Questionnaire assessment of usual practice in mood and cognitive assessment in Scottish stroke units
Bibliographic record
Abstract
PURPOSE: National and International guidelines recommend cognition and mood assessment for all stroke survivors. However, there is no consensus on preferred screening tool or method of assessment. We aimed to describe clinical practice in cognitive and mood assessment across Scottish stroke services. METHOD: We used a questionnaire based survey. After local piloting, we distributed the questionnaire using mixed methodologies (online and paper) across all Stroke Managed Clinical Networks in Scotland. We also distributed the questionnaire to specialist societies representing stroke physicians, nurses and allied health professionals and through the UK Stroke Forum delegate pack. RESULTS: We received 174 responses from nurses, physiotherapists, psychologists, occupational therapists and medical staff. Medical staff made up the largest group of respondents (61, 35%). Of the respondents 148 (85%) routinely assess cognition and 119 (72%) mood. A variety of tools were used (cognitive n = 45 tools; mood n = 17); Mini Mental State Examination (n = 103, 59% of respondents) and the Hospital Anxiety and Depression Scale (n = 76, 44%) were the most commonly employed tools. CONCLUSION: Response rate was modest but included all mainland Scottish regions with active stroke services. Although the majority of responders are assessing cognition and mood there is substantial heterogeneity in measures used and certain commonly used tools are not validated or appropriate for use in stroke. We suggest development of evidence based, standardised assessment protocols. IMPLICATIONS FOR REHABILITATION: Screening stroke survivor's for cognitive and mood issues is recommended but there is little guidance on the preferred assessment strategy Across Scottish stroke services there is a lack of consensus in assessment and management of cognition and mood post stroke Sixty-two different cognitive/mood assessment tools were found to be in use across the country Careful consideration must be given when inspecting assessment tools and use of caution when interpreting results.
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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 | 0.008 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".