Understanding the importance of physical activity partners for women diagnosed with cancer
Bibliographic record
Abstract
Many female cancer survivors report lack of social support as a barrier for physical activity (PA), but this association is underexamined. Three studies were used to understand social support in female cancer survivors. In study 1, N=200 (Mage=54.0, SD=13.4 years) breast cancer survivors completed an online questionnaire and 70% identified finding a PA partner as a key PA barrier. In study 2, an online platform was developed to match female cancer survivors with a PA partner (ActiveMatch; www.activematch.ca). Women who signed up for ActiveMatch (N=165; Mage=47.0, SD=10.0) reported wanting one partner (95%) and preferred walking as PA (90%). In study 3, multiple case studies were completed with three dyads (N=6, Mage=51.8, SD=8.7) matched for personality. For 28 days, dyads wore pedometers and completed daily questionnaires. Case 1 dyad was not in contact often (6/28 days) and walked less on days where there was no contact. Both women reported being incompatible on preferred method of contact (i.e., receiving social support). Case 2 dyad supported one another 32% of the days. While they walked fewer total steps on days where there was contact, this difference was less compared to case 1. Case 3 dyad supported each other for 46% of the days. One member increased her steps and the other maintained. They reported setting a common goal to motivate themselves. Overall, findings highlight importance of social support for PA in samples of survivors, demonstrate that phone calls and texts are effective social support modes, and importance of partners is highlighted.
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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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".