A systematic gender-based review of physical activity correlates in coronary heart disease patients
Bibliographic record
Abstract
Coronary heart disease is the leading cause of death for Canadian men and women due largely to insufficient cardiovascular fitness gained via physical activity. Thus, health promotion efforts should be directed at increasing physical activity levels in both men and women living with heart disease. These efforts should be informed by research identifying the key correlates of physical activity that influence the uptake and long-term maintenance of physical activity among men and women with heart disease. The objective of this article was to provide a review of physical activity correlates in men and women with heart disease by sourcing information from eligible gender-based studies on physical activity and heart disease. The social ecological model was used to organise the physical activity correlates at the intrapersonal, interpersonal, institutional, community and policy levels. Despite certain methodological challenges and inconsistencies across studies, findings indicated that physical activity in men and women with heart disease is largely influenced by intrapersonal correlates. Specifically, physical activity in women with heart disease is more influenced by physical barriers, while physical activity in men with heart disease is more influenced by psychological issues and social support.
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 | 0.006 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.012 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".