Telerehab at Home: Mobile Tablet Technology for Patients With Poststroke Communication Deficits—A Pilot Feasibility Randomized Control Trial
Bibliographic record
Abstract
PURPOSE: Poststroke communication deficits (PSCD) are common following stroke. Early and intensive speech and language therapy is recommended to maximize outcomes. We wanted to test the feasibility of providing telerehabilitation for patients with PSCD using mobile tablet-based technology to bridge the gap between acute stroke care and outpatient speech-language therapy (SLT) services. METHOD: This was a prospective, randomized, open-label, blinded end-point design. Patients were randomized to either the treatment arm (mobile tablet) or the control arm (standard of care). The study duration was either 8 weeks or when the patient was called to start outpatient SLT services, whichever occurred first. The primary outcome was feasibility, while secondary objective was to assess patient engagement and to explore improvement in communication ability. RESULTS: We had a 38% recruitment rate, with a 100% retention rate for the treatment arm and a 50% retention rate for the control arm. Fifty percent of patients in the treatment arm adhered to the recommended 1 hr per day, whereas none of the control arm did. Patients were engaged in using the mobile tablet and feedback on the protocol was positive. CONCLUSIONS: SLT using telerehabilitation via mobile technology is feasible in the very early stages of acute stroke recovery. It is potentially an effective means of bridging the gap between discharge from the acute care setting to the start of outpatient SLT services. Our study supported proceeding to a clinical trial to assess efficacy of the intervention. SUPPLEMENTAL MATERIAL: https://doi.org/10.23641/asha.21844569.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".