Primary healthcare professionals’ views on cardiovascular rehabilitation and disease management
Bibliographic record
Abstract
Background Despite its benefits, cardiovascular rehabilitation (CR) is underutilised and not widely accessible globally, including in Brazil, where public CR programs are linked to the Unified Health System (SUS). Limited availability, significant access barriers, and the essential role of professionals in Basic Health Unit (BHU) — that is, community-based facilities that deliver primary healthcare services — impact CR's reach in Brazil. Aim To explore the perspectives and experiences of BHU professionals regarding CR and the management of cardiovascular diseases (CVDs) in Adamantina, Brazil. Methods A qualitative approach was used, involving nine focus groups with 71 BHU healthcare providers, including nurses, physicians, nursing assistants, community health workers, physiotherapists, and nutritionists. Thematic analysis was conducted. Findings Participants had an average age of 39.5 years and 9.9 years of professional experience; 71.8% held a university degree or higher. On average, they managed 584 patients monthly, with 53% diagnosed with CVD. Five main themes were generated: (1) comprehensive management of CVD, (2) roles of BHU professionals, (3) awareness of CR, (4) challenges in patient adherence to behaviour change, and (5) obstacles in accessing CR services. Participants demonstrated limited knowledge of CR, with inadequate referral processes and infrastructure challenges impeding effective CR integration. Discussion Findings highlight the need to address knowledge gaps, improve referral pathways, and enhance infrastructure to better integrate CR into primary healthcare. Despite recognising CR's importance, BHU professionals face significant challenges in its implementation and promotion. Conclusion Strengthening professional education, optimising referral systems, and improving infrastructure are critical to increasing CR accessibility and improving outcomes in primary care settings.
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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 | 0.006 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".