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Record W7067437559

Learning and quality improvement : nursing in the pediatric intensive care unit

2017· article· en· W7067437559 on OpenAlexaboutno aff

Bibliographic record

VenuecIRcle (University of British Columbia) · 2017
Typearticle
Languageen
FieldNursing
TopicNursing education and management
Canadian institutionsnot available
Fundersnot available
KeywordsExperiential learningQuality managementContext (archaeology)Quality (philosophy)Social learningUnit (ring theory)Pediatric nursingPediatric intensive care unit
DOInot available

Abstract

fetched live from OpenAlex

Maintaining a high quality of care in a Pediatric Intensive Care Unit (PICU) is a constant challenge. Continual 24/7 staffing, ongoing staff turnover, and the constant introduction of new equipment and procedures in a highly technologically-dependent unit requires continuous learning to deliver and improve the quality of children’s care. While all staff consider continuous learning important to maintaining and improving care, learning as quality improvement is made most explicit when new nursing staff are hired and incorporated into the PICU. In this dissertation, I investigated the process of learning by individuals in the interactive social environment of the PICU to answer the following questions: How does learning occur among the newly hired nurses in the PICU? And, how does learning contribute to quality improvement? In this mixed method inquiry, I employed ethnography, Social Network Analysis and simple descriptive and inferential statistical methods to explore process of learning among the newly hired nurses in Western Canada Hospital. I found that learning among newly hired nurses happened through face to face interactions in the context of two main activities: Orientation sessions and their Preceptorship. The most significant learning for the newly hired nurses, however, happened during their Preceptorship. Learning in the Preceptorship was social and experiential as they moved from legitimate peripheral participation in the multi-disciplinary and complementary social environment of the PICU into full participation as members of the PICU Community of Practice (CoP). This learning required the transformation and development of their individual and collective identity, as their preceptors, fellow nurses, and other staff employed scaffolding to mentor them through their constantly evolving Zone of Proximal Development (ZPD). Social and experiential learning activities became the basis for continuous quality improvement (CQI). I conclude that, in the PICU, quality improvement is the tangible manifestation and product of social and experiential learning. Rather than a sequence of corrective actions, in its most effective form, quality of care is improved through scaffolded ongoing learning activities in the authentic setting of a CoP. I recommend the unit to adopt a “learning together” sociocultural approach with scaffolding as key component for successful learning and CQI.

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)0.005
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.005
Scholarly communication0.0060.004
Open science0.0010.003
Research integrity0.0010.002
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 head0.021
GPT teacher head0.265
Teacher spread0.244 · 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 designNot applicable
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
Published2017
Admission routes1
Has abstractyes

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