A Survey of Physical Activity Programming and Counseling Preferences in Young-Adult Cancer Survivors
Bibliographic record
Abstract
BACKGROUND: Few research studies have focused on physical activity in young-adult cancer survivors despite the potential long-term health consequences of inactivity in this population. OBJECTIVE: Understanding the unique physical activity programming and counseling preferences of young-adult cancer survivors may inform future research as well as nursing practice. METHODS: Participants were 588 young-adult cancer survivors (20-44 years old) who completed a mailed survey in the province of Alberta, Canada, that assessed physical activity preferences and standard demographic and medical variables. RESULTS: Most young-adult cancer survivors indicated that they were interested (78%) and able (88%) to participate in an activity program. Young-adult cancer survivors also preferred receiving activity counseling from a fitness expert at the cancer center (49.6%), information by brochure (64%), starting activity after treatment (64%), walking (51%), doing activity with others (49%), and doing activity at a community fitness center (46%). The χ analyses indicated that younger cancer survivors (20-29 vs 30-39 vs 40-44 years) were less likely to prefer walking (P < .001), more interested in receiving information (P = .002), and more likely to prefer receiving information by e-mail (P = .044) or Internet (P = .006). CONCLUSIONS: Young-adult cancer survivors show interest in receiving physical activity counseling. There were some consistent programming preferences, although other preferences varied by demographic and medical factors. IMPLICATIONS FOR PRACTICE: Nurses may play a key role in promoting physical activity in young-adult cancer survivors. Understanding the physical activity preferences of young-adult cancer survivors may help nurses make practical recommendations and referrals.
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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 | 0.000 | 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) | 0.002 | 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".