People tend to falsely assume that the more unintelligible a child?s speech is, the more cognitively impaired that child is. However, intelligibility is not strongly correlated with intellect. In fact, many children with profound speech impairments have cognitive abilities that far exceed their speech abilities. Unfortunately, this false assumption leads to a series of negative social, educational, health, quality of life, and eventual employment outcomes ? outcomes that are all too common for the 1 in 100-125 people in the U.S. with such severe speech disabilities that they require augmentative and alternative communication (AAC). If children could use AAC to ?speak? in sentences, this would transform expectations and outcomes. Two gaps in knowledge prevent preliterate children from producing sentences via AAC: (1) data-based interventions have focused almost exclusively on basic social and vocabulary skills - not sentence-building skills; and (2) the AAC apps on iPads and other mobile technologies are too complex. Preliterate children spend precious cognitive resources searching for picture symbols instead of building sentences. The result is that they ?speak? using single words in most cases, despite an underlying ability to produce full sentences. Therefore, a critical need exists to develop data-driven interventions that support AAC sentence-building while minimizing the learning demands of current technologies. Failure to conduct this research will result in preschoolers with severe speech impairments continuing to experience a lifetime of underachievement and poor quality of life. The long-term goal for this line of research is to identify AAC interventions that enable children to become fully competent communicators as early in life as possible, thereby gaining access to a wealth of opportunities. The focus of the current proposal is to compare the effectiveness of the AAC Generative Language Intervention approach to an AAC Standard of Care condition on preschool sentence productions. All children will use existing AAC iPad applications. The central hypothesis is that preschoolers receiving AAC Generative Language Intervention will create longer, more grammatically complete sentences compared with the Standard of Care condition.
Specific Aim 1 compares these interventions for preschoolers with severe speech impairments and typical receptive language, and Specific Aim 2 does the same for children with Down syndrome.
Specific Aim 3 tests for possible moderation of the intervention effect by age, dynamic assessment scores, sentence type, receptive language abilities, prior AAC use, sex, mental age, and disability.
Aims 1 and 2 will be accomplished using randomized controlled trials. Hierarchical linear modeling will be used to examine interactions for Aim 3. The achievement of the aims will have a broad impact on early sentence development and long-term quality of life for children who use AAC. This work will chart a new horizon of AAC research to create data-based interventions that capitalize on the availability of current technologies, simplify existing AAC apps, and promote early sentence productions, with the goal of mirroring the language skills and quality of life outcomes of peers.
Individuals with profound speech disorders who can benefit from augmentative and alternative communication (AAC) have an estimated incidence rate of 1 in 100 ? 125 in children and adults in the U.S., making this a relatively common condition for individuals with neurodevelopmental disorders. Because the project is focused on ameliorating the long-term expressive language deficits of children who use AAC, the project is relevant to NIDCD?s mission to address the biomedical and behavioral problems associated with individuals who have communication disorders. Failing to attain functional language skills presents a significant public health problem. These outcomes have profound effects on short- and long-term educational, social, and quality of life outcomes, as well as having negative impacts on employment opportunities in adulthood.
