Percepções dos Participantes de Reabilitação Cardíaca sobre seus Comportamentos em Saúde e Necessidades de Informação durante a Pandemia COVID-19 no Brasil
Bibliographic record
Abstract
BACKGROUND: COVID-19 has impacted how people receive health care for many conditions, including cardiovascular diseases. OBJECTIVES: To examine perceptions of cardiac rehabilitation (CR) participants regarding their health behaviors and information needs during the COVID-19 pandemic in Brazil. METHODS: In this cross-sectional study, a 27-item questionnaire, developed by the investigators, was administered online to participants from two CR programs. Questions included health literacy (HL; using the Brief Health Literacy Screening Tool), technology use, perceptions before and during the COVID-19 pandemic, and information needs. Pearson correlation coefficients, paired t-tests, and ANOVA were used as appropriate. P < 0.05 was considered statistically significant for all tests. RESULTS: Overall, 159 (25.5%) CR participants answered the questionnaire. Of these, 89.9% had limited or marginal HL and 96.2% reported having internet access at home. Patients are mainly concerned about their family's health and their own, as well as how the coronavirus is dangerous to their health and how it has changed their lifestyle. Participants perceived that the quality of their health behaviors significantly decreased during the pandemic. The pandemic also changed information needs of CR participants as new needs emerged, such as the control of anxiety levels, staying motivated to live healthily during a pandemic, and how COVID-19 can impact their health condition. Participants with adequate HL significantly perceived the severity of the disease and having access to information significantly more than those with limited HL. CONCLUSIONS: Our results highlighted the impact of the pandemic on CR participants' perceptions regarding their health behaviors and information needs, which can be influenced by HL levels.
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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 | 0.003 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".