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Record W3193768992 · doi:10.1002/nop2.1046

Licenced practical nurses' perceptions of their work environments and their intention to stay: A cross‐sectional study of four practice settings

2021· article· en· W3193768992 on OpenAlexaffabout
Leah Phillips, Nyla de Los Santos, Jennifer Jackson

Bibliographic record

VenueNursing Open · 2021
Typearticle
Languageen
FieldNursing
TopicNursing education and management
Canadian institutionsUniversity of CalgaryCollege & Association of Registered Nurses of Alberta
Fundersnot available
KeywordsStaffingCross-sectional studyDescriptive statisticsNursingWork (physics)PerceptionPsychologyWork environmentMedicineJob satisfactionSocial psychologyEngineering

Abstract

fetched live from OpenAlex

AIMS AND OBJECTIVES: This study aimed to understand how licenced practical nurses perceive their work environments across different work settings and to analyse the association between these nurses' perceptions of their work environments and their intentions to stay employed at their current nursing unit. DESIGN: A cross-sectional descriptive survey was conducted with Licensed Practical Nurses in Alberta, Canada. METHODS: The study population consisted of 598 licenced practical nurses. Survey measures included demographic information, the Perceived Work Environment-Nursing Work Index, and an intention to stay scale. Descriptive statistics were calculated and mean scores for perceptions about the work environment were compared by work setting. The associations between perceived work environment and intention to stay were analysed using linear regression. RESULTS: Overall, licenced practical nurses rated their work environment as mixed, with statistically significantly lower scores in acute care settings. Nurse manager ability and adequate staffing and resources were the highest contributing variables.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.556
Threshold uncertainty score0.641

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.051
GPT teacher head0.401
Teacher spread0.351 · 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 designObservational
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

Citations10
Published2021
Admission routes2
Has abstractyes

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