Long-term Physical Activity Behavior After Completion of Traditional Versus Fast-track Cardiac Rehabilitation
Bibliographic record
Abstract
BACKGROUND: Despite the health benefits associated with regular physical activity (PA), many cardiac patients fail to maintain optimal levels of PA after completing cardiac rehabilitation (CR). The long-term impact of different CR delivery models on the PA habits of cardiac patients is not completely understood. OBJECTIVE: The purpose of this study is to use a multisensor accelerometer to compare the long-term impact of a traditional versus fast-track CR on the PA of patients with coronary artery disease 6 months after CR entry. METHODS: Forty-four participants attended either traditional (twice a week, 12 weeks; n = 24) or fast-track (once a week, 8 weeks; n = 20) CR. Exercise capacity (ie, 6-minute walk test distance) and PA were assessed at baseline and at 12 weeks and 6 months after CR entry. RESULTS: At 12 weeks, exercise capacity increased significantly in both groups and remained elevated by the 6-month follow-up. Sedentary time decreased from baseline to 12 weeks. However, at 6 months, it was comparable with the baseline level. There was no significant change in any other PA marker (ie, steps/day, time in light and moderate-vigorous PA) over the course of the study. CONCLUSIONS: Findings support the long-term effectiveness of CR on exercise capacity irrespective of the delivery model. However, participation in CR program, whether it be a traditional or fast-track CR exercise program, may not lead to long-term PA behavior change. Thus, CR participants may benefit from structured strategies that promote long-term PA adherence in addition to facilitating exercise capacity improvement.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.001 | 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".