Using Language Environment Analysis System (LENA) in Natural Settings to Characterize Outcomes of Pivotal Response Treatment.

Purpose: Despite the importance of monitoring changes in expressive language in early intervention, existing approaches to language assessment are often costly, time-intensive, and capture limited variability in autistic children. The Language ENvironmental Analysis (LENA) system has thus received considerable attention as an automated approach that may hold promise for capturing fine-grained changes in language development in a more efficient and cost-effective manner. However, evaluations of the utility of the LENA system for tracking response to early intervention in unstructured contexts are currently limited.

Methods: This study aimed to build on prior research through evaluating the use of LENA in the context of a well-defined clinical sample from a randomized controlled trial (RCT) of Pivotal Response Treatment (PRT) that demonstrated expressive language gains across standardized and manually-coded measures.

Results: Exploration of automatically-derived LENA metrics (i.e., child vocalizations, conversational turns) revealed no significant association with standardized language assessments (i.e., Mullen expressive language subscale, MacArthur Bates Communicative Development Inventory, Vineland-II expressive language subscale). Furthermore, relative to the delayed treatment group, children participating in PRT did not show significantly greater improvement in the number of vocalizations or conversational turns during naturalistic, daylong LENA recordings collected in home settings from baseline to post-intervention.

Conclusion: Implications and future directions for natural language sampling and the measurement of expressive language in early intervention are discussed.