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Record W2088414665 · doi:10.12968/ijpn.2010.16.2.46753

Clinical competence in palliative nursing in Norway: the importance of good care routines

2010· article· en· W2088414665 on OpenAlexaboutno aff
Kari Slåtten, Lisbeth Fagerström, Ove Edvard Hatlevik

Bibliographic record

VenueInternational Journal of Palliative Nursing · 2010
Typearticle
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsnot available
Fundersnot available
KeywordsBachelorNursingPalliative careCompetence (human resources)AnxietyNursing carePsychologyMedicineSocial psychologyPsychiatry

Abstract

fetched live from OpenAlex

AIM: This paper examines how clinical nurse specialists assessed their competences in relief of symptoms, and explores factors affecting good care routines in palliative care. METHODS: A prospective survey among 235 former post-bachelor (response rate 50.6 %) students at two university colleges in Norway. RESULTS: Correlations between the measured concepts showed a medium to high correlation between all five competences. Use of care routines correlated with all the other factors. The ability to identify lack of care showed significant correlation with one concept: time available for nursing. The results from the regression analysis supported a model with good care routines as a dependent variable (F=22.59, df=91, P<0.001). The independent variables in the model explained almost 57% of the variance in using care routines. Competences dealing with mouth problems, nausea, anxiety and the use of the Edmonton symptom assessment system (ESAS) had a positive effect on care routines. On the other hand, the ability to identify lack of care had a significant negative effect on the use of care routines. CONCLUSIONS: The importance of systematic assessment of the palliative patient;s care needs and symptom management are emphasized, and use of the ESAS, and good care routines was affected by post-bachelor competences.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.556

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.111
GPT teacher head0.500
Teacher spread0.389 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations19
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Palliative NursingSame topicPalliative Care and End-of-Life IssuesFrench-language works237,207