Responsiveness of a parent-reported outcome measure to evaluate AAC interventions for children and youth with complex communication needs
Bibliographic record
Abstract
Evaluation of the effectiveness of augmentative and alternative communication (AAC) interventions requires reliable measures that are responsive to change. The aim of this study was to explore the potential of the Family Impact of Assistive Technology Scale for AAC (FIATS-AAC) to detect functional change in children and youth with AAC needs, aged 3-17 years, and their families, 6 and 12 weeks after receiving a graphic-based, speech-generating device (SGD). Parents whose children were awaiting a SGD as part of their regular AAC service participated in the study. In all, 45 parents completed the FIATS-AAC during each of three phone interviews: at the time of device delivery, and then 6 weeks and 12 weeks after receiving the device. Children and youth were aged 3-16 years (M = 7.8, SD = 3.3) and were mostly context-dependent communicators. Paired t-tests indicated statistically significant gains in functioning from baseline to both 6 and 12 weeks after receiving the AAC device. Effect sizes were 0.41 and 0.38, respectively. This study provides initial support for the ability of the FIATS-AAC to detect functional changes in children and youth and their families after receiving a graphic-based SGD.
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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 | 0.022 | 0.060 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".