Amount and Socio-Ecological Correlates of Exercise in Men and Women at Cardiac Rehabilitation Completion
Bibliographic record
Abstract
OBJECTIVE: The aim of the study was to describe (1) the amount of physical activity (PA) in cardiac rehabilitation (CR) graduates by sex, and (2) the correlates of their PA. DESIGN: Secondary analysis of baseline data from a randomized trial was undertaken. Graduates were recruited from three CR programs. Participants completed a questionnaire, which assessed constructs from the socio-ecological model (i.e., individual-level, social- and physical-environmental levels). Physical activity was measured objectively using an ActiGraph GT3X accelerometer. Multilevel modeling was performed. RESULTS: Two hundred fifty-five patients consented, of which 200 (78.4%) completed the survey and provided valid accelerometer data. Participants self-reported engaging in a mean ± standard deviation of 184.51 ± 129.10 min of moderate-to-vigorous-intensity PA (MVPA) per week (with men engaging in more than women, P < 0.05). Accelerometer data revealed participants engaged in 169.65 ± 136.49 mins of MVPA per week, with 43 (25.1%) meeting recommendations. In the mixed models, the socio-ecological correlate significantly related to greater self-reported MVPA was self-regulation (P = 0.01); the correlate of accelerometer-derived MVPA was neighborhood aesthetics (P = 0.02). CONCLUSIONS: Approximately one-quarter of CR program completers are achieving MVPA recommendations, although two-thirds perceive they are. The CR programs should exploit accelerometry and promote self-regulation skills, namely, self-monitoring, goal-setting, positive reinforcement, time management, and relapse prevention. Patients should be encouraged to exercise in pleasing locations.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".