Desenvolvimento e validação da versão em português da Escala de Barreiras para Reabilitação Cardíaca
Bibliographic record
Abstract
BACKGROUND: Cardiovascular diseases show high incidence and prevalence in Brazil; however, participation in Cardiac Rehabilitation (CR) is limited and has been poorly investigated in the country. The Cardiac Rehabilitation Barriers Scale (CRBS) was developed to assess the barriers to participation and adherence to CR. OBJECTIVE: To translate, cross-culturally adapt and psychometrically validate CRBS to Brazilian Portuguese. METHODS: Two independent initial translations were performed. After the reverse translation, both versions were reviewed by a committee. The new version was tested in 173 patients with coronary artery disease (48 women, mean age = 63 years). Of these, 139 (80.3%) participated in CR. Internal consistency was assessed by Cronbach's alpha, test-retest reliability by intraclass correlation coefficient (ICC) and construct validity by factor analysis. T-tests were used to assess criterion validity between participants and non-participants in CR. The applied test results were evaluated regarding patient characteristics (gender, age, health status and educational level). RESULTS: The Brazilian Portuguese version of the CRBS had Cronbach's alpha of 0.88, ICC of 0.68 and disclosed five factors, most of which showed to be internally consistent and all were defined by the items. The mean score for patients in CR was 1.29 (SD = 0.27) and 2.36 for ambulatory patients (SD = 0.50) (p <0.001). Criterion validity was also supported by significant differences in total scores by gender, age and educational level. CONCLUSION: The Brazilian Portuguese version of CRBS has shown adequate validity and reliability, which supports its use in future studies.
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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 | 0.052 | 0.120 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".