Active With Whom? Examining the Social Context of Physical Activity in Individuals After Stroke and Their Partners
Bibliographic record
Abstract
Engaging in regular moderate-to-vigorous intensity physical activity (MVPA) is crucial to reduce future health risk for individuals living with the effects of a stroke and their partners. Although numerous studies point to the importance of social factors in physical activity engagement, little is known about with whom individuals after stroke and their partners engage in physical activity with and whether different physical activity companions are uniquely associated with MVPA. Eighty-nine community-dwelling individuals after stroke (Mage = 68.64, SD = 10.44; 74% male) and 83 partners (Mage = 66.04, SD = 9.91; 24% male) completed 14 consecutive days of daily life assessments that included wearing physical activity monitors (accelerometers) and self-reporting physical activity companions (n = 1,961 days). Results show that average levels of MVPA were correlated between partners (r = 0.38), as were day-to-day MVPA fluctuations (r = 0.34). Importantly, for individuals after stroke, being active with their partner, but not with any other physical activity companion, was linked with elevated daily MVPA. In contrast, for partners of individuals after stroke, engaging in physical activity with a variety of different companions (partner, other family member, friend, colleague) was each associated with higher MVPA in daily life. For both individuals after stroke and their partners being active by oneself (without a companion) on a given day was not associated with elevated MVPA. Findings suggest that interventions that promote physical activity engagement should consider the role of meaningful others, with the partner being particularly key for individuals living with chronic health conditions.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 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".