Spanish Translation, Adaptation, and Validation of Strategies to Mitigate Cardiac Rehabilitation Barriers
Bibliographic record
Abstract
Background: Despite its demonstrated benefits, cardiac rehabilitation (CR) is grossly underutilized. Validated interventions are needed to mitigate the established barriers to accessing and adhering to these services. A strategy has been created based on the Cardiac Rehabilitation Barriers Scale (CBRS), by the International Council of Cardiovascular Prevention and Rehabilitation (ICCPR), with initial support of helpfulness. Purpose: To translate, adapt, and content validate the CR barrier mitigation strategy for the Colombian context. Methods: A 2-phase exploratory sequential multimethod study was conducted in accordance with best practices. The 21 barrier mitigation strategies were first translated to Spanish by a bilingual health care professional and then adapted for the Colombian population following semi-structured interviews with 6 Colombian CR staff. The second phase of content validation involved 8 experts and 8 CR patients, who evaluated the mitigation strategies regarding engagement, comprehensibility, applicability, acceptability, and motivation on a 5-point Likert scale (higher scores more favorable). The content validity coefficient was computed. Results: Content analysis of interviews resulted in revisions to all 21 Spanish barrier mitigation strategies. Content validity of the revised version was rated as at least acceptable (≥0.70) for all 21 strategies, but each strategy was rated as requiring revision on 1 to 4 of the above indicators. Revisions ensued accordingly. Conclusions: The rigorous adaptation and content validation process has established the Spanish CR barrier mitigation strategies, which will now be tested at the bedside in a randomized controlled trial in Colombia to determine effect on CR use.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".