National survey of Canadian occupational therapists’ assessment and treatment of cognitive impairment post-stroke
Bibliographic record
Abstract
AIM: This study examined variations in management of cognitive impairment post-stroke among occupational therapists and factors associated with variations in practice. METHODS: Canada-wide cross-sectional telephone survey. Clinicians' practices were examined using standard patient cases (vignettes). SETTING: Acute care, inpatient rehabilitation and community-based sites providing stroke rehabilitation in all Canadian provinces. PARTICIPANTS: Occupational therapists (n=663) working in stroke rehabilitation as identified through provincial licensing bodies. MAIN OUTCOME MEASURES: Type and frequency of cognition-related problem identification, assessment and intervention use. RESULTS: Respectively, 69%, 83% and 31% of occupational therapists responding to the acute care, inpatient rehabilitation and community-based vignettes recognised cognition as a potential problem. Standardised assessment use was prevalent: 70% working in acute care, 77% in inpatient rehabilitation and 58% in community-based settings indicated using standardised assessments: 81%, 83% and 50%, respectively, indicated using general cognitive interventions. CONCLUSION: The Mini-Mental State Examination was often used incorrectly to monitor patient change. Executive function, a critical component of post-stroke assessment, was rarely addressed. Interventions were most often general (e.g. incorporated in activities of daily living) rather than specific (e.g. cueing, memory aids, computer-based retraining).
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".