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Record W2162768255 · doi:10.5539/gjhs.v6n6p88

Factors Affecting Nurses’ Coping With Transition: An Exploratory Qualitative Study

2014· article· en· W2162768255 on OpenAlexvenueno aff
Jalil Azimian, Reza Negarandeh, Ali Fakhr‐Movahedi

Bibliographic record

VenueGlobal Journal of Health Science · 2014
Typearticle
Languageen
FieldNursing
TopicNursing education and management
Canadian institutionsnot available
Fundersnot available
KeywordsNursingCoping (psychology)Economic shortageExploratory researchQualitative researchNursing shortageContent analysisAccountabilityPsychologyMedicineNurse educationGovernment (linguistics)Clinical psychologyPolitical scienceSociology

Abstract

fetched live from OpenAlex

AIM: One of the most important factors contributing to staff shortage is nurses' ineffective coping with transitions. Changes in nurses' official positions are usually associated with varying degrees of transition. Identification of affecting factors on nurses' coping in responding to transition can promote quality of nursing activity and prevent nurses' shortage. So the aim of this study was to explore factors affecting nurses' coping with transitions. METHODS: The participant of this exploratory qualitative study consisted of sixteen nurses that were work in medical wards of four hospitals in Qazvin, Iran. Data collected by semi-structured interviews. The data were analyzed by qualitative content analysis approach. RESULTS: The main theme of the study was 'inadequate preparation for transition'. This theme consisted of six categories including "staff training and development", "professional relationships", "perceived level of support", "professional accountability and commitment", "welfare services", and "nursing staff shortage". CONCLUSION: Nursing managers and policy makers need to pay special attention to the affecting factors on nurses' coping with transition and develop effective strategies for facilitating it.

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)0.004
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.064
Threshold uncertainty score0.459

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.068
GPT teacher head0.440
Teacher spread0.373 · 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

Citations26
Published2014
Admission routes1
Has abstractyes

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