The Assessment of Phase of Preschool Language: Applying the language benchmarks framework to characterize language profiles and change in four- to five-year-olds with autism spectrum disorder
Bibliographic record
Abstract
Background and aimsWe introduce the Assessment of Phase of Preschool Language (APPL), a rating form that characterizes children’s language according to a well-established framework recommended by Tager-Flusberg et al. (2009). The language benchmarks framework defines children’s language as falling at one of the Pre-verbal, First Words, Word Combinations, Sentences, or Complex Language phases for phonology, vocabulary, grammar, pragmatics, and overall language. The APPL is a flexible assessment tool that allows assessors to determine language phase using a range of assessment sources: natural language samples, standardized measures, and/or parent rating forms. Using the APPL, we examined language profiles in four- and five-year-olds with autism spectrum disorder and explored language development during a community-based Naturalistic Developmental Behavioral Intervention program.MethodsCommunity speech-language pathologists completed the APPL with 95 four- and five-year-olds at the beginning of the treatment. The APPL was re-administered after a mean of 10 months of intervention (SD = 2 months) for 46 of these children. Children received treatment for up to 15 h per week in their homes and/or community childcare centers. Pivotal Response Treatment was the main form of intervention. The Picture Exchange Communication System or other augmentative and alternative communication systems were also used with many pre-verbal children.ResultsAt the beginning of intervention, the most common language phase was Word Combinations (44%), followed by Pre-verbal (26%), Sentences (20%), and then First Words (10%). Only 24% of children had even profiles (i.e. phonology, vocabulary, grammar, and pragmatics skills at the same level). Phonology was a common area of relative strength, and pragmatics was a common area of relative weakness. Ten months of intervention was associated with gains in overall language phase for 37% of children. Approximately half gained at least one phase in Grammar (57%), Vocabulary (51%), and Phonology (46%), while Pragmatics improved for 33%. Gains varied based on initial language phase. Inclusion of skills using augmentative and alternative communication enhanced interpretation of change during intervention.ConclusionsFour- and five-year-olds with autism spectrum disorder in this sample tended to have uneven skills across expressive language domains. Community-based Naturalistic Developmental Behavioral Intervention was associated with gains in language phase in older preschoolers with autism spectrum disorder. Gains varied across language domains and were influenced by initial language phase.ImplicationsThe Assessment of Phase of Preschool Language is a useful tool to support consistent application of the language benchmarks framework. It is important to consider all language domains when characterizing language skills and treatment impact in children with autism spectrum disorder.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".