INDIVIDUAL AND SOCIAL FACILITATORS OF PHYSICAL ACTIVITY IN STROKE SURVIVORS: EVIDENCE FROM DAILY LIFE ASSESSMENTS
Bibliographic record
Abstract
Abstract Physical activity is a means through which stroke survivors can reduce their future stroke risk. Individual intentions (purposeful aims to engage in a behavior) and self-efficacy (beliefs about their capacity to successfully perform the behavior) have been associated with more physical activity. Spouses are underrecognized resources that may facilitate physical activity engagement. We specifically examined dyadic intentions (shared aims to engage in a behavior) and dyadic self-efficacy (beliefs about the capacity to engage in a behavior with a partner) to explore the important role of spouses in facilitating physical activity. 88 Canadian stroke survivors (Mage = 67.84, SD = 10.79; 73% male; 35% with college degrees; 82% White) wore physical activity monitors for up to 14 consecutive days and completed morning and evening questionnaires including daily individual and dyadic intentions and self-efficacy. Results reveal positive associations between individual morning intentions and physical activity (self-report and accelerometer based) but not for individual self-efficacy. Dyadic variables (intentions and self-efficacy) were positively associated with self-reported physical activity but not with accelerometer assessed physical activity. Notably, associations differed by analytical level: within-person effects were significant for individual intentions and dyadic self-efficacy, whereas between-person effects were significant for both individual and dyadic intentions. This project highlights and discusses the importance of considering within and between person effect to provide more granular insights on the complexity of the targeted phenomenon as well as issues of physical activity measurement (self-report, device-derived) to light on avenues for increasing physical activity engagement in stroke survivors.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".