Who will be active? Predicting exercise stage transitions after hospitalization for coronary artery diseaseThis paper is one of a selection of papers published in this Special Issue, entitled Young Investigators' Forum.
Bibliographic record
Abstract
We describe transitions between exercise stages of change in people with coronary artery disease (CAD) over a 6-month period following a CAD-related hospitalization and evaluate constructs from Protection Motivation Theory, Theory of Planned Behavior, Social Cognitive Theory, the Ecological Model, and participation in cardiac rehabilitation as correlates of stage transition. Seven hundred eighty-two adults hospitalized with CAD were recruited and administered a baseline survey including assessments of theory-based constructs and exercise stage of change. Mailed surveys were used to gather information concerning exercise stage of change and participation in cardiac rehabilitation 6 months later. Progression from pre-action stages between baseline and 6 month follow-up was associated with greater perceived efficacy of exercise to reduce risk of future disease, fewer barriers to exercise, more access to home exercise equipment, and participation in cardiac rehabilitation. Regression from already active stages between baseline and 6 month follow-up was associated with increased perceived susceptibility to a future CAD-related event, fewer intentions to exercise, lower self-efficacy, and more barriers to exercise.
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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".