The Use of Mobility-Focused Outcome Measures for Young Adults With Cancer Undergoing Chemotherapy
Bibliographic record
Abstract
Background: Young adults living with cancer face many unique challenges during treatment and throughout survivorship. Chemotherapy is a standard anticancer treatment that has been known to lead to negative side effects on health including loss of muscle mass, strength, and physical function (ie, physical mobility). This scoping review aimed to explore what, how, and when mobility-focused outcome measures are being used during chemotherapy treatments for young adults living with cancer to examine changes in physical mobility. Methods: Five databases were searched. To be included in this review, studies must have included young adults (age 18-40) living with cancer, who were receiving chemotherapy treatment and used any form of physical mobility measurement during treatment. Duplicates were removed, and all screening and data extraction were performed by 2 or more independent reviewers. Results: A total of 1734 studies were screened, and four studies were included in this review. Three studies included a self-reported activity log. All studies assessed physical mobility using types of performance-based outcome measures such as accelerometers, muscle strength tests, cycle ergometer testing, or the 6- minute walk test. Assessments were conducted in person by study personnel in 2 studies. Outcomes were assessed throughout the chemotherapy cycle, including preadministration, over the first 7 days, weekly, and months into treatment. Conclusion: Although a scarcity of available literature exists, this review highlights the potential for screening and monitoring changes in mobility for young adults with cancer. Clinical application of the measures highlighted in this review shows promise in guiding appropriate interventions and informing changes in treatment dosage. Future research should build upon existing work to address the limited availability of mobility measures validated in this population.
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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 | 0.024 | 0.116 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.006 |
| Bibliometrics | 0.011 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".