Past experiences, current realities and future possibilities for HIV nursing education and care in Canada
Bibliographic record
Abstract
Nurses may have inadequate basic education and opportunities for continuing education in relation to HIV care. As well nurses may perpetuate and impose stigma. We developed, implemented and evaluated an educational intervention to reduce stigma and discrimination among nurses providing HIV care. The intervention used a mentorship model that brought experienced nurses in HIV care and people living with HIV together with nurses who wanted to learn more about HIV nursing care. We examined our findings in relation to past experiences, current realities and future possibilities for HIV nursing education and care in Canada. Our findings demonstrated that many nurses were interested in improving their HIV care, yet few opportunities existed for them to do so. We found that HIV nursing education and expertise were significantly different among participants and across clinical sites. This difference was visible in basic education, services offered for HIV and AIDS care, the collaborative and inter-professional nature of care, and opportunities for continuing education. Mentorship education is an effective strategy to not only address a critical void in knowledge, but also to promote a fundamental shift in attitudes. With the recent call by the World Health Organization to place nurses in key positions to provide HIV care, treatment and prevention, it is imperative to prepare nurses at both the undergraduate and graduate level, as well as those in practice, to fulfill this call.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.015 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".