The Meaning to Nurses of the Work Process in the Intensive Care Units of a University Hospital in São Paulo State
Bibliographic record
Abstract
Background: This paper presents the results of focus groups conducted to prepare for the potential rollout of PrEP, or preexposure prophylaxis.PrEP would involve taking a pill a day of antiretroviral drugs, the only known effective treatment for AIDS, as a way to help prevent HIV, particularly in high-risk populations.Methods: During the summer of 2009, 10 focus groups were conducted with 77 at-risk African American young adults in Atlanta, GA, ages 18 to 24.Participants for 8 of the focus groups (58 participants) were recruited by trained ethnographers working in communities with high STD/HIV prevalence.Two focus groups (19 participants) were venue specific, held via support groups for young African American men who have sex with men (MSM).Focus groups assessed knowledge, risk perceptions, and stigma about HIV/AIDS, access to health care, and attitudes about this potential new biomedical HIV prevention technology.Results: Focus group participants evidenced limited knowledge about HIV transmission and safer sex practices and frequent mention of attitudes reflecting stigma/myths.Ninety percent of the participants were without any health care insurance, and were unable to afford or did not like taking prescribed oral medication.If PrEP proves to be highly effective, accessible, and free, these young adults would be interested in utilizing a daily dose of antiretrovirals for HIV prevention.Conclusions: Focus group results uncovered culturally specific dynamics that will need to be considered in program design.The experience from this study could help inform plans for operations research during PrEP implementation with this population.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".