Using a Virtual Game System to Innovate Pulmonary Rehabilitation: Safety, Adherence and Enjoyment in Severe Chronic Obstructive Pulmonary Disease
Bibliographic record
Abstract
OBJECTIVE: The present pilot study tested the use of a virtual game system (VGS) for exercise training in patients with moderate to very severe chronic obstructive pulmonary disease undergoing pulmonary rehabilitation (PR). Safety, feasibility, enjoyment and adherence were assessed. METHODS: VGS (Wii [2006], Nintendo, USA) games were prescreened and categorized into lower- and upper-body workouts. Patients admitted for a three- to four-week inpatient PR program exercised daily. They were provided an opportunity to individually engage in VGS sessions three times weekly, varying with length of stay. Dyspnea, oxygen saturation and heart rate were measured before, during and after game sessions. Patients were considered to be adherent if they attended at least 50% of VGS sessions. Adverse events and enjoyment were evaluated. RESULTS: Thirty-two patients with a mean (± SD) age of 66±9 years and a mean forced expiratory volume in 1 s of 0.72±0.40 L participated. Among the 25 patients completing the program, adherence was 76%, with a mean attendance rate of 64±35%. Mean dyspnea score was 1.5±1.1 before and 3.2±1.2 after exercise. Mean oxygen saturation changed from 94±3% to 91±5% (P<0.001), while heart rate increased from 88±15 beats⁄min to 102±18 beats⁄min (P<0.001). One patient reported chest pain requiring nitroglycerin spray and five experienced transient desaturation below 85% with play. Patients enjoyed the program (visual analogue score 8±2.6⁄10) and most would highly recommend it to others. CONCLUSIONS: Moderate exercise using a VGS was safe, feasible and enjoyed as an adjunct to inpatient PR. This modality may encourage patients to maintain physical activity after PR.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".