Multicentre comparison of self-management in patients with COPD
Bibliographic record
Abstract
In patients with COPD, self-management plays an important role in disease management. Recently, self-management programmes have expanded patient education practices to include a variety of disease management techniques. We hypothesised that COPD patients have insufficient and/or different self-management needs according to institution. We compared information needs of patients between specialised clinics in Canada (SCC) and Japan and a hospital outpatient clinic in Japan (HCJ), all employing different self-management interventions. This cross-sectional study evaluated patients' information needs for disease management using the Lung Information Needs Questionnaire (LINQ). Furthermore, we assessed pulmonary function tests, modified Medical Research Council (mMRC) dyspnoea scale and frequencies of hospitalisations and emergency visits. The total number of patients was 183. Those attending SCC were younger (p=0.047), with lower forced expiratory volume in 1 s % predicted (p<0.0001), and scored higher on the mMRC dyspnoea scale. Total LINQ scores showed differences between institutions (p<0.0001). There was no difference for the smoking domain; however, SCC recorded significantly lower information needs for all other domains (p<0.02). No significant difference in emergency visits was seen between institutions, but HCJ recorded the highest rate of emergency visits, while SCC had significantly higher rates of hospitalisation (p=0.004). Differences were seen for frequency and duration of education between institutions. These results highlight the differences in information needs by institution and the importance of assessing individual needs. We believe, despite representing only one aspect of self-management, our findings reflect real-world circumstances, adding to the argument that self-management education should be structured, but flexible, to meet the changing needs of COPD patients.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".