Critical Education in Community Health Literacy for Brazilian Nurses: A Course Evaluation
Bibliographic record
Abstract
This article presents an immediate evaluation of a professional development course in community health literacy for Brazilian nurses. An evaluation based on an applied thematic analysis of the accounts of 63 attendees in three Brazilian cities (January 2020) was guided by the following themes: (a) expansion of understanding about community health literacy as a pillar for planning and providing health care; (b) encouragement of innovation in research and/or practice; and (c) plans to incorporate the information shared in the course into professional projects. The evaluation disclosed the complexity of social contexts for health literacy, which is intertwined with ethnocultural diversity and deep socioeconomic disparities, such as restricted access to essential public health services for socially deprived and vulnerable individuals. Expanded understanding about community health literacy is a pillar for care planning and delivery, as well as innovation in research and practice projects. Participants’ evaluations revealed ideas to improve nurses’ practice in promoting community health literacy and empowerment, as well as quality of life and social well-being. Future knowledge dissemination may impact nurses’ clinical practice and management actions, bringing changes in various areas of practice to redesign more socially inclusive actions for clientele. Keywords: Community health literacy; extracurricular education; immediate evaluation; nursing; professional development course.
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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 | 0.017 | 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 | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".