Evaluating The Patient Experience In Virtual Lung Cancer Exercise Rehabilitation
Bibliographic record
Abstract
Exercise trials for people with lung cancer have experienced low adherence and high attrition. A virtual group exercise protocol may assist in overcoming reported barriers to participation, such as fatigue and challenges with travel to in-person programs. PURPOSE: To evaluate participant experience in a virtual, supervised, group-based exercise program for people with lung cancer. METHODS: Participants with inoperable lung cancer undergoing systemic therapy were recruited to "Mitigation of decline with Virtual Exercise (MoVE)," a prospective single-arm, feasibility trial (n = 27). The study was a 12-week, supervised, virtual group exercise intervention. In a purposive sample of participants (n = 9), semi-structured interviews were conducted by a research assistant who did not deliver the program. The interview focused on motivation, benefits and obstacles, proposed improvements, and willingness to pay. Interviews were transcribed verbatim and analyzed using inductive thematic analysis. RESULTS: Four themes were identified. 1) The program was perceived as beneficial: Participants reported a perceived increase in strength and capacity for exercise. 2) The delivery method was acceptable: The group environment played a significant role in motivating participants to attend; many reported feeling accountable to the group and a sense of community. Virtual delivery was cited as convenient, enabling many to attend most sessions. All participants reported feeling safe with only online supervision. 3) Obstacles: Technological obstacles such as trouble changing the video size or Internet connection were reported, but were resolved by the participant early in the program. 4) Suggestions for future programs: More opportunities for socializing beyond opening the video-conferencing room early, such as a hybrid delivery model, were suggested. Subsidized programs were looked upon favourably. Having a company sponsor the program was acceptable, though advertisements and anonymity were a concern. CONCLUSIONS: MoVE was well-accepted, and the virtual delivery method facilitated its success. This virtual group exercise design is feasible and acceptable for this population. Suggestions for future iterations of MoVE centered around increased opportunities for socializing and subsidized programming. BC Lung Foundation
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".