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Record W3028977392 · doi:10.1111/nin.12365

Exploring the meaning of critical incident stress experienced by intensive care unit nurses

2020· article· en· W3028977392 on OpenAlexaff
Giuliana Harvey, Dianne M. Tapp

Bibliographic record

VenueNursing Inquiry · 2020
Typearticle
Languageen
FieldHealth Professions
TopicEthics in medical practice
Canadian institutionsUniversity of CalgaryUniversity of AlbertaMount Royal University
Fundersnot available
KeywordsCritical Incident TechniqueIntensive care unitNursingTransformative learningIntensive careIncident reportCritical care nursingBurnoutPsychologyPerceptionPsychological interventionMeaning (existential)Qualitative researchHealth careMedicineClinical psychologyPsychotherapistSociologyPsychiatryDevelopmental psychology

Abstract

fetched live from OpenAlex

The complexity of registered nurses' work in the intensive care unit places them at risk of experiencing critical incident stress. Gadamer's philosophical hermeneutics (1960/2013) was used to expand the meanings of work-related critical incident stress for registered nurses working with adults in the intensive care unit. Nine intensive care unit registered nurses participated in unstructured interviews. The interpretations emphasized that morally distressing experiences may lead to critical incident stress. Critical incident stress was influenced by the perception of judgment from co-workers and the organizational culture. Nurses in this study attempted to cope with critical incident stress by functioning in 'autopilot', temporarily altering their ability to critically think and to conceal emotions. Participants emphasized the importance of timely crisis interventions tailored to support their needs. This study highlighted that critical incident stress was transformative in how intensive care unit nurses practiced, potentially altering their professional self-identity. Work-related critical incident stress has implications for nurses, the discipline, and the health care system.

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)0.050
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.058
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.050
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.003
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 head0.449
GPT teacher head0.547
Teacher spread0.098 · 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.

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

Citations13
Published2020
Admission routes1
Has abstractyes

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