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Record W2165799193 · doi:10.1177/1049732307313354

A Context of Uncertainty: How Context Shapes Nurses' Research Utilization Behaviors

2008· article· en· W2165799193 on OpenAlexaff
Shannon D. Scott, Carole A. Estabrooks, Marion Allen, Carolee Pollock

Bibliographic record

VenueQualitative Health Research · 2008
Typearticle
Languageen
FieldHealth Professions
TopicHealth Sciences Research and Education
Canadian institutionsMacEwan UniversityUniversity of Alberta
Fundersnot available
KeywordsContext (archaeology)TeamworkWork (physics)EthnographyUnit (ring theory)NursingPsychologyKnowledge managementMedicineSociologyComputer sciencePolitical science

Abstract

fetched live from OpenAlex

Context has often been cited as a significant factor in shaping research utilization behavior, yet scholars have been unable to provide specific detail as to how and why it is important. From an ethnographic study of research utilization in a pediatric intensive care unit, we determined that the primary characteristic of this nursing unit was uncertainty. We identified four major sources of uncertainty: (1) the precarious status of seriously ill patients, (2) the inherent unpredictability of nurses' work, (3) the complexity of teamwork in a highly sophisticated hospital environment, and (4) a changing management. We found that uncertainty shaped nurses' behaviors such that research use was irrelevant. Reducing uncertainty is a necessary precursor to any increase in research utilization by nurses. Future knowledge translation strategies need to begin by decreasing and managing uncertainty.

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)0.019
metaresearch head score (Gemma)0.077
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.981
Threshold uncertainty score0.099

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.077
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0030.003
Scholarly communication0.0050.003
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.885
GPT teacher head0.737
Teacher spread0.148 · 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.

Study designQualitative
DomainMethods
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

Citations98
Published2008
Admission routes1
Has abstractyes

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