Exercise psychology and cardiac rehabilitation symposium: Psychological factors related to adherence to exercise maintenance in cardiac rehabilitation
Bibliographic record
Abstract
Relatively little attention has been paid to fostering self-regulatory efficacy (SRE) beliefs for exercise in cardiac rehabilitation (CR: Woodgate & Brawley, 2008). However, this efficacy belief is a crucial mechanism for individuals to adhere to exercise therapy in both the initial stages of CR (Rejeski et al, 2004) and for the persistence required for longer term maintenance. The purpose of this paper in the symposium is to present theoretically-driven research that a) identifies psychological factors that are related to differences in the relative strength of SRE and exercise adherence outside structured CR when program access is challenged, and b) illustrates how social persuasive, efficacy-enhancing readiness manipulations can encourage CR exercise maintainers to consider adding self-managed exercise to their weekly structured CR exercise and approach recommended volumes of activity for people their age. Results of 3 studies will be presented. Implications for theoretically-based interventions for individuals engaged in maintenance CR will be drawn. Acknowledgments: Funding: SSHRC Canada Research Chair Award; Saskatchewan Health Research Foundation
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".