Psychometric validation of the Cardiac Rehabilitation Barriers Scale Revised (CRBS-R) for hybrid delivery
Bibliographic record
Abstract
OBJECTIVE: To test the measurement properties of the revised version of the English Cardiac Rehabilitation Barriers Scale (CRBS-R), suitable for hybrid delivery, structural validity, internal reliability, as well as face, cross-cultural, construct and criterion validity were assessed. DESIGN: Cross-sectional study, where participants completed an online survey via Qualtrics (2023-2024). SETTING: Multicentre, with cardiac rehabilitation (CR) programmes recruiting patients globally; most patients stemmed from a hybrid programme in Iran and supervised programme in Brazil. PARTICIPANTS: Participants include inpatients or outpatients with a cardiovascular diagnosis or procedure that is indicated for participation in CR. MEASURES: In addition to sociodemographic and CR use items, the 21-item CRBS-R was administered. It assesses multilevel barriers and was revised based on a literature review. Responses range from 1 to 5, with higher scores indicating greater barriers. RESULTS: 235 patients participated from all 6 WHO regions. Items were rated as highly applicable, and open-ended responses revealing no key barriers were omitted, supporting face and cross-cultural validity. Cronbach's α for the total CRBS-R was 0.82. Principal components analysis resulted in the extraction of 4 components, which collectively accounted for 60.5% of the variance and were all internally consistent. Construct validity was supported by associations of total CRBS scores with work status (p=0.04), exercise history (p=0.01) and social support (p=0.03). Total CRBS-R scores were significantly lower in patients who were referred and enrolled versus those who were not (both p≤0.01), confirming criterion validity. CONCLUSIONS: The CRBS-R is a reliable and valid scale comprising four subscales, applicable to hybrid CR across diverse settings. It can serve as a valuable tool to support identification of patient's CR barriers, to optimise secondary prevention utilisation globally.
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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 | 0.011 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".