In-Home Synchronous Telespeech Therapy to Improve Functional Communication in Chronic Poststroke Aphasia: Results from a Quasi-Experimental Study
Bibliographic record
Abstract
BACKGROUND: Although the use of telepractice in speech-language therapy for assessment purposes is well documented, its effectiveness and potential for rehabilitation in poststroke aphasia remain largely unknown. The purpose of this study was to investigate the effectiveness of a remotely delivered synchronous pragmatic telespeech language therapy for improving functional communication in aphasia. METHODS: A pre-/post-test design was chosen in which each participant was his or her own control. Using a telerehabilitation platform and software (Oralys TeleTherapy) based on the Promoting Aphasics' Communicative Effectiveness (PACE) approach, 20 participants with chronic poststroke aphasia received 9 speech therapy sessions over a 3-week period. RESULTS: Teletreatment with the PACE pragmatic rehabilitation approach led to improvements in functional communication, marked by (a) an increase in communication effectiveness, reflecting significantly improved autonomy in functional communication; (b) a decrease in communication exchange duration, meaning that the treatment made communication faster and more efficient; (c) a decrease in the number of communication acts, meaning that, after treatment, less information was needed to be efficiently understood by the communication partner; and (d) an increase in the number of different communication strategies used, meaning that the treatment fostered the use of a variety of alternative communication modes. CONCLUSIONS: This study provides additional arguments about the benefits of telerehabilitation for poststroke patients with aphasia. It showed that multimodal language therapy delivered through synchronous telerehabilitation had positive effects on functional communication in chronic aphasia.
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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 | 0.009 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".