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Record W1879699441 · doi:10.5430/jnep.v6n1p104

Difficulties experienced by newly-graduated nurses in Turkey: A qualitative study of the first six months of employment

2015· article· en· W1879699441 on OpenAlexvenueno aff
Betül Sönmez, Aytolan Yıldırım

Bibliographic record

VenueJournal of Nursing Education and Practice · 2015
Typearticle
Languageen
FieldNursing
TopicNursing education and management
Canadian institutionsnot available
Fundersnot available
KeywordsWorkloadQualitative researchNursingData collectionStratified samplingPsychologyQualitative propertyMedical educationMedicineSociologyManagementSocial science

Abstract

fetched live from OpenAlex

Objective : The aim of this study was to identify the difficulties experienced by newly-graduated nurses within the first six months of employment. Methods : This research was designed as a qualitative study based on content analysis. The study sample consisted of nurses who had graduated from nursing in 2010, have been working at a public university hospital in Istanbul for at least six months, and were selected via “maximum variation sampling” from purposeful sampling methods. Data were collected via semi-structured in-depth interviews. The data collection process ended at the end of the fifteenth interview when data saturation was reached. Results : The results obtained based on the qualitative sampling isolated four general themes explaining the difficulties newly-graduated nurses experience within the first six months of their employment: lack of knowledge, heavy workload, lack of clinical skills and communication difficulties. Conclusions : The findings of this first qualitative study conducted with nurses in Turkey are in support of the related literature. Among the difficulties experienced by the newly-graduated nurses within the first months of employment, educators should address the issue of lack of knowledge and managers should address the other issues raised.

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)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.085
Threshold uncertainty score0.346

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.088
GPT teacher head0.453
Teacher spread0.365 · 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

Citations24
Published2015
Admission routes1
Has abstractyes

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