Health Literacy Among Patients With Chronic Lung Disease Entering Pulmonary Rehabilitation and Their Resident Loved Ones
Bibliographic record
Abstract
PURPOSE: The objective of this study was determine the prevalence of low health literacy (HL) and low reading ability among patients with chronic lung disease referred for pulmonary rehabilitation (PR) in the Netherlands and their loved ones; and to understand whether low HL or low reading ability influence PR outcomes. METHODS: Health literacy was measured using the Health Literacy Survey-Europe Q16 (HLS-EU-Q16). Reading ability and cognitive functioning were measured using the Rapid Estimate of Adult Literacy in Medicine-Dutch (REALM-D) and the Montreal Cognitive Assessment. Exercise capacity, health status, and symptoms of anxiety and depression were assessed. RESULTS: Patients (n = 120) entering PR and loved ones (n = 41) participated. Of all patients, 51% had low HL and 29% had low reading ability. Also, 39% of all loved ones had low HL. PR outcomes were comparable between patients with low or adequate HL. Patients with adequate reading ability showed greater improvement in symptoms of depression than patients with low reading ability (P = .047). CONCLUSION: Low HL and low reading ability are common among patients entering PR and their loved ones. For patients with low or adequate HL, PR is an effective treatment. Whether considering low HL and low reading ability by offering tailored education during treatment could augment the benefits of PR warrants further study.
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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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 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".