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Record W7074568228

The experience of witnessing patients' trauma and suffering for acute care nurses

2009· other· en· W7074568228 on OpenAlexaff

Bibliographic record

VenuecIRcle (University of British Columbia) · 2009
Typeother
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geochemical Analysis
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsCompassion fatigueBurnoutDistancingAcute careAcute Stress DisorderEmpathyWork (physics)Nursing care
DOInot available

Abstract

fetched live from OpenAlex

Research has shown there are many stresses that nurses endure as a result of their work and workplace environment. Burnout and stress are common issues that have been proven to be quite prevalent in the nursing world. More recently, compassion fatigue is starting to be studied as part of the struggles that many nurses face. This study is an initial attempt to describe the experience of witnessing patients’ trauma and suffering for acute care nurses to see if this could also be an aspect of the stress. Phenomenological reduction of the data yielded several themes: A witnessing of a traumatic event and/or prolonged witnessing of suffering; a group of common effects as a result of the witnessing, distancing and guilt secondary to the effects; change in self; and finally what nurses do to cope and what they feel would help aid further coping. Recommendations for resources and further research are made.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0070.005
Scholarly communication0.0040.003
Open science0.0010.006
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.005
GPT teacher head0.169
Teacher spread0.164 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations0
Published2009
Admission routes1
Has abstractyes

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