Understanding relational perceptions in cardiac rehabilitation: Early findings and possible implications
Bibliographic record
Abstract
Cardiac rehabilitation (CR) represents a clear form of what is known as proxy-agency where patients receive assistance to help them successfully self-regulate lifestyle change. In situations of proxy-agency it has been suggested that in addition to self-efficacy, relational perceptions such as proxy-efficacy, and relation-inferred self-efficacy (RISE) beliefs may be important correlates of participants' social-cognitions. However, only recently has research begun to emerge highlighting the importance of these relational perceptions in exercise. Indeed, work within CR as well as healthy populations has supported the relationships of proxy-efficacy with both adaptive (e.g., intentions) and maladaptive (e.g., reliance) social cognitions. Despite their potential importance, RISE beliefs have gone largely unexamined within an exercise rehabilitation context. The current presentation draws evidence from two prospective studies to highlight the importance of understanding the interrelationships between relational and self-perceptions (e.g., self-regulatory efficacy) in cardiac rehabilitation, with a specific focus on RISE beliefs. Results suggest that RISE beliefs are related to both relational perceptions and social cognitions relevant to self-regulation. These findings are discussed in relation to the possible implications for practitioners with respect to the delivery of exercise-based CR.Acknowledgments: SSHRC grant 41020060927
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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 | 0.006 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".