Study protocol: investigating the feasibility of a hybrid delivery of home-based cluster set resistance training for individuals previously treated for lung cancer
Bibliographic record
Abstract
BACKGROUND: Symptom burden remains a critical concern for individuals with non-small cell lung cancer (NSCLC) following the completion of treatment. The most common symptom clusters, dyspnea (shortness of breath) and fatigue, can contribute to physical decline, reductions in quality of life, and a higher risk of comorbidities and mortality. Dyspnea is a primary limiter of exercise capacity in individuals with lung cancer, resulting in exercise avoidance and an accelerated physical decline. As such, designing resistance training with cluster sets to mitigate symptoms of dyspnea and fatigue may result in improved exercise tolerance. Thus, maintaining the exercise stimulus via cluster sets, combined with improved tolerance of the exercise, could result in the maintenance of physical function and quality of life. The purpose of this study is to investigate the feasibility and preliminary efficacy of a hybrid-delivery home-based cluster-set resistance training program in individuals with NSCLC. METHODS: Individuals with NSCLC (n = 15), within 12 months of completion of treatment, will be recruited to participate in this single-arm feasibility trial. Participants will complete 8 weeks of home-based resistance training designed to minimize dyspnea and fatigue. The hybrid delivery of the program will include supervised sessions in the participants' home and virtual supervision via video conferencing. The primary outcome of feasibility will be quantified by recruitment rates, retention, acceptability, and intervention fidelity. Exploratory outcomes (dyspnea, fatigue, quality of life, physical function, and body composition) will be assessed pre- and post-intervention. DISCUSSION: This study will provide important data on the feasibility of delivering this intervention and inform procedures for a future randomized controlled trial. TRIAL REGISTRATION: Record not yet public.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".