Bibliographic record
Abstract
People with cancer face many challenges related to their disease and its associated treatments. This dissertation consists of two studies directly evaluating the effects of exercise on cancer survivors who participated in a community-based exercise program (CanWell program) and a measurement paper that evaluated a measure of symptom burden. The first study outlines the development and effectiveness of the CanWell program as measured by the 6-minute walk test, STEEP treadmill test, Functional Cancer Therapy Assessment – General, and the Edmonton Symptom Assessment System (ESAS). This study found that participants in the CanWell program have significantly improved physical abilities, improved quality-of-life, and lower levels of cancer disease burden. The second study was conducted to evaluate the long-term exercise compliance, facilitators and barriers to continuation of exercise. Outcome measures used were similar to those in the first study with a survey explored facilitators and barriers to exercise. The results of this study found that while CanWell graduates were able to maintain the functional levels (no change in 6-minute walk test), there were significant reductions in exercise aerobic abilities (time on treadmill). The main exercise barriers included fatigue, cost, and return to work. In the last study, the measurement properties of the ESAS were investigated using Rasch analysis leading to a revised scoring algorithm to meet unidimensionality and interval scaling. The ESAS scores from study #1 were re-analyzed using the new interval-level scoring scheme. This Rasch-based scoring resulted in different conclusions than the traditional ordinal scaling.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.136 | 0.021 |
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".