Application of an access technology delivery protocol to two children with cerebral palsy
Bibliographic record
Abstract
PURPOSE: This study further delineates the merits and limitations of the Access Technology Delivery Protocol (ATDP) through its application to two children with severe disabilities. METHOD: We conducted mixed methods case studies to demonstrate the ATDP with two children with no reliable means of access to an external device. Evaluations of response efficiency, satisfaction, goal attainment, technology use and participation were made after 8 and 16 weeks of training with custom access technologies. RESULTS: After 16 weeks, one child's switch offered improved response efficiency, high teacher satisfaction and increased participation. The other child's switch resulted in improved satisfaction and switch effectiveness but lower overall efficiency. The latter child was no longer using his switch by the end of the study. CONCLUSIONS: These contrasting findings indicate that changes to any contextual factors that may impact the user's switch performance should mandate a reassessment of the access pathway. Secondly, it is important to ensure that individuals who will be responsible for switch training be identified at the outset and engaged throughout the ATDP. Finally, the ATDP should continue to be tested with individuals with severe disabilities to build an evidence base for the delivery of response efficient access solutions. Implications for Rehabilitation A data-driven, comprehensive access technology delivery protocol for children with complex communication needs could help to mitigate technology abandonment. Successful adoption of an access technology requires personalized design, training of the technology user, the teaching staff, the caregivers and other communication partners, and integration with functional activities.
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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 | 0.008 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".