semantic, and morphosyntactic). Linear regression models were also used to evaluate the influence of age and PIQ on the children's language performance.

Results: The children showed widespread difficulties across language systems and modalities. Performance was particularly low in expressive language and phonological awareness tests; however, MV children showed relatively better performance in receptive and organizational language, especially in tests that utilized visual support cues. Notably, performance in organizational language tests significantly exceeded performance in both expressive and receptive language tests. Regression analyses indicated a significant negative association between age and language performance across most domains, suggesting an age-related decline in the children's language abilities. No significant relationship was found between PIQ and language outcomes, indicating that nonverbal intelligence did not predict linguistic performance.

Conclusions: The study confirms that MV autistic children experience substantial but non-uniform language difficulties. While expressive and phonological skills were severely compromised, receptive and organizational language skills showed relative strengths, particularly when tests incorporated nonlinguistic knowledge and visual scaffolding. The negative effect of age on language performance underscores the risk of language deterioration over time for the specific population, while the lack of correlation between language performance and PIQ suggests that linguistic ability in MV autistic children is not tightly linked to their general cognitive function. The findings also reinforce the notion that language development in MV children is a heterogeneous process influenced by task effects.

Implications: The findings have significant implications for the design of language assessment and intervention strategies for MV children. Interventions that draw on semantic scaffolding and incorporate visual aids-such as picture-based communication tools-seem to be a promising approach to implement language treatment programs for the specific population. Also, the variability across language domains emphasizes the need for personalized intervention plans grounded in detailed language profiling rather than broad cognitive assessments. Finally, the results highlight the urgency of early identification and targeted support, and call for the development of standardized criteria for MV classification to facilitate cross-study comparability and improved clinical practices.