Professional education among haemophilia nurses: a survey of current practices
Bibliographic record
Abstract
Abstract Background: Guidance from the European Association for Haemophilia and Allied Disorders (EAHAD) sets out the educational milestones haemophilia nurses should aim to achieve. However, little is known about the resources nurses use for education and current awareness. Aims: To assess the current educational level of haemophilia nurses, how and where they access ongoing education, where they feel they need extra support, and how best this teaching could be delivered. Methods: Haemophilia nurses in the Haemnet Horizons group devised and piloted a questionnaire. This was distributed in hard copy to nurses attending the 2019 EAHAD Congress and promoted as an online survey hosted by Survey Monkey. Results: Seventy-five replies were received from nurses in Europe (46 in the UK), and two from nurses in Chile and the Philippines. Most described their role as ‘specialist nurse’, with the majority having worked in haemophilia care for up to ten years. Half had a nursing degree and one quarter had a nursing diploma. Three quarters had attended at least one course specifically related to haemophilia nursing. Almost all used academic sources, study days and the websites of health profession organisations as information sources. Most also used Google or Wikipedia, but fewer used Twitter. Patient association websites were more popular among non-UK nurses. About half attended sponsored professional meetings and three quarters reported that educational meetings were available in their workplace. A clear majority preferred interactive and face-to-face activities using patient-focused content. Conclusions: The study shows that nurses, predominantly in Western Europe, access a range of educational resources, most of which are ‘traditional’. Use of online sources is high, but social media are less popular than Google or Wikipedia. Further research is needed to explore the potential of new media for haemophilia nurse education, and whether the current educational levels and needs highlighted in the survey remains the same across the whole of Europe.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.196 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".