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Record W1520223695 · doi:10.1002/nur.21596

Organizational Climate and Hospital Nurses' Caring Practices: A Mixed‐Methods Study

2014· article· en· W1520223695 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueResearch in Nursing & Health · 2014
Typearticle
Languageen
FieldNursing
TopicNursing education and management
Canadian institutionsMcGill UniversityUniversité de MontréalUniversité LavalThe Quebec Population Health Research Network
FundersCanadian Institutes of Health ResearchHealth CanadaCanadian Health Services Research Foundation
KeywordsNursingWorkloadOrganisation climatePsychological interventionQualitative researchOrganizational cultureHealth careAmbiguityMedicinePsychologyPublic relationsSocial psychologyPolitical science

Abstract

fetched live from OpenAlex

Organizational climate in healthcare settings influences patient outcomes, but its effect on nursing care delivery remains poorly understood. In this mixed-methods study, nurse surveys (N = 292) were combined with a qualitative case study of 15 direct-care registered nurses (RNs), nursing personnel, and managers. Organizational climate explained 11% of the variation in RNs' reported frequency of caring practices. Qualitative data suggested that caring practices were affected by the interplay of organizational climate dimensions with patients and nurses characteristics. Workload intensity and role ambiguity led RNs to leave many caring practices to practical nurses and assistive personnel. Systemic interventions are needed to improve organizational climate and to support RNs' involvement in a full range of caring practices.

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.

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)0.010
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.881
Threshold uncertainty score0.771

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
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 head0.086
GPT teacher head0.544
Teacher spread0.458 · 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