Language ENvironment Analysis (LENA) in Phelan-McDermid Syndrome: Validity and Suggestions for Use in Minimally Verbal Children with Autism Spectrum Disorder

Abstract

Phelan-McDermid syndrome (PMS) is a single-locus cause of developmental delay, autism spectrum disorder, and minimal verbal abilities. There is an urgent need to identify objective outcome measures of expressive language for use in this and other minimally verbal populations. One potential tool is an automated language processor called Language ENvironment Analysis (LENA). LENA was used to obtain over 542 h of audio in 18 children with PMS. LENA performance was adequate in a subset of children with PMS, specifically younger children and those with fewer stereotypic vocalizations. One LENA-derived language measure, Vocalization Ratio, had improved accuracy in this sample and may represent a novel expressive language measure for use in severely affected populations.

Profiles of vocalization change in children with autism receiving early intervention

“…In particular, LENA accuracy (against human transcribers) was negatively correlated with child chronological age, with the authors suggesting that acoustic changes in the voices of older children leading to increasing incidences of LENA misclassifying as adult vocalizations. Consistent with Dykstra et al [], Rankine et al [] suggested that high levels of echolalia and repetitive speech may confound interpretation of the data, with the quantity and quality of vocalizations not necessarily correlated. To illustrate, it is possible that two children––one with relatively mild ASD characteristics displaying frequent directed and flexible communication and another with severe intellectual disability and high rates of echolalia and repetitive speech may present with a similar rate of CVs as measured using LENA (i.e., quantity of vocalizations), despite a fundamental difference in the quality of their vocalizations.…”

“…Rankine et al [] examined the validity and reliability of LENA variables against transcribed samples and standardized measures, for a group of 18 minimally verbal children (i.e., not using phrase speech) with Phelan‐McDermid Syndrome (commonly associated with ASD), aged 30–172 months. Each participant completed between one and three whole day recordings (maximum 16 hr) across home, education, and clinical settings.…”

“…From these, 36 × 5‐min intervals were selected for transcription and analysis. The authors reported moderate overall reliability between human transcribers and LENA measures ( k = 0.455, P < 0.001), 95% CI 0.437–0.473), with a tendency for LENA to underestimate the number of CVs to avoid false positives [Rankine et al, ]. In particular, LENA accuracy (against human transcribers) was negatively correlated with child chronological age, with the authors suggesting that acoustic changes in the voices of older children leading to increasing incidences of LENA misclassifying as adult vocalizations.…”

“…Rankine et al [] proposed that a ratio measure––calculated using the ADEX tool by dividing the total duration of the child's speech sounds by the duration of nonspeech sounds––may provide a more useful indication of children's communication development. Citing the work of Plumb and Wetherby [], they noted that a higher proportion of speech to nonspeech vocalizations has been found to be positively correlated with other measures of expressive language [EL; Plumb & Wetherby, ].…”

“…The contrast in findings between the two studies may be due to differences in the populations (e.g., preschool versus school aged), methods of analyses (paired t ‐tests based on two time‐points versus linear models with multiple time points), and apparent lack of statistical power in the case of Bak et al [] due to a small sample size. It is also not clear if the use of a ratio measure, as proposed by Rankine et al [] may have yielded additional insights, given the authors reiterated the need for caution in inferring communication quality based on a measure of vocalization quantity. Identifying, and ultimately understanding, the communication trajectories of children with ASD, would benefit from further research examining their vocal behavior at multiple timepoints, and focusing on both the quantity and quality of the vocalizations.…”