Dysarthria following stroke – the patient’s perspective on management and rehabilitation
Bibliographic record
Abstract
OBJECTIVE: To explore the perceptions of people with stroke-related dysarthria in relation to the management and rehabilitation of dysarthria. DESIGN: Qualitative semi-structured interviews. SETTING: Community setting Subjects: Twenty-four people with an acquired dysarthria as a result of a stroke in the previous three years. All were living at home at the time of the interview. None exhibited a co-existing impairment (for example, aphasia, apraxia or cognitive impairment) that might have contributed to their communicative experiences. RESULTS: Participants described the considerable efforts they made to maximize their communicative effectiveness prior to, and during, communicative interactions. Activities described included careful articulation and vocal projection as well as more inconspicuous strategies including pre-planning interactions, focused, effortful speech and word substitution. Communication was facilitated by a range of strategies including drafting, rehearsal, manoeuvring and ongoing monitoring and repair. Self-led speech rehabilitation activities were functionally based and often undertaken regularly. Some novel reading-aloud and speaking-aloud activities were described. CONCLUSION: The quantity and nature of inconspicuous, internalized, cognitive activities people with dysarthria engage in to maximize their communicative effectiveness should be considered in evaluating the impact of dysarthria following stroke. Focusing upon externally observable characteristics alone is insufficient. Challenging, functionally relevant, patient-focused activities, materials and targets are more likely to be perceived by the patient as relevant and worthwhile and are thus more likely to ensure adherence to recommended rehabilitation 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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".