Assessing the Relationship Between Physical Fitness Activities, Cognitive Health, and Quality of Life Among Older Cancer Survivors
Bibliographic record
Abstract
Chemotherapy-related cognitive impairment, known as "chemobrain," has been described as a side effect of chemotherapy and is associated with cognitive changes on quality of life especially among older cancer survivors. This longitudinal feasibility study examined the relationship between physical fitness, cognitive health, and quality of life among two groups of older adults: those on chemotherapy, and those who have completed chemotherapy. To assess cognitive health, we used the Montreal Cognitive Assessment and demographic information from the Healthy Brain Questionnaire. For quality of life, we used the McGill Quality of Life assessment. Physical activity was assessed using Metabolic Equivalency Tasks from the Compendium of Physical Activities classification system. t-Tests and regression analyses indicated that at Time 1 those on chemotherapy had lower cognitive health scores than those off chemotherapy. Yet at Time 2, as physical activities increased, cognitive health and quality of life improved for those on chemotherapy. However, those who had completed chemotherapy also benefited from an increase in physical activities over time. The results have implications for health care practitioners in oncology settings to better inform patients of cognitive challenges resulting from chemotherapy and the importance of participation in physical activities. Future research should compare different age groups among a larger sample.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".