Communication Bridge: A pilot feasibility study of Internet‐based speech–language therapy for individuals with progressive aphasia
Bibliographic record
Abstract
INTRODUCTION: Individuals with aphasia symptoms due to neurodegenerative dementia are under-referred for speech-language therapy (SLT) services. We sought to determine the feasibility of utilizing telepractice, via Internet video conferencing, to connect an individual with progressive aphasia due to dementia to a speech-language pathologist for treatment. METHODS: Participants received an Initial Evaluation, 8 person-centered Internet-based SLT sessions and two Post-Therapy Evaluations. The feasibility of providing web-based SLT, strategies used and their compliance, functional gains and the duration of benefit were assessed. RESULTS: Thirty-four participants from 21 states and Canada were enrolled. Thirty-one participants completed the 6-month Evaluation. Speech-language pathologist-assessed and self-reported functional gains, as well as increased confidence in communication were documented at 2-months and maintained at 6-months post-enrollment. DISCUSSION: Internet-based SLT using person-centered interventions provides a feasible model for delivering care to individuals with dementia and mild/moderate aphasia symptoms who have an engaged care-partner and prior familiarity with a computer.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".