Enhance Access to Pulmonary Rehabilitation with a Structured and Personalized Home-Based Program—reabilitAR: Protocol for Real-World Setting
Bibliographic record
Abstract
Home-based models represent one of the solutions to respond to the poor accessibility of pulmonary rehabilitation (PR) services in patients with chronic respiratory disease (CRD). The main goal of this protocol is to present the implementation of the first nationwide home-based PR program—reabilitAR—in Portugal and the strategies to assess its benefits in patients with CRD. The program consists of 2 phases: a 12-week intensive phase and a 40-week maintenance phase (total: 52 weeks, 1 year). The intervention in both phases is composed of presential home visits and phone-call follow ups, including exercise training and the self-management educational program Living Well with COPD. Dyspnea, impact of the disease, emotional status, and level of dyspnea during activities of daily living are used as patient-reported outcomes measures. A one-minute sit-to-stand test is used as a functional outcome, and the number of steps as a measure of physical activity. To ensure safety, fall risk and the cognitive function are assessed. Data are collected at baseline, at 12 weeks, at 26 weeks and at 52 weeks. This is the first nationwide protocol on enhancing access to PR, providing appropriate responses to CRD patients’ needs through a structured and personalized home-based program in Portugal.
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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 | 0.011 | 0.010 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.046 | 0.010 |
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".