Barriers to Cardiac Rehabilitation
Bibliographic record
Abstract
In Brief PURPOSE To quantitatively investigate age differences in barriers to cardiac rehabilitation (CR) enrollment and participation. METHODS Cardiac outpatients (N = 1,273, mean age = 65.9 ± 11.2) completed a mailed survey to discern barriers to CR enrollment and participation. Both enrollees and nonenrollees were asked to rate 18 CR barriers on a 5-point Likert scale. RESULTS Of the respondents, 535 (43%) reported participating in CR at 1 of 40 sites, with younger patients being more likely to participate (P = .002). Older age was positively related to total CR barriers (P < .001). Older patients more strongly endorsed the following CR barriers: already exercising at home (P = .001), confidence in ability to self-manage their condition (P = .003), perception of exercise as tiring or painful (P = .001), not knowing about CR (P = .001), lack of physician encouragement (P < .001), comorbidities (P < .001), and perception that CR would not improve their health (P < .001). CONCLUSION Given that the benefits of CR are achieved in older patients as well as the young, interventions to overcome these modifiable barriers to enrollment and participation are needed. Compared with younger patients, older patients more strongly identified several barriers to cardiac rehabilitation (CR) participation including already exercising at home, confidence in ability to self-manage condition, perception of exercise as tiring or painful, not knowing about CR, lack of physician encouragement, comorbidities, and perception that CR is ineffective.
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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 | 0.002 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".