Co-Exercise and Mood: The Role of Relationship Type in the Link Between Physical Activity and Positive Affect
Bibliographic record
Abstract
Abstract Physical activity is known for its positive health benefits, including improvements in mood. While research supports the association between physical activity and elevated positive affect, the possibly unique role of exercising with close social connections (i.e., co-exercise), such as spouses, friends, and family, in enhancing these mood benefits remains less understood. This study used ambulatory assessment data from 140 dyads, each consisting of an older adult (60+) and a close social connection (56.6% spouses, 30.2% friends or family members; aged 21-95 years, M = 68.59 years, SD = 10.56). Participants completed a 10-day assessment period with morning and evening surveys on affect (0-100), along with self-reported and accelerometer-measured physical activity. Multilevel models examined the relationship between physical activity and end-of-day positive affect and whether these associations varied by relationship type. A moderation analysis assessed whether the effect of co-exercise on mood differed by relationship type (spouse/partner vs. friend/family). Participants reported engaging in physical activity with their study partner on 35% of days. Higher self-reported physical activity was associated with higher positive affect (b = 0.13, SE = 0.01, p<.001), and this effect was stronger on days when participants exercised with their study partner (b = 1.44, SE = 0.69, p=.039). However, the effect of co-exercise on positive affect did not differ by relationship type. Future analyses will explore whether a similar pattern is seen with accelerometer-measured physical activity. These findings suggest that co-exercise may enhance the mood benefits of physical activity, regardless of relationship type, and may be valuable in interventions supporting the physical and mental health of older adults.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".