Distance learning and its impact on educational intervention on palliative care to nursing professionals–A pilot study
Bibliographic record
Abstract
Background and objective: Distance education (DE) is a professional training tool that was utilized to work with nursing professionals in this investigation on palliative care. This innovative form of care is used by interdisciplinary teams in a holistic way, with biological, psychological and spiritual aspects. Besides it is uniquely significant during pandemic lockdowns such as the current restrictions in nowadays. The aim of the study was to evaluate the knowledge of nursing professionals about palliative care, before and after an educational intervention through distance education.Methods: This is a quasi-experimental study carried out in a medium-sized state teaching hospital located in the Midwest region of Brazil. Participants: 31 nursing professionals who worked in the internal medicine ward. First phase, the prior knowledge about palliative care was evaluated through a questionnaire containing 24 semi-structured questions. In the second phase seven 20-minute video lessons were prepared, recorded and sent to the participating group. Third phase the same questionnaire was used to evaluate participants and they were inquired how they perceived they knowledge after distance learning.Results: A total of 31 professionals were enrolled in the first phase of the study and 29 answered the evaluation questionnaire after DE intervention. Most nursing professionals (61.2%) had between 31 and 50 years, 30 (96.7%) professionals had studied between 10 and 20 years. After DE there was an increase of 33% correct answers. Distance learning improved professional practice and increased confidence at work.Conclusions: Distance education is well accepted and promotes an increase of knowledge by up to a third on palliative care issues and also increased self-confidence among professionals.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".