WALKING FOR OUR HEALTH: MARRIED PARTNERS’ COLLABORATION AND PHYSICAL ACTIVITY
Bibliographic record
Abstract
Despite the known benefits of regular physical activity (PA), less than 5% of older adults meet PA recommendations, and maintaining PA is even more challenging. Several couple-focused interventions have been tested to promote PA, and findings have been mixed. The purpose of this study was to examine whether collaborative strategies to promote PA may be facilitated when partners are working toward similar PA goals. The Walking for Our Health intervention study included older adult couples (n = 32), and partners were randomized together into two goal-setting conditions. In the collaborative goal-setting condition, partners set a combined goal and tracked cumulative steps taken by both members of the couple. Partners in the concurrent individual goal-setting condition set goals and tracked their steps independently. Partners’ use of collaborative strategies to increase PA (e.g., worked together) was assessed pre and post intervention. Moderate to vigorous PA was measured objectively using accelerometers pre and post intervention. During the 8-week intervention, participants tracked daily steps using pedometers, and participated in weekly goal-setting phone consultations. Following the goal-setting intervention, partner’s reports of collaborating with one another to be more active increased (p < 0.001) in both intervention conditions. Additionally, weekly minutes of moderate to vigorous physical activity increased (p < 0.001), and BMI decreased (p < 0.01), on average. There was no difference in changes across intervention conditions. Future research should examine whether collaborative strategies are effective in facilitating health behavior change and maintenance in the context of married partners.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 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".