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Record W2146437817 · doi:10.5430/jha.v1n2p42

Preceptorship: Exploring the experiences of final year student nurses in acute hospital setting.

2012· article· en· W2146437817 on OpenAlexvenueno aff
Lorraine Varley, Catherine MacNamara, Patricia McNamara

Bibliographic record

VenueJournal of Hospital Administration · 2012
Typearticle
Languageen
FieldNursing
TopicNursing education and management
Canadian institutionsnot available
Fundersnot available
KeywordsPreceptorScheduleNursingMedicineMedical educationQualitative research

Abstract

fetched live from OpenAlex

Background: Preceptors play a pivotal role in inducting, supporting, teaching and assessing students on clinical placement. This research sought to examine student nurses’ experiences of preceptorship during their clinical placement in their final year of studies in order to further illuminate what is known about preceptorship in Ireland. Method: A qualitative research design was adopted for this study. Forty-seven final year nursing students were questioned using a structured enquiry schedule about their experiences of preceptorship during clinical placement. All participants were female. The data were analysed thematically according to Smith, Flowers and Larkin’s (2009) framework. Results: The results indicate that while a small minority found the experience of preceptors enhanced their learning while on clinical placement, the majority has a less than optimal experience. Reasons for this included: busy workloads of preceptors, difficulty in the accessibility of the preceptor and lack of preceptor training. Conclusions: The results highlight a number of challenges facing students and preceptors in the study. The authors advocate for a more systematic national study into preceptorship implementation in Ireland. This is necessary in order to inform a more coherent framework with national standards for preceptor training and implementation.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.370
Threshold uncertainty score0.305

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.026
GPT teacher head0.328
Teacher spread0.302 · 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 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

Citations9
Published2012
Admission routes1
Has abstractyes

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