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Record W2794511841 · doi:10.26550/2209-1092.1021

Reshaping perioperative nursing practice to get the job done: A constructivist grounded theory study

2018· article· en· W2794511841 on OpenAlexaboutno aff
Sharon Linsey Bingham, Kenneth Walsh, Karen Ford

Bibliographic record

VenueJournal of Perioperative Nursing · 2018
Typearticle
Languageen
FieldMedicine
TopicCardiac, Anesthesia and Surgical Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsConstructivist grounded theoryGrounded theoryConstructivist teaching methodsNursing theoryPerioperative nursingNursing practicePerioperativeSociologyNursingEpistemologyPsychologyQualitative researchMedicineMEDLINEPedagogySocial sciencePolitical sciencePhilosophyTeaching method

Abstract

fetched live from OpenAlex

An estimated 234 million operations are performed in hospitals each year and complications of surgery are common and often preventable. The rates of complications vary between studies with reports of perioperative death rates of between 0.4 and 0.8 per cent and rates of complications between 3 and 17 per cent. Adverse events can lead to patient disability, death, or increased length of stay, imposing a significant burden on the health care system, patients and their families. Perioperative nurses have a key role in securing patient safety and preventing mistakes and these are recognised as both the nurses’ responsibility and within their locus of control. Research and evidence-based actions to minimise the risk of patient harm inform the standards developed by the Australian College of Perioperative Nurses. These standards are closely aligned with similar standards in the UK, US and Canada and represent the accepted standard of professional practice for perioperative nurses in Australia.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.144
Threshold uncertainty score0.899

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
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 head0.024
GPT teacher head0.378
Teacher spread0.354 · 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 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

Citations1
Published2018
Admission routes1
Has abstractyes

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