Chronic disease self-management for individuals with stroke, multiple sclerosis and spinal cord injury
Bibliographic record
Abstract
PURPOSE: The purpose of this study was to explore the experience of people with neurological conditions who take the chronic disease self-management (CDSM) programme. The CDSM programme is used to teach skills to manage chronic conditions, and prevent secondary conditions. Few studies have explored the use of the CDSM programme with people with neurological conditions, in spite of the long standing and sometimes unpredictable nature of those conditions. METHOD: This qualitative study explored the experience of people with stroke, multiple sclerosis (MS) and spinal cord injury (SCI) who participated in the CDSM programme. We completed individual interviews using a semi-structured interview guide with 22 individuals with stroke, MS and SCI. RESULTS: Five categories emerged from the interview discussions including: (1) pre-programme influences; (2) group; (3) factors affecting learning opportunities; (4) workshop content and (5) outcomes. CONCLUSIONS: The results of this study provide insights regarding the optimal way to present the CDSM programme to people with neurological conditions.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 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".