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Record W3098402815 · doi:10.5539/gjhs.v12n13p86

Lived Experiences of First Time Baccalaureate Nursing Students in the Clinical Practice

2020· article· en· W3098402815 on OpenAlexvenueno aff
Maria Jocelyn B. Natividad, Ibtehal I. Qazanli, Khalid A. Aljohani

Bibliographic record

VenueGlobal Journal of Health Science · 2020
Typearticle
Languageen
FieldNursing
TopicNursing education and management
Canadian institutionsnot available
Fundersnot available
KeywordsNursingClinical PracticeNurse educationQualitative researchNursing practicePsychologyAnxietyMedical educationMedicineSociology

Abstract

fetched live from OpenAlex

INTRODUCTION: Nursing students’ first clinical exposure may raise anxiety as they question their ability and experienced a lack of confidence as they adjust themselves in the clinical learning environment. AIM: To explore the lived experiences of first-time Baccalaureate nursing students in the clinical area. METHODS: A phenomenological qualitative research design was utilized where 18 Baccalaureate nursing students were individually interviewed. Data were analyzed using the seven steps of Collaizi’s method. RESULT: Three main themes that emerged were clinical practice on the first-hand look; uncertainties in a new learning environment; and nursing as a life-changing experience. Subthemes were recorded and explained in the research report. CONCLUSION: Nursing students who had their first-ever exposure to clinical practice had various experiences both positive and negative. The Nursing College must emphasize comprehensive orientation before students’ exposure to clinical practice.

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)0.004
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0060.008
Scholarly communication0.0070.002
Open science0.0010.007
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.080
GPT teacher head0.488
Teacher spread0.408 · 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 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".

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Citations1
Published2020
Admission routes1
Has abstractyes

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