The effect of a Finnish national palliative care specialisation education on nurse's palliative care competence: A pretest-posttest study
Bibliographic record
Abstract
BACKGROUND: Nurses play an important role in caring for patients in palliative care and they need sufficient palliative care competence. Additionally, the need for palliative care is increasing. Therefore, palliative care and end-of-life care is one of the fields where nurses' specialisation education is needed the most. The aim of this study was to assess the effect of postgraduate specialist education on nurses' palliative care competence and the association between participants' age or work experiences and changes in their palliative care competencies. METHODS: The data were collected through electronic surveys at the beginning and at the end of specialisation education in 17 universities of applied sciences in Finland. The survey was conducted using the Nurses' Core Competence in Palliative Care (NCPC) instrument. The survey response rate was 89% (pre-training) and 69% (post training). Of 286 nurses, 143 completed both the pre- and post-survey. The data were analysed using nonparametric tests. The level of statistical significance was set at p ≤ 0.05. RESULTS: After the education participants' self-assessed core competencies in palliative care increased compared to before the education, indicating that their knowledge and skills increased in all five domains. Knowledge in Symptom Management, Systematic Use of the Edmonton Symptom Assessment System (ESAS), Teamwork Skills and Interpersonal Skills increased statistically significantly (P < 0.001). Likewise, Life Closure Skills increased statistically significantly (P = 0.044) after the education. Some associations were found, those who had five years or less of work experience in palliative care or end-of-life care reported a greater increase in Interpersonal Skills compared to those with more than ten years of work experience (P = 0.002). Also, those aged 40 or younger reported a greater increase in Interpersonal Skills than those aged 41-50 (P = 0.017). CONCLUSION: This study shows that palliative care specialist education increased nurses' palliative care competence. No statistical association was found between work experience in healthcare and changes in competence; the competence of all participants increased during the education. Palliative care specialist education improves nurses' self-assessed competence in palliative care and may indirectly improve the quality of palliative care.
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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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".