The role of oral and pharyngeal motor exercises in post-stroke recovery: A scoping review
Bibliographic record
Abstract
OBJECTIVE: To analyze intervention goals, protocols, and outcome measures used for oral and pharyngeal motor exercises in post-stroke recovery. DATA SOURCES: MEDLINE, EMBASE, CINAHL, PsychINFO, and Cochrane databases were searched in September 2022. METHODS: Studies were included if they (1) recruited post-stroke adult patients, (2) administered exercises for the oral and/ or pharyngeal muscles, and (3) reported results at baseline and post-exercise. The extracted data included intervention goals, protocols, and outcomes. All outcomes were classified according to the International Classification of Functioning, Disability and Health (ICF). RESULTS: A total of 26 studies were identified. Their intervention goals aimed to rehabilitate a broad spectrum of muscle groups within the oral cavity and pharynx and to improve the functions of swallowing, speech, facial expressions, or sleep breathing. Protocol duration ranged from 1 to 13 weeks, with various exercise repetitions (times per day) and frequency (days per week). Half of the studies reported using feedback to support the training, and these studies varied in the feedback strategy and technology tool. A total of 37 unique outcome measures were identified. Most measures represented the body functions and body structure component of the ICF, and several of these measures showed large treatment effects. CONCLUSIONS: This review demonstrated inconsistency across published studies in intervention goals and exercise protocols. It has also identified current limitations and provided recommendations for the selection of outcome measures while advancing a multidisciplinary view of oral and pharyngeal exercises in post-stroke recovery across relevant functions.
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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 | 0.014 | 0.054 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.016 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| 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".