Milestones and turning points in the experience of physical activity throughout cancer care: a qualitative study to inform physical activity promotion
Bibliographic record
Abstract
PURPOSE: Physical activity (PA) is an important supportive care strategy to manage cancer and treatment-related side effects, yet PA participation is low among people diagnosed with cancer. This study examined patients', health professionals', and managers' perspectives on PA throughout cancer care to glean implications for PA promotion. METHODS: Random selection and purposeful sampling methods allowed for the recruitment of 21 patients (76.2% women) and 20 health professionals and managers (80% women) who participated in individual semi-structured interviews. Interview questions explored facilitators and barriers to PA participation and promotion across the cancer care continuum. Interviews were audio-recorded and transcribed. Then, qualitative thematic analysis was performed. RESULTS: The analysis produced five main themes describing milestones in PA participation throughout cancer care: (1) Getting Started, (2) Discovering PA Resources, (3) Taking Action, (4) Striving for Change, and (5) Returning to a "New Normal." The sub-themes underscored turning points, i.e., tasks and challenges to PA participation that had to be overcome at each milestone. Achieving milestones and successfully navigating turning points were dependent on clinical, social, and community factors. CONCLUSION: Cancer patients appear to progress through a series of milestones in adopting and maintaining PA throughout cancer care. Intervention strategies aimed at promoting PA could test whether support in navigating turning points could lead to greater PA participation. These findings require replication and extension, specifically among patients who are men, younger adults, and culturally diverse.
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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 | 0.013 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.009 | 0.009 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".