Conceptual validation of an innovative remote pulmonary rehabilitation solution for Chronic Obstructive Pulmonary Disease
Bibliographic record
Abstract
INTRODUCTION: Chronic Obstructive Pulmonary Disease (COPD) is the third leading cause of death in the world. Pulmonary rehabilitation (PR) reduces COPD hospitalisations, although its use is low. Telerehabilitation is effective; however, in Chile the development of remote PR technology is incipient. Therefore, the aim of the study was to validate conceptual aspects of an innovative remote PR solution for COPD. METHODS: This mixed study used a nonprobabilistic sample of PR professionals and people with COPD (PwCOPD) from Santiago. The perception of a conceptual solution for PR through a semi-structured interview was determined. Professionals were also asked about willingness to use technology using a questionnaire designed and validated in 75 professionals in this study. The study was approved by the Ethics Committee and data were collected after informed consent. RESULTS: Twenty-two participants were recruited, of which 14 were professionals and eight were PwCOPD. Among professionals and patients, the willingness to use the solution is positive because it would reduce visits and improve self-management, although it should include a remote/in-person combination, training, and user-friendly interface. Most of the professionals were willing to use technology for pulmonary rehabilitation. CONCLUSIONS: The development of telehealth technologies should consider the expectations of patients and professionals and may incorporate elements of persuasive technologies in the design. The results could contribute to the development of digital solutions for remote PR in PwCOPD.
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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 | 0.017 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 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".